List of Abbreviations and Nomenclature

	Maximum Biomass Concentration (g/L)
	Adjusted Correlation Coefficient
qO2	Specific Oxygen Uptake Rate (h-1)
qp	Specific HBP production rate (h-1)
qs	Specific DBT Consumption rate (h-1)
µ	Specific Growth Rate (h-1)
µmax	Maximum Specific Growth Rate (h-1)
2,2’-BHBP	2,2’-Bihydroxybiphenyl
2-HBP	2-Hydroxybiphenyl
2HMBT	2-hydroxymethyl benzothiophene
2HMT	2-hydroxymethyl thiophene
2-MBP	2-Methoxybiphenyl
3-MBT	3-Methylbenzothiophene
4,6-DBDBT	4,6-Dibutyldibenzothiophene
4,6-DEDBT	4,6-Diethyldibenzothiophene
4,6-DMDBT	4,6-Dimethyldibenzothiophene
4,6-DPDBT	4,6-Dipropyldibenzothiophene
4HMBT	4-hydroxymethyl benzothiophene
4-MDBT	4-Methyldibezothiophene
7-EBT	7-Ethylbenzothiophene
7-HBT	7-Hexylbezothiophene
7-MBT	7-Methylbenzothiophene
7-PBT	7-Propylbenzothiophene
AH	Acid hydrolysis
ATP	Adenosine triphosphate
BBD	Box-Behnken Design
BDS	Biodesulfurization
BNT	Benzonaphthothiophene
BP	Biphenyl
BT	Benzothiophene
C*	Saturation Concentration of Dissolved Oxygen,
CCD	Central Composite Design
Co	Initial Concentration of the Dissolved Oxygen
DBS	Dibenzylsulfide
DBT	Dibenzothiophene
DBTO	Dibenzothiophene Sulfoxide
DBTO2	Dibenzothiophene Sulfone
DCW	Dry Cell Weight
DDBT	The desulfurizing capability index (%gcell/L/h)
DGGE	Denaturing Gradient Gel Electrophoresis
DMF	Dimethylformamide
DMSO	Dimethylsulfoxide
DO	Dissolved Oxygen
DOE	Design of Experiment
DPS	Diphenylsulphide
E	Fractional Approach to Equilibrium
ED	Entner–Doudoroff
FAD	Flavin Adenine Dinucleotide
FFD	Fractionation Factorial Design
FWHM	Full Width at Half Maximum
Gr	Cell Growth (mg/L)
H/A	Hydrocarbon to Aqueous Phase Ratio
HB	Higher is Better
HBPS	2′-Hydroxybiphenyl-2-sulfinic acid
HCLN	High Carbon and Low Nitrogen
HGO	Heavy Gas Oil
HN	High nitrogen
JA	Jerusalem Artichoke
JAJ	Jerusalem Artichoke Juice
JAJt	Treated Jerusalem Artichoke Juice
kcat	Turnover Number (min-1)
kLa	Gas Liquid Mass Transfer Coefficient (s-1)
Km	Saturation Constant or Michaelis constant (g/L)
Ks	Monod Saturation Constant (g/L)
LB	Lower is Better
LN	Low nitrogen
MBC	Minimum bacteriocidal concentration
MIC	Minimum Inhibitory Concentration
NAD	Nicotinamide Adenine Dinucleotide
NADH	Nicotinamide Adenine Dinucleotide, reduced form
NADP	Flavin Adenine Dinucleotide Phosphate
NADPH	Flavin Adenine Dinucleotide Phosphate, reduced form
NB	Nominal is Better
O/W	Oil/Water
OA	orthogonal arrays
OFP	Organic Fraction Phase
OSCs	Organosulfur compounds
OTR	Oxygen Transfer Rate
OUR	Oxygen Uptake Rate
PASHs	Polyaromatic Sulfur Heterocyclic Compounds
PC/O	Partition Coefficients between the Biocatalyst and the Oil Phases
PC/W	Partition Coefficients between the Biocatalyst and the Aqueous Phases
PM/W	Partition coefficient between membrane and water
PO/W	Partition coefficient of a solvent
QDBT	Maximum Value of the Specific Desulfurization Rate (mmol/gcell/h)
qHBP	2-HBP specific production rate
R2	Correlation Coefficient
RMSE	Root Mean Square Errors
RPS	Recycled Paper Sludge
RSM	Response Surface Methodology
S/N	Signal to Noise Ratio
SBM	Sugar Beet Molasses
SFM	Sulfur Free Medium
SSE	Sum of Squares Errors
SSF	Simultaneous Saccharification and Fermentation
STBR	Stirred Tank Bioreactor
TCA	Tricarboxylic Acid Cycle
TG	Generation Time
Th	Thiophene
Ug	Superficial Gas Velocity (L/min)
ULS	Ultra-low sulfur
ULSD	Ultra-low sulfur diesel
XBDS	Biodesulfurization yield
YDBT	2-HBP Yield as a Measure for BDS Efficency
YE	Yeast Extract
v	Working Volume (L)

8.1 Introduction

There are two pathways involved in the biodesulfurization (BDS) pathways: a ring destructive one that is in the C-C cleavage via the Kodama pathway and complete mineralization pathway and the non-destructive pathway that is in the C-S cleavage, which is the 4S-route (Chapter 6). The recommendable pathway for the petroleum industry is the 4S-pathway, retaining the calorific value of fuel.

It has been frequently reported in the literature that there are several factors affecting BDS rate and efficiency: substrate diffusion problems, the presence of inhibition effects, and the necessity of cofactors re-generation, but the cell membrane transport rate, the reduced cofactors concentration, and HpaC Flavin reductase activity are not the only factors limiting the BDS rate (Alcon et al., 2005; 2008). Some points other than the main physicochemical factors are also important to achieve a successful BDS process with a high desulfurization rate. For example, resting cells are preferable over growing cells (Chang et al., 2000). Further, the immobilization of biocatalysts helps in easy separation and reusability of the biocatalysts (Ansari et al., 2007). The biphasic reaction systems are the ones to be applied in the real industry, enhancing the solubility and availability of hydrophobic substrates to the biocatalyst and limiting biocatalyst inhibition by hampering the accumulation of 2-HBP. However, the viability of bacteria would be affected by the toxicity of solvent, mass, and oxygen transfer (Marcelis et al., 2003; Kawaguchi et al., 2011). The pH, process temperature, biomass concentration, oil/water O/W ratio, and initial S-concentration are other important factors that should be considered for a successful BDS process.

It should also be noted that the physicochemical parameters affecting the BDS capacity interact with each other and most of the published studies investigated different factors and discussed their mutual effect, not only their individual effects.

This chapter illustrates the different physicochemical parameters affecting the BDS-process and summarizes the worldwide studies for enhancing its rate.

8.2 Effect of Incubation Period

It is very important to know the time at which the biocatalyst would give the highest BDS efficiency. The shorter the time, the higher the BDS rate, and the more beneficial it will be for the industrial application and commercialization of BDS-process.

The time dependent desulfurization of DBT into 2HBP has been studied for Rhodococcus erythropolis IGTS8, Rhodococcus erythropolis D-1, Rhodococcus erythropolis KA2–5-1, Mycobacterium sp. G3, Rhodococcus sp. P32C1, Bacillus subtilis WU-S2B, Mycobacterium phlei WU-F1, and Paenibacillus sp. All-2 (Kilbane and Bielage, 1990; Li et al., 1996; Ohshiro et al., 1996a; Konishi et al., 1997; Oldfield et al., 1997; Ishii et al., 2000; Maghsoudi et al., 2001; Kirimura et al., 2001; Furuya et al., 2001a).

Yoshikawa et al. (2002), Okada et al. (2002), and del Olmo et al. (2005a) reported that the capacity of R. erythropolis IGTS8 expressed its maximum DBT-BDS capacity in shaken flask cultures at the end of the exponential phase of growth of the cells (between 15 and 25 h of growth time). In another study, high values of BDS capacity were maintained for cells cultured during longer periods when dissolved oxygen (DO) concentration was constant and equal to 10% of saturation. The maximum BDS capacity was similar for stirrer speeds of 250 and 400 rpm, reaching approximately 80% for 30 h of growth. Afterwards, this capacity slightly decreased. However, upon working at 150 rpm, this decrease took place at a faster interval as a consequence of the oxygen transport limitation during growth (Gomez et al., 2006a). Other researchers reported that it is not a must that the time for maximum DBT removal be the same for obtaining maximum growth and 2-HBP. This phenomenon is mainly related to the feedback inhibition of the end products of BDS. Thus, it is important during the optimization of a BDS to know the incubation period that would give appropriate microbial growth with maximum enzymatic activity and BDS-efficiency.

Okada et al. (2002) reported the methoxylation of 2-HBP to 2-methoxy-biphenyl (2-MBP) in the DBT-BDS using Mycobacterium strain G3. The time course of methoxylation and desulfurization in a growing cell culture has been investigated. The desulfurization activity was induced at the end of the exponential phase and the highest level of desulfurization activity was observed in the middle of the stationary phase. On the other hand, the methoxylation activity was observed in the early growth phase, up to 4 d after inoculation, and decreased in the middle of the stationary phase. This indicated that both activities were expressed by the independent regulation systems. In a 1/1 (O/W) biphasic batch BDS process of model oil (100 mM 4,6-dipropylDBT in n-tetradecane) using resting cells of Mycobacterium strain G3, the desulfurization recorded 4% at 37 °C within 2 h and, by increasing the incubation period to 15 h, the desulfurization rate of 4,6-dipropyl DBT increased by approximately three-fold.

Wang et al. (2004) reported the maximum desulfurization activity for a batch DBT-BDS process occurred at a late exponential growth phase of Corynebacterium sp. ZD-1 and recommended the preparation of active resting cells of ZD-1 in that period. Verma et al. (2016) reported maximum DBT removal using growing cells of Bacillus sp. E1 within 72 h and remained sustained thereafter, while maximum 2-HBP occurred within 48 h recording 1.103 mM and decreased at a longer incubation period. This was attributed to the transformation of 2-HBP to biphenyl and 2-methoxybiphenyl. Zakharyant et al. (2004) reported that the enrichment of Rhodococcus erythropolis Ac-1514D and Rhodococcus ruber Ac-1513D, in a selective liquid medium containing DBT before their inoculation into a batch DBT-BDS process, decreased the lag phases from 120–122 h to 20–22. That is approximately a six-fold decrease. R. ruber Ac-1513D recorded about 63–65% DBT removal from the initial concentration of 0.43 mM within 80 h, while R. erythropolis recorded about 78–80%.

In a batch DBT-BDS using growing cells of Lysinibacillus sphaericus DMT-7, Bahuguna et al. (2011) reported 97% BDS of 0.2 mM DBT within 30 d with the production of only 121 µmol/L 2-HBP after 15 d of incubation which remained nearly sustained recording 122.5 µmol/L after 30 d. The onset of 2-HBP production occurred within 24 h, recording 5.1 µmol/L. A sharp decrease in DBT occurred within 15 d, recording 77% out of which 60% desulfurized to 2-HBP. However, an exponential increase in the growth of DMT-7 occurred up to 12 d. Bahuguna et al. (2011) also reported that the induction period prior the application of the microorganisms in BDS process is recommended. Upon the performance of a comparative study for a batch BDS of DBT (0.2 mmol/L) with Lysinibacillus sphaericus DMT-7 previously induced by pre-growing on 0.2 mmol/L DBT for 7 d and a non-induced one by pre-growing DMT-7 on 0.5 mmol/L MgSO₄ for 7 d, a difference in the onset of 2-HBP production was observed. The DBT-BDS to 2-HBP started within 6 h, producing 5.2 µmol/L. Then, the concentration of 2-HBP in the cultures increased linearly up to 107 µmol/L up to 5 d, attaining maximum production of 129.2 µmol/L of 2HBP (65% desulfurization) within 10 d of growth and thereafter it became stationary. In contrast to the induced culture, the non-induced DMT-7 cultures, pregrown on MgSO₄, required a prolonged lag phase of 24 h and 15 d for the accomplishment of a maximum DBT desulfurization of 60% accompanied by production of 119.5 µmol/L 2-HBP. The inducibility of desulfurization pathways has been also reported by Kayser et al. (1993), Ohshiro et al. (1996a), and Ohshiro and Izumi (1999).

Maass et al. (2015) reported that modeling of the phenomena associated with logarithmic phase appears to be the most important in the BDS experiments since the highest rates of DBT removal and 2-HBP production occur within the growth phase. The same was reported in this study, where a high BDS rate occurred during the logarithmic phase regardless of the initial DBT concentration. Nassar et al. (2017a) also reported the sharp depletion of DBT within 72 h of incubation by Rhodococcus erythropolis HN2 during the logarithmic growth phase regardless of the initial DBT concertation. The absence of a lag phase in all cultures of the studied initial DBT concentrations (100–1000 ppm) was attributed to the adaptation of NH2 to high concentrations of DBT as it was isolated from an Egyptian coke sample of high S-content (2.74%) and previously enriched on 1000 ppm DBT (El-Gendy et al., 2014). Nevertheless, it is not clear up till now, whether the decrease in activity at longer incubation periods is due to the exhaustion of a carbon source or due to accumulation of 2-HBP and other by-products which express some toxicity to the microorganism.

8.3 Effect of Temperature and pH

Several reports have been published concerning the effects of operational temperature and pH.

Enzymes are reported to be affected by the pH variations in the system because of the dependence of their 3D shape on the pH. The impact of pH variation is not only the on shape of enzymes, but it also affects the electrical charge properties of the substrate in such a way that the substrate cannot bind to the enzyme active site. Thus, the enzyme cannot undergo its catalytic activity (Berg et al., 2002). Barrios (2011) reported that the change in pH has a great effect on the microbial metabolism, as well as the solubilization and adsorption/desorption of ions and hydrocarbons to be metabolized.

Changes in pH would occur due to the production of metabolites. Thus, it should be controlled sometimes with diluted NaOH solution or tris-HCl buffer. There would be a drop in pH if it is not controlled. Most reports apply 30 °C and pH values between 6–5 – 7.5 (Omori et al., 1995; Patel et al., 1997; Ohshiro et al., 1998; Folsom et al., 1999; Kaufman et al. 1999; Setti et al., 1999; Abbad-Andaloussi et al., 2003; Maghsoudi et al., 2001; Matsui et al., 2001; Ardakani et al., 2010; Derikvand et al., 2014). Lu et al. (2003) reported that the BDS efficiency of the lyophilized cells of Pseudomonas delafieldii R-8 is not affected by the change in pH (4.6–8.5) which would be favorable for the fuel desulfurization. However, upon the application of growing cells of R-8, the growth and, consequently, the BDS activity were inhibited with an initial pH below 5. Kim et al. (2004) reported the highest growth and BDS efficiency of Gordonia sp. CYKS1 is at pH 7–8, while at a pH < 6 neither a significant desulfurization of DBT nor an observable cell growth occurred.

There are various reported DBT-desulfurizing microorganisms that work via the 4S-pathway that can be categorized according to the optimal working temperature as mesophilic (Patel et al., 1997; Ohshiro et al., 1996b; Kirimura et al., 2001; Wang et al., 2004; Nassar et al., 2017b), moderately thermophilic (Furuya et al., 2003), and hyper-thromophilic (Kargi and Robinson, 1984; Gün et al., 2015). However, most of the reported BDS processes are working at 30 °C. Furuya et al. (2006) reported that the first and third enzymes in the 4S-pathway (D_SZC and D_SZB) are more sensitive to temperature changes, compared to other enzymes, and are BDS-rate limiting. Most of the isolated Rhodococcus strains that are capable for DBT-BDS throughout the 4S-pathway are reported to be mesophilic, including R. erythropolis IGTS8 (Li et al., 1996), R. erythropolis D-1 (Ohshiro et al., 1996a), and Rhodococcus sp. strain P32CI (Maghsoudi et al., 2001).

Furuya et al. (2001b) reported that during the BDS of DBT by the thermophilic Mycobacterium phlei WU-F1, conversion of DBT to DBTO₂ would be stopped at high temperatures, while the conversion of DBTO₂ and other intermediate compounds would continue within the same high temperature. Furuya et al. (2001b) concluded that the activity of the first enzyme in the 4S-pathway, which oxidizes DBT to DBTO₂ is more sensitive to temperature variations and is considered as the BDS rate-limiting enzyme.

Jiang et al. (2002) studied the effect of initial pH (2.9–10.29) and incubation temperature (20–40 °C) on the BDS-activity of Pseudomonas delafieldii R-8 and the optimum pH and temperature were 7.2 and 32 °C. Xu et al. (2002) studied the effects of different initial pH on batch BDS of 0.5 mmol/L DBT by Rhodococcus. sp. 1awq strain within 48 h and found 30 °C and pH7 to be the best.

Martin et al. (2005) reported the great influence of incubation temperature on the growth and BDS activity of Pseudomonas putida CECT5279. The highest values of the growth parameters, such as specific growth rate µ (h^-1) and maximum biomass concentration (g/L), are obtained when the cells were grown at 26 °C and these parameters reached their lowest values at 32 °C. Nevertheless, the best BDS-capability was obtained when the bacterium growth occurred at 30 °C.

The effect of incubation temperature (25, 30, 45 °C) and initial pH (4–10) on batch DBT-BDS (0.2 mM in ethanol) using growing cells of Rhodococcus spp Eu-32 has been studied (Akhtar et al et al., 2009) and showed that isolate Eu-32 is a neutrophilic mesophile and the maximum BDS-efficiency was recorded within 72h at a temperature of 30 °C and pH 7.0.

Arabian et al. (2014) proved that Bacillus cereus HN performs good BDS capacity over a wide range of temperature (30–40 °C), but the optimum is 40 °C, while Praveen Reddy and Umamaheshwara Rao (2015) reported the isolation of two DBT-biodesulfurizing Streptomyces species, Streptomyces sp. VUR PPR 101 and Streptomyces sp. VUR PPR 102, from oil contaminated sites with a maximum growth at 30 °C and pH 7.

In a study performed for the optimization of bacterial growth and BDS efficiency of R. erythropolis HN2, it was observed that the optimum pH and temperature for microbial growth (pH 7 and 30 °C) were slightly different from that obtaining maximum BDS efficiency (pH 6.69 and 27.47 °C). This was explained by the ability of HN2 to survive and propagate on the available added co-substrates, 0.09 M glycerol and 0.35 g yeast extract (Nassar et al., 2017). Similar observation was reported by Konishi et al. (1997) and ascribed this phenomenon in part to the weak desulfurizing activities of cell enzymes at such low temperatures. Nassar et al. (2017b) attributed the recorded large decrease in cell growth and, consequently, the decrease in the BDS activity of HN2 at higher incubation temperatures (> 30 °C) to the solubility of DBT. Moreover, at a low temperature (<25 °C), the insoluble DBT was not highly available for the microbial cells to induce its enzymatic activity. Although DBT is known to be an intrinsically xenobiotic water insoluble compound (Marzona et al., 1997), the water solubility of DBT is reported to increase with the increase in temperature (Kayser et al., 2002) and, according to Kim et al. (2004), the water-soluble compounds play an inhibitory role on cell growth and enzyme activities.

A study performed by Gunam et al. (2016), in biphasic batch biodesulfurization (1:5 O/W) of model oil 200 ppm DBT, in n-tetradecane using resting cells of Agrobacterium tumefaciens LSU20 of age 4 d at 150 rpm, showed the highest BDS rate at 37 °C and pH7 in the presence of glucose as a C-source, recording a DBT-removal percentage of 76.9% within 96 h. Similarly, Gunam et al. (2012) reported a DBT removal percentage of approximately 75.21%, using Pseudomonas sp. strain KWN5, under the same aforementioned conditions of LSU20, but KWN5 expressed nearly the same BDS efficiency within a pH range of 6.5–7.5, recording ≈ 72–75%, but KWN5 lost about 40% of its activity at pH < 5.5.

8.4 Effect of Dissolved Oxygen Concentration

Biodesulfurization (BDS) is the generic term which defines all processes where microorganisms catalyze the desulfurization reaction and remove the recalcitrant S-compounds under mild pressures and temperatures (Monticello and Finnerty, 1985). It has been described that aerobic, anaerobic, and facultative anaerobic microorganisms effectively degrade DBT and its analogs (McFarland, 1999), but the anaerobic BDS is characterized by a slow rate (Ohshiro and Izumi, 1999). The BDS capacity and intracellular enzyme activities are highly affected by the dissolved oxygen concentration in the broth. The 4S-BDS pathway is highly sensitive to oxygen availability even under oxygen limiting conditions (Martinez et al., 2016). Del Olmo et al. (2005b) reported that the concentration of the dissolved oxygen can be controlled by the agitation speed. However, sparging of gas increases turbulence and bubble release at the liquid surface produces dramatic changes in local velocity driven by surface tension. Consequently, it would have a negative influence on the performance of suspended cells. Thus, the mixing and oxygen transfer rates in a bioreactor depend on the power dissipated by agitation and aeration. If the stirrer speed was restricted to avoid shear effects, mixing or mass transfer would limit the performance of the culture. On the other hand, if agitation in the bioreactor exceeds a certain level, the hydrodynamic forces can affect the cells. Consequently, the optimal situation will take place when the mixing and mass transfer rates satisfy the oxygen and nutrient uptake rates by the cells and the overall process rate is determined by the cell metabolism (Gomez et al., 2015; Escobar et al., 2016).

It is worthy to know that a correct understanding of the role of oxygen transfer and uptake rates (OTR and OUR, respectively) in aerobic BDS processes is a crucial aspect to the design, operation, and scale-up of bioreactors (Garcia-Ochoa and Gomez., 2009).

In a study performed by del Olmo et al. (2005b) on Rhodococcus erythropolis IGTS8, the highest growth rate and maximum biomass concentration were obtained by culturing at 30 °C and pH 6.5 controlled by a diluted NaOH addition and a dissolved oxygen concentration constant value of 20% saturation. Under these conditions, optimal BDS capability was also developed by the cells under the same operating conditions although similar BDS capability was also obtained when pH was maintained at 6.5 using either diluted NaOH or Tris HCl buffer. On the other hand, high values of BDS were maintained during more growth time when dissolved oxygen was maintained at a constant value of 10% of saturation.

It has been reported that the dissolved oxygen concentration is a key factor in the flow of source carbon for cell growth and biodesulfurization capacity of R. erythropolis IGTS8 and that both may be modified by power input. This not only affects the growth rate, but also the enzymes developed by the cells which are afterwards used in BDS, being measured by resting cell assays (Gomez et al., 2006a). In a study performed by Gomez et al. (2015) on R. erythropolis IGTS8, it was observed during the growth curve on DBT at a different agitation speed, the dissolved oxygen (DO) concentration decreased to reach a minimum value corresponding to a point halfway through the exponential growth phase where the demand for oxygen by the cells is the highest. However, the change in oxygen concentration with time was lower with the increase in agitation speed. Moreover, under very low agitation conditions (100–150 rpm), the DO concentration reached nearly 0% only after a few hours of growth (between 12 and 15 h) remaining in that position until the end of the growth stage. The culture is oxygen limited under these operating conditions and the oxygen transfer rate controls the overall process rate and, consequently, the growth rate increases when the stirrer speed is increased. The specific growth rate and maximum cell growth were low at agitation speeds < 250 rpm. This was attributed to the fluid dynamic conditions in the bioreactor under that condition, resulting in the oxygen transport rate being insufficient (lower than the maximum uptake rate) and the DO becoming the limiting nutrient. It increased and remained nearly constant within an agitation speed of 250- 450 rpm, recording approximately 0.26 h^–1 and 1.8 / L, respectively. Then, both decreased at a higher agitation speed recording 0.146 h^–1 and 1.018 g/L at 700 rpm. Since the cells were adversely affected by the intense mechanical agitation, this proved that either hydrodynamic forces or oxygen level are affecting the cell metabolism, which can be detected by a decrease in the specific oxygen uptake rate, q_O2.

The growth rates of P. putida CECT5279 (Gomez et al., 2006b) and KTH2 (Escobar et al., 2016) are reported to be strongly dependent on the availability of dissolved oxygen concentration. This, consequently, affects the activities of the intracellular enzymes involved in the 4S-pathway. Escobar et al. (2016) proved the inactivation by oxidation of DszB desulfinase when the OTR increases, that is increasing the dissolved oxygen concentration available for the cells.

As the aeration in a bioreactor is somehow linked with the hydrodynamic damage to suspended cells (Chalmers, 1994; Garcia et al., 2001), Gomez et al. (2015) studied the effect of the gas flow rate on R. erythropolis IGTS8 biomass growth in the STBR at a constant stirrer rate of 250 rpm and varied gas flow rate of 1–10 L/min. This revealed that a constant specific growth rate of µ and maximum growth of 0.26 h^-1 and 1.73 g/L, respectively, and the evolution of dissolved oxygen (DO) concentrations were similar over the different studied air flow rates. Therefore, the change of the aeration rate between 1 and 10 L/min does not affect the specific growth rate and no hydrodynamic stress effect is detected under these conditions.

8.5 Effect of Agitation Speed

The effect of the mixing rate (that is the agitation speed or shaking speed) is a very important factor in bioprocesses. One of the challenges facing the scale-up of the BDS process is the turbulence effect. The increase of the power dissipation per volume unit, usually caused by an increase of the agitation, is often beneficial in most bioprocesses due to the improvement of mass transfer and mixing rates. However, excessive agitation causes a concomitant increase in hydrodynamic forces, which may become a negative factor due to the interaction of turbulence with living cells, also called hydrodynamic stress. These restrictions have great influence on the bioreactor operating conditions, the scale-up criteria, and the selection of the type of bioreactor to be used.

The shear effects of flow turbulence inside the bioreactor have a great influence on the cellular response, their morphology (Märkl et al., 1991; Sahoo et al., 2003; Chisty, 2010), their metabolic and enzymatic activities (Hewitt et al., 1998; Sahoo et al., 2003), and, consequently, affects the growth (Sahoo et al., 2003; Hodaifa et al., 2010), the production (Calik et al., 2004; Olmos et al., 2013), and the nutrient consumption rates (Prokop and Bajpai, 1992; Olmos et al., 2013). The effects of agitation can be evaluated in terms of the threshold values of either shear rate, shear stress, or stirrer speed, above which the growth rate and cell viability (Meijer et al., 1994; Yepez and Maugeri, 2005; Kao et al., 2007), product yield (Kao et al., 2007; Olmos et al., 2013), or some other critical culture parameters are significantly affected (Bronnenmeier and Markl, 1982; Arnaud et al., 1993).

It is important to reach the optimal agitation level which yields the optimal growth rate or biomass concentration with the optimal enzymatic activities. For cell suspension cultures, the independent effect of agitation is difficult to quantify as it is coupled with various other phenomena (mixing and oxygen transfer rates and hydrodynamic stress, mainly). In many cases, microbial growth rate is claimed to increase by improving the oxygen transfer rate, therefore, the positive effect of agitation is asserted, which is also able to compensate for the possible cell damage by shear stress. When understanding the influence of hydrodynamic conditions in the bioreactor on the biocatalyst production of biodesulfurizing strains, it is important to separate the positive influence of the transport rate from the possible damage due to shear effects. Thus, for an adequate description of the system, it is necessary to know the dependence of the oxygen transfer coefficient on fluid dynamics and the evaluation of the associated physical and biological parameters.

Wang et al. (2006) reported the maximum BDS efficiency of model oil (1 mmol/L DBT in n-hexadecane) by resting cells of Corynebacterium sp. ZD-1 was 1:2 (O/W) and 250 r/min. This was discussed at lower rotation rate, where increasing the shake rate improves the mixing of the two phases, thus accelerating the transfer of DBT to the cells in the water phase and enhancing the transport of oxygen as well. Thus, the concentration of 2-HBP increased with the increasing rotation rate before it reached 250 r/min, but at a higher rotation rate, the mass-transfer limited the BDS process and turned it to a controlled reaction. Moreover, too high a rotation rate would be harmful to the bacteria.

Abin-Fuentes et al. (2013) applied a mixing speed of 500 rpm to minimize the mass transport limitations in a batch BDS using R. erythroplos IGTS8 in a bioreactor with a bi-phasic system (aqueous/model oil of DBTin n-hexadecane).

Gomez et al. (2015) studied the effect of agitation speed on growing cells of R. erythropolis in a stirred tank and shaken flasks. The growth rate was found to be increased when the stirrer speed increased between 100 and 450 rpm. However, at higher stirrer speeds between 500 and 700 rpm, the cell growth rate was sharply decreased. This decrease, with a concomitant decrease in µ and , indicated that the hydrodynamic forces or the oxygen level affected the cell metabolism and can be detected by a decrease of the specific oxygen uptake rate, q_O2 (Garcia-Ochoa et al., 2015). Not only this, but Calzada et al. (2009a,b) proved that this behavior of metabolic changes also affects the BDS-capacity, which is directly related to the 4S-route enzyme (DszA, DszB, DszC and DszD) activity. Gomez et al. (2015) concluded that the values of the growth parameters obtained for the runs of R. erythropolis IGTS8, when the cells are cultured in shaken flasks (in orbital shaker at 210 rpm) and in the bioreactor (STBR) between 250 and 450 rpm, were very similar. Those recorded were 0.26 h^–1 for the specific growth rate and 1.8 g/L for the maximum biomass concentration. Thus, the specific growth rate in shaken flasks at 210 rpm in orbital shaker is the same as that found in STBR between 250 and 450 rpm, with the air flow rate used (2 L/min) and the tank, stirrer, and gas distributor geometry employed in that study. Therefore, fluid dynamic conditions must be similar. Unless ptherwise therwise stated, the relationship between OTR, OUR, and the shear stress must be similar in both types of operations.

Upon studying the effect of agitation speed on the growth and BDS capacity of P. putida KTH2 (Escobar et al., 2016) in a stirred tank bioreactor (STBR), the obtained experimental results indicated that cultures were influenced by the fluid dynamic conditions in the bioreactor. An increase in the stirrer speed, from 400 to 700 rpm, expressed a positive influence on the cell growth rate. This was attributed to the consequence of the combined effect of an improvement of the mass transfer rate and a decrease in the resistance to the transport of nutrients to cells, mainly because the culture is oxygen limited (that is under aerobic conditions). However, the increase of agitation from 700 to 2000 rpm hardly expressed any influence on the growth rate. Thus, it was concluded that no hydrodynamic stress was observed for P. putida KTH2 until 2000 rpm, where the kinetic growth parameters, increased with the stirring speed from 400–600 rpm and remained constant between 700–2000 rpm. Thus, the µ_max and increased from 0.439 to 0.520 h^-1 and from 2.983 to 4.916 g/L when the speed increased from 400 to 700 rpm, respectively. Although, other microorganisms, such as R. erythropolis IGTS8, are reported to suffer this stress on growth at much lower stirrer speeds (Gomez et al., 2015). The slightly lower values of growth parameters at relatively lower speeds (< 700 rpm) was attributed to the amount of dissolved oxygen, as the oxygen transfer rate is the limiting step of the overall growth process. The consumption rate of nutrients, such as glycerol and glutamic acid, also increased with a speed of 400–700 rpm. The effect of fluid dynamics on the cell development of the BDS capacity of the cells during the cell growth was different and, consequently, the activities of the intracellular enzymes involved in the 4S-pathway changed with the dissolved oxygen concentration. The enzyme activities have been evaluated in cells at several growth times and different hydrodynamic conditions. An increase of the agitation from 100 to 300 rpm had a positive effect on the overall BDS capacity of the cells during growth. However, the BDS capacity decreased at higher stirrer speeds, the activity of the enzyme monooxygenases DszC and DszA was dramatically decreased, and the highest value of the activity of the DszB enzyme was obtained with cells cultured at 100 rpm and decreased at a higher speed, becoming the step that controls the overall rate of the process (that is to say, the rate limiting step). Escobar et al. (2016) proved that the desulfinaze enzyme D_SZB is adversely affected at two levels: by the growth time of the cells and by the increase of the stirring speed during growth. Thus, at higher growth agitation speed, with higher improvement in the oxygen transferred in the culture, although P. putida KTH2 showed an improved specific growth rate, it expressed a dramatic decrease in the BDS capacity.

The BDS efficiency of heavy crude oil was reported to increase with the increase of rotation speed, recording 48% and 76% at 180 and 250 rpm, respectively, in shaken flasks in a batch BDS with a 1/3 O/W ratio using growing cells of Gordonia sp. IITR100 (Adlakha et al., 2016). However, upon the application in a pilot study, commercial diesel oil with an initial S-content of 50 ppm in 5 L bioreactor of 2 L working capacity using a 1/3 O/W phase ratio and 15 g/L sucrose was used as a carbon source. The impeller speed was optimized to ascertain uniform dispersion of oil droplets in an aqueous medium and obtain a representative sample using different agitation speeds of 300–800 rpm. Though the dispersion as measured by uniformity of the oil in the outlet samples was found to be satisfactory at the stirrer speed of 400 rpm, it was not considered adequate for proper oxygen and other nutrient transport. Therefore, the range was narrowed down with a higher starting agitation (500–625 rpm). Higher agitation rates (> 625 rpm) were not considered as they might lead to cell damage by shear stress without giving any significant increase in the transport of nutrients. Agitation at 600 rpm was found to be optimal and the S-content reduced to 15 ppm within 3 days and no further removal occurred at longer incubation periods. However, the growth continued after 3 days and that was explained by the presence of sulfur released in an aqueous phase and with a residual carbon source which could have still supported the growth. Reduction in sulfur was also accompanied by increased bisphenol levels. Sucrose concentrations decreased from about 15 g/L to 5.6 g/L by the end of the 4^th day and no further decrease was observed thereafter.

Peng and Zhou (2016) studied the effect of an initial biomass concertation (8.4 and 25.6 g DCW/L) and agitation speed (300 and 600 rpm) on a batch BDS of crude oil (0.3 O/W) using resting cells of Rhodococcus sp. MP12 that were pregrown on DMSO. The maximum desulfurization activity, which was measured as sulfate production rate (µmole sulfate/g DCW/h), occurred within the first 48 h and then decreased with further increments of the incubation period. The low concentration of initial biomass expressed higher BDS efficiency than the higher biomass concentration. The best was 8.4 g DCW/L, however, the maximum desulfurization activity of high density cells (25.6 g DCW/L) increased sharply by approximately 90% when the agitation speed was raised from 300 to 600 rpm. This was explained by a higher agitation speed of 600 rpm better breaking up high density cell aggregates and, thus, improving the mass and oxygen transmission due to decreased aggregate size, lower fraction of cells in aggregates, and higher fractions of free and oil-adhered cells in a crude oil system, which leads to an increase in the total desulfurization rate, but upon the increment of agitation speed from 300 to 600 rpm with low cell density cultures, there was no statistical significant influence on the desulfurization activity (p > 0.05). This indicated that the agitation speed at 300 rpm might have been enough to break up cell aggregates of low density cells to overcome mass transport limitations and, when increasing the agitation speed to 600 rpm, it would have been hard to continually improve the biocatalyst’s kinetic rate for desulfurization activity.

Nassar et al. (2017b) observed that the growth and BDS activity of R. erythropolis HN2 is highly affected by the shaking speed, where the optimum speed was found to be 150 rpm, recording a BDS of 80% from the initially added 1000 ppm DBT. The growth was sharply decreased at a higher shaking speed (> 150 rpm) and, consequently, the BDS decreased to 73%. This was explained because at a relatively lower range of shaking speed (< 150 rpm), increasing the shaking speed improved the mixing and contact of an insoluble substrate (DBT) and microbial cells (HN2) and also would have enhanced the transport of oxygen. However, Wang et al. (2006), Purwanto et al. (2009), and Adlakha et al. (2016) reported that a high shaking speed is harmful to the bacteria due to the turbulence increment which would cause cell rapture. Thus, at a higher shaking speed, the mass-transfer limiting the BDS-process would be reaction controlled.

8.6 Effect of Initial Biomass Concentration

Several studies concluded that the BDS yield is substantially higher at lower oil fraction phases and DBT concentrations, but higher cell concentrations (Maghsoudi et al., 2001; Abbad-Andaloussi et al., 2003; Luo et al., 2003; Jia et al., 1996; Rashtchi et al., 2006). A high cell density can reduce operating costs (Arabian et al. 2014), however, Nassar et al. (2017b) observed, upon the optimization of initial inoculum size for a shaken flask batch DBT-BDS process using growing cells of R. erythropolis HN2, that the increase of an initial inoculum size expressed a negative impact on the microbial growth and, consequently, BDS-efficiency. According to Abusham et al. (2009), the high initial inoculum size would cause a lack of oxygen and depletion of nutrients in the culture medium.

The effect of the initial biomass concentration (20–120 g DCW/L) of resting cells of Rhodococcus sp strain P32C1 (which was formerly identified as Corynebacterium sp. P32C1 by the National Collection of Industrial and Marine Bacteria (NCIMB Japan)) in a batch BDS of model oil 24 mM DBT in n-hexadecane and 50 vol.% (O/W) bi-phasic system was studied (Maghsoudi et al., 2001). The production rates of 2HBP at higher cell concentrations were lower, probably due to mass transfer limitation, especially for oxygen transfer needed for the oxidation reaction of DBT, but the maximum conversions of DBT were higher.

The effect of the initial biomass concentration (20–80 mg DCW/L) of resting cells of Gram-negative P. delafieldii R-8 in a biphasic BDS-system (1:1 O/W) of model oil 1 mM DBT in dodecane was that the DBT-BDS rate was decreased with increasing cell concentration due to the mass-transfer resistance, which is the controlling step in these cases. Also, at a higher initial biomass concertation the separation after the BDS process was difficult and the results showed that almost all cell pastes suspended at the organic–aqueous interface when the cell concentration was 20 mg/mL after the centrifugation to separate the oil from the aqueous phase after finishing the reaction. Not only this, but it was also observed, at high cell concentration, that part of the cells suspended at the organic–aqueous interface while others precipitated at the bottom of the centrifuge bottle, which might mean that these cells precipitated at the bottom did not contact well with the oil phase to react with DBT. From such phenomena, it was speculated that the desulfurization process might be limited by the rate of surface renewal as a new biocatalyst interacts with the organic–aqueous interface to acquire the DBT substrate as found by Kaufman et al. (1998).

The effect of the initial biomass concentration of resting cells of Corynebacterium sp. ZD-1 in a batch BDS process of 0.5 mmol/L DBT dissolved in ethanol was studied (Wang et al., 2004), where the production rate of 2-HBP was higher at a lower initial biomass concentration and recorded its maximum (0.067 mmo/L) at 9.2 g DCW/L. This was attributed to the mass transfer limitation at higher cell concentrations, especially, oxygen transfer, which is needed for the oxidation of DBT.

Caro et al. (2007a) reported in aqueous phase study, with an initial DBT concentration of 54.27 µM, that the maximum specific HBP production rate of 6.3 mmol HBP produced/kg DCW/h with 70% DBT removal at P. putida CECT 5279 initial biomass concentration of 8 g/L which decreased at a higher biomass concentration probably due to oxygen mass transfer or the inhibitory effect of 2-HBP, while R. erythropolis recorded complete DBT removal at an initial biomass concentration of 28 g/L, with a constant maximum specific 2-HBP production rate of 5 mmol HBP produced/kg DCW/h within a range of 2 to 16 g/L initial biomass concentration.

The effect of initial biomass concertation in batch shaken flasks of a DBT–BDS process was studied using Rhococcus spp Eu-32 and it was depicted that the rate of BDS decreased at a higher initial inoculum size (> 4 g/L) (Akhtar et al., 2009). This indicated that the oxygen is a limiting factor for dibenzothiophene desulfurization by the growing cells. Mohebali et al. (2007) reported that increasing cell concentrations led to a decrease in the dibenzothiophene degradation by the formation of cellular flocs due to the hydrophobic nature of biodesulfurizing bacteria. Akhtar et al. (2009) assumed that the same phenomenon may have been taking place in the case of Eu-32 because the formation of cellular colloidal material at high cell mass concentrations could limit the BDS activity by lowering the mass transfer of DBT and dissolved oxygen available to the growing bacterial aggregates.

Arabian et al. (2014) reported that the BDS efficiency in a biphasic system (aqueous/500 ppm DBT in dodecane 1:2 O/W), using Bacillus cereus HN, increases with the increment of biomass concentration due to the increase of the available biocatalyst, but to a certain limit. At a higher cell density (3x10⁷), the percentage of desulfurization would fall. This can be explained by the mass-transfer limitations and inability of some cells to be in contact with the organic phase. In fact, the rate at which DBT can be converted by cells is higher than the mass transfer rate of DBT from the organic phase into the cells. Therefore, the mass transfer of DBT from an organic phase into the cells controls the overall process.

8.7 Effect of Biocatalyst Age

One of the important factors that recently gained attention is the age of the biocatalyst. Table 8.1 summarizes the published BDS-efficiencies of some bacterial strains at the selected optimal resting cell age.

A maximum DBT conversion, using P. putida CECT5279, is reported to be achieved when cells collected at 9 h of growth time are employed for DBT desulfurization in resting cell conditions (Martin et al., 2004; 2005). It was proved in another study of BDS using resting cells of CECT5279 that the transport of all 4S-route intermediates across the cell membrane is not a mass transport controlling resistance and that neither the intracellular concentrations of reducing cofactors or the NADH dependent reductase HpaC have influence in the desulfurization rate (Alcon et al., 2005). Moreover, upon measuring the evolution of in vivo enzymatic activities of DszA, DszB, and DszC, along the growth curve of P. putida CECT5279 maximum activities of both flavin dependent monooxygenases, DszC and DszA, were found in cells of 23 h of growth time and a maximum activity for the desulfinase, DszB, was observed in cells of 5 h of growth time of P. putida CECT5279. These different patterns of expression of monooxygenases, DszA and DszC, and desulfinase, DszB, along the growth curve explained the behavior of cells collected at 9 h of growth time (Calzada et al. 2009a). Thus, upon using a biocatalyst mixture of resting cells collected after 5 and 23 h in a 1:1 ratio, the BDS efficiency was higher relative to simple biocatalysts and composed exclusively by 9 h cells (Calzada et al. 2009b). However, upon another study for the optimization of the biocatalyst mixture, a total biomass concentration of 2.1 g DCW/L of a cell mixture containing 66.7% of 23 h growth time cells that has a 1:2 ratio of cells collected at 5 and 23 h of growth time, expressed the best BDS-efficiency in resting cells among all the proposed biocatalyst formulations. Thus, this was the best DBT conversion and reduction time needed for BDS (Calzada et al., 2011). Del Olmo et al. (2005a) reported that the maximum DBT-BDS activity of R. erythropolis IGTS8 is achieved at the end of the exponential phase of the growth of the cells (between 15 and 25 h of growth time).

Rashtchi et al. (2006) reported that the activity of strain RIPI-22 is sensitive to the growth phase. The cells harvested in the late-exponential growth phase displayed the maximum specific activity which was 2.03 mmol 2HBP/kg DCW/h. Gomez et al. (2015) studied the effects of R. erythropolis of different biocatalyst ages (16, 24, and 30 h) in shaken flasks at 210 rpm and STBR at different agitation intensities (from 100 to 700 rpm). Short age biocatalysts (16 h) yielded a lower HBP concentration, thus expressimg a lower BDS capacity than those of longer ages (24 and 30 h), which expressed the same BDS capacity.

However, Gün et al. (2015) reported the BDS of DBT by the inoculation of the batch process by Sulfolobus solfataricus P2 cells grown at the mid-log phase.

Escobar et al. (2016) studied the effect of P. putida KTH2 biocatalyst age on desulfurization efficiency. The results revealed that, under relatively low agitation conditions (from 100 to 300 rpm), the DBT consumption rate was faster on more advanced age cells; that is, higher HBP concentration is obtained with cells of 23 h of growth time. However, at relatively higher agitation speeds (about 500 rpm), there were increases in the DBT consumption rate and HBP production rate to 15 h of growth age. Nevertheless, for cells of 23 h age, a decrease has been observed in the consumption of DBT and a smaller HBP production, but with a higher agitation speed of 800 rpm, all cell ages performed lower DBT consumption and, consequently, lower production of HBP.

8.8 Effect of Mass Transfer

Another important parameter is the influence of mass transfer on the overall reaction rate and process yield as the reaction is carried out in a complex medium with two immiscible liquid phases. This parameter is essential for the implementation of the BDS-technology of fuels. It depends on the hydrophobicity of the compound and its alkylation degree, molecular structure, and weight.

Marcelis et al. (2003) have indicated that the greatest resistance to the mass transport of compounds from organic to an aqueous phase occurs in the water phase, but there has also been indication that it is the microbial process which is the global rate limiting step.

Caro et al. (2007a) reported the effect of mass transfer limitation in a biphasic system with an initial DBT concentration of 54.27 µM, using R. erythropolis IGTS8 and P. putida CECT 5279, which proved the results mainly depend on the hydrophobicity of the biocatalyst itself. The desulfurization yield increased with the increase of an initial biomass concentration recording 41.4% at 24 g/L of initial CECT 5279 biomass concentration with a low production rate of 2-HBP. Nevertheless, the BDS yield of IGTS8 was higher, recording 80%, with an initial biomass concentration of 8 g/L. Then, is kept stable at a higher initial biomass concentration due to the saturation of the interface surface by the biocatalyst cells. Thus, increasing the interface surface, the process would achieve better conversion levels, but the specific 2-HBP production rate was also low due to both the inhibition and mass transfer limitations. Caro et al. (2007b) reported that in spite of the lower HBP inhibition effects with biphasic media, other pathway compounds accumulated in the aqueous phase can be responsible for inhibition.

Upon combining the oil fraction phase, substrate concentration, and cellular density effects, mass transfer limitation is responsible for the BDS yield in resting cell system conditions in low oil fraction and low substrate concentrations, but where high cell densities were used (Jia et al., 2006; Caro et al., 2007b).

8.9 Effect of Surfactant

DBT as a model for recalcitrant organosulfur compounds (OSCs) is known to be a very hydrophobic compound exhibiting water solubility around 0.005 mM. This very low concentration can be increased by the action of biosurfactants produced endogenously by the applied microorganisms (i.e. the biocatalyst) used in the BDS process (Maghsoudi et al., 2001). However, it has been reported that the capability of the bacteria to pick up the DBT from the organic phase and its subsequent insertion inside the cells is independent of the produced biosurfactants (Noda et al., 2003). R. erythropolis IGTS8 is known to be characterized by a high hydrophobicity (Abbad-Andaloussi et al., 2003) and the uptake of the DBT takes place on the interface surface (Monticello, 2000; Le Borgne and Quintero, 2003). However, high mass transfer limitations occur when this surface is saturated by adhered biocatalyst cells (Maghsoudi et al., 2001). Marzona et al. (1997) reported that the addition of cyclodextrins improves the diffusion of DBT into the aqueous phase upon the formation of DBT-cyclodextrin complexes. Moreover, it takes up the HBP, avoiding the potential inhibition effects produced by the 4S-pathway’s final product accumulation. Cyclodextrins cannot be metabolized by the microbial cells and have no toxic effects on the cells (Setti et al., 2003). Upon the addition of 5% (v/v) of the non-ionic surfactant Tween-80 (polyethylene glycol sorbitan monooleate) and an oil-in-water emulsifier in a batch BDS process of 0.3 mM DBT using Gordonia sp. CYKS1, the growth rate and BDS-capacity increased from 0.06 h^–1 and 4.70 µmol/L/h to 0.08 h^–1 and 5.90 µmol/L/h (Kim et al. 2004). Feng et al. (2006) reported the enhancement effect of Tween 80 on the BDS of Rhodococcus species 1awq in an aqueous one-phase system where the addition of 0.4% Tween 80 enhanced the growth and BDS efficiency of 0.5 mM DBT. The specific desulfurization activity was 1 µmol/g/min. This activity was 35% higher than that seen without Tween 80. This was explained by the nonionic chemical surfactant’s, Tween 80, ability to enhance BD activity in both aqueous and biphasic systems by reducing the concentrations of the products around the cells. Tween 80 can also reduce the concentrations of hydrophobic substrates associated with the cells. As long as the concentrations support adequate reaction rates, this reduction will not limit the overall conversion. If a substrate is also inhibitory at high concentrations, the addition of Tween 80 is, theoretically, stimulatory.

Wang et al. (2006) studied the effect of different surfactants, including Triton-100X, Tween-80, Brij 35, and cyclodextrin, on the biphasic batch of BDS (DBT in n-hexadecane) in 72 h at 30 °C, pH, and 150 r/min, using resting cells of Corynebacterium sp. ZD-1, that were harvested at the late exponential phase. The solubility of DBT was found to linearly increase with the increase of surfactant concentration. The solubility enhancement efficiencies of surfactants above the critical micelle concentration (CMC) followed the order Triton-100X > Tween-80 > Brij 35 > cyclodextrin, but both Brij and Triton-100X inhibited DBT desulfurization. β-cyclodextrin produced almost no effect. Nevertheless, Tween-80 increased the desulfurization efficiency. This was attributed to the toxicity of Brij and Triton-100X to the bacteria. Although β-cyclodextrin did not inhibit cells growth, its ability for DBT solubilization was much less than Tween-80, where Tween 80 increased the growth in DBT-cultures because Tween-80 increased the absorption and degradation of the bacteria to DBT and supplied the bacteria with enough sulfur-source necessary for growth. The optimum value of Tween-80 concentration for desulfurization was found to be 0.5 g/L. The amount of 2-HBP formed with 0.5 g/L Tween-80 present was about 50% more than that formed without surfactant. This was better than the effect of cyclodextrine on R. erythropolis IGTS8 (Setti et al., 2003).

In studies of BDS on bunker oil (heavy oil), BDS efficiency was reported to be only 2–3% by different microorganisms (Jiang et al., 2014). However, the activity is reported to increase up to 36–50% by use of either deasphalted oil or the use of surfactants, which decrease the viscosity of heavy oil (Li and Jiang, 2013; Jian et al., 2014). Throughout the addition of 0.5 g/L Tween-80 in a batch BDS of heavy crude oil of 1/3 O/W using Gordonia sp. IITR100, the BDS percentage increased from 48% to 65%. The higher BDS efficiency was nearly equivalent to that obtained after two successive rounds of 7 days. Thus, addition of surfactants eliminated an extra BDS-step. This was attributed to the addition of surfactants, which resulted in overcoming mass transfer problems (Adlakha et al., 2016).

Span-80 and Tween-80 are reported for the enhancement of BDS efficiency using Pseudomonas delafieldii (Li et al., 2008). The addition of nonionic surfactants, Tween-80 or Span-80, to a biphasic system, inoculated with immobilized R. erythropolis R1 alginate beads, also enhanced the BDS efficiency and increased the production of 2-HBP (Derikvand et al., 2014) since both surfactants have an oleate-chain with 18 carbons and an unsaturated bond that could improve the stability of the O/W interface layer. The surfactants would enhance DBT dissolution in the aqueous phase and also facilitate its penetration into the immobilizing beads. Moreover, 2-HBP as a product of DBT-BDS, had a limited solubility in the aqueous phase and displayed an inhibitory role on the BDS efficiency by aggregation around the cells. Since, the surfactants also increase the solubility and dispersion of 2-HBP, they reduce its concentration around the cells and, consequently, improve the BDS efficiency (Li et al., 2008a). However, Span-80 expresses a higher BDS efficiency than that obtained with Tween-80 (Derikvand et al., 2014) since the average droplet sizes produced by Span 80 are smaller than those of Tween 80 (Schmidts et al., 2009) and reported higher DBT removal efficiency, probably due to differences in the size of the droplets.

However, it should be noted that in oil desulfurization processes the production of a large amount biosurfactants by biocatalysts would enhance the bioavailability of organic sulfur compounds in fuel oils and at the same time increase the reaction rate by improving the contact between the oil and aqueous phases. However, it should be noted that the biosurfactants could cause the formation of excessively stable emulsion and, thus, may cause serious phase separation problems in real processes and the toxicity of OSCs would be increased in the presence of biosurfactants.

8.10 Effect of Initial Sulfur Concentration

Sulfur accounts for approximately 0.5–1% of the dry weight of the cell (Kertesz, 2000), thus, the required sulfur level for cell growth is limited. For example, Rhodococcus sp. 1awq was found to require only 0.5 mmol/L Na₂SO₄ for the achievement of maximum cell growth (Xu et al., 2002). Although it is known that as water-solubility of compounds increases, its inhibitory effect on cell growth and enzymatic activity increases. Otherwise, with the extremely low solubility of DBT in water (around 0.005 mM), it precipitates on being added to the aqueous culture medium; DBT in solid form in the medium would be expected to have negligible effects, if any, on desulfurization activity and cell growth, but DBT is intrinsically a xenobiotic compound and there have been several reports addressing that a high concentration of DBT had inhibition effects on cell growth and desulfurization activity (Oshiro et al., 1995; Setti et al., 1996; Goindi et al., 2002; Ansari et al., 2007; Dejaloud et al., 2017). This might be attributed to the secretion of biosurfactants, as most of the microbial strains with DBT desulfurization activity are known to secrete some biosurfactants to solubilize and thus enhance the bioavailability of DBT. Consequently, upon the secretion of the biosurfactant, the effects of the amount of DBT added would not be limited by its intrinsic solubility to water.

The different reported biodesulfurizing microorganisms have different optimum DBT concentrations and incubation periods. For example, Gordonia alkanivorans strain 1B reported 64.8% of 0.5 mM DBT within 120 h (Van der Ploeg and Leisinger, 2001), Microbacterium ZD-M2 reported 100% of 0.2 mM DBT within 58 h (Li et al., 2005), Rhodococcus erythropolis R1 reported 100% of 0.3 mM DBT within 72 h (Etemadifar et al., 2008), Microbacterium sp. NISOC-06 reported 90.6% of 1 mM DBT within 120 h (Papizadeh et al., 2010), and Stenotrophomonas sp. NISOC-04 reported 82% of 0.8 mM DBT within 48 h (Papizadeh et al., 2011).

The bacterial growth of Rhodococcus sp. strain P32C1 on different initial concentrations of DBT 0.05–0.5 mM was generally the same. However, the resting cells collected at the late exponential phase, from the 0.1 mM DBT cell culture, showed the highest BDS-activity on 0.5 mM DBT which was 30 mmol 2-HBP/kg DCW/h (Maghsoudi et al., 2001). In a study performed on model oil, DBT in n-hexadecane and the BDS efficiency of resting cells of Staphylococcus sp. strain S3/C increased with the increase of initial DBT concentration, recording its maximum at 57% at 463 mg/L, with initial sulfur/biomass (0.16). Further increase in initial sulfur to 800 mg/L (S/B 0.31) declined the sulfur removal to 32% and attributed this to the limitation of O₂ in the biphasic reaction mixture (Goindi et al., 2002). A similar observation was reported by Guerinik and Al-Mutawah (2003) for model oil with DBT in n-tetradecane, where the specific desulfurization activity increased as DBT concentration increased. However, there is an optimum DBT concentration beyond which there is no effect on the activity. This is the point where mass transfer ceases to be a problem and some other factor, like product inhibition, becomes operational. Moreover, the BDS was limited by the availability of DBT to the organism and the interfacial mass transfer through the aqueous-organic layer was confirmed to be a limiting factor. In another study performed by Kim et al. (2004), the BDS rate increased as the initial DBT concentation increased from 0.3 to 1.5 mM, recording approximately 4.7 and 12.5 µmol/L/h, respectively, and then sharply decreased at a higher initial DBT concentration recording 4.5 µmol/L/h at 4.0 mM DBT. Ansari et al. (2007) reported the inhibitory effects of DBT for Shewanella putrefaciens NCIMB 8768 at concentrations ≥ 0.6 mM.

Casullo de Araújo et al. (2012) reported that DBT expressed the same minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) (3.68 mM) on Serratia marcescens UCP 1549. Moreover, the specific growth rate in a batch BDS of different initial DBT concentrations at 28 °C, recorded 0.15, 0.11, and 0.05 h^-1 with a generation time (T_G) of 4.6, 6.27, and 13.8 h, with 0.5, 1.0, and 2.0 mM of DBT, respectively. However, the specific desulfurization rate recorded 0.038, 0.022, and 0.038 h^-1, respectively. After 96 h, the percentage desulfurization was 50, 84, and 98%, respectively, with a complete removal of 0.5 and 2 mM DBT within 120 h, but complete removal of 1 mM occurred within a longer incubation period of 144 h.

The BDS of model oil (DBT in dodecane) using Bacillus cereus HN in a biphasic system 1:10 O/W showed an increase in the BDS efficiency as the DBT concentration increased and was attributed to the enhancement in the DBT diffusion to the oil-water interface (Arabian et al., 2014).

The specific growth rate of the acidophilic and hyper-thermophilic Sulfolobus solfataricus P2 was reported to decrease with the increase of DBT concertation (Gün et al., 2015) and recorded its highest BDS at 0.1 mM DBT, producing 1.23 µ mol 2-HBP/h/g DCW in a one phase BDS system.

Dejaloud et al. (2017) reported that the increase of initial DBT concentration form 0.03 mM to 0.05 mM increased the biomass concentration and BDS-efficiency of Ralstonia eutropha (PTCC1615). However, further increase in initial DBT-concentration decreased the desulfurization activity of the cell.

8.11 Effect of Type of S-Compounds

Not all microorganisms utilize the same pathway for the BDS of different organosulfur compounds (OSCs). Also, not all the microbial strains utilize all the OSCs. They also never use all the OSCs with the same rate or efficiency. This is related to the different molecule structures of substrates such as the extent of alkyl group substitution (Grossman et al., 2001), as well as the enzymes involved in the BDS of each S-compound.

The induction of the dsz operon by DMSO in Rhodococcus sp. 1AWQ has shown similarities to DBT (Ma et al., 2006) and Mohebali et al. (2008) showed that the 2-HBP production of resting cells grown on DMSO was higher than that of DBT. In another study, Jiang et al. (2002) reported that the shortest induction time and highest growth rate for Pseudomonas delafieldii R-8 occurred with DMSO, relative to DBT and MgSO₄. Not only this, but Jiang et al. (2002) reported the broad versatility of two bacterial isolates, Pseudomonas delafieldii R-8 and Nocardia globerula R-9, to utilize different S-compounds as a sole S-surfur source. The most important observation was their ability to desulfurize 4,6-DMDBT at a higher rate than DBT, recording a desulfurization rate of 2.46 and 2.25 mg DMDBT/g DCW/h and 2.26 and 1.98 mg DBT/g DCW/h for R-8 and R-9, respectively, with a higher desulfurization rate for DBT-sulfone relative to DBT at 2.35 and 2.45 mg DBTO₂/g DCW/h, respectively. They are also capable of desulfurizing BT and DBS, recording 1.34 and 1.04 mg BT/g DCW/h and 1.93 and 2.06 mg DBS/g DCW/h, respectively. The Gram +ve Mycobacterium sp. ZD-19 reported to desulfurize different S-compounds in the following order: Th>BT>DPS > BT>4,6-DMDBT (Chen et al., 2008a). However, the rate of BDS of DBT was decreased in the presence of 4,6-DMDBT, although DBT appeared to be attacked preferentially by ZD-19 enzymes when DBT and 4,6-DMDBT coexisted. This is refered to as the substrate competitive inhibition. Resting cells of ZD-19 recorded a specific desulfurization rate of 2.984, 1.756 mM S/kg DCW/h for DBT and 4,6-DMDBT, respectively, in a single substrate system, with an overall desulfurization percentage of 100 and 57.3% from 0.5 mM DBT and 4,6-DMDBT, respectively, within 8 h. However, in a binary substrate system, the specific desulfurization rate recorded 1.78 and 0.624 mM S/kg DCW/h, with a BDS percentage of 91.6 and 53.2 of 0.3 mM DBT and 0.2 mM 4,6-DMDBT, respectively, with a total S-removal of 77% within 8 h.

In an attempt to study the substrate specificity, Konishi et al. (2002) used the cell-free extracts of a desulfurizing mesophile, Rhodococcus erythropolis KA2–5-1 (the Dsz system), and Escherichia coli JM109, which possesses the desulfurizing genes of thermophile Paenibacillus sp. A11–2 (the Tds system), to investigate the reactivity of desulfurizing enzymes toward 4,6-dialkyl dibenzothiophenes (4,6-dialkyl DBTs) and 7-alkyl benzothiophenes (7-alkyl BTs). Both systems desulfurized DBT and all the studied 4,6-dialkyl DBTs, including 4,6-DMDBT, 4,6-DEDBT, and 4,6-DPDBT, to their corresponding hydroxybiphenyls, but they did not desulfurize 4,6-DBDBT. Although some alkylated BTs were degraded by the Dsz system, no desulfurized compounds were detected. This was attributed to the limit of the catalyzing ability of the desulfurizing enzymes. The desulfurization activity of various alkylated DBTs has been examined by the recombinant KA2–5-1/pRKPBP cells using an oil-water resting cell system (Kobayashi et al., 2001), where the bacterial cells were not able to incorporate highly alkylated DBTs, such as 4,6-dipropyl DBT, from the oil phase. The reactivity of the Tds system toward alkylated BTs was higher than that of DBT. In contrast to the Dsz system, the Tds system yielded desulfurized compounds from BT and all of the studied alkylated BTs: 7-MBT, 7-EBT, 7-PBT and 7-HBT. The 7-Hexyl BT was more efficiently degraded by Tds than the Dsz system (70% vs 30% of 0.5 mM in 1 h reaction), although the rate of degradation was the lowest. Konishi et al. (2002) also pointed out the strong effect of the position of the alkyl chain on the reactivity of Dsz enzymes. An alkyl chain near the sulfur atom of the BT molecule is evidently desirable for enzyme reactivity in contrast to chemical catalysts. The presence of alkyl groups attached to the thiophene ring of the BT molecule is important for complete desulfurization in the Dsz system. The reactivity in the Dsz system was also found to be heavily affected by the position of the alkyl group attached to the ring of the BT molecules. The substrates with the alkyl group on a non-thiophene ring of the BT molecules exhibited poor reactivity. The desulfurized phenolic products were observed for only 2-methyl, 2-ethyl, 3-methyl, and 2,7-diethyl BTs. The Dsz system exhibited a reduced desulfurization rate with the increase in the length of the alkyl chain attached to the DBT molecule. 4,6-dimethyl- and diethyl-DBTs were completely desulfurized to corresponding phenolic compounds, whereas a small amount of desulfurized compounds (less than 5% of the initial substrate concentration, 0.5mM) were detected by GC analysis from 4,6-dipropyl DBT in spite of the decrease in substrate. This was explained by the probability of the conversion of most of the 4,6-dipropyl DBT to water-soluble intermediates, such as sulfonate, which could not be extracted by the organic solvent. The reactivity of Tds toward DBT was weaker than that of the Dsz system, where the Tds enzymes exhibited much stronger activity (about 1.5–2 times) toward alkylated BTs than toward alkylated DBTs. All the studied substrates, as well as 7-alkyl BT, were desulfurized to corresponding phenolic compounds and the reactivity had almost no relation with the length or the position of the alkyl chain attached to the BT molecule. Interestingly, 4,6-dimethyl DBT and 4,6-diethyl DBT, which are bulkier substrates than DBT, were more rapidly desulfurized than DBT in contrast to the Dsz system. This study proved the efficiency of cell free extracts over free whole cells. For example, R. erythropolis KA2–5-1 did not grow on BT, 5- methyl BT, and was unable to utilize 7-alkyl BT as a sulfur source, although it can grow on 3-methyl BT (Kobayashi et al., 2000).

Rhodococcus sp. WU-K2R preferentially degraded BT for a BT/naphtho-thiophene mixture (Kirimura et al., 2002). Rhodococcus sp. strain K1bD can individually desulfurize DBT and 1,4-dithiane, but when they were supplemented together, only DBT-BDS occured (Kirkwood et al., 2005). Similarly, the desulfurization of benzothiophene or 1,4-dithiane by Rhodococcus sp. strain JVH1 was delayed significantly in the presence of benzyl sulfide in the culture medium (Kirkwood et al., 2007). In another study, the BDS of BNT by a mixed culture was decreased significantly in the presence of DBT (Jiang et al., 2014). The same was reported for Gordonia sp. IITR 100, where complete removal of 0.3 mM BNT and DBT occurred within 6 d when incubated individually. However, in their presence together, the BDS of DBT was not affected, but the BNT-BDS was completely inhibited for up to four days. Then, the desulfurization of BNT was observed between the fourth and the sixth day of incubation when the level of DBT dropped to < 0.01 mM, but the reaction stopped again thereafter. Moreover, when the recombinant E. coli-DszC was applied, it expressed lower DBT-BDS efficiency (≈ 60%) than that for BNT. Although the rate of DBT-BDS in binary system remained nearly the same as in single-substrate system, the BDS of BNT was completely inhibited in a binary substrate system of DBT and BNT. The observed inhibition during the metabolism of BNT by E. coli-DszC into BNT-sulfone suggested that the competition between the two substrates sets in the first step itself. The results are consistent with an earlier study (Jiang et al., 2014) where the biodesulfurization of BNT by a mixed culture decreased significantly in the presence of >0.1 mM DBT.

G. alkanivorans strain 1B showed vigorous growth on sulfate, sulfide, sulfite, and elemental sulfur and on DBT, DBT sulfone, BT, 2-methylthiophene, and 2-mercaptoethanol, in the presence of glucose as a C-source, which clearly demonstrates that the G. alkanivorans strain 1B utilizes different sources of sulfur-containing aromatic hydrocarbons, including alkylated thiophene, BT, and DBT, suggesting its ability to decrease the sulfur content of fossil fuels. However, although 1B can utilize DBT and DBT-sulfone individually as sole S-sources, upon their presence together the bacterial growth stopped and, consequently, so did the BDS capability. Upon utilizing a binary substrate system of BT and DBT, the specific desulfurization rate recorded 0.954 and 0.813 µmol DBT/g DCW/h, respectively (Alves et al., 2005). In another study, Alves et al. (2008) reported the specific desulfurization rates in the model oil for DBT, 4-MDBT, and 4,6-DMDBT to be 0.78, 0.68. and 0.41 µmol/g DCW/h, respectively, in a batch culture inoculated with G. alkanivorans strain 1B.

Pantoea agglomerans D23W3 showed good BDS potential on BT, DBT, and 4,6-DMDBT, but it could not desulfurize 4,6-DEDBT (Bhatia and Sharma, 2010). This was attributed to an increase in the C-number of the alkyl substituent group resulting in increased d size and hydrophobicity, which, consequently, increased the expulsion of the compound from the aqueous phase which rarely comes in contact with the bacteria present in the aqueous.

Ahmad et al. (2015) studied the BDS of dibenzylsulfide (DBS) and dibenzothiophene (DBT) as model compounds for sulfides and thiophenes in petroleum and its fractions in single and binary substrate systems using Gordonia sp. IITR100. In a single substrate system, desulfurization of DBS by IITR100 was marginally better than DBT and both the chemicals were utilized completely within 3 and 4 days of incubation, respectively, but when the two chemicals were present together, an enhanced preference for the desulfurization of DBS was observed. Here, while nearly all of DBS was metabolized after 4 days of incubation, approximately 50 % of DBT was still present in the medium after the same period.

Aggarwal et al. (2013) reported that G. alkanivorans prefers BT over DBT as a sulfur source. This preference may be driven by the lower NADH requirements for BT metabolism, rather than the higher affinity of the transport system for BT.

One mmol/L DBT in n-dodecane was reported to be completely desulfurized with an almost stoichiometric production of 2-HBP, within 10 h at pH7, 30 °C, and 170 rpm, in a batch bi-phasic BDS process (1:1 O/w) using resting cells of Nocardia globerula R-9 collected at the late exponential phase, while 1 mmol/L 4,6-DMDBT was desulfurized by about 70% using the same conditions. The initial desulfurization rate for 4,6-DMDBT was about 5.9 mmol S/kg DCW/h, which was about 40% of that for DBT (Mingfang et al., 2003). While using a binary substrate system (0.5 mmol/L DBT and 0.5 mmol/L 4,6-DMDBT), both compounds were desulfurized simultaneously without preference for either one, which is of great importance in the practical desulfurization of petroleum products. The initial desulfurization rates for DBT and 4,6-DMDBT were 4.0 and 3.0 mmol S/kg DCW/h, respectively, but the overall desulfurization rates for both compounds, when present together, were lower than those found when treated separately (Mingfang et al., 2003). This was attributed to competitive inhibition of substrates. Similar phenomenon was reported for Rhodococcus erythropolis KA2–5-1 (Morio et al., 2001). In another study performed by Luo et al. (2003) using resting cells of the Gram negative P. delafieldii R-8 in biphasic system (1:1 O/W) of model oil 10 mM DBT or 4,6-DMDBT, BDS efficiencies of 97 and 86% were recorded, respectively, within 18 h of reaction time with mean specific desulfurization rates of 11.4 and 9.4 mmol S/kg DCW/h, respectively, while the volumetric desulfurization rate, with respect to the volume of dispersion, (mixture of the oil and water) was 0.29 and 0.24 mmol S/L_dispersion/h for DBT and 4,6-DMDBT, respectively.

The desulfurization rate of DBT-sulfone is reported to be twice that of DBT in a growing cell culture of Corynebacterium sp. ZD-1 (Wang et al., 2004). The acidophilic and thermophilic S. solfataricus P2 was reported to utilize DBT, DBT-sulfone, and 4,6-DMDBT, but cannot utilize BT as sole S-source. Thus, it was concluded that S. solfataricus P2 has a metabolic pathway specific for DBT and its derivatives and a recorded growth rate µ of 0.0179 and 0.0172 h^-1 for DBT-sulfone and 4,6-DMDBT, respectively (Gün et al., 2015).

Derikvand et al. (2015a) mentioned that the presence of the dszC gene in Paenibacillus validus (strain PD2) confirmed that DBT desulfurization occurred through the 4S pathway. Upon studying its ability to desulfurize different S-compounds, including thiophene, DBT, DMSO, and MgSO₄, a higher cell density was obtained when DMSO was used as the sole sulfur source. This was attributed to the easy metabolization of DMSO over other sulfur sources (Bustos-Jaimes et al., 2003). Moreover, the growth rate was inhibited by production of 2-HBP when DBT is used as the sulfur source. The growth on MgSO₄ was more than that on DBT or thiophene, which was attributed to the lower water solubility of DBT and thiophene and its lower bioavailability to the cells. Although the dsz operon is reported to be repressed by MgSO₄ as a sole sulfur source during the growth (Li et al., 1996), which explained the low BDS activity of resting cells grown on MgSO₄, which is the re-expression of the dsz operon.

The maximum BDS activity of the PD2 strain resting cells was achieved when they were grown on DMSO, where the maximum growth and the highest induction in the dsz operon obtained by Paenibacillus validus (strain PD2) was in the presence of dimethyl sulfoxide (DMSO) as the sole sulfur source.

El-Gendy et al. (2015) studied the main and interactive effects of polyaromatic sulfur heterocyclic compounds (PASHs) on the growth and biodegradation efficiencies of Bacillus sphaericus HN1, which was isolated for its ability to utilize DBT as a sole sulfur and carbon source (Figure 8.1). The biodegradation efficiency of the studied PASHs, Th, BT, and DBT, has been found to be ranked in the following decreasing order: BT > DBT > Th, whether in a single- or tertiary-substrate system. The biodegradation of Th decreased in a multi-substrate system by ≈ 14%, 18%, and 20% in the presence of BT, DBT, and in tertiary mixtures systems, respectively. The biodegradation of BT was not affected by the presence of other PASHs, while the biodegradation of DBT was slightly enhanced by ≈ 4% in presence of BT, but decreased in a binary mixture with Th by ≈ 12% and tertiary mixture of the three studied PASHs by ≈ 10.4%.

The overall removal of total PASHs decreased in the following decreasing order: single-substrate batch system > binary-substrate batch system > tertiary-substrate batch system, recording average biodegradation percantages of ≈ 94%, 87%, and 75%. This was in agreement with the bacterial growth trend in the three studied systems and might be attributed to the increase of total sulfur concentration, which might have expressed higher toxicity to bacterial cells and, consequently, a decrease in their enzymatic activity.

Regardless of the type of PASHs and whether they are in single- or multisubstrate systems, bacterial growth was stopped or depleted before the complete removal of the PASHs. This was attributed to the biodegradation process itself, which might produce toxic metabolites to the cell, but from the time profile of each PASH, it was obvious that the degradation trait was expressed at increasing levels during the bacterial growth cycle even after reaching its maximum growth. This indicated that stationary phase cells have the ability to continue degrading PASHs. Sahinkaya and Dilek (2007) mentioned an important point; in the calculation of degradation rate values, total biomass concentration is considered. However, only a fraction of biomass is responsible for the degradation of a particular substrate.

Ismail et al. (2016) reported the changes in an AK6- mixed culture community structure according to the provided sulfur sources (DBT, 4-MDBT, 4,6-DMDBT, or BT). The major denaturing gradient gel electrophoresis (DGGE) bands represented members of the genera Sphingobacterium, Klebsiella, Pseudomonas, Stenotrophomonas, Arthrobacter, Mycobacterium, and Rhodococcus. However, Sphingobacterium sp. and Pseudomonas sp. were abundant across all cultures utilizing any of the tested thiophenic S-compounds, but Mycobacterium/Rhodococcus spp. were restricted to the 4-MDBT culture which had the highest of the species’ richness and diversity.

Peng and Zhou (2016) reported that DMSO is a kind of sulfur source better than DBT or MgSO4 for the growth of Rhodococcus sp. MP12. Not only this, but it was found that resting cells previously grown on sodium sulfate did not express any BDS activity on DBT. This raised the possibility that sulfate can significantly repress the desulfurizing activity of the enzymes in the genus of Rhodococcus, but cells that harvested cells in mid-and late-exponential phases during growth with DBT or DMSO as sulfur sources seem to have better desulfurization activity in a DBT system. The maximum BDS activity happens in a mid-exponential phase when the OD is between 4 and 6 for DBT or DMSO cells. A maximum value of desulfurization activity (10.5 µmol/g DCW/h) occurred with cells pre-grown for 48 h with DMSO as a sulfur source. This was double that of cells pre-grown for 36 h with DBT, which recorded 4.3 µmol/g DCW/h. Thus, DMSO was also a better sulfur source than DBT or MgSO₄ for the expression of desulfurizing enzymes of Rhodococcus sp. MP12 (Peng and Zhou, 2016).

8.12 Effect of Organic Solvent and Oil to Water Phase Ratio

Various hydrocarbons are present in gasoline (C6 –C9) and diesel oil (C12 –C23) (Mingfang et al., 2003). As hexadecane comprises about 400 g/kg of certain diesel oils, it is considered a representative aliphatic hydrocarbon in diesel oil. However, the effect of an organic solvent or, in another word, the influence of an organic fraction phase (OFP) is a very important factor for the success of any BDS process.

The antimicrobial action of a solvent is correlated to its hydrophobicity and can be measured as the logarithm of the octanol–water partition coefficient log P_O/W (Laane et al. 1987; Osborne et al. 1990; Sikkema et al., 1994). According to this scale, enzymes and microorganisms present a minimum of activity with solvents with log P values of 0–2 and 2–4, respectively, after which the use of solvents with increasing log P values will result in increased biocatalyst stability. However, the actual concentration of the solvent in the bacterial cell membrane depends both on the solvent concentration in the water phase and on the partitioning of the solvent from the water phase to the membrane. Sikkema et al. (1994) proposed an equation to correlate the log P_O/W value of a solvent and its partitioning value between the membrane and water, log P_M/W.

Hydrophobic solvents, with a log P_O/W > 4, accumulate in the membrane, but will not reach a high membrane concentration and are not toxic because of their low water solubility. On the contrary, solvents with a log P_O/W between 1 and 4 present higher water solubility values, while also being able to partition to biological membranes, resulting in relatively high concentrations of these solvents in the membranes and high toxicity to the cells (de Bont, 1998).

Many organic solvents are reported in BDS studies, such as diethylether, ethanol, DMSO, dimethylformamide (DMF), n-hexane, xylene, dodecane, n-tetradecane, and n-hexadecane, where upon the choice of the solvent its toxicity on the cells activity should be considered. Solvents with high partition coefficient to the membrane, such as n-dodecane and n-hexadecane, are not toxic to bacterial cells and are applied in many BDS processes in model oil studies.

For example, Mingfang et al. (2003) examined the effect of n-hexane, cyclohexane, heptane, n-octane, dodecane, and hexadecane on the BDS of Nocardia globerula R-9. The results revealed that the desulfurization rate increased with the increase of the number of carbon atoms in the range of C6–C16. The resting cells of Nocardia globerula R-9 showed higher desulfurization activity in hexadecane and dodecane than in hexane and heptane and showed that it is more appropriate to apply Nocardia globerula R-9 in the BDS of diesel oil rather than gasoline.

Jiang et al. (2002) studied the effect of different solvents (hexadecane, ethanol, DMF, and adding DBT, directly in aqueous system) on the BDS activity of Pseudomonas delafieldii R-8. The concentration of DBT in a hexadecane broth decreased from 0.2 to 0.002 mmol/L within 80 h. It was about 1.4 and 1.2 times faster than in DBT-ethanol and DBT-DMF cultures, respectively, but the slowest was with the direct use of DBT powder. This was explained by the ability of hexadecane to increase the contact area between cells and DBT, which increases the growth and, consequently, the BDS-rate. The specific activity of the non-genetically engineered strain RIPI-22 in both biphasic and aqueous reaction systems were detected as 6.5 and 4.52 µmol 2-HBP/g DCW/h, respectively. It was concluded that the reason of the differences is the cell’s affinity to the organic phase is because of its surface hydrophobicity in the condition; the cells could use the substrate directly from oil fractions (Rashtchi et al., 2006). The solubility of DBT in water is in the order of 0.005 mM and can be increased a little by surfactant produced by cells. Since cells were suspended in the aqueous phase, the increased rates in higher hydrocarbon fractions might suggest the transfer of DBT through the interface between the aqueous and hydrocarbon phase or the adsorption of cells at the interface (Maghsoudi et al., 2001).

Alves and Paixão (2011) reported that Gordonia alkanivorans strain 1B is more sensitive to DMF than R. erythropolis D1. The IC₅₀ of DMF was found to be 6.56% and 9.91%, while the IC₅₀ of ethanol was found to be 10.56% and 10.52% for 1B and D1, respectively. This highlights the preferential use of ethanol as a solvent in BDS studies (Maghsoudi et al., 2001; Guerinik and Al-Mutawah, 2003; Mingfang et al., 2003; Wang et al., 2004; Labena et al., 2005; Tangaromsuk et al., 2008; Chen et al., 2009; Akhtar et al., 2009; Boniek et al., 2010; Davoodi-Dehaghani et al., 2010; Pikoli et al., 2014; Ismail et al., 2016; Papizadeh et al., 2017). However, methanol is also reported as a solvent in the BDS of DBT by Lysinibacillus sphaericus DMT-7 (Bahuguna et al., 2011). Neverthless, ethylether was used as a solvent in the BDS OF DBT by Candida parapsilosis Nsh45 (El-Gendy et al., 2006), R. erythropolis HN2 (El-Gendy et al., 2014), Brevibacillus invocatus C19 (Nassar et al., 2013), and Brevibacillus brevis HN1 (Nassar et al., 2016). Morever, n-hexane was also reported as a solvent for the BDS of DBT using R. erythropolis HN2 (Nassar et al., 2017a,b). The oil/water phase ratio affects the bioavailability of OSCs at the interface (Mohamed et al., 2015; Adlakha et al., 2016). From a practical point of view, the biodesulfurization (BDS) process has to be performed with really high proportions of organic solvent. Thus, for more economic benefits, it is preferable to work with the lowest water content and as much high BDS efficacy as can be reached for a high initial S-content oil feed. In a bi-phasic system (i.e. oil/water), the transfer of OSCs from the oil to the aqueous phase is one of the most determinant parameters in the BDS process. Therefore, using hydrophobic biocatalysts, such as Rhodococcus and Gordona cells, are preferable because they are capable of being joined at the oil/water interface for the uptake of OSCs there. Their ability of stabilizing the oil/water emulsion is related to cell surface hydrophobicity that may be related to cell surface long mycolic acids (Mohebali et al., 2007). Reaching for microbial isolates tolerable to high contraptions of oil fraction is recommended for the success of the BDS process. For example, the presence of heavy gas oil (HGO) in the culture medium of Rhodococcus erythropolis ATCC 4277 promotes a higher cell growth, especially for HGO concentrations from 10 to 50 % (v/v). Other researchers reported a good cell adaptation when using approximately 20 % (v/v) of the organic phase (Izumi and Ohshiru, 2001; Kirimura et al., 2001; Naito et al., 2001; Li et al., 2008b). The presence of hydrocarbons in abundance, as well as nitrogen and sulfur compounds, contributes to a better nutrition of the microorganism acting as a substrate and co-substrate. However, the decrease in cell concentration for higher concentrations of the oil fraction phase is due to the resistance of the microorganism decreasing with the increase of the toxicity of the system, making it impossible to maintain cell viability under more severe conditions (Carvalho et al., 2004, 2005).

Moreover, the 4S-pathway is reported to be energetically expensive due to a great consumption of reducing equivalents and oxygen before the production of the free sulfur product (Tao et al., 2006). Thus, the success of BDS as an alternative or complementary conventional desulfurization technique, on industrial scale, to produce ultra-low sulfur (ULS) fuels depends on the design of the microbial strains which remove sulfur in the presence of great proportions of organic solvents, with a higher rate or longer stability of desulfurization activity even at high temperatures. These criteria come in parallel with the worldwide depletion in reserves of high quality, low S-content conventional crude oil and the growing increment of utilizing the low quality, high S-content crude oil. The organosulfur compounds (OSCs) contribute to viscosity and other problems, such as pipeline corrosion and environmental pollution (Chapter 1). One of the recently recommended ways for upgrading heavy crude oils is the application of biodesulfurization (BDS). Most of the studies on heavy crude oil BDS have been limited to microorganisms which can either desulfurize aromatic or aliphatic organosulfur compounds.

Several studies have been focused on the isolation of new extremophilic microorganisms or the development of genetic modifications on natural strains (Xu et al., 2006), improving the design of solvent tolerant strains which metabolize a broad range of organic sulfur compounds (Gunam et al., 2006; Kilbane, 2006; Yu et al., 2006a,b) under high temperatures (Li et al., 2007) and with two-layer and continuous bioreactors (Yang et al., 2007).

Several other studies have been performed on the Gram –ve Pseudomonas species for being solvent tolerable with good biodesulfurizing activity (Setti et al., 1994, 1997; Luo et al., 2002; Martin et al., 2004; Alcon et al., 2005; Tao et al., 2006). Moreover, a two-phase system has been tested in many BDS studies, using Rhodococcus sp., in which hexane, heptane, and xylene were mainly used as the oil phase (Maghsoudi et al., 2001; Ma et al., 2006). The specific production rates increased with the increase in the DBT concentration and the hydrocarbon fraction using resting cells of Rhodococcus sp. P32C1 (Maghsoudi et al., 2001).

Effects of different O/W phase ratios have been studied for the batch biodesulfurization of model oil DBT in n-hexadecane using resting cells of Staphylococcus sp. strain S3/C (Goindi et al., 2002). The maximum extent of desulfurization (57%) with an overall rate of sulfur removal (2.2 mg S/L/h) occurred at an optimum hydrocarbon to an aqueous phase ratio (H/A) of 2:1, whereas the maximum specific sulfur removal rate (0.8 mg S/h/g DCW) at H/A was 3:1. The recorded low specific sulfur removal rate (0.2 mg S/h/g DCW) at a low hydrocarbon phase (0.5) was attributed to the limitation of effective contact of the hydrocarbon phase with the cells suspended in the aqueous phase under experimental conditions, while the observed repression of the specific sulfur removal rate at H/A 10:1 was attributed to the mass transfer limitation of O₂ to the high concentration of cells suspended in the aqueous phase. A similar effect of a decrease in the sulfur removal rate at a high cell concentration in high H/A was reported on Rhodococcus sp. P32C1 (Maghsoudi et al. 2001). Tolerance of the resting cells of Staphylococcus sp. strain S3/C at an H/A as high as 5:1 was observed by its recorded specific sulfur removal rate of 0.4 mg S/h/g DCW. However, in a study performed by resting cells of Pseudomonas delafieldii R-8, when the phase ratio was lower than 1 (O/W), the reaction proceeded more efficiently in comparison with that without the addition of dodecane (i.e. the non-aqueous or oil phase). The optimum phase ratio was found to be 1:4 (O/W) with an initial desulfurization rate of 4.6 mmol S/kg DCW/h. The possible reason for this was the formation of oil-in-water emulsion, where the interfacial area was increased resulting in the increase of the specific desulfurization rate. However, the high dodecane concentration (1.5 and 2.0 O/W) did not increase appreciably with the specific desulfurization rate. DBT was hardly desulfurized in dodecane without the addition of an aqueous phase. This was attributed to the activity of enzymes which need water.

Wang et al. (2006) reported that the optimum BDS of model oil (0.5 mmol/L DBT in n-hexadecane) by resting cells of Corynebacterium sp. ZD-1 was 1:2 (O/W) and the specific production rate of 2-HBP was about 1.72 times that in the aqueous phase and under higher oil held-up with an O/W ratio of over 2:1 and far less BDS activity was detected. This was explained because under low concentration, an oil-in-water emulsion was formed with the oil/water interface increasing with the proportion of oil. Meanwhile, hexadecane decreased the feedback inhibition of the biocatalyst due to the by-products’ accumulation in the water phase. However, because water was necessary for enzyme activity, too high a concentration of hexadecane resulted in a low desulfurization rate.

A comparison study has been performed by Caro et al. (2007b) on the aerobic, Gram +ve Rhodococcus erythropolis IGTS8 and the genetically modified strain Pseudomonas putida CECT 5279 for the BDS process in both aqueous and biphasic media of model oil (DBT/n-hexadecane). This was undertaken over different experimental conditions, including different oil fraction phase (OFP) percentages, substrate concentrations, and cellular densities, using resting cells as an operation mode. Generally, when cell densities were not too high, both biocatalysts achieved better DBT conversion with higher biomass concentrations and lower oil fractions and DBT concentrations. It was proved that the P. putida CECT 5279 strain is more sensitive for DBT mass transfer limitation and the encouragement results for the recommendation of applying the hydrophobic IGTS8 in biphasic systems is practical in the BDS process. Because of the oil–water partition coefficient of 2-HBP, its inhibition effect is lowered in a biphasic system. The evaluation was based on measuring serval parameters, such as BDS yields and BDS percentages (X_BDS) defined as the ratio between HBP concentrations produced and the initial substrate concentration used. The specific DBT consumption (q_s) and HBP production (q_p) rates were achieved after analyzing the samples after a prescribed time interval. They were found to decrease with the increase of OFP and there was no recorded BDS at OFP higher than 50% (i.e. > 1:1 O/W v/v). The CECT 5279 expressed a longer lag phase for BDS than that of IGTS8. This was attributed to the disability of CECT 5279 to uptake DBT directly from the solvent and in the absence of a co-solvent, such as ethanol, in the aqueous phase where there is practically no DBT bioavailable in the aqueous phase for the bacteria to start BDS. IGTS8 recorded an increase in specific DBT consumption and HBP production rates up to 40% (v/v) of OFP and then a drop to zero with 75% (v/v). This was explained by the increment of the organic interface surface with the OFP increment (Luo et al., 2003) and the high capability of Rhodococci’s to uptake organic compounds from the oil interface (Monticello, 2000). Thus, rates were higher until an oil–water proportion near 1:1, after which emulsion conditions might change (when there were water drops instead of oil ones) by avoiding cell-oil drop contact or where toxic oil effects were excessively influenced. In an aqueous phase system, the decrease of BDS efficiency was more pronounced with IGTS8 when the initial DBT concentration increased from 25 to 271 M, since the studied concentration range overcame the aqueous DBT solubility and the bioavailability did not go up enough. Furthermore, the steady production rate values of 2-HBP were attributed to its inhibitory effect, as it is a strong conversion inhibitor in the 4S-pathway (Ohshiro et al., 1995a; Patel et al., 1997; Monticello, 2000). CECT 5279 recorded a higher q_s and q_p in a biphasic system than in an aqueous one. This was explained by the higher bioavailability of DBT due to better diffusion in the aqueous phase, where the highest HBP production activity recorded 3.32 mmol HBP/kg DCW/h for an initial DBT concentation of 271 M. However, IGTS8 activity was not changed in the biphasic system, recording a maximum HBP production of 5.7 mmol HBP/kg DCW/h, for an initial DBT concentation of 271 M. The consumption rate of CECT 5279 was lower than that of IGTS8 in a biphasic system, recording a maximum value of 43 mmol DBT removed/kg DCW/h.

The growth rate of Pantoea agglomerans D23W3 was 50% slower when more than 10% of different oil feed, including light crude oil, heavy crude oil, diesel oil, hydrodesulfurized diesel, and aviation turbine fuel, were applied (Bhatia and Sharma, 2010). The oil/water phase ratio of 1:9 (i.e. 10%) was used in different BDS studies (Rhee et al., 1998; Li et al., 2003, 2007). Arabian et al. (2014) reported the BDS of model oil (500 ppm DBT in dodecane) by Bacillus cereus HN, where the BDS efficiency decreased with the increase of OFP and the highest of ≈ 60% occurred at 1/10 O/W.

Gün et al. (2015) reported the BDS of model oil (0.1 mM DBT in xylene) by the acidophilic and hyper-thermophilic S. solfataricus P2 in an oil/water phase ratio of 40% (v/v) which recorded approximately 22% within 72 h.

The resting cells of Bacillus strain KS1 also expressed higher DBT-BDS activity in a biphasic system of model oil DBT in tetradecane (1:1 O/W) than in an aqueous phase (Rath et al., 2012). The resting cells of S. subarctica T7b in a biphasic system were reported to exhibit the complete removal of DBT (1.36 mM) within 24 h (Gunam et al., 2013). Verma et al. (2016) reported a higher BDS efficiency in a biphasic system (0.2 mM DBT in n-hexadecane) by resting cells of Bacillus sp. E1 than in free resting cells, which recorded 63.6 ± 1.93 % with a 2-HBP production of 1.291 ± 0.095 mM in a biphasic system, while the other recorded 54.1 ± 2.19 % BDS% with a 2-HBP production of 0.913 ± 0.014 mM. The higher BDS efficiency in a biphasic system is due to the fact that in a biphasic system, 2-HBP accumulates in the oil phase, expressing lower toxic effects to the cells (Guobin et al., 2006). Moreover, the dissolution of DBT in the nonaqueous phase increases the bioavailability of DBT to the cells (Davoodi-Dehaghani et al., 2010).

Usually, upon the BDS-studies performed on heavy crude oil, dilution with organic solvents are performed. For example, Grossman et al. (1999) reported ten-fold dilution of crude oil with decane and a 30% reduction in total sulfur was observed using Rhodococcus sp. ECRD-1. Similarly, Ishii et al. (2005) observed a 52% reduction in a 12 fold diluted crude straight run light gas oil fraction using Mycobacterium phlei WU-0103. Adlakha et al. (2016) reported five fold dilution of heavy crude oil using n-hexadecane. This dilution was found to be appropriate for accuracy in measurements in experiments. Adlakha et al. (2016) mentioned that further oil dilution (> 5 fold) would involve the cost of additional diluent. In that study, the effects of different oil/water (O/W) phase ratios were studied for the BDS of heavy oil with an S-content of 4.53 mass percentge, which was decreased to 1.083 ± 0.5% upon the 5 fold dilution using n-hexadecane, using growing cells of Gordonia sp. IITR100. The recorded maximum S-decrease was 48% at 180 rpm and 30 °C with either 1:3 or 1:5 (O/W) after a 7 d incubation period. The least S-removal was recorded for an O/W phase ratio of 1:9. This was attributed to the high water volume which leads to the dilution of the enzyme activity and a decrease in overall desulfurization activity. Also, the 1:1 O/W expressed a low BDS efficiency, since higher oil content causes mass transfer limitations and limits the oxygen supply (Caro et al., 2008). The 1:20 O/W was reported for the BDS of crude oil by resting cells of Rhodococcus erythropolis XP (Yu et al., 2006a). Torkamani et al. (2008) reported an oil/water ratio of 1:10 for the BDS of Kuhemond heavy crude oil. An oil/water ratio of 1:50 has been reported for the BDS of heavy oil (Bunker oil) by a mixed culture (Jiang et al., 2014).

The effect of the O/W phase ratio was studied for the BDS of model oil 0.3 mM DBT in n-hexadecane using resting cells of Gordonia sp. JDZX13 in an attempt to decrease the feedback inhibition of the end products, 2-HBP and sulfate ions (Feng et al., 2016). The DBT removal efficiencies of the 2:1, 1:1, 1:2, and 1:3 systems were 20.89%, 13.89%, 24.40%, 41.92%, and 44.14%, respectively. Compared to the aqueous phase, although an oil phase was introduced, the removal efficiency decreased with the increase of the OFP. The reason for this might be that a higher oil/aqueous ratio reduced the effective space of cell growth, resulting in a lower biomass for further BDS (Alves and Paixão, 2011; Srivastava, 2012). However, the highest DBT-removal efficiency was achieved in the 1:3 O/W ratio system. Considering the amount of water used, the DBT-removal efficiency of the oil/aqueous ratio 1:2 system reached 0.188 mmol/L water, which was the highest among all the systems. Thus, the oil/aqueous ratio of 1:2 (improved by 100.7%) was determined as the best choice for better balancing the feedback inhibition effects of 2-HBP and sulfate ions.

8.13 Effect of Medium Composition

The production of biomass with high BDS efficiency is important since the BDS-degree developed during microbial-growth is useful not only to compare the results achieved under different media and conditions, but also to compare different microorganisms with desulfurization capability. This mainly depends on the composition of the media applied for the BDS process. For example, the effect of an addition of co-substrate, either as a sulfur source (such as dimethylsulfoxide DMSO or sulfate) or carbon source (such as glucose, glycerol citrate, etc). Not only this, but one of the main limitations to the BDS industrial application is the high costs of the nutritional medium compounds.

Usually, some solvents are used to dissolve DBT (such as n-hexane, ethanol, diethylether, etc.) before its addition in a culture medium. Thus, the medium usually inevitably contains a certain amount of these solvents. Some reports pointed to the enhancement of the rate of BDS through the addition of these solvents. For example, the addition of DBT dissolved in ethanol provided more rapid growth and desulfurization than only DBT powder (Setti et al., 1995).

Carbon and nitrogen concentration in a BDS-culture medium significantly affected the BDS process (del Olmo et al., 2005a; Maass et al., 2015; Porto et al., 2017). The carbon source that is most commonly employed is glucose (Izumi et al., 1994; Ohshiro et al., 1994; Wang and Krawiec, 1996; Oldfield et al., 1997; Folsom et al., 1999; Kobayashi et al., 2000; Yan et al., 2000; Matsui et al., 2001; Nakayama et al., 2002), but glycerol is also used (Kilbane and Jackowski, 1992; Kayser et al., 1993; Denome et al., 1994; Kishimoto et al., 2000; Maghsoudi et al., 2001; Abbad-Andaloussi et al., 2003) and other sources, such as ethanol (Wang and Krawiec, 1994; Onaka et al., 2000; Yan et al., 2000), sodium succinate (Omori et al., 1995; Setti et al., 1999; Abbad-Andaloussi et al., 2003), and tetradecane (Ohshiro et al., 1995a) have been reported, while the common nitrogen source that is usually employed is ammonium as NH₄Cl, but ammonium nitrate is also reported (Omori et al., 1995; Setti et al., 1997; Abbad-Andaloussi et al., 2003). Different organic S-compounds are also reported as sulfur sources. Some of these are 4S route compounds (Kayser et al., 1993; Denome et al., 1994; Ohshiro et al., 1996b; Wang and Krawiec, 1996; Setti et al., 1999; Yan et al., 2000; Maghsoudi et al., 2001), including dimethylsulfoxide (DMSO) (Oldfield et al., 1997; Folsom et al., 1999; Kayser et al., 1993; Omori et al., 1995; Abbad-Andaloussi et al., 2003) and others, such as thiophenes, sulfides, mercaptans, naphthalenes, and amminoacids (Kayser et al., 1993; Izumi et al., 1994; Omori et al., 1995). Recently, new studies have been reported for using some natural agro-industrial wastes, such as molasses, cassava waste, trub, etc., in the BDS-culture media since they are rich in essential components required for microbial growth and high enzymatic activities.

The pulp and paper industries generate large amounts of waste throughout the year (Thomas, 2000). Concentrated sludge generated by wastewater treatment facilities of recycled paper plants is currently a major disposal problem concerning the paper industry that has to be urgently solved (Oral et al., 2005). Recycled paper sludge (RPS) (after neutralization) is reported to be made up of approximately 35% cellulose, 10% xylan, and 20% lignin (on a dry-weight basis) and the remaining is mainly inorganic ash. Due to this high polysaccharide content, RPS appears as a promising feedstock for the formulation of inexpensive culture media (Van Wyk and Mohulatsi, 2003), providing their polymeric carbohydrates are broken down into fermentable monosaccharides. This hydrolysis can be carried out by chemical or enzymatic methods. The latter is advantageous since it is more specific and allows milder operation conditions leading to reduced production of biologically inhibitory compounds (such as sugar and lignin degradation products) and the biocatalysts are potentially reusable (Wen et al., 2004).

Alves et al. (2008) investigate the possibility of using the RPS hydrolysates obtained either with dialyzed enzymes (dialyzed hydrolysate) or non-dialyzed enzymes (non-dialyzed hydrolysate) as a carbon source in a concentration of 10 g/L glucose for DBT-BDS using Gordonia alkanivorans strain 1B in a batch culture containing 0.25 mM DBT. The maximum specific growth rates, µ_max, recorded 0.051 and 0.035 h^-1 in the presence of non-dialyzed hydrolysate and dialyzed hydrolysate, respectively, compared to 0.019 h^-1 in the presence of commercial grade glucose as the only carbon source. However, 125 µM 2-HBP with the BDS of 250 µM DBT was only observed in the presence of dialyzed hydrolysate with a maximum specific productivity of 2-HBP at 1.1 µmol/g (DCW)/h. Dialysis was performed aiming to remove possible sulfur compounds present on the enzymatic formulation that could be more easily assimilated than DBT by bacterial cells, unless a recombinant strain (lacking dsz substrate repression) is used. Then, Alves et al. (2008) investigated the capability of using the dialyzed hydrolysate as a complete culture medium. The results revealed that RPS hydrolysate, without additional nutrients and with phosphates or with phosphates and magnesium, did not allow a significant growth or 2-HBP production. However, RPS hydrolysate with ammonia allowed high initial growth and 2-HBP, but both were lost after 72 and 96 h, respectively. This was attributed to the absence of some nutrients, but a complete consumption of the 250 µM DBT and glucose occurred in the cases of RPS hydrolysate with ammonia + phosphate, RPS hydrolysate + phosphates + ammonia + magnesium, RPS hydrolysate + phosphates + ammonia + magnesium + Zinc, and RPS hydrolysate + phosphates + ammonia + magnesium + trace elements solution (all the nutrients were added according to the components of sulfur-free medium (SFM) as described by Alves et al., 2007) and ZnCl₂ in 10 mg/L. Any of the listed formulas can be used as complete mediums for DBT-BDS by G. alkanivorans strain 1B. Nevertheless, the highest specific maximum growth rate, µ_max 0.03 h^-1, and 2-HBP production rate, 5.7 µM/h, occurred with RPS hydrolyzate + phosphates + ammonia + magnesium + zinc due to the presence of Zn. Thus, upon the application of that formula for the batch BDS of model oil containing 2 mM each of DBT, 4-MDBT, and 4,6-DMDBT dissolved in n-heptane, a final ration of 1/10 O/W occured. Total consumption of glucose occurred within 96 h with a µ_max of 0.062 h^-1 and decrease of total S-content occurred by 2.6 fold reaching 2.23 mM after 168 h of cultivation. The specific desulfurization rates after 24, 48, and 72 h were 22.2, 11.1, and 4.8 µmol/g DCW/h, respectively (Alves et al., 2008). Realistically, for a potential industrial application, an inexpensive culture medium would have to be employed in a large-scale process. Therefore, the cost of commercial enzyme formulations might economically hamper the suggested process by Alves et al. (2008), unless the enzymes added in the hydrolysis step are recovered and reused. However, Alves et al. (2008) suggested that this might be achieved by developing a process based on an enzymatic membrane reactor in which a semi-permeable ultrafiltration membrane is used to retain the enzymes in the reactor while preserving their activity.

Carob kibbles are another agro-industrial waste characterized by a high content of soluble sugars, mainly sucrose, glucose, and fructose, which are easily extractable by water, producing sugar-rich syrups (Mansom et al., 2010), but these wastes have high concentrations of sulfate, thus to use carob pulp liquors for BDS processes, it is necessary to reduce the sulfate concentration to minimum levels. Silva et al. (2013) studied the removal of such sulfate by precipitation, using BaCl_2, producing the less toxic, low water soluble BaSO₄ (0.00285 g/L at 30 °C) (Guo et al., 2009). During this treatment, an accumulation of barium sulfate occurs which can constitute an environmental problem in large-scale BDS application. However, Silva et al. (2013) mentioned that this drawback can become an economic advantage, suggesting that the recovered barium sulfate at the end of the process can be used as a component of oil well drilling (the main application of this material) or as a component of white pigment for paints. The treatment of carob pulp liquor by 0.5% of BaCl₂ for 21 h led to carob pulp liquor with a maximum sulfate concentration of 15–18 mg/L sulfate. Upon the application of treated carob pulp liquor in the ratio of 1:6 as the sole C-source to a batch BDS process, using Gordonia alkanivorans strain 1B, with an initial DBT concentration of 400 µmol/L dissolved in DMF, a maximum BDS efficiency was measured by the produced 2-HBP and recorded as 237 µmol/L (Silva et al., 2013).

The commercially and readily available sugar beet molasses (SBM), which is rich in sucrose (~50 %, w/v) that can be hydrolyzed to glucose and fructose, has been used for the enhancement of the BDS efficiency of G. alkanivorans 1B (Alves and Paixão, 2014a). Untreated SBM revaled good microbial growth with µ_max of 0.067 h^–1 and a biomass yield of 0.471 g/g within 3 d, but no DBT-BDS has occurred. Upon the pretreatment of SBM by 0.25% BaCl₂ overnight (16–18 h) to precipitate the unwanted sulfates (denoted SBM_t), the BDS efficiency as measured by the produced 2-HBP and recorded at 200 µM from the BDS of 250 µM DBT. Alves and Paixão (2014a) also investigated the effect of different SBM pretreatment methods on DBT-BDS: (i) DBT desulfurization using directly SBM_t, (ii) DBT desulfurization using SBM_t after acidic hydrolysis (SBM_t–AH) to convert sucrose to glucose and fructose, and (iii) DBT desulfurization using SBM_t in a SSF approach with Zygosaccharomyces bailii strain Talf1 crude enzymatic extract exhibiting invertase activity. This showed that the addition of SBM_t in a dilution of 1:50 i.e. 12 g/L sucrose in a batch culture of 250 µM DBT, within 96 h, 1B produced 122 µM 2-HBP and a µ_max of 0.04 h^–1 with a biomass yield of 0.377 g/g sugar, maximum 2-HBP production rate of 2.56 µM/h, and a maximum 2-HBP specific production rate q_HBP 2.2 µmol/g DCW/h. This was attributed to the presence of some nutrients in this complex alternative carbon source, which can promote a faster bacterial metabolism. Upon the application of SBM_t–AH, the DBT-BDS was further enhanced recording µ_max of 0.0575 h^–1, with a biomass yield of 0.488 g/g sugar within 3 days of incubation, which was approximately 44 % higher than in the growth with SBM_t that was not hydrolyzed. Maximum production of 2-HBP, 168 µM, was achieved after 66 h with a maximum and specific production rate of q_HBP 5.76 µM/h and 2.61 µmol/g DCW/h, respectively. The rate of fructose utilization was higher than that of glucose; the maximum fructose consumption rate was 0.167 g/L/h and the maximum glucose consumption rate changed from 0.078 g/L/h (during the high availability of fructose) to 0.134 g/L/h (after the low availability of fructose). However, in order to make the process more eco-friendly and decrease the costs associated with the sucrose hydrolysis of SBM_t, the utilization of invertases in a simultaneous saccharification and fermentation approach was also studied. Alves and Paixão (2014a) performed another set of DBT desulfurization assays using SBMt and a crude enzymatic extract containing inulinase/invertase activity produced by the yeast Z. bailii strain Talf1 (1 % v/v) in the SSF approach. The SSF process allowed a faster growth of strain 1B with a µ_max of 0.08 h^–1 and a higher biomass yield of 0.72 g/g sugar during 55 h. The 2-HBP recorded a maximum quantity of 249.5 µM at 47.5 h of culture, which corresponds to the total desulfurization of DBT present in the culture medium (250 µM). The maximum 2-HBP production rate achieved was 7.78 µM/h and the q_HBP was 3.12 µmol/g DCW/h. Alves and Paixão (2014a) estimated that the application of SBM in BDS as carbon source instead of sucrose would lead to a cost reduction of 3-fold. Moreover, SBM utilization in an SSF process, with invertase crude extract, contributes to an improved DBT desulfurization due to possible nutrients/inducers from the molasses or enzymatic extract.

Jerusalem artichoke (JA, Helianthus tuberosus), also known as topinambur, is a species of sunflower and is cultivated worldwide for animal consumption and/or sugar (Baldini et al., 2004). Recently, it founds its way to use in biofuels, including bioethanol and biodiesel production and in the biochemical industry (Cheng et al., 2009; Liang et al., 2012; Guo et al., 2013; Li et al., 2013). The JA can grow on poor land, being resistant to frost, drought, pests, diseases, and saline soils and it is characterized by high fertility and demands low amounts of fertilizers (Zhao, 2011). As it is drought-resistant, it can be used to improve soil and water conservation in arid regions. Moreover, JA tubers accumulate inulin, a polydisperse fructan polymer composed by linear chains of β-2,1-linked D-fructofuranose molecules terminated by a glucose residue through a sucrose-type linkage at the reducing end. Inulin is soluble in water and, after hydrolytic breakdown by inulinases, it releases fructose and glucose producing sugar-rich juices, containing up to 95% fructose (Makino et al. 2009; Kango and Jain 2011). Thus, JA is considered as a natural source of fructose for the industry and an attractive alternative carbon source for microbial growth and further application to bioprocesses that use fructophilic microorganisms, such as BDS (Paixão et al., 2013; Alves and Paixão 2014b). However, the sulfate concentration of JA reaches up to > 450 mg/L. Thus, sulfate removal is a must before its application in BDS process.

Silva et al. (2014) reported the acid hydrolysis of Jerusalem artichoke (JA) to produce fructose rich juice to be used as a carbon source for batch DBT-BDS using the fructophilic bacterium G. alkanivorans 1B. The amounts of sugars (sucrose, glucose, and frustose) in the acid hydrolyzed JA juice (JAJ) are about 85% higher than those in JA. Upon the application of JAJ in a batch BDS of DBT with an initial concentration of 400 µmol/L, where inulin was the main C-source, the µ_max recorded 0.0546 h^–1 due to the low available fermentable sugars (4 g/L) and the high sulfate concentration, 77.8 mg/L, (as JAJ was added 1:6, so it was diluted) stopped the BDS and no 2-HBP was produced. Nevertheless, upon the application of acid hydrolyzed JAJ with approximately 25 g/L glucose and fructose, the µ_max increased to 0.0816 h^–1 due to the presence of high C-nutrients (sugars and growth inducing compounds, such as vitamins and amino-acids), but still no 2-HBP was produced due to the high concentration of sulfate (~ 75 mg/L). Upon the treatment of JAJ and acid hydrolyzed JAJ, denoted JAJ_t with 0.5% BaCl₂ at pH8.73, the production of 2-HBP was observed with both juices; for JAJ_t with < 1 g/L of fermentable sugars, the bacterial growth achieved a µ_max 0.0428 h^–1. The 2-HBP production began at 18 h, reaching a maximum concentration of 43 µmol/L by the end of the growth. The maximum production rate was 1.74 µmol/L/h and the specific production rate (q_2-HBP) was 1.23 µmol/g DCW/h. These results showed the effectiveness of BaCl₂ treatment, where, despite the small growth, the production of 2-HBP was observed, meaning that only a residual sulfate level was introduced in a test medium and it was non-inhibitory for the BDS process. The limiting factor in that process was the very low level of available fermentable sugars for growth. In acid hydrolyzed JAJ_t, with residual sulfates (<2 g/L) and all sugar content as fermentable sugars bioavailable (25 g/L), the BDS results were remarkable: µ_max 0.06 h^–1 with total consumption of the available carbon source within 96 h. Total consumption of DBT occurred with a nearly stoichiometric production of 2-HBP, which was initiated within 18 h and attained ~ 400 µmol/L within 73 and 96 h, that corresponded to an overall production rate of 4.48 µmol/L/h and to a maximum production rate of 28.2 µmol/L/h, with a related q_2-HBP of 5.06 µmol/g DCW/h. Using the BaCl₂ treated hydrolyzed JAJ_t, the amount of 2-HBP produced (µmol) per gram of sugar consumed averaged 16 µmol/g (Silva et al., 2014).

Cassava wastewater has a high pollution potential, primarily because of its high organic load. However, this residue also has essential nutritional components, such as the sugar combination of sucrose, fructose, glucose, and mainly soluble starch (Barros et al., 2013), and ammonium ions (NH₄+) and nitrate (NO₃^–) as nitrogen sources (Barros et al., 2008). Trub is a precipitation by-product from the wort boiling process in brewing industries. Its composition is comprised of 40–70% protein, 10–20% hop bitter acid, 7–8% polyphenols, 7–10% carbohydrate, and 1–2% fatty acid (Kunze, 2014). In the beer manufacturing process, the complete removal of trub is essential to ensure the quality of the final product in terms of the yield of bitter substance (Kühbeck et al., 2007). Thus, the application of these wastes in the BDS process would solve some waste management problems and would have a positive impact on the economy, environment, and energy.

Porto et al. (2017) reported a specific desulfurization rate of 453 mg S/kg HGO/h, with a BDS efficiency of 75% within 12 h using R. erythropolis ATCC 4277 in the presence of cassava waste water as a source of carbon co-substrate and nitrogen, while, upon the application of hot trub, the BDS percentage reached 70% within only 1 h of incubation with a specific desulfurization rate of 5073 mg S/kg HGO/h.

In a process for diesel oil BDS, ethanol was added for the enhancement of phase separation, as it acts as a de-emulsifier to three phase (diesel oil/biocatalyst/aqueous phase) emulsion. It promoted the phase separation, recovery of desulfurized diesel oil, and microbial cells from the very stable emulsion from the BDS-reactor (Choi et al., 2003). After the phase separation, the major portion of the added ethanol remains in the aqueous phase containing microbial cells, which can serve as a good carbon source for the growth of the recovered cells to be recycled to the reactor, replacing, at least partially, the carbon source requirements.

However, Kim et al. (2004) reported that the growth rate and BDS efficiency performed by Gordonia sp. CYKS1, in presence of ethanol, was higher than that in the presence of glucose. The BDS-rate increased about 2.5 times (from 1.71 to 4.02 µmol/L/h) as the ethanol concentration increased from 3 to 20 g/L. The Monod-model equation was found to fit the growth of Gordonia sp. CYKS1on ethanol and glucose, with maximum specific growth rates (µ_max) of 0.2 and 0.08 and saturation constants (K_m) of 2.76 and 6.29 g/L, respectively.

BDS can be enhanced by promoting the oxidoreductase activity via the addition of a carbon source. To test whether biodesulfurization can be enhanced by oxidoreductase co-expression, three different sources of carbon were used; glucose, glycerol, and acetate were used to supplement the resting cells medium of Rhodococcus species supplemented with 1% DBT. The rate of HBP production was highest with glucose, followed by glycerol and acetate, in a decreasing order, recording 5.82, 4.77, and 2.48 µmol 2-HBP/g-cell/h, respectively. This corresponds with the theoretical yields of NADH from the carbon sources of 10, 6, and 0.5 for glucose, glycerol, and acetate, respectively (Guerinik and Al-Mutawah, 2003).

However, in a study performed by Luo et al. (2003) on resting cells of Pseudomonas delafieldii R-8 in biphasic batch BDS process (1:1 O/W) of model oil (1 mM DBT in dodecane), using different aqueous reaction media, such as saline (0.85 g NaCl/L), 0.1 M phosphate buffer (pH 7.0), and sulfur free medium (SFM), the results showed that the rates of DBT consumption and 2-HBP production were almost linear in the initial stage of reaction. The DBT was completely removed within 8 h with an almost stoichiometric production of 2-HBP in all the studied aqueous phases. The most valuable observation was the proceeding of DBT-BDS by the R-8 lyophilized cells in the non-growth media (i.e. saline and phosphate buffer) being as efficient as in the growth medium (i.e. SFM). Not only this, but the results also also that the DBT-BDS by whole cells of R-8 did not need the addition of any other cofactors or reducing agents.

In another study performed by Xu et al. (2002) on batch BDS of 0.5 mmol/L DBT by Rhodococcus. sp. 1awq strain within 48 h at 30 °C and pH7, glycerol showed the highest growth followed by citrate, glucose, and acetate in a decreasing order. The effect of glycerol concentration was also studied and higher concentrations (>0.5%) were not favorable. Not only this, but higher concentrations of NH₄Cl (>0.5%) were not favorable either in the presence of 0.4% glycerol or 1 mmol/L Na₂SO₄.

Alves et al. (2004) reported the BDS of 478 µM DBT by Gordonia alkanivorans strain 1B in the presence of glucose as a co-substrate to 168 µM, within 120 h of culture, with a specific desulfurization rate of 1.03 µmol DBT/g DCW/h. This rate is similar to that obtained with Gordonia sp. strain CYKS1 at 0.917 µmol DBT/g DCW/h, which reduced the concentration of DBT from 320 to 50 µM within 120 h (Rhee et al., 1998). The maximum extracellular concentration of 2-HBP, however, was somewhat lower at about 120 µM, which is only 27% of the consumed DBT (450 µM).

Labana et al. (2005) reported the batch BDS of 27 ppm DBT dissolved in ethanol by growing cells of Rhodococcus sp. and Arthrobacter sulfureus isolated from oil-contaminated soil/sludge samples in the presence of 10 mM sodium succinate as a C-source, where the S-level decreased to 8 and 10 ppm, recording a BDS percentage of 70 and 63%, respectively, within a 30 d incubation period.

Yan et al. (2000) studied the relative efficacy of ethanol, glucose, and glycerol as sole carbon sources for the growth and desulfurizing activity of R. erythropolis. They reported ethanol to yield the highest growth and desulfurizing rates, followed by glucose, then glycerol. The recorded results were as follows: the highest growth rate of 1.39 h^-1 and the highest desulfurizing rate of 0.18 mmol HBP/g DCW/h for ethanol. In contrast, the rates were 0.60 h^-1 and 0.08 mmol HBP/g DCW/h for glucose and 0.59 h^-1 and 0.07 mmol HBP/ g DCW/h for glycerol. Similar observations were obtained by Aggarwal et al. (2011) using R. erythropolis, where the desulfurization and growth rates, relative to those of ethanol, decrease in the following order: ethanol (0.18 mmol HBP/g DCW/h as 100% and 1.39 h^-1 as 100%) > lactate (67%) > citrate (48%) > glutamate (44%) > glucose = fructose (43%) >glycerol (42%) > gluconate (40%). These results can be attributed to the NADH and carbon metabolism. Ethanol yields more NADH during this metabolism than glucose and glycerol. The more the NADH, the more the bacterial growth and it enables more of the cells to increase the flux (i.e. the desulfurizing rate) of the 4S pathway. Aggarwal et al. (2013) investigated the effect of 17 carbon sources (acetate, citrate, ethanol, formate, fructose, fumarate, gluconate, glucose, glutamate, glycerol, lactate, malate, oxaloacetate, oxoglutarate, pyruvate, and succinate) on growth and the BDS activity of G. alkanivorans. Ethanol was found to be the best for growth and BDS activity, recording µ_max 0.027 h^-1 and a BDS-efficiency of 3.3 mmol HBP/g DCW/h. Relative to the maximum activity that occurred with ethanol (considered as 100%), those obtained with other studied sugars ranked as follows: fumarate (80%) > oxoglutarate (78.79%) > pyruvate (78.43%) > glutamate (78.24%) > succinate (78%) > acetate ≈ fructose ≈ glucose ≈ lactate (76.86%) > glycerol (75%) > citrate (71.88%) > oxaloacetate (69.70%) > malate (69.11%) > formate (50%). This ranking remained unchanged even for BT as the sole sulfur source. This was attributed to the production of NADH. For the cell to consume 1 mol of DBT as a sulfur source via the 4S pathway, it requires 4 moles of NADH (Aggarwal et al., 2011). Additionally, NADH is required for other growth related activities. The carbon nutrient is the main source of this energy. It affects the cofactor regeneration in cellular metabolism. Therefore, a carbon source that provides more NADH during its metabolism is likely to support higher desulfurization and growth. One mole of ethanol generates two additional moles of NADH (Aggarwal et al., 2011), which is the highest among all the studied 17 substrates. So, it can be concluded that any changes in medium design or genetic manipulations that increase NADH regeneration and supply within the cellular metabolism are likely to enhance desulfurization activity.

Recently, Alves and Paixão (2014b) described Gordonia alkanivorans strain 1B as being fructophilic. This means it prefers fructose to glucose as a carbon source to grow, growing faster and, thus, desulfurizing at faster rates in the presence of fructose, where, upon studying the effect of different carbon sources in a batch BDS of 500 µM DBT, the lowest values for the growth rate (0.025 h^-1) and overall 2-HBP production rate (1.80 mM/h) by the strain 1B were obtained in glucose grown cultures. Strain 1B grew considerably in the presence of glucose and sucrose, but the bacterial growth was much higher when fructose was used as the only carbon source. In fact, after five days of growth, the optical density obtained in a fructose medium was about 5 and 3.3 fold relative to that of glucose and sucrose, respectively. Moreover, this higher growth in the presence of fructose led to a higher 2-HBP production (248.1 mM), thus, the desulfurization ability was 5 and 6 fold higher, relevant to that obtained in the presence of sucrose (53.9 mM) and glucose (41.0 mM), respectively. However, no significant bacterial growth was observed in culture media containing cellobiose or xylose as the only carbon source. Strain 1B grew about 3.6 fold faster when fructose was present as a carbon source instead of glucose. The amount of 2-HBP produced µmol/g of sugar consumed by G. alkanivorans in glucose, sucrose, fructose, and fructose + glucose recorded 19.6, 20.8, 30, and 24.2 µmol/g consumed sugar, respectively. When using sucrose, the increase in the growth rate exhibited by strain 1B led to a higher biomass productivity, which induced a slight increase in the 2-HBP production rate (1.91 µM/h). Conversely, in terms of a 2-HBP specific production rate (q_HBP), the value obtained was markedly lower (0.718 µmol/g/h in sucrose versus 1.22 µmol/g/h in glucose). When a mixture of glucose and fructose was used as a carbon source, strain 1B reached a value of q_HBP 1.90 µmol/g/h, close to that in fructose (q_HBP 2.12 µmol/g/h). The highest values for both cell growth (µ_max 0.091 h^-1) and 2-HPB production (9.29 µM/h) were obtained when strain 1B was desulfurizing DBT in the presence of fructose as the only carbon source, indicating a fructophilic behavior by this bacterium. The greater number of functional cells conducted a more effective BDS process by strain 1B, as they attained a q_HBP about 74% higher than in glucose grown cultures, increasing from 1.22 to 2.12 µmol/g/h. Furthermore, the significant BDS enhancement has been better observed in terms of the overall 2-HBP production rate, which increased over 5 fold from 1.80 µM/h (in presence of glucose) to 9.29 µM/h (in presence fructose). This fact is in agreement with the highest value of biomass productivity by strain 1B in fructose, which resulted in a higher number of cells fulfilling DBT-desulfurization. The greater number of functional cells conducted a more effectivene BDS process by strain 1B, as they attained a q_HBP about 74% higher than those in glucose grown cultures. Moreover, this significant BDS enhancement can be better observed in terms of the overall 2-HBP production rate, which increased over 5 fold from 1.80 mM/h (in glucose) to 9.29 mM/h (in fructose). Fructophilic pathways were usually associated with yeasts; in fact, until the discovery of this characteristic, lactic bacteria were the only exception (Sutterlin, 2010; Endo, 2012). Since the utilization of microorganisms in the industry requires cheap carbon sources to be productive, the fact that this strain is fructophilic opens new possibilities in terms of available carbon sources, allowing the exploration of some fructose rich residues and plants that might both make the process cheaper and more efficient.

Alves and Paixão (2014b) also studied the effect of fructose pulse by fructose addition to a batch DBT-BDS using G. alkanivorans 1B and glucose as a C-source in the middle of an exponential phase that was after 96 h of cultivation, which led to the enhancement of the BDS-process; the growth rate increased from 0.025 h^-1 to 0.072 h^-1, the biomass production rate increased from 0.005 g/L/h to 0.147 g/L/h, biomass yield increased from 0.327 g/g to 0.455 g/g, the rate of 2-HBP production increased from 0.72 µM/h to 11.59 µM/h, and the specific production rate of 2-HBP q_HBP increased from 1.7 µmol/g/h to 4.96 µmol/g/h. Finally, upon the comparison of the efficiency of 1B resting cells pregrown on glucose or fructose, 150 µM DBT, and harvested at the late exponential phase on a batch BDS of 500 µM DBT, resting cells pre-grown in fructose, showed an overall 2-HBP specific production rate of 3.6 µmol/g DCW/h, which was about 67% higher than that obtained using resting cells pre-grown in glucose (2.16 µmol/g DCW/h) (Alves and Paixão, 2014b).

Dejaloud et al. (2017) investigated the importance of the maintenance energy during BDS of different concentrations of DBT, where glucose as the most common energy substrate in biotechnology industries was used at two different initial concentrations. The energy-limited growing cell culture of Ralstonia eutropha PTCC1615, using glucose at 55 mM, was used to describe cell behavior when the availability of the energy source became limited (denoted case-A). The energy-sufficient medium prepared using glucose at 111 mM, as the initial concentration, showed the amount of energy source to be in considerable excess over other cell requirements, such as nitrogen or sulfur sources (denoted case-B). PTCC1615 showed sufficient growth in both cases, without any lag phase, reaching the stationary phase within 10 h with complete consumption of glucose and 40–50 mM remaining in case-A and B, respectively. This was accompanied with a decrease in pH due to the production of acetic acid. It is worth noting that the yield of 2-HBP as a measure for BDS-efficiency (Y_DBT%) was higher in the energy-sufficient media when compared with energy-limited cultures, regardless of the initial DBT-concentration. The recorded maximum Y_DBT value of 90.7% was obtained in initial DBT and glucose concentrations of 0.05 and 111 mM, respectively. The specific growth rate (µ h^-1) was higher in energy-limited cultures of DBT (0.56–0.61 h^–1) than in energy-sufficient media (0.32–0.41 h^–1), since all the cells’ efforts in the “B” cultures are directed toward the DBT-BDS process and the cells focused less on biomass formation. But, in a control culture with NH₄SO₄ instead of DBT, the recorded p (0.63 h^–1) with 111 mM glucose was higher than that with 55 mM glucose (0.49 h^–1). This indicated that the cells’ need for NAD(P)H and FMNH₂ is low in the absence of the DBT-BDS process. In that study, with DBT as a toxic substrate, showed that its presence in growing cell cultures of cases “A” and “B” cultures exert a tension on the cells and the formation of 2-HBP in the DBT-BDS process may be considered as the product formation case, which has been described before as the formation and excretion of only one predominant product (Tsai and Lee, 1990). Considering the dynamic behavior of the cells, this type of expression occurs under certain conditions (Tsai and Lee, 1990; Zeng and Deckwer, 1995). The activity of the enzymes responsible for the product’s synthesis is one of the mentioned conditions. For instance, the responsible enzymes are expressed under the control of the dsz operon in the Rhodococcus sp. strain IGTS8 during the BDS process. The cellular pools of the produced NADH and FMNH₂ coenzymes should be directed toward the BDS process and the excess energy in the cells in the form of accumulated coenzymes can be relieved in this way (Figure 8.2). The response of chemoheterotrophic microbes to the energy substrate in a particular medium defines the cell behavior in regulating the metabolic activities by balancing between catabolic and anabolic reactions (Russell and Cook, 1995). However, in many cases, the amount of energy (ATP) generated through exogenous oxidizable substrates, such as glucose, is not directly proportional to the cell growth yield. Although the logistic model is referred to as the substrate-independent model in some texts (Zhang et al., 2013), the initial concentration of the substrate actually determines the highest achievable cell density in a particular environment. In other words, reflects the capacity of the environment to support cell growth. The important point to realize is the aerobic cell requirements of the carrier molecules that are needed to transfer electrons of the energy substrate (i.e., glucose) to O₂ as the final electron acceptor molecule (Figure 8.2). Aerobic respiration (in terms of the microbe’s bioenergetics) involves the formation of 3 and 2 moles of ATP, respectively, per 1 mol of NADH or FADH₂ being oxidized (Berg al., 2010). The NADH requirements for the DBT-BDS process have been reported and this electron rier was found to be more efficient than NADPH (Ohshiro et al., 1994; Boniek etal., 2015). The findings using this approach showed that 4 moles of NADH are needed to convert 1 mol of DBT to 1 mol of 2-HBP through the 4 S pathway (Oldfeld et al., 1997). Although, the inhibitory concentration of substrate or product are the main effective factors on cell growth inhibition and the increased requirement of maintenance energy which, adversely, cause a reduction in the specific growth rate and cell growth yield. However, in that study, no substrate or product inhibitory effects were observed.

The optimum production medium for R. erythropolis IGTS8 with high BDS-capability is reported to be composed of 20 g/L glucose, using 670 ppm NH₄⁺ and 1300 M DMSO as carbon, nitrogen, and sulfur sources, respectively (del Olmo et al., 2005a). It is proven that the addition of ammonium as a nitrogen source is necessary for the good development of the enzymatic pool during the growth of the microorganism used afterwards in the 4S-BDS route (del Olmo et al., 2005a).

The effect of nitrogen in the form of ammonium tartrate on the BDS efficiency of the lignin-degrading white basidiomycete Coriolus versicolor has been investigated in the presence of glucose as a carbon source (Ichinose et al., 2002b). The fungal conversion of 2-hydroxymtheyl thiophene (2HMT) was examined under either high nitrogen, HN (12 mM), or low nitrogen, LN (1.2 mM). The same metabolites were produced under the two applied conditions, but the rate of desulfurization was twice as fast in the HN culture as that in the LN culture. This was attributed to the higher mycelium dry weight, which was twice that obtained in LN culture. Moreover, 2-hydroxy-methyl benzothiophene (2HMBT) and 4-hydroxymethyl dibenzothiophene (4HMDBT) were metabolized more effectively in an HN culture medium than in an LN medium. However, upon the investigation on higher S-compounds, the conversion of DBT, 4-MBT, and 7-MBT to their corresponding sulfones, only observed under ligninolytic conditions, i.e. high carbon and low nitrogen (HCLN), suggesting that the S-oxidation reactions were catalyzed by ligninolytic enzyme(s) (Ichinose et al., 2002b).

Martin et al. (2005) reported that the highest growth rate and maximum biomass concentration of Pseudomonas putida CECT5279 were obtained when glutamic acid was used as the carbon, while the lowest occurred upon the usage of citrate as the C-source. Furthermore, the highest percentage of DBT-BDS was obtained in a non-buffered medium with glutamic acid, but it remained constant for more time in buffered media, although, in this case, the value of the desulfurizing capability was smaller. Glucose showed lower growth and BDS for Pseudomonas putida CECT5279, which contradicts with R. erythropolis IGTS8 (del Olmo et al., 2005a). The maximum values of the D_DBT reported by Martin et al. (2004) using glutamic acid as the carbon source in the P. putida resting cells assay were close to the values reported in that of Martin et al. (2005). Involvement of this amino acid in nitrogen metabolism in bacteria should be referenced (Figure 8.2). The excess or limitation of nitrogen in a growth medium is clearly described in the literature in terms of the ratio of alpha-ketoglutarate (an intermediate of TCA cycle) to glutamine, where the low ratio reflects the excess of nitrogen in a prepared medium, while the high level of this ratio is indicative the nitrogen limitation (Zubay, 1998). The BDS-enhancing role of some intermediates of the TCA cycle have also been reported recently (Martinez et al., 2015).

Sagardia et al. (1975) reported that Pseudomonas aeruginosa PRG1 cannot grow on BT alone in BSM; 0.05% yeast extract was a suitable substrate for its growth and attack on BT. Premchaiporn and Akaracharanya (2000) reported that YE is a growth limiting factor of Bacillus K10 grown in a BSM-DBT medium. The concentration of YE higher than 2.0% (w/v) inhibited DBT desulfurization by Bacillus K10. Hirano et al. (2004) reported DBT-removal through the Kodama pathway by Xanthobacter polyaromaticivorans sp. in the presence of 0.05 g/L of YE in a carbon and sulfur-free medium. Kim et al. (2004) reported that the removal rate of the PASHs increased with increasing amounts of YE. However, Ohshiro et al. (1996a) and Xiaojuan et al. (2008) reported that upon adding YE, this could remarkably increase cell growth, but did not increase the removal rate of DBT and Th. Yu et al. (2006) reported that YE is an excellent nitrogen source for bacterial growth because it contains all the metal ions and required micro-nutrients. Zahra et al. (2006) reported that Trichosporon sp. gave better growth when glucose (5 g/l) and yeast extract (0.05 g/l) were added to BSM containing DBT. Wang et al. (2015) reported batch DBT-BDS by a thermophilic mixed culture of Paenibacillus spp. “32O-W” and “32O-Y” in a minimal medium supplemented with glucose and yeast extract. However, Salmani et al. (2015) reported the best conditions for BDS activity of R. erythropolis IGTS8 were 2 g/L NH₄Cl and 10 g/L glycerol.

Alves et al. (2005) reported that glucose, sucrose, n-hexadecane, and mannitol, in a decreasing order, are the most suitable sources of carbon to support the bacterial growth of G. alkanivorans strain 1B in a batch BDS of 0.2 mM DBT. Strain 1B showed poor growth on tetrahydrofuran and anthrone and for the other sources of carbon tested, including DBT sulfone and 2-HBP, no bacterial growth was observed. Moreover, no bacterial growth was detected when DBT was used as sole S- and C- sources. This added to the privilege of strain 1B, as it does not affect the hydrocarbon skeleton. Li et al. (2007) studied the effect of different C-sources, including glycerol, glucose, sucrose, ethanol, trisodium citrate dehydrate, sodium succinate, potassium acetate, and paraffin, on the growth and BDS of 0.2 mmol/L DBT using growing cells of R. erythropolis LSSE8–1. Glycerol expressed the highest growth and BDS efficiency, followed by other C-sources, but Paraffin showed the lowest growth and BDS efficiency. Li et al. (2007) also studied the effect of different N-sources, including ammonium chloride, urea, ammonium nitrate, ammonium acetate, and magnesium nitrate. NH₄Cl was found to be the best N-source for obtaining high growth and BDS efficiency. Upon the growth on different S-sources to get efficient resting cells with high BDS capabilities, DBT, DMSO, sodium sulfate, and taurine were tested. Resting cells of 48 h age grown on DBT expressed the highest BDS capabilities. DBT and DMSO was used to obtain high cell density culture in a jar-fermenter. 1 g/L of yeast extract was supplemented to enhance cell growth and the function of the small quantity of DBT with the inducement of Dsz enzymes.

Bordoloi et al. (2014) reported that the addition of glycerol as a carbon source in the BDS process of hydrodesulfurized diesel oil by resting cells of Achromobacter sp. led to good BDS efficiency without compromising the quality of oil.

Abo-State et al. (2014) investigated the effect of different C-sources as co-substrates in shaken flask batch DBT-BDS processes using Brevibacillus invocatus C19 and Rhodococcus erythropolis IGTS8. Within the studied five carbon sources (glycerol, saccharides, glucose and sucrose, and organic acid salts, sodium lactate and sodium succinate), glucose and glycerol expressed the highest biodesulfurization efficiency of 1000 ppm DBT for C19 and IGTS8, respectively. This recorded good growth with a BDS percentage of 82.3 and 67.34%, with non-stoichiometric production of 2-HBP of 48.06 and 40.67 ppm, respectively.

Gün et al. (2015) studied the effect of different C-sources, including D-glucose, D-arabinose, D-mannitol, and ethanol, at an initial concentration of 2 g/L on the growth of the acidophilic and thermophilic biodesulfurizing S. solfataricus P2. This recorded a maximum growth rate of 0.0164 h^–1 and a biomass concentration of 0.149 g DCW/L using glucose, while the other C-sources did not support the growth. This was attributed to the possession of S. solfataricus by a semi-phosporylative Entner–Doudoroff (ED) pathway for sugar metabolism (Sato and Atomi, 2011; Kouril et al., 2013). Thus, since glucose is the first metabolite necessary to initiate glycolysis, better glucose utilization than the other sugars would occur. Further, Sato and Atomi (2011) proposed well-defined pentose mechanisms in S. solfataricus for both D- and L-arabinose that include intermediates which are not heat stable. Thus, these products may become degraded while enough ATP is accumulated to allow cells to survive. Kouril et al. (2013) also reported unstable intermediate metabolites in the semi-phosporylative ED pathway during glucose metabolism using hyperthermophiles that grow at extreme temperatures. Therefore, a similar type of unstable intermediate production in the pentose mechanism may prevent the growth of S. solfataricus cells under scarce sugar supplies. Upon studying the effect of different glucose concentrations on P1, the highest growth rate and biomass concentation of 0.0339 h^-1 and 0.157 g DCW/L were obtained at 20 g/ L, respectively. Moreover, the time for achieving maximum growth decreased from 60.9 h using 2 g/L glucose to 29.5 h at 20 g/L glucose with an observed decrease in lag phase and time required for reaching the stationary phase.

Papizadeh et al. (2017) studied the effect of different C-sources, including benzoate, glucose, and glycerol, on the BDS of DBT using Entreobacter sp. strain NISOC-03, where the BDS efficiency decreased from 64% in the presence of benzoate to 19.6% in the presence of the other C-sources. In comparison, in the presence of benzoate and DBT as the carbon and sulfur sources, the rate of the DBT biodesulfurization was 3.26 times higher than that in the presence of glucose.

The addition of some nutrients and nitrogen sources, such as yeast extract (El-Gendy et al., 2014; Gün et al., 2015) and glutamic acid (del Olmo et al., 2005; Martin et al., 2005), have been reported to enhance the rate of BDS.

Yan et al. (2008) reported that the addition of nicotinamide and riboflavin as cofactor precursors to the 4S-pathway would enhance the BDS efficiency. The addition of nicotinamide and riboflavin would also increase the BDS efficiency in multiple uses of immobilized cells. However, their addition to batch DBT-BDS, using G. alkanivorans, expressed no effect on growth or BDS-activity (Aggarwal et al., 2013). This was explained by the possibility of their action at the regulatory or transcriptional level rather than the metabolic level as hypothesized by Yan et al. (2008).

Derikvand et al. (2014) observed the loss of BDS efficiency (X_BDS%) of γ-Al₂O₃NPs/alginate immobilized R. erythropolis R1 after 4 successive cycles from 81% to 59%, in spite of the preservation of cell viability, which was attributed to the great loss in the cofactors (NADH₂ and FMNH₂). But, the addition of 10 mmol/L nicotinamide and 40 mmol/L riboflavin as precursors of NADH₂ and FMNH₂, respectively, to the BDS media in BDS activity, enhanced and maintained approximately 77% BDS efficiency after the 4^th cycle.

Moreover, the addition of co-substrates can regenerate some of the key cofactors involved in microbial metabolism, such as NADH and NAD(P) H, by means of the coupled enzyme approach, which would, consequently, enhance the yield of a whole cell-based bioprocess (Wichmann and Vasic-Racki, 2003). The 4S-pathway is deeply influenced by the availability of ATP because of the crucial importance of this cofactor in the energetic metabolism and the 4S-pathway as an energy-intensive bioprocess. NADH regeneration also implies an enhancement of the availability of other key cofactors, such as ATP (Zhou et al., 2009), which is the most important energy source for metabolic reactions. Currently, the study of its role on the BDS process is becoming more important. It has been confirmed that the uptake of DBT into cells is ATP-driven (Wang et al., 2011) and ATP is also used in the formation and consumption of sulfite and sulfate for biomass formation during DBT metabolism (Aggarwal et al., 2012). Martinez et al. (2015) reported that it is possible to improve the yield of the BDS process using resting cells of Pseudomonas putida CECT5279 by adding short chain organic acids, such as acetic, citric, and succinic acids. There was an optimal concentration of acetic and succinic acids that maximizes the BDS capacity (1.5% in both cases). The use of citric acid did not present the same trend; an improvement of the BDS capacity was observed, but there was a wider range of concentrations where the maximum improvement was reached. In all the situations of single age cells, a strong inhibition of the process was observed at higher concentrations (3%). However, upon the application of a consortium of mixed aged resting cells (67% of cells grown for 23 h and 33% of cells grown for 5 h), citric acid performed the best yield. The addition of this co-substrate also provided higher intracellular concentrations of some key metabolites, such as NADH and ATP. Upon using cells of a single age as a biocatalyst, it was possible to enhance the yield of the process up to 140% in a batch process and, when employing the optimal mixture of the cells’ age, an improvement of 122% was achieved in a fed-batch process. The initial intracellular concentrations of ATP and NADH also increased to 58 and 42%, respectively, and the initial rate of all of the 4S route was increased. The consumption of both cofactors was very similar with and without a co-substrate (0.50 µmol_NADH/gX and 30 nmol_ATP/gX, respectively) and the differences in the concentrations of the cofactors at the end of the process were much higher when acetic acid was supplied (74% 6for NADH and 181% for ATP). Moreover, the addition of co-substrates decreased the loss of 2-HBP with time and improved the life of the biocatalyst.

The addition of DMSO in bi-phasic systems is reported to increase the BDS efficiency as it increases the cell wall permeability, thus increasing the uptake of organosulfur compounds by microorganisms. Adlakha et al. (2016) reported that the addition of 0.2% DMSO increased the BDS of heavy crude oil from 29.73% to 67.71% within 72 h using resting cells of Gordonia sp. IITR100 in a batch BDS-process of 1/3 O/W. At that DMSO concentration, the possible intracellular concentrations of cytoplasmic enzymes and the proper orientation of the bacterial membrane were maintained. However, as the concentration of the permeabilizing agent (i.e. DMSO) was increased, a decrease in the BDS efficiency was observed. This indicated the occurrence of irreversible damage done to the cells. Moreover, DMSO could not be used with growing cells because it could act as a sulfur source as well as preventing the uptake of organosulfur compounds present in crude oil.

Upon optimization of medium composition for obtaining good growth for two biodesulfurizing Streptomyces species, Streptomyces sp. VUR PPR 101 and Streptomyces sp. VUR PPR 102, it was found that Streptomyces sp. VUR PPR101 expressed relatively more growth than Streptomyces sp. VUR PPR102 in the presence of all the studied carbon sources and for all the studied N-sources except for casein. However, both the species showed maximum growth in the presence of glucose and the least in the presence of cellulose. The obtained maximum growth of both species was found to be decreasing according to the following order: Glucose > Maltose > Starch > Glycerol > Mannitol > Fructose > Sucrose > Cellulose. The optimal nitrogen sources for Streptomyces sp. VUR PPR 101 and Streptomyces sp. VUR PPR 102 were found to be yeast extract and potassium nitrate, respectively. The least growth was expressed by both bacteria with urea (Praveen Reddy and Umamaheshwara Rao, 2015). Moreover, methionine was found to be the best amino acid source for both the Streptomyces species. The other studied amino acids, pheylalanine, tyrosine, alanine, arginine, lysine, proline, glutamine, and cysteine, also expressed good growth and the optimum salt concentration (i.e. NaCl) was found to be 1% (Praveen Reddy and Umamaheshwara Rao, 2015).

Amino acids, such as arginine, histidine, isoleucine, leucine, lysine, phenylalanine, tryptophan, tyrosine, and valine, are reported not to affect the growth nor desulfurization activity of G. alkanivorans. In contrast, cysteine and methionine had strong effects on desulfurization. The sulfur-containing amino acids, such as cysteine and methionine, decreased desulfurization activity of G. alkanivorans (Aggarwal et al., 2013). Similar to R. erythropolis, G. alkanivorans has the ability to utilize cysteine as a sole sulfur source, which is energetically less expensive than DBT (1 mole DBT requires additional 4 moles of NADH). Therefore, the cell prefers to consume cysteine rather than DBT and inhibit the DBT-BDS (Aggarwal et al., 2011), while the reduced desulfurization in the presence of methionine may be due to the inability of G. alkanivorans to produce all the sulfur-containing metabolic precursors solely from methionine. For instance, they cannot produce cysteine, L-homocysteine, coenzyme A, etc. solely from methionine and, hence, need an additional sulfur source such as DBT or BT. However, Alanine, asparagine, aspartate, glutamine, glutamate, glycine, proline, serine, and threonine improved growth and desulfurization greatly. These, in contrast to cysteine and methionine, can serve as sole carbon sources as well. Thus, they supplement glucose and promote higher growth and cofactor regeneration. Since sulfur is essential for growth, higher growth leads to greater sulfur usage and higher desulfurization (Aggarwal et al., 2013).

8.14 Effect of Growing and Resting Cells

Growing and resting cells can be used for the BDS process, but resting cells are preferable as they offer greater desulfurization yields (Ohshiro et al., 1996b; Konishi et al., 1997) and overcome the problem of cofactor (NADH) regenerations, which is an important factor and supports the first three oxygenation steps in the 4S-pathway (Luo et al., 2003; Alcon et al., 2005). Moreover, the aqueous phase can also be reduced using high densities of resting cells. They are also reported to give higher BDS efficiencies than the growing ones (Caro et al., 2007b). Ohshiro et al. (1994) and Setti et al. (1997) reported that NADH is a fundamental limiting factor with growing cell conditions. However, in a study performed by Adlakha et al. (2016), the BDS of heavy crude oil applying resting cells was lower than that obtained using growing cells of Gordonia sp. IITR100. But, upon applying resting cells of Ralstonia eutropha (PTCC1615) collected at the mid-exponential growth phase in batch a BDS of DBT (0.05 mM), the specific BDS rate was much higher than that using growing cells, recording 0.01674 and 0.002 mmol/g_cell/h, respectively.

8.15 Inhibitory Effect of Byproducts

As it has been previously mentioned (Chapter 6), the 4S pathway is a four-step enzymatic pathway that converts DBT to 2-hydroxybiphenyl (HBP) and/or 2,2′-bihydrobiphenyl (2,2′-BHBP) and sulfate (Figure 8.3). The first two steps are the conversion of DBT to DBT sulfoxide (DBTO) and then to DBT sulfone (DBTO₂). These steps are catalyzed by the enzymes DszC monooxygenase and DszD oxidoreductase in synchrony. The third step is the conversion of DBTO₂ to 2-(2′-hydroxyphenyl) benzene sulfinate (HBPS), which is catalyzed by DszA monooxygenase and DszD oxidoreductase in synchrony. The final step is the conversion of HBPS to HBP and sulfite by DszB desulfinase (Gray et al., 2003).

However, it has been reported by several researchers that the main obstacle making BDS not commercially viable are the process limitations caused not only by mass transfer problems, its slower rate than the conventional HDS process, and the short life time of the biocatalyst, but also the cellular deactivation caused by the inhibitory effects of products such as biphenyl (BP), 2-HBP, and/or 2,2′-BHBP (Oshiro et al., 1995, 1997; Setti et al., 1996; Maxwell and Yu, 2000; Abin-Fuentes et al., 2013; Akhtar et al., 2016), and also, sulfate accumulation (Li et al., 1996). The inhibition effect of 2,2′-BHBP is known to be lower than that of 2-HBP (Kim et al., 2004).

The amount of sulfate detected in BDS cultures are always non-stoichiometric with the amount of desulfurized DBT. According to Kilbane (1990), the sulfate released is consumed by the bacteria to satisfy their growth requirements and any remaining sulfur is stored by the organisms for future use. Consequently, very little sulfate sulfur would be left to be released in the media.

Although the sulfate enhances the growth rate, the produced sulfate in the 4S-pathway is also reported to cause repression of dsz genes (Kayser et al., 1993; Ohshiro et al, 1995b; Wang and Krawiec, 1996; Oldfield et al., 1997; Kim et al., 2004; Wang et al., 2004; del Olmo et al., 2005a; Alves et al., 2005; Mohebali et al., 2008; Silva et al., 2013). The inhibition of DBT desulfurization activity by sulfate is considered to be a gene-level regulation. The expression of dsz genes that are involved in the desulfurization of DBT is strongly repressed by sulfates (Li et al., 1996). The organism needs 4 moles of NADH per 1 mol of DBT to use DBT to get the needed sulfur for growth. In contrast, the organism does not need this extra NADH for metabolizing sulfate. Thus, sulfate promotes higher growth at lower energy and so the organism prefers sulfate consumption over DBT conversion. Only when sulfate is limited, does it desulfurize DBT (Aggarwal et al., 2011). Omori et al. (1995) also observed enhanced desulfurizing rates arising from the removal of byproduct sulfate from a succinate-based medium. Wang et al. (2004) reported the complete inhibition of DBT-BDS by growing cells of Corynebacterium sp. ZD-1 with almost no 2-HBP production when the concentration of SO₄^2- was above 0.2 mmol/L. This was related to sulfate ions and their strong inhibition effect on the production of DBT-desulfurization enzymes. However, it has no effect on the BDS activity of resting cells. The BDS of 100 ppm DBT in the presence and absence of sulfate was investigated using Pantoea agglomerans D23W3, which expressed 23 and 92% removal after 24 h, respectively, which proved the suppression of BDS in presence of sulfate (Bhatia and Sharma, 2010). An amount as low as 6 mg/L of sulfate is enough to cause more than 22% inhibition in DBT-BDS by Gordonia alkanivorans strain 1B (Silva et al., 2013), while 60 mg/L sulfate was reported to completely inhibit the BDS activity of G. alkanivorans 1B and the IC_50–72h for desulfurization activity was estimated to be 13.6± 0.6 mg/L (Silva et al., 2013). From the process point of view, the removal of such feedback regulation is very essential for the success of the BDS-process.

It should be known that most of the published studies prove the non-stoichiometric relation between the consumption of DBT and the production of 2-HBP and/or 2,2′-BHBP and attributed this to the accumulation of 2-HBP and other 4S-pathway intermediates (up to a certain threshold) inside and on the surface of the cells (Alves et al., 2005; Derikvand et al., 2015b). On the other hand, Wang and Krawiec (1994) suggested that the difference might be owed to the volatile characteristics of 2-HBP. Alves et al. (2005) reported the maximum extracellular concentration of 2-HBP was about 120 µM, which is only 27% of the consumed DBT (450 µM). This non-stoichiometric accumulation of 2-HBP had also been observed in Nocardia sp. strain CYKS2 (Chang et al., 1998), Bacillus subtilis strain WU-S2B (Kirimura et al., 2001), Corynebacterium sp. ZD-1 (Wang, 2004), Rhodococcus spp. Eu-32 (Akhtar et al., 2009), Lysinibacillus sphaericus DMT-7 (Bahuguna et al., 2011), Bacillus pumillus-related strain (Buzanello et al., 2014), Actinomycete R3 (Khedkar and Shanker, 2015), 10 new isolates of genera Gordonia, Amycolatopsis, Microbacterium, and Mycobacterium (Akhtar et al., 2016), and another three bacterial isolates, P. putida TU-S2, B. pumilus TU-S5, and R. erythropolis TU-S7 (Shahaby and Essam El-din, 2017). In a batch DBT-BDS by bacterial consortium AK6, approximately 90% DBT removal was recorded, but only 11% of the utilized DBT substrate were recovered as 2-HBP (Ismail et al., 2016). This non-stoichiometric relation can be attributed to the 4S-pathway itself since the 4S pathway for the conversion of DBT to HBP is a multistep pathway catalyzed by a series of enzymes with different activities, controls, and regulations (Gray et al., 1996). For example, the enzyme dibenzothiophene sulfone monooxygenase (catalyzing conversion of DBTO₂ to DBT- sulfinate) has five times the activity of the enzyme desulfinase (catalyzing conversion of DBT-sulfinate to HBP) (Gray et al., 1996). A maximum consumption rate of DBT (11 µmol/g DCW/h) was observed at the early exponential growth phase of Rhodococcus sp. strain SA11 and the maximum 2-HBP formation rate (4 µmol/g DCW/h) was reached in the mid exponential growth phase (Mohamed et al., 2015). This was also observed in another study by Bordoloi et al. (2014), where Achromobacter sp. desulfurized 0.5 mM DBT to 0.03 mM 96 h post incubation, while the concentration of 2-HBP produced from the DBT never exceeded 0.01 mM. However, some microbial strains reported the formation of 2-HBP to be almost equal to DBT removal (i.e. the stoichiometric production of 2-HBP with the depletion of DBT), for example, Pseudomonas delafieldii R-8 (Lu et al., 2003), Nocardia globerula R-9 (Minfang et al., 2003), and Mycobacterium sp. ZD-19 (Chen et al., 2008a). However, in a study performed by Alves and Paixão (2011) on Gordonia alkanivorans 1B and Rhodococcus erythropolis D1, it was proven that microorganisms exhibiting faster generation times could be more resistant to 2-HBP accumulation during a BDS process. In other words, strains presenting a lower growth rate are characterized by a higher sensitivity to 2-HBP and attributed this to lower cell numbers in contact with the toxicant (i.e. 2-HBP). The inhibitory concentration that causes an inhibition of 50% of the bacterial baseline respiration rate i.e., the IC₅₀, were recorded. The acute toxicity assay revealed that the 2-HBP IC_50–3h values were 0.52 mM for strain D1 and 0.62 mM for strain 1B, while the chronic toxicity assays revealed that the 2-HBP IC_50–72h and IC_50–120h values were 0.27 mM and 0.21 mM, respectively, for G. kanivorans 1B and 0.49 mM and 0.38 mM for R. erythropolis D1, respectively. However, Dejaloud et al. (2017) reported that no inhibition of cell growth was observed at low concentrations of 2-HBP (<0.1 mM).

Usually, the production of 2-HBP occurs within 48 h (Monticello, 2000) and the presence of DBTO₂ till 120 h in cultures is unique since DBTO₂ is usually present for a short time, as it is a transition phase in the pathway during the conversion of DBT to 2-HBP (Gray et al., 1996; Chen et al., 1998b). However, in batch DBT-BDS culture using Pantoea agglomerans D23W3, DBTO₂ accumulated up to 120 h and 2-HBP appeared only after 120 h. Thus, the conversion of DBTO₂ to 2-HBP was considered as the rate limiting step in the 4S-pathway by Pantoea agglomerans D23W3 (Bhatia and Sharma, 2010). The delay in accumulation of 2-HBP is beneficial for the continuous desulfurization of DBT, as the accumulation of 2-HBP leads to the inhibition of the microbial activity to desulfurize DBT (Gray et al., 1996; Chen et al., 1998b).

Upon the exogenous addition of 2-HBP in a batch BDS of DBT using Gordonia sp. CYKS1 (Kim et al., 2004), it was found to retain a 90% desulfurization rate upon the addition of 0.1 mM 2-HBP compared to that with an exogenous addition of HBP. However, upon the exogenous addition of ≥ 0.15 mM 2-HBP, no significant cell growth or DBT-BDS were observed, but upon the exogenous addition of 2,2′-BHBP, most of the added DBT (0.3 mM) was desulfurized in 72 hours in the presence of 0.2 mM of 2,2’-BHBP. About 0.25 mM of DBT was desulfurized when 0.4 mM of 2,2’-BHBP was added, but no significant DBT-BDS was observed in the presence of 0.8 mM 2,2’-BHBP. Upon the exogenous addition of Na₂SO₄, the BDS capacity decreased. When 0.07 mM of sulfate was initially added, only about 0.02 mM of DBT was desulfurized in 72 hours, while 0.27 mM of DBT was desulfurized in the case of the control in which only DBT was the sole sulfur source. The desulfurization rate at 0.07 mM of sulfate was 3.13 µmol/L/h being about 70% of that (4.70 µmol/L/h) obtained in the control, but no significant DBT-BDS occurred at a higher initial sulfate concentration ≥ 0.7 mM. The initial exogenous addition of 2-HBP was also reported to inhibit the growth and BDS activity of Rhodococcus sp. MP12, where the cells hardly grew when the initial 2-HBP concentration was above 0.2 mM in a growth medium with 300 µL/L DMSO as a sulfur source. In this case, the increase of 2-HBP from 0.0 to 0.8 mM decreased the relative cell growth activity from 100% to 0% (Peng and Zhou, 2016), but the desulfurization activity of MP12 cells decreased sharply by 60% when the initial 2-HBP concentration in the DBT system reached 150 M and, further, increased the initial 2-HBP concentration to 250 M, which obviously led to the significant inhibitory effect on desulfurization activity. Moreover, it was noted that there was no significant inhibitory effect on desulfurization activity when the initial 2-HBP concentration was less than 100 M. This indicated that the exogenous 2-HBP had a significant inhibition on the desulfurization activity of MP12 cells grown with DMSO as a sulfur source and the desulfurization activity decreased with an increase of initial 2-HBP concentration. Breifly, initial 2-HBP expresses an inhibitive effect on both growth characteristics and the desulfurization activity of strain MP12. However, Abin-Fuentes et al. (2013) concluded that both generated endogenously or supplied exogenously 2-HBP reduces the overall biocatalyst activity and 2-HBP added exogenously cannot be used to quantitatively predict the effect of HBP on a typical BDS process where DBT is added exogenously and HBP is generated endogenously within the cytoplasm of the cells.

In a study performed by Gray et al. (1996), where R. erythropolis IGTS8 lysates were initially supplied with 200 M DBT and the concentrations of DBT, DBTO₂, HBPS, and HBP were monitored over time, after 10 min all DBT was depleted, the HBPS concentration was approximately 130 M, and the HBP concentration was approximately 50 M. From 10 to 60 min, the HBPS concentration decreased steadily from 130 to 0 M and the HBP concentration increased from 50 to 200 M, but no DBTO₂ was detected at any time. The DszB of Rhodococcus erythropolis IGTS8, which catalyzes the slowest reaction, has a turnover number (k_cat) of about 2 min^-1, while DszA and DszD have k_cat values of 60 and 300 min^-1, respectively (Gray et al., 1996).

Watkins et al. (2003) appropriately modeled the DszB kinetics by the Michaelis-Menten model with a Michaelis constant (K_m) of 0.90 ± 0.15 µM and a k_cat of 1.3± 0.07 min^-1. The activity of DszC from R. erythropolis D-1 was reported to be 30.3 nmol DBTO₂/mg DszC/min (Ohshiro et al., 1997). It is worth noting that DBTO is usually not typically observed during the BDS process because its rate of consumption is much faster than its rate of production (Gray et al., 1996). Abin-Fuentes et al. (2013) explained the data obtained by Gray et al. (1996) by another study performed by resting cells of R. erythropolis IGTS8 as follows: the k_cat of DszA was approximately 7 times that of DszC. The consumption rate of DBTO₂ was found to be significantly greater than its generation rate. This explained the non-detection of DBTO₂ in that study. Moreover, the buildup of HBPS within the first 10 min is consistent with the fact that its consumption rate (DszB k_cat 1.7 min^-1) is significantly slower than its generation rate (DszA k_cat 11.2 min^-1). The fact that the HBP concentration accumulates to over 130 M within the first few minutes indicated that DszC would have been severely inhibited by HBPS at that point in time. As HBPS is consumed, DszC inhibition by HBPS is relieved, but then HBP inhibition of DszC (and DszA and DszB) becomes more significant. Furthermore, HBPS inhibition of DszC is responsible for maintaining a low BDS rate at the beginning of the BDS process when HBP levels are still low. Once HBP levels rise, HBP inhibition of DszA, DszB, and DszC is mostly responsible for the inhibition of the BDS rate.

Several researchers reported that the decrease in BDS activity is attributed to the accumulation of 2-HBP (Naito et al., 2001; Schilling et al., 2002; Kilbane et al., 2006). Honda et al. (1998) reported the growth inhibition of R. erythropolis IGTS8 by HBP at concentrations > 200 µM; the same was also reported by Ohshiro et al. (1996b) for R. erythropolis H-2. Nakayama et al. (2002) reported the inhibition of R. erythropolis KA2–5-1 DszB enzymatic activity and its reduction by 50% at HBP concentrations of ≈ 2,000 µM. It has also been reported in other published studies that 2-HBP is toxic to bacterial cells and that once the concentration of 2-HBP reached 0.2 mM, the BDS of DBT was inhibited by Rhodococcus erythropolis D-1 (Ohshiro et al., 1996a), Gordona strain CYKS1 (Rhee et al., 1998), and Mycobacterium sp. X7B (Li et al., 2003). Akhtar et al. (2009) observed a complete growth inhibition of Rhodococcus Eu-32 when the concentration of 2-HBP was > 0.4 mM. However, the 2-HBP concentration above 47.6 µM expressed an inhibitory effect on growth and, consequently, the BDS activity of S. solfataricus P2 (Gün et al., 2015).

Corynebacterium sp. ZD-1 showed no growth on DBT with an exogenous addition of 0.1 mmol/L 2-HBP, but it did not affect the growth on NaSO₄, although 1 mmol/L 2-HBP expressed toxicity on it. This was attributed to the inhibitory effect of 2-HBP on DBT-BDS, which would lead to a lack of S-supply necessary for microbial growth (Wang et al., 2004). Caro et al. (2008) also studied the inhibition effect of 2-HBP on the BDS activity of R. erythropolis IGTS8 throughout the exogenous addition of 50 µM HBP in an aqueous system using resting cell suspension of 2 g DCW/L, supplied with only one of the 4S pathway compounds (either DBT, DBTO, DBTO₂, or HBPS). The disappearance rate of DBTO and HBPS were significantly reduced by the presence of 50 M HBP, suggesting the inhibitory effect of HBP on the enzymes responsible for the conversion of DBTO and HBS, DszC and DszB, respectively. In a similar study on resting cells of Microbacterium sp. strain ZD-M2, the DBT-desulfurization rate was found to decrease significantly when HBP was added exogenously at concentrations ranging from 0 to 2000 M (Chen et al., 2008b). However, the exogenous addition of HBP does not give an accurate indication of the effect of HBP on the BDS efficiency, since, upon the exogenous addition of HBP, a significant fraction would be retained by the cell wall and may never reach the cytoplasm, where the inhibition of the desulfurization enzymes occurs. On the other hand, HBP generated endogenously within the cytoplasm is immediately at the location where it can be inhibitory to the desulfurization enzymes. Therefore, the specific HBP loading of the biocatalyst (mg HBP/g DCW) that leads to a certain level of reduction in BDS activity may be significantly larger when HBP is added exogenously.

Schilling et al. (2002) studied the kinetics of DBT-BDS by R. erythropolis IGTS8 of cell density 66 g DCW/L in a model oil (19,000 M DBT in n-hexane 1:1 v/v). This was found to follow the first order decay, with a decay constant of 0.072 h^-1, and the loss of biocatalyst activity was attributed to the exposure of increasing HBP concentrations. The cells were active for 24 h, and, although only 7,000 out of 19,000 M DBT in oil was consumed, the final concentration of HBP accumulated in the oil phase after 24 h was only 3,300 M. This discrepancy has been suggested to be due to the accumulation of pathway intermediates or the retention of DBT and/or HBP within the biocatalyst. The amount of DBT or HBP retained by the biocatalyst depends on the partition coefficients between the biocatalyst and the oil or aqueous phases, P_C/O or P_C/W, respectively (where C, O, and W represent cells, oil, and water, respectively). Based on the finding reported by Lichtinger et al. (2000), the Gram +ve R. erythropolis, as a member of the Actinomycetes family, is characterized by a cytoplasmic membrane surrounded by a thick cell wall composed of a thick peptidoglycan structure to which fatty acid molecules are attached. Moreover, the cell wall is composed of mycolicacids of C-length ranges between 30–45 C-atoms that are perpendicular to the cell surface, which makes the cell wall of R. erythropolis highly hydrophobic.

Several researchers reported that the decrease in BDS activity is attributed to the accumulation of 2-HBP (Naito et al., 2001; Schilling et al., 2002; Kilbane, 2006). Honda et al. (1998) reported the growth inhibition of R. erythropolis IGTS8 by HBP at concentrations > 200 µM. Nakayama et al. (2002) reported the inhibition of R. erythropolis KA2–5-1 DszB enzymatic activity and its reduction by 50% at HBP concentrations of ≈ 2,000 µM. Mohamed et al. (2015) reported that DBT-cultures of Rhodococcus sp. strain SA11 exhibited around 30% growth retardation at 0.3 mM 2-HBP. Moreover, upon the exogenous addition of 0.5 mM 2-HBP during the log growth phase, a sharp drop in growth occurred within 1 h after addition.

The activity of a R. erythroplis IGTS8 resting-cell suspension of 15.5 g DCW/liter was decreased by 90% when the HBP concentration in the aqueous medium reached 40 M (Abin-Fuentes et al., 2013). The dose-response experiments performed by Abin-Fuentes et al. (2013) to identify major inhibitory interactions in the most common 4S-BDS pathway revealed that HBP is responsible for three of the four major inhibitory interactions identified. The concentrations of HBP that led to a 50% reduction in the enzymes’ activities (IC₅₀s) for DszA, DszB, and DszC were found to be 60±5 µM, 110±10 µM, and 50± 5 µM, respectively. The fact that the IC₅₀s for HBP are all significantly lower than the cytoplasmic HBP concentration suggests that the inhibition of the desulfurization enzymes by HBP is responsible for the observed reduction in biocatalyst activities concomitant with HBP generation.

Gün et al. (2015) reported the effects of using different inorganic S-sources (elemental sulfur, sodium sulfite, sodium sulfate, potassium persulfate, and potassium disulfite) on the growth of the acidophilic and hyper-thermophilic S. solfataricus P2 and revealed a high growth rate and maximum biomass concentration of 0.0220 h^-1 and 0.651 g DCW/L in sulfate sources, respectively. This was followed by the disulfite source recording 0.0254 h^-1 and 0.623 g DCW/L, then the sulfite, recording 0.0226 h^-1 and 0.628 g DCW/L, respectively, while the elemental S recorded the lowest at 0.0165 h^-1 and 0.586 g DCW/L, respectively. However, all the studied inorganic sulfur sources led to rapid cell death after a maximum biomass cell density was obtained, except for in the elemental sulfur case which showed a sustained stationary phase. The observed rapid microbial death with sulfate and sulfite was explained by the excess uptake of these anions by the cells, leading to a demand for counter ion balance, which can be maintained by excess accumulation of cations to cells, causing an osmotic imbalance.

Feng et al. (2016) studied the detailed effects of the major end products 2-HBP and sulfate ions (0, 0.05, 0.1, or 0.2 mmol/L) on cell growth and transcriptional levels of dszA/dszB/dszC and desulfurization efficiency of Gordonia sp. JDZX13 in a batch BDS of 0.3 mmol/L DBT at 35 °C and 170 rpm within 80 h, while the resting cells were used as the indicator of desulfurization enzyme activity at 30 °C, 170 rpm, and 12 h. 2-HBP was found to be highly toxic to cell growth and, consequently, desulfurization activity. The results revealed the decrease in the specific growth rate with the increase of exogenous 2-HBP concentration recording 0.147, 0.139, 0.131, and 0.11 h^-1. It was also depicted that the lag phase was lengthened with the increase of 2-HBP concentration, while DBT was completely removed in the control flasks (i.e. without 2-HBP) and at 0.05 mmol/L recorded 98.8% and 20.2% with 0.1 and 0.2 mmol/L, respectively. The effect on BDS efficiency, applying resting cells recorded 20.89%, 15.71%, 11.51%, and 3.31%, respectively. These results confirmed the strong inhibition effect of the desulfurization enzyme activity. The effects of different 2-HBP densities on the transcriptional level of key desulfurization related genes and fluorescent quantitative PCR was performed. With an increase in 2-HBP, the transcriptional levels of the desulfurization genes dszA/dszB/dszC gradually decreased. Compared to the blank system, the transcriptional levels of the desulfurization genes dszA/dszB/dszC were 0.89, 0.71, and 0.65 times, respectively, in 0.05 mmol/L 2-HBP. Compared to the blank system, the transcriptional levels of desulfurization genes dszA/dszB/dszC were 0.81, 0.66, and 0.59 times, respectively, in the 0.1 mmol/L 2-HBP system. Compared to the blank system, the transcriptional levels of the desulfurization genes dszA/dszB/dszC were 0.77, 0.59. and 0.56 times, respectively, in the 0.2 mmol/L 2-HBP system. The effect of SO₄^2- depicted a specific growth rate of 0.147 h^-1, where the values were 0.171 h^-1, 0.163 h^-1, and 0.157 h^-1 with the addition of 0.05, 0.1, or 0.2 mmol/L SO₄^2-, respectively. At low sulfate ion concentration cell growth was accelerated. In contrast to the situation of 2-HBP, which was eliminated from the cell, part of the sulfate ion remains in the cell acted as a sulfur source for synthetic cysteine, methionine, vitamins, and other material necessary for life and the other part is excreted (Caro et al., 2008). However, there was a slight inhibition with an increase in sulfate ion concentration compared to lower sulfate ion concentration. The reason for this may be that the sulfur source was not the limiting factor and feedback inhibition was gradually generated by excess sulfate ions (Soleimani, et al., 2007; Abro et al., 2014). The BDS effeminacy using growing cells was also affected by the intial SO₄^2- concentrations. In the blank and 0.05 mmol/L sulfate ion systems, DBT was completely eliminated, while 95.6% and 15.6% DBT removal were recorded with 0.1 mmol/L and 0.2 mmol/L sulfate ions systems, respectively. Thus, sulfate increases the growth rate, but inhibits the BDS efficiency. This was attributed to the fact that excessive sulfate ions inhibit the expression of desulfurization genes or even directly reduce enzyme activity, which, consequently, lower the desulfurization efficiency (Caro et al., 2007b; McFarland et al., 1998; Abin-Fuentes et al., 2013). Moreover, the BDS efficiency of the resting cells, compared to the control flasks (i.e. without exogenous addition of sulfate), slightly decreased with sulfate ion concentrations, recording 23.70%, 33.12%, and 37.80% for 0.05, 0.1, and 0.2 mmol/L sulfate ions systems, respectively. This confirmed that the desulfurization enzyme activity was slightly inhibited under higher sulfate ion concentration. To confront the increase in sulfate ions, the transcription of desulfurization genes, dszA/dszB/dszC, first, upregulated and then decreased. Under 0.05 mmol/L sulfate ions, the transcriptional levels of the desulfurization genes dszA/dszB/dszC were 3.61, 2.00, and 2.62 times, respectively, its original level. This was attributed to the utilization of sulfate ions for the synthesis of cellular substances which sequentially stimulate the expression of the desulfurization gene (Li et al., 2006; Kilbane, 2006; Chauhan et al., 2015). Under a 1 mmol/L sulfate ion, the transcriptional levels of dszA/dszB/dszC were only 0.33, 0.14, and 0.53 times, respectively, the original level. Different from 2-HBP, the expression of dszB and dszC down-regulated compared to dszA, thus the third and fourth steps were inhibited by sulfate ions. Compared to the equal 2-HBP concentration, the negative effect of sulfate ions on the desulfurization gene was more significant. Under the 0.2 mmol/L sulfate ion, the transcriptional levels of the desulfurization gene dszA/dszB/dszC severely down-regulated and were only 0.015, 0.004, and 0.011 times, respectively, the original level. These results also prove that the DBT removal performance of the resting cells was greatly inhibited under a higher sulfate concentration.

Thus, it can be concluded that accumulation of 2-HBP and sulfate ions would form prominent feedback inhibition effects on cell growth and biodesulfurization efficiency. Generally, the feedback inhibition effects of sulfate ions can be weakened by eliminating excess sulfate ions into the extracellular aqueous phase. Concerning 2-HBP, since it is hydrophobic in water and prefers to return back into the oil phase, it is well known that in a biphasic system, bacterial cells primarily grew in the aqueous phase and then a large number of cells gathered at the oil–aqueous interface due to the hydrophobic interaction between the cells (Gün et al., 2015), so Feng et al. (2016) suggested overcoming such bottleneck via using the biphasic system with an appropriate O/W phase ratio.

8.16 Statistical Optimization

Although there are many published studies about the BDS-process concerning isolation of new biodesulfurizing microorganisms, studies for the physiology of microorganisms and their gene modifications, as well as the metabolic pathways and kinetics of desulfurization in one phase and two phase systems of model and real oil feed, there are few reports on the significance of operational factors and their optimization through statistical methods.

It is difficult to identify the important factors and interactions between a large number of variables. Usually, one factor at a time technique is the conventional optimization procedure and involves altering one parameter at a time, keeping all other parameters constant, which enables one to assess the impact of those particular parameters on the process performance. However, it is time consuming.

The DOE or the experimental design is a powerful statistic-based approach to design experiments in order to achieve a predictive knowledge of a complex, multi-variable process with the fewest acceptable trials. It enables designers to simultaneously determine the individual and interactive effects of many factors that could affect the output results in any design. Thus, DOE provides a full insight of interaction between design elements; it helps to pin point the sensitive parts and areas in designs that cause problems in the yield, so designers would be then able to fix these problems to achieve robust performance and produce higher yield designs prior to going into production (Buasri et al., 2014). The essence of DOE is to plan informative experiments, analyze the resulting data to get a good model, and from the model, create meaningful maps of the system.

Taguchi orthogonal array experimental design is based on mixed levels of highly fractional factorial designs and other orthogonal arrays (OA) to perform the fewest number of experiments in a timely manner and at lower costs (Taguchi, 1986). It distinguishes between control variables which are the factors that can be controlled (i.e. inner array), and noise variables (i.e. outer array), which are factors that cannot be controlled except during experiments in the lab. Taguchi design provides information about the interaction between the controllable and noise variables. Each run in the inner array would be performed for all of the combinations in the outer array. A signal to noise (S/N) ratio, which summarizes the mean and variance information, is defined and data analysis would be carried out for this ratio using ANOVA to determine the optimum conditions, as well as the contribution of each factor in the experimental results (Biria and Balouchi, 2013). There are three applicable types of S/N ratio, depending on the optimization criteria: (1) lower is better (LB), (2) nominal is better (NB), and (3) higher is better (HB). The DOE using the Taguchi approach can economically satisfy the needs of problem solving and process design optimization projects. By applying this technique, engineers, scientists, and researchers can significantly reduce the time required for experimental investigations. It helps in examining the effect of different process parameters on the mean and variance of performance characteristics, which determine the proper functioning of the process. It is very effective with a nominal number of parameters (3–50) with few interactions between them and very few significant contributing ones.

Montgomery (2013) has noted that by using experimental design, engineers can determine which subset of the process variables has the greatest influence on process performance. The results of such experiments can lead to improved process yield and reduced design and development time and operation cost. Also, Box and Wilson applied the idea of DOE to industrial experiments and developed the response surface methodology RSM (Cavazzuti, 2013).

Response Surface Methodology (RSM) is one of the well-known statistical methods which is utilized for evaluating the important factors and finding a relationship between effective variables and one or more responses in a system. In another word, RSM is a collection of mathematical and statistical techniques that are useful for modeling and analysis of a process in which a response of interest is influenced by several variables and the objective is to optimize this response in that complex process. Accordingly, RSM is a 3-D response surface plotted on the basis of the predicted model equation to investigate the interaction among the variables and to determine the optimum condition (range) of each factor. The response surface of the response variable is mapped out and the process is moved as close to the optimum as possible, taking into account all constraints, supposing that the outputs are defects or yields and the goal is to minimize defects and maximize the yield. If these optimal points are in the interior of the region in which the experiment is to be conducted, we need a mathematical model that can represent curvature so that it has a local optimum. Response surface models may have quadratic and possibly cubic terms to account for curvature. The RSM helps in understanding the pattern in which the dependent variables are affected by the corresponding changes in the independent variables, improving the product of predicted property values, and predicting the interactive effects of two or more factors and the effects caused by the collective contributions of the measured response. This method is often employed after a “vital few” controllable factors have been identified in order to find the factor settings that optimize the response (Deriase et al., 2012; Alhassan et al., 2014). A contour plot is a graph that can be used to explore the potential relationship between three variables (i.e. the two independent variables and the response variable), where it displays a 3-D relationship in two dimensions, with independent variables plotted on the x- and y- scales and response values represented by the contours. In another word, a contour plot is like a topographical map in which x-, y-, and z-values are plotted instead of longitude, latitude, and elevation, where the contour lines corresponding to different levels will not cross each other and the contour lines of the same level may appear to intersect (Anderson and Whitcomb, 2015).

In this approach, analysis of variance (ANOVA) and regression techniques are employed to estimate a low degree polynomial model for optimization of the levels of significant explanatory variables in a limited number of experiments (El-Gendy et al., 2014). Central Composite Design (CCD) and Box-Behnken Design (BBD) of RSM are fractional factorial designs for the optimization of variables with a limited number of experiments.

The Box-Wilson or central composite design, which is commonly called the “central composite design (CCD)”, is a design that contains an imbedded factorial or fractional factorial design with center points that are augmented with a group of “star points” which allows estimation of curvature. The addition of center points to the 2k design, based on the idea of replicating some of the runs in a factorial design, runs at the center to provide an estimate of error and allows the experimenter to distinguish between two possible models of the first and second order. The CCD is a very effective design for fitting a second-order response surface model.

Thus, the CCD has a different structure from that of BBD, where in the former a ball is used, in which all of the corner points lay on the surface, while in the BBD, the ball is located inside the box defined by a wire frame that is composed of the edges of the box. Also, the number of observations for BBD are lower than those of CCD (Rezaei et al., 2013). Based on the CCD matrix, the studied independent factors would vary within a defined range to reach the optimum condition for the response (Koohikamali et al., 2012). In order to reduce the effects of any uncontrolled factor on the response, the sequence of the experiments in the designed matrix can be randomized (Montgomery, 2013). For k factors, 2k star points and one central point are added to the 2^k full factorial, bringing the sample size for the central composite design to 2^k + 2k+1, i.e. CCD is a 2^k full factorial to which the central point and the star points are added.

The Box-Behnken design (BBD) was devised by George E.P. Box and Donald Behnken in 1960 (Cavazzuti, 2013) to achieve a design where each factor is placed at one of three equally spaced points that are usually coded as -1, 0, and +1, where at least three levels for each factor are needed, taking into consideration that the design should be sufficient to fit a quadratic model and the ratio of the number of experimental points to the number of coefficients in the quadratic model should be reasonable.

One factor at a time technique was applied to select the optimal carbon, nitrogen, and sulfur sources for Rhodococcus erythropolis LSSE8–1, which is capable of desulfurizing DBT via the 4S-pathway to 2-HBP as an end product (Li et al., 2007). Glycerol expressed the highest growth and BDS capacity of 3.850 × 10^–3 mmol/L/h. NH₄Cl as an N-source showed the highest growth and BDS capacity of 3.96 ×10^–3 mmol/L/h. Resting cells of age 48 h that were grown on DBT, expressed the highest BDS of 7.46 × 10^–3 mmol/L/h. Upon applying Taguchi methodology, five factors, namely glycerol, ammonium chloride, DMSO, magnesium chloride, and a trace element solution at four levels with an orthogonal array layout of L16 (4⁵), were selected. The analysis of variance techniques to determine which factors were statistically significant for growth revealed that the influence of these variables on the growth (48 h), on a fermenter scale, was found to decline in the order: DMSO > magnesium chloride > ammonium chloride > trace element solution > glycerol. The resulting optimum conditions were glycerol 10 g/L, ammonium chloride 3 g/L, DMSO 3 mmol/L, magnesium chloride 2 g/L, and a trace element solution 0.5%. This showed an enhanced cell production of 70% from 3.40 to 5.78 g dry cells/L at 48 h cultivation (Li et al., 2007).

Upon experimental and numerical approaches for studying different factors affecting the growth and DBT removal efficiencies of Bacillus sphaericus HN1, Nassar (2009) found that the best equation model correlating both of the above mentioned response variables were incubation period (day), shaking speed (rpm), temperature (°C), and pH, represented as a simple k degree polynomial in the form:

where y stands for response (dependent) variable (the remaining DBT concentration (ppm i.e. mg/L) in the cultures or HN1 cell growth expressed in dry weight (mg/L)) and x represents the independent variable (the above mentioned key process variables applying one factor at a time). The b₀ represents the free regression coefficient parameter, a_k’s are the regression coefficients, and n is the degree of the polynomial. Table 8.2 represents the degree of the resulting polynomial.

The validity of the fitted models was evaluated using the analysis of variance (ANOVA) with the values of R² (unadjusted coefficient of multiple determination) and (adjusted coefficient of multiple determination). is computed using the formula:

where N represents the number of observations (data points), p is the number of parameters (regression coefficients), ŷ_i is the i^th observation of the dependent variable y, y_i represents the experimental value of the variable, ȳ is the average value of y, and R² and have a value closer to 1, indicating a better fit,

The Fischer’s (F) value is the ratio of the mean regression sum of squares divided by the mean error sum of squares. The value of prob(F) is the probability that all of the regression coefficients are zero. In general, the (F) value with a low probability (prob(F)) value indicates high significance of the regression model. The student t-test (t) can be used as a tool to check the significance of the regression coefficient. The prob(t) value is the probability of obtaining the estimated value of the regression coefficient. The smaller the value of prob(t), the more significant the coefficient is.

Nassar (2009) observed that the values of the calculated R² > 0.9406, > 0.901, F ratio, prob(F), and prob(t) were statistically significant and proved the goodness of fit of the predicted model equations. The optimum conditions for maximum growth and DBT-removal using Bacillus sphaericus HN1 were found to be 10 days’ incubation period, 200 rpm shaking speed, 30 °C, and pH7. These recoded an approximately complete removal of 250 ppm DBT with a maximum growth of approximately 8 × 10⁹ cells/mL.

One factor at a time technique was also applied by Nassar et al. (2017b) to optimize the growth and BDS efficiency of R. erythropolis HN2 in shaken flasks of batch a BDS of 1000 ppm DBT. Several model equations (Gaussian, polynomial, and exponential functions) were investigated to assess the relationships between the variable operating conditions and both cell growth and the percentage of BDS.

The relationships between the change in microbial growth (CFU/mL), with respect to variations in initial pH, incubation temperature, and shaking speed, were found to be best described by the Gaussian model for fitting peaks (Giraud, 2008)

where “a” is the height of the curve’s peak or amplitude (i.e. the curve maximum) and the graph expands vertically as “a” increases, “b” is the position of the center of the peak, that is, as “b” increases the graph is shifted to the right and upon the decease of “b”, the graph is shifted to the left, and “c” controls the width of the curve and is related to the full width at half maximum (FWHM) of the peak. As “c” is made small, the graph shrinks horizontally, and as “c” is made large, the graph expands horizontally. “n” is the number of peaks to fit.

The effects of initial pH, incubation temperature, and initial inoculum size on BDS-efficiency were found to be best described by a polynomial function of n^th degree

where P₁, …, P_n+1 are polynomial coefficients and x is the independent variable.

However, the exponential function which calculates the natural exponential of all the data was found to be the best at describing the effect of both the shaking speed on BDS-efficiency and initial inoculum size at maximum achieved microbial growth (CFU/mL). The general form of exponential function can be written as:

where a, b, c, and h are exponential coefficients and x is the independent variable.

Accepted mathematical model equations have been characterized by three common validity tests: (1) high correlation coefficient (R²) and adjusted correlation coefficient (), which indicate the applicability and reliability of a given model, (2) the accepted model must have the least values of sum of squares errors (SSE) and root mean square errors (RMSE) relative to those obtained for other tested mathematical models, and (3) a close agreement between the calculated and experimental values.

MATLAB software package 7.9.0 (R2009b) was used for numerical investigation, regression analysis of the data obtained, and estimation of the coefficients of the regression equation with 95% confidence bounds. The optimum values of the selected predictor (explanatory) variables were obtained by solving the corresponding predicted model equation using LINGO software package version 6.01 for mathematical optimization (http://www.LINDO.com). The predicted mathematical model equations that best represent the effects of different studied physicochemical operational parameters on microbial growth and DBT-BDS efficiency of growing cells of R. erythropolis HN2 in shaken flasks of batch BDS of 1000 ppm DBT, together with the corresponding goodness of fit parameters, are illustrated in Table 8.3. Thus, the optimum condition for maximum growth of HN2 was predicted to be a pH7, 29.48 °C, initial OD_600nm of 0.1 which is equivalent to 3.73 × 10⁴, and 155.9 rpm, while those for maximum BDS efficiency were a pH6.69, 27.47 °C, initial OD_600nm of 0.1, and 154.19 rpm. These recorded a BDS efficiency of approximately 82% in shaken flasks of a batch BDS of 1000 ppm DBT using R. erythropolis HN2 with a maximum growth of 3.2 × 10⁹ cells/mL within 8 d of incubation.

Physicochemical parameters	Model equations	Optimum predicted value	R2		SSE	RMSE
Initial pH		7	0.9716	0.9527	3.561e+17	3.445e+8
	%BDS = –8.84(pH)2 + 118.3(pH) – 319.9	6.69	0.988	0.980	37.9	3.554
Incubation Temperature		29.48 °C	0.9751	0.9585	1.84	0.7842
	%BDS = 0.005411(T)3 – 0.8483(T)2 + 34.36(T) – 340.6	27.47 °C	0.9938	0.9846	24.71	3.515
Initial Inoculum Size	CFU/mL = (7.894e + 9)exp(–8.152 * (OD600))	0.1 OD600	0.9964	0.9952	3.185e+16	1.03e+8
	%BDS = –168.1(OD600)3 +257.9(OD600)3 – 154.9(OD600) + 93.37	0.1 OD600	0.9931	0.9726	6.015	2.453
Shaking Speed		155.9 rpm	1.00	1.00	3.031e+13	3.893e+6
	%BDS = –(2.606)exp(0.0231*V) + (18.66)exp(0.01448 * V)	154.19 rpm	0.9962	0.985	11.41	3.378

where the CFU/mL is the total viable count of HN2 (i.e. the microbial growth), T is the process temperature (°C), OD is the optical density of the microbial cells culture (i.e. the absorbance at λ_600nm), and V is the shaking speed (rpm).

Taguchi design procedure was applied to study the effects of cell density, pH, and phase ratio at three levels on the desulfurization reaction of a biphasic system at 30 °C and 175 rpm using model oil (2.7 mM DBT in hexadecane) and resting cells of a newly isolated strain of RIPI-22, harvested in the late exponential phase (Rashtchi et al., 2006), where An L₉(3⁴) OA, which has 8 d.f., was used. The amount of 2HBP production as an indication for BDS-efficiency was measured in the hydrocarbon phase as a result of each trial condition. After performing the experiments, the analysis of data was accomplished using the standard approach determination of the main effects and formation of the ANOVA table and signal to noise (S/N) analysis by WinRobust™ and Qualitek-4^TM software. The data analysis revealed that the extent of desulfurization by RIPI-22 was hardly dependent on the pH, but the volume ratio of the hydrocarbon-aqueous phase significantly affected the desulfurization activity. The extent of desulfurization increased with raising cell density from 7 to 11 g/L, where the higher cell concentration (> 11 g/L) did not significantly influence the desulfurization. In addition, the results showed that DBT-BDS was well accomplished in a low phase ratio and the maximum activity occurred at a 30% (O/W) phase ratio. Using two aforementioned softwares, the optimum desulfurizing conditions using the newly isolated strain RIPI-22 were determined to be pH 6, 11 g DCW/L, and a hydrocarbon fraction of 30% (O/W) (Rashtchi et al., 2006).

Taguchi optimization was applied for preparation of an immobilized biocatalyst of Rhodococcus erythropolis R1 (NCBI GenBank Accession No. GU570564) resting cells in Ca-alginate beads (Derikvand et al., 2014). This was throughout the consideration of some important factors for achieving a successful BDS using immobilized cells, such as the alginate concentration, size of the beads, the concentration of surfactants, and γ-Al₂O₃ nanoparticles. The age of the resting cells was 72 h cultivated on 0.3 mM DBT. The immobilized beads were applied on a bi-phasic system (aqueous/1 mM DBT in n-tetradecane 2:1 v/v). The aim was to maximize the biodesulfurization yield (X_BDS). Thus, the S/N ratio with HB characteristics was utilized in the applied Taguchi design and was calculated as follows:

where n is the number of repetitions and X_BDS are the experimental results of BDS capacity (i.e. BDS-yield) and was calculated as follows:

where C_{2-HBP, 20} is the experimental concentration of 2-HBP at the end of prescribed time, t = 20 h, and C_DBTo is the initial DBT concentration at time zero.

Taguchi L18 orthogonal array for the three parameters is in three levels (3³) and one parameter in two levels (2¹), with a layout of 2¹ x 3³ was used indicating 18 experimental runs in duplicate. Moreover, the effects of factor levels on the BDS efficiency were determined employing analysis of variance (ANOVA) and the statistically significant factors were distinguished for P value < 0.05. The contribution percentage of the factors in the final results was calculated as well. Derikvand et al. (2014) found that the influence of the studied variables on the 2-HBP production was found to decline in the order: nano-γ-Al₂O₃ > surfactant > bead size > alginate concentration. The results revealed that all factors under investigation were significant (P < 0.05). The BDS efficiency increased by decreasing the bead size and was explained as the lower size of the bead, the higher the surface to volume ratio would be and thus, more interactions would occur between the cells and DBT. Surfactants were highly statistically, significantly effective in BDS (P-value = 0.001). Nevertheless, the addition of the Span-80 had a higher efficiency than Tween-80. The nano-γ-Al₂O₃ was found to be absolutely critical and was considered as the most effective factor in the BDS of DBT (percentage of contribution = 55.2% and P-value = 0). The optimum conditions were found to be 20% (w/w) nano γ-Al₂O₃, 1.5 mm bead size, 1% (w/v) alginate concentration, and 0.5% (v/v) Span-80 instead of Tween-80, which recorded X_BDS% of 81%.

RSM was used to optimize the pH, temperature, and shaking speed of a BDS-process using Stenotrophomonas maltophila strain Kho1. The optimum conditions were found to be pH7.2, 29 °C, and 180 rpm, respectively, which recorded a maximum growth of 0.42 g DCW/L and 63.15 µM 2-HBP from 1 mM DBT within 96 h (Ardakani et al., 2010).

RSM based on CCD was applied to optimize and study the interactive effects of the oil/water (O/W) phase ratio and initial sulfur concentration in shaken flasks of batch desulfurization of diesel oil using growing cells of G. alkanivorans RIPI90A (Irani et al., 2011). A quadratic polynomial model was predicted to identify the relationship between the response BDS percentage (Y) and the studied variables, X₁: O/W and X₂: initial S-content:

ANOVA analysis revealed that the linear and square effect of the initial S-concentration were found to be more statistically significant (p < 0.1), while the contour plot representing the response, i.e. the S-removal (mg/L) and the combined effect of initial sulfur concentration (mg/L) and oil/water phase ratio (%), showed that the S-removal increased with the increase in the initial sulfur substrate concentration and decrease of oil/water phase ratio.

Response optimization helps to identify the factor settings that optimize a single response or set of responses. It is useful in determining the operating conditions that will result in a desirable response. Thus, upon optimization, the optimum conditions, which are defined as the best combination of factors set for achieving the optimum response were found to be 30% O/W, 28 mg/L initial S-concentration for a predicted response of 21.25 mg/L S-removal, and a desirability score of 1 (Irani et al., 2011).

Irani et al. (2011) also used RSM based on a CCD to study the interactive effect and optimize the independent variables, such as superficial gas velocity (U_g, L/min) and working volume (v, L), which are related to the liquid level above the riser section, on the response gas liquid mass transfer coefficient (k_La, s^-1) for a loop sparger in an airlift bioreactor for an emulsion of 30:70 diesel/water for a batch BDS using growing cells of G. alkanivorans RIPI90A.

The k_La was calculated as the slope of the linear equation:

where the E is the fractional approach to equilibrium and can be estimated using following equation:

where C* is the saturation concentration of dissolved oxygen and C_o is the initial concentration of the dissolved oxygen at time, t_0, when a hydrodynamic steady-state has been reestablished upon the beginning of aeration and C is the dissolved oxygen concentration at any time, t.

The relationship between the two variables, U_g (X₁) and v (X₂), and the response, k_La, was predicted to be:

ANOVA analysis revealed that all linear, square, and interaction terms of X₁ and X₂ (P < 0.05) were found to be significant on the k_La. The contour plot between the response, i.e. k_La and the combined effect of superficial gas velocity, Ug, and working volume, v, showed that the value of k_La increased in the beginning and decreased after increasing from middle values. The optimum condition which is defined as the best combination of factor setting for achieving the optimum response was found to be a superficial gas velocity (2.5 L/min) and working volume (6.6 L) for a predicted response of 0.0206 s^-1 and desirability score of 1 (Irani et al., 2011). Upon applying these conditions in a bioreactor with 30% diesel/water and an initial S-content of 28 mg/L, the recorded S-removal was 14 mg/L within 30 h (Irani et al., 2011).

Based on four levels of full factorial design (4²), a statistical design of experiments was used to investigate two cases of DBT-removal in batch processes using Bacillus sphaericus HN1, involving factors of yeast extract and dimethylsulfoxide (DMSO) or magnesium sulfate for first and second cases, respectively. Four quadratic polynomial model equations were predicted finding out how significant the effects of these variables (factors) and their interactions are in practice (Deriase et al., 2012).

The first case exhibited the effect of yeast extract (X₁, g/L) and DMSO (X₂, mM) concentrations on cell growth (Y₁, DCW, mg/L) and DBT removal were expressed as the remaining DBT (Y₂, mg/L).

The second case exhibited the effect of yeast extract (X₁, g/L) and MgSO₄ (X₃, g/L) concentrations on cell growth (Y₂, DCW, mg/L) and DBT removal expressed as the remaining DBT (Y₄, mg/L).

It was depicted that yeast extract (YE) significantly influenced the growth pattern and DBT-removal of B. sphaericus HN1, in the two studied cases with an increase of YE concentration, an increase of cell growth occurred, and the remaining concentration of DBT decreased, i.e. high removal of DBT occurred. DMSO expressed negative influence on both growth and DBT-removal. MgSO₄ had a positive effect on growth, but negative influence on DBT removal. Moreover, the interaction effect of YE with MgSO₄ was more significant than that of YE with DMSO.

One of the greatest advantages of the response surface methodology (RSM) is to illustrate a correlation between variables in the form of three-dimensional (3D) surface and two-dimensional (2D) contour plots to visualize the effect of the studied factors.

Figures 8.4a and b show the surface and contour plots of the effect of YE (g/L) and DMSO mM on cell growth, Gr (mg/L). They illustrates the significant increase of cell growth with an increment of YE concentration and decrement of DMSO concentration, i.e. higher values of Gr (mg/L) were noticed at a lower concentration of DMSO.

Figures 8.5a and b show the surface and contour plots of the interaction effects of YE g/L and DMSO mM on DBT concentration mg/L. The lowest remaining concentration of DBT, reflecting the highest removal, was noticed at a high level of YE concentration and a low level of DMSO concentration.

It is clear from the surface and contour plots for the interaction effect of YE (g/L) and MgSO₄ (g/L) on Gr (mg/L) of HN1 (Figure 8.6a and b), that increasing concentrations of YE and MgSO₄ enhanced microbial growth.

It was evident from the surface and contour plots for the interaction effect of YE (g/L) and MgSO₄ (g/L) on removed DBT (mg/L) using HN1 (Figure 8.7a and b) that the remaining DBT concentration significantly decreased with increasing both YE and MgSO₄ concentrations.

The elliptical contour plots (Figures 8.6b and 8.7b) indicate that the interactions between the corresponding variables YE and MgSO₄ are more significant than those of YE and DMSO.

LINGO optimization revealed that the optimum values of the test variables were 1.5 g/L YE and 0.86 mM DMSO, which corresponded to a maximum cell growth of 954 mg DCW/L and a minimum DBT concentration of 21.47 mg/L that is ≈ 91.4% removal from the initial concentration of 250 mg/L, while a maximum cell growth of 1,136 mg/L and a minimum DBT concentration of 4.25 mg/L equivalent to ≈ 98.3% removal were achieved at 1.497 g/L YE and 0.25 g/L MgSO₄ (Deriase et al., 2012).

Arabian et al. (2014) reported the application of RSM, based on CCD, to optimize the effect of three variables: biocatalyst cell density (A; cell/mL), oil phase fraction (B), and initial DBT concentration (C, ppmw), with three levels on BDS using Gram +ve Bacillus cereus HN in a biphasic system (aqueous/DBT in dodecane) at 30° C, 180 rpm, and 48 h. A quadratic model equation was found to be the best correlating to studied variables with the response, i.e. BDS percentage:

The optimum conditions were predicted to be a biocatalyst cell density of 3.6 × 10⁷ (cell/mL), oil phase fraction of 0.2, and initial DBT concentration of 1086 ppmw, that provided ≈ 79% biodesulfurization (Arabian et al., 2014).

Bordoloi et al. (2014) reported the application of RSM based on a central composite design (CCD) of four independent variables: incubation time (h) (C₁), initial DBT concentration (% v/v) (C₂), initial inoculum size (% v/v) (C₃), and medium pH (C₄) with three levels to optimize the bacterial growth and BDS efficiency of Achromobacter sp. and to study their interactive effects on the BDS process. The overall second-order polynomial regression equation showing the empirical relationship between the bacterial growth (Y) of the four tested were predicted to be:

The coefficients of the model, including the significance of each coefficient as determined by t-test and p-values, showed that the incubation time, DBT level, and inoculum level had significant effects (p < 0.05) on bacterial growth. The optimum conditions were predicted to be 3.5 mM of DBT and 3.5% (v/v) inoculum size at pH 10.0 of the medium for 132 h post incubation at 37 °C (Bordoloi et al., 2014).

Based on five levels of full factorial design, a statistical design of experiments was used to investigate two cases of DBT-BDS in batch processes, involving yeast extract and glucose or glycerol as factors for Brevibacillus invocatus C19 and Rhodococcus erythropolis IGTS8, respectively. Cubic and quadratic predictive models, significantly describing the interactive relationships between dependent and independent variables, were established for C19 and IGTS8, respectively. The statistical analysis and optimization revealed the optimum values of glucose and yeast extract concentrations for maximum BDS efficiency and microbial growth in a batch DBT-BDS using Brevibacillus invocatus C19 were 0.05 M glucose and 0.3 g/L YE, which recorded 95% BDS of 1000 ppm DBT with the production of 65.20 ppm 2-HBP and the cell biomass was nearly doubled, while for R. erythropolis IGTS8, the optimum values for glycerol and YE were 0.07 M and 0.1 g/L, respectively, which recorded a production of 47.82 ppm 2-HBP with a percentage BDS of 76.81% where the growth was nearly doubled (Abo-State et al., 2014).

Based on the five levels of full factorial design, RSM was used for modeling, optimization, and studying the interactive effects of two variables: nitrogen source, YE and carbon co-substrate, and glycerol in a batch process for DBT-BDS using a new Gram-positive bacterial isolate R. erythropolis HN2 (accession no. KF018282) (El-Gendy et al., 2014). Four quadratic polynomial model equations were predicted to correlate the studied variables A: concentration of YE (g/L) and B: concentration of glycerol (M) and four responses, Y₁, Y₂, Y₃, Y_4, which represent cell growth ln(cell/mL), DBT-BDS percentage, the produced 2-HBP mg/L, and the end product 2,2′-DMBP mg/L, respectively.

The statistical analysis of the data obtained revealed that all the responses were very sensitive to the changes in glycerol concentration. However, they were less sensitive to changes in YE concentration. The YE expressed no significant effect on cell growth, but expressed a relatively significant effect on DBT-BDS and production of 2-HBP and 2,2′-DMBP, but the increase in glycerol concentration expressed a highly significant effect on cell growth, DBT-BDS, and production of 2-HBP and 2,2′-DMBP, where it was obvious from the RSM 3-D plots (Figure 8.8) that within the studied YE concentrations, with the increase of glycerol concentration, cell growth, BDS activity, the production of 2-HBP and 2,2′-DMBP increased, reaching their maximum values at 0.1 M glycerol.

The optimum operating conditions for DBT-BDT using R. erythropolis HN2 were found to be 0.35 g/L yeast extract and 0.09 M glycerol in a batch shaken flasks BDS of 1000 ppm DBT, pH7, 30 °C, and 150 rpm, which recorded, 23, 97%, 65 mg/L, and 29 mg/L, cell growth (ln[cells/mL]), DBT-BDS percentage, and production of 2-HBP and 2,2-DMBP mg/L, respectively (El-Gendy et al., 2014).

Quadratic and 2F1 models were established on the basis of the results obtained from the CCD of experiments to represent the relationship between the responses, i.e. surface tension and emulsification index of the biosurfactants and the multiple independent variables, namely dilution rate, recycle ratio, and inlet sulfur concentration in a continuous 2.5 dm³ B.Braun chemostat with a working volume of 1.5 dm³ (Bandyopadhyay and Chowdhury, 2014):

where Y is surface tension (dynes/cm), E is the emulsification index (%), A is the dilution rate (D) (h^-1), B is the recycle ratio (R), and C is the inlet sulfur concentration (S₀ mg/L). The quadratic effects of A, B, and C are found to be significant (p <0.0001). Process optimization has been done using the Design Expert software and it revealed that the optimum values of surface tension and the emulsification index were 28 dynes/cm and 60.2 at S₀ of 540 ppm, D of 0.01 h^-1, and R value of 0.4 with a desirability of 0.72.

Poto et al. (2017) applied CCD for the optimization of BDS-culture medium for the enhancement of heavy gas oil (HGO) BDS using R. erythropolis ATCC 4277 in a biphasic system at 20% HGO and 80% aqueous phase. In a CCD of three variables, different concentrations of YE, glucose, and process time when yeast extracted concentration, was fixed at 4.0 g/L to the highest BDS percentage occurred with a minimum glucose concentration (1.0 g/L) within 72 h and specific desulfurization rate of 73 mg/kg HGO/h was recorded. However, there was an interesting result in the test without glucose at a shorter processing time of 12 h obtaining a specific desulfurization rate of 418 mg sulfur/kg HGO/h and BDS percentage of 72.7%. From that preliminary study, Porto et al. (2017) concluded that sometimes the BDS percentages are similar, but the desulfurization rate and the desulfurization kinetics are different. Under some conditions desulfurization occurred quickly, while in other cases it gradually increased with time. The effects of estimated analysis for glucose and yeast extract variables were also carried out for a second-order model at a 95% confidence interval and a significant level of α = 0.05 (Porto et al., 2017). In the tests with a fixed glucose concentration, the linear term of the yeast extract concentration and the interaction between glucose and yeast extract concentrations had a significant effect on BDS capacity. The desirability profile indicated that the responses were maximized by using just 10 g/L of yeast extract and 12 h of BDS was enough. Moreover, for the tests with fixed YE concentration, only the linear term of time had a significant effect on sulfur removal. Thus, it seemed that glucose concentration can be minimized in the medium without affecting process efficiency. The desirability profile confirmed that the best process conditions were those that minimized glucose concentration and the process time. In another CCD of different concentrations of C-sources (glucose, malt extract) and an N-source (yeast extract) to achieve maximum BDS of HGO, the highest growth of 4.35 g/L occurred at optimum concentrations of 2 g/L glucose, 6.5 g/L YE, and 9.62 g/L malt extract, that were accompanied with a BDS percentage of 51.4% and specific desulfurization rate of 295 mg/kg HGO/h, while the maximum BDS percentage of 75% with the highest specific desulfurization rate of 454 mg/kg HGO/h occurred within 12 h at optimum concentrations of 2 g/L, 12.39 g/L, and 5 g/L of glucose, YE, and malt extract, respectively (Porto et al., 2017). The observed lower biomass concentration was attributed to the fact that CCD was designed to achieve higher sulfur removal and not higher cellular concentrations. Other studies also noticed that the best biodesulfurization capability was obtained under different conditions to those for the best biomass growth (Del Olmo et al., 2005ab). Porto et al. (2017) showed that the optimum nutritional composition of 1.55 g/L glucose, 5.15 g/L malt extract, and 12.39 g/L yeast extract revealed a specific desulfurization rate of 423 mg S/kg HGO/h and a constant BDS percentage of 70% from 8 to 12 h and a high BDS efficiency in a shorter time.

Fractional factorial design (FFD) of a 2^6–1 was realized using CaCO₃ (g/L, D), glucose (g/L, B), malt extract (g/L, C), yeast extract (g/L, A), agitation (rpm, F), and temperature (°C, E) as independent variables to permit the identification of the culture conditions which present a significant influence on the cell growth of R. erythropolis ATCC 4277 (Todescato et al., 2017). A total of 36 runs with different combinations of six factors were carried out. A multiple regression analysis was applied to experimental results in order to obtain an equation capable of predicting biomass production BC_Re:

Thus, a higher concentration of yeast extract expressed a clear influence in the quantity of biomass produced. Moreover, the interaction effect of yeast extract and agitation speed presented a major positive effect in biomass concentration. However, the evolution in the biomass concentration was dimensioned by an increase in the calcium carbonate (CaCO₃), concentration, and temperature.

A central composite design (CCD, 2⁴) was accomplished in order to optimize the variables by a response surface methodology (RSM) for R. erythropolis ATCC 4277. The factor levels were decided based on the range obtained with the previous fractional factorial design (FFD) (Todescato et al., 2017). Thus, the factors that were not statistically significant were maintained at the lowest level, settling the malt extract and glucose concentrations in 5.0 and 2.0 g/L, respectively. The remaining variables were displaced considering the effects noted in the FFD: yeast extract concentration (g/L, A) and agitation speed (rpm, D) with positive effects and concentration of CaCO₃ (g/L, B) and the temperature (°C, C) with negative effects. Statistical analysis permitted the development of a model that describes the R. erythropolis ATCC 4277 cell growth BC_Re:

The higher coefficients of yeast extract and CaCO₃ concentrations, temperature, and agitation indicate that cell growth of R. erythropolis ATCC 4277 was highly affected by these parameters.

The optimal conditions, yielding 6 g/L cell density, were found to be 2 g/L glucose, 5 g/L malt extract, 6.15 g/L yeast extract and 1.16 g/L CaCO₃, temperature of 23.7 °C, and agitation of 180 rpm. Moreover, the optimized conditions resulted in a maximum specific growth rate of 0.116 h^–1, growth yield coefficient of 0.675 g/g, and Monod saturation constant of 20 g/L (Todescato et al., 2017).

Doehlert uniform design (Doehlert, 1997) was applied to study the effect of two factors, X₁ or BaCl₂ concentration and X₂ or exposure time for sulfate precipitation in carob pulp liquor; the response, Y, to be applied in the BDS process using Gordonia alkanivorans strain 1B (Silva et al., 2013). A second order polynomial model equation was predicted to correlate the variables with the response:

The results indicated that a BaCl₂ concentration of 0.125% is not enough to obtain significant sulfate precipitation, independent of the exposure time. However, at higher BaCl₂ concentrations, the longer the exposure time is, the greater the occurrence of sulfate precipitation. Furthermore, the exposure time was found to have five fold less influence on the final sulfate concentration than the amount of BaCl₂ used in the process. The response surface showed that a small variation of BaCl₂ concentration produces a response in the sulfate concentration. The optimum conditions to obtain a carob pulp liquor with minimal sulfate concentration (0–5 mg/L) were found to be a BaCl₂ concentration above 0.4% with an exposure time of 36 h. However, combination of 0.5% of BaCl₂ and a time of exposure of 21 h produced carob pulp liquor which led to a maximum BDS efficiency of 400 µmol/L DBT producing 237 µmol/L 2-HBP.

In a similar study, statistically validated experimental design followed the Doehlert distribution for two factors, BaCl₂ concentration (X₁) and pH (X₂), to study their effects on the sulfate precipitation (response, Y) in the acid hydrolysate of Jerusalem artichoke juice (JAJ) and a second order polynomial model was predicted to describe the process (Silva et al., 2014).

Then, to evaluate the treatment effect on both microbial growth and BDS ability by G. alkanivorans, the different JA juices, treated and untreated, were added to the desulfurization medium (dilution in a 1:6 ratio to adjust the initial concentration to ~25 g/L of total sugars) and tested as carbon sources in a batch BDS with an initial DBT concentration of 400 µmol/L. The surface response methodology according to a Doehlert distribution for the studied two factors revealed that both factors, BaCl₂ concentration and initial pH, have relevant effects on the sulfate removal from hydrolyzed JAJ. When the concentration of BaCl₂ was doubled at pH 5.27 and pH 8.73, the average amount of final sulfate concentration decreased about 6.7 and 5.4 fold, respectively, indicating a less efficient sulfate removal at a high pH 8.73. This also confirmed that for lower concentrations of BaCl₂ (0.25%), increasing pH from 5.27 to 8.73 decreased the sulfate 3.2 fold, while for higher concentrations of BaCl₂ (0.5%), the same pH increase led to a 2.6 fold drop in sulfate. Thus, a more efficient sulfate removal occurs at a higher pH, but with low BaCl₂ concentration, which was also indicated by the negative coefficients of X₁² and X₂² and positive coefficients of the interactive effect X₁X₂ in the predicted polynomial equation. The response surface revealed that the relative effect of BaCl₂ concentration on the final sulfate concentration is greater than that of pH. Small concentrations of BaCl₂ seem to be less effective at an acidic pH. The maximum removal of sulfate occurred around pH7 and a BaCl₂ concentration of 0.5–0.55%. However, the optimum conditions were predicted to be 0.5% (w/v) BaCl₂ and pH 8.73. The most efficient treatments, with very similar values of DBT removal and 2-HBP production, were the treatment with 0.5% BaCl₂ and pH 8.73 achieved at a maximum of 353 µmol/L 2-HBP and the treatments with 0.375 and 0.63% at pH 7 reached 330 µmol/L and 328 µmol/L 2-HBP, respectively. However, upon the application of the predicted optimum conditions, µ_max reached 0.06 h^-1 with a total consumption of the available carbon source (glucose and fructose ~ 25 g/L) by the end of the growth (96 h). Production of 2-HBP was also initiated at 18 h, but attained ~ 400 µmol/L between 73 and 96 h, corresponding to an overall production rate of 4.48 µmol/L/h and to a maximum production rate of 28.2 µmol/L/h with a related q_2HBP of 5.06 µmol/g DCW/h with a total consumption of the DBT. Using the BaCl₂ treated hydrolyzed JAJt, the amount of 2-HBP produced (µmol) per gram of sugar consumed was ≈ 16 µmol/g (Silva et al., 2014).

Lin et al. (2014) reported 100% degradation of DBT by the new isolate Pseudomonas sp. LKY-5, via the application of RSM based on Box-Behnken design (BBD). A total of 29 experiments were conducted on four factors: initial DBT concentration (X₁), temperature (X₂), pH (X₃), and agitation rate (X₄) at three levels with BBD. A second order polynomial equation was found to best describe the interactive effects of the four studied variables on the DBT-removal percentage (Y):

The value of determination coefficient R²=0.9534 indicated a satisfactory agreement between the quadratic model and experimental data. The analysis of variance ANOVA proved that DBT removal was more significantly affected (P< 0.0001) by the initial DBT concentration compared with the other three studied parameters. The optimum operation conditions with 100% DBT-removal were found to be 100 mg/L initial DBT-concentration at a temperature range of 25–35 °C, an agitation rate of 140–180 r/min, and a pH value of 6.5–8.5 within 7 days, while, upon applying, the RSM optimized settings included an agitation rate of 140 r/min, a temperature of 33°C, and a pH value of 8.28 and 56 percent biodegradation of DBT at a high initial concentration of 200 mg/L was achieved after a cultivation period of 7 days (Lin et al., 2014).

DBT concentration, temperature, and pH were optimized statistically for growing and resting cells of Paenibacillus validus (strain PD2) by using RSM (Derikvand et al., 2015a). All the parameters in growing cells had a significant effect on 2-HBP production during the BDS of DBT by P. validus PD2. However, in resting cells in a temperature range of 20–40 °C was not a significant factor. Maximum BDS for growing cells was obtained at 0.41 mM DBT concentration, pH 6.92, and temperature of 31.23 °C, while for resting cells, optimum pH, temperature, and DBT concentration were 6.62, 27.73 °C, and 7.86 mM, respectively (Derikvand et al., 2015a).

Box-Behnken RSM was applied to the study of interactive effects of initial DBT concentration, temperature, and pH on the BDS activity of Rhodococcus erythropolis PD1 and used to determine the optimum value of these factors for both growing and resting cell conditions in aqueous and biphasic (2:1 aqueous/model oil; DBT in n-tetradecane v/v) systems, respectively (Derikvand et al., 2015b), where a 3-factor and 3-level Box-Behnken design (BBD) was used to determine the optimum level of the studied factors and to study their interactive relationship to the BDS efficiency. The used resting cells were the bacterial cells grown and harvested at the late exponential phase. The BDS efficiency was evaluated by the concentration of the produced 2-HBP.

A quadratic polynomial equation was predicted to best fit and describe the relationship between the BDS efficiency as expressed by the production of 2-HBP and the studied three factors in a one phase aqueous system:

where Y is the response value (i.e. the produced 2-HBP mM), X₁ is the initial DBT concentration (mM), X₂ is temperature (°C), and X₃ is initial pH. Positive and negative signs before each term indicate synergistic and antagonistic effects, respectively (El-Gendy et al., 2014). The ANOVA results for 2-HBP production by growing cells have shown that the initial DBT concentration, initial pH and incubation temperature, and the interactive effects of the initial DBT concentration with incubation temperature and that of incubation temperature with the initial pH have significant effects on the BDS efficiency in an aqueous system (p<0.05). The optimum conditions for maximum efficiency in a one-phase aqueous system, using R. erythropolis PD1, were found to have an initial DBT concentration of 0.38 mM and initial pH of 6.88 at 27.57 °C, which produced 0.21 mM 2-HBP within 48 h (Derikvand et al., 2015b), while the quartic model equation describing the effect of three studied variables on the BDS efficiency in a bi-phasic system using resting cells of R. erythropolis PD1 was predicted to be:

The ANOVA test proved the significant effects of initial DBT concentration, incubation temperature, and their interactive effect (p< 0.05). The optimum predicted conditions using the resting cells of PD1 in biphasic system were found to be 7.73 mM, 26.13 °C, and 6.29 initial DBT concertation, incubation temperature, and initial pH, respectively, which performed a maximum BDS activity of 0.46 µM 2-HBP/g DCW/min, within 20 h (Derikvand et al., 2015b). The optimum higher initial DBT concentration (7.73 mM) in the bi-phasic system, relative to the lower value in an aqueous phase system (0.38 mM), was explained by the low solubility of DBT in an aqueous phase and its high solubility in n-tetradecane (organic phase) which reduces its toxic effect on bacteria. Moreover, the produced 2-HBP accumulation in the cells would be lower because of its high solubility in the solvent phase (Kawaguchi et al., 2012).

A 3-factor and 3-level Box-Behnken design (BBD) based on RSM was applied to determine the optimum level of variables of DBT concentration (X₁: 2, 6, and 10 mM), incubation temperature (X₂: 20, 30, and 40 °C), and pH (X₃: 5, 7, and 9) and to study their relationship in a biphasic (1:2 O/W) batch BDS process of model oil (DBT in n-tetradecane) using magnetic nanoparticle (MNPs) immobilized cells of R. erythropolis R1 (Etemadifar et al., 2014). A model of coded units, after removing non-significant parameters, was depicted to correlate the response, i.e. the BDS-efficiency, represented as the amount of produced 2-HBP:

where the equation indicates a quadratic linear relationship between variables and 2-HBP (Y).

According to the depicted model, DBT concentration, temperature, and interaction between them were significant, but pH and its interaction with other factors was not statistically significant. The interaction of each of the two independent factors was shown by a response surface with a contour plot, while another factor is fixed at the level of zero. The fitted surface and contour plots were between DBT concentration and temperature, DBT concentration and pH, and temperature and pH. The highest 2-HBP production was obtained when all factors were at the middle level: 6.76 mM, 29.63 °C and pH6.84.

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