Multi-component cocktail designing to develop a cost effective second generation bioconversion technology

doi:10.21203/rs.3.rs-3776796/v1

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Multi-component cocktail designing to develop a cost effective second generation bioconversion technology

https://doi.org/10.21203/rs.3.rs-3776796/v1

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In this study, the recombinant fungal auxiliary and accessory enzymes derived from thermophilic/thermotolerant fungi and heterologously expressed in methylotrophic yeast Pichia pastoris X33 were evaluated to modulate the hydrolytic efficiency of most advanced cellulase preparation (i.e. Cellic CTec3). The saccharification of diluted acid pre-treated unwashed rice straw slurry obtained from PRAJ and IOCL Industries was carried out using combinations of recombinant proteins & Cellic CTec3, in which the recombinant proteins of Scytalidium thermophilum CM-4T, PMO9D_SCYTH (LPMO), XYL43B_SCYTH (β-xylosidase) and FAED_SCYTH (feruloyl esterase) were found to enhance the saccharification at maximum level when they were supplemented to the Cellic CTec3 (~2.3 mg protein/g substrate) preparation. Employing simplex-lattice mixture design an optimized cocktail of PMO9D_SCYTH, XYL43B_SCYTH & FAED_SCYTH and Cellic CTec3 was designed for saccharification. It was found that the mixture containing [PMO9D_SCYTH: 33.4%; XYL43B_SCYTH: 33.4%; & FAED_SCYTH: 33.4%] optimally hydrolyzed unwashed acid steam pretreated rice straw slurry obtained from PRAJ Industry, showed 70.39% saccharification efficiency (glucan+xylan), while mixture containing [PMO9D_SCYTH: 16.70%; XYL43B_SCYTH: 16.70%; & FAED_SCYTH: 66.70%] was found optimum for the hydrolysis of unwashed rice straw slurry obtained from IOCL Industry showing 84.46% saccharification efficiency (glucan+xylan).

LPMO

β-xylosidase

Feruloyl esterase

Cocktail mixture designing

Diluted acid pre-treated unwashed rice straw slurry

Cellic CTec3

Blending of auxiliary/accessory proteins with Cellic CTec3 for enhanced hydrolysis
Multi component cocktail designing using simplex-lattice mixture designing (SLMD)
Mixture formulation optimization of AA9, GH43 and CE1 with Cellic CTec3
Potential of formulated blends to hydrolyse industry relevant pre-treated substrate
Improved saccharification of unwashed dilute acid pre-treated rice straw slurry

The production of second generation bioethanol is expected to increase in near future as new ventures of establishing agro-residues based bio-refineries in India, China, Romania and other European countries is abreast, notwithstanding the fact that few of commercial plants like POET-DSM, DuPont 2G ethanol plants have stopped the production in USA that was due to combination of technical and EPA (Environmental Protection Agency) support withdrawal (Nuelle, 2019). However, European countries, China and India are still positive to establish bioethanol plants based on agro-residues such as corn residues, wheat straw, barley straw, rice straw etc. (Kamani et al., 2019; Sharma et al., 2020; Malode et al., 2021). The bioconversion of agro-residues nonetheless is challenging because of recalcitrant nature of lignocellulosics that needs to be pre-treated so as to make it amenable to the lignocellulolytic enzymes at high substrate concentrations (20–25%) in order to achieve sugar syrup (10–12%) rich in monomeric sugars for subsequent fermentation to ethanol. However, the operating plants also face technical issues while operating at high substrate concentrations those results in clogging of pipes, inefficient mixing of enzyme and substrate given the heterogeneity of the substrate that dynamically changes in its complexity during severe pre-treatment conditions (Sankaran et al., 2020, Duque et al., 2021, Martín et al., 2023). In addition, the catalytic efficacy of lignocellulolytic enzymes needs to be addressed under the process conditions as the hydrolysis in the bio-refinery setup is carried out at 17–22% (Inamdar et al., 2011, Smits et al., 2019) and under high substrate levels the enzyme substrate interactions as well as end product inhibition severely affect the performance of enzyme unlike 2–5% substrate concentrations generally employed for carrying out hydrolysis in many of the publications (Hu et al., 2014; Mokomele et al., 2018; Tang et al., 2019). Moreover, the bio-refineries prefer to carry out hydrolysis of the pre-treated slurries without washing, which removes inhibitors as well as pentose sugars that are mainly present in the slurry, therefore the robustness of enzymes that are resistant to negative effects of inhibitors (furfural, acids and lignin degradation components) are also desired (Duque et al., 2021). The optimized commercially developed cellulase preparations have taken the above cited factors into consideration while developing state of art cellulases and have brought down the amount of enzyme required appreciably to around 5 mg enzyme protein/g substrate to achieve a hydrolysis efficiency between 60–70% (Agrawal et al., 2015; Nwamba et al., 2021). Clariant Inc. recently reported that it carried hydrolysis of the acid pre-treated corn stover slurry with an in-house enzyme at as low as 5 mg protein/g at a substrate loading rate of 20% obtaining glucose syrup of ~ 50 g L^− 1 (Rarbach et al., 2014). However, there is always a scope for improving the efficiency of these enzyme preparations as the cost of lignocellulolytic enzymes required during hydrolysis is considered as one of the most critical factor, besides pre-treatment, that significantly governs economics of the bioconversion platform. Therefore, efforts to discover novel and robust lignocellulolytic enzyme cocktails that show high rates of catalysis at low required enzyme amounts in terms of amount of protein or FPU/g substrate is an area of continued research (Usmani et al., 2021). In recent past enzyme manufacturer like Novozymes™ and DuPont have developed highly advanced enzymes like Cellic CTec3 and Accellerase® TRIO™, respectively; in addition to DSM who has developed in-house strains for on-site production of lignocellulolytic enzymes. Approaches which includes screening of diverse and novel genes coding for robust enzymes from the vast genome data generated in the recent times (Chai et al., 2020) and employing these enzyme components to design customized lignocellulolytic enzyme cocktails for saccharification of pre-treated substrates as one way to reduce the cost, as each substrate and the pre-treatment process brings about very specific and subtle changes in the structure of pre-treated substrate (Adsul et al., 2020). The newly designed cocktails focus on their catalytic efficacy and selection of component enzymes which can act efficiently lower the enzyme doses in terms of protein/FPU per g of substrate are being targeted (Nwamba et al., 2021).

Recent reports on the incorporation of LPMO proteins which are known to attack the crystalline cellulose fibre causing oxidation at either C₁/C₄ during each catalytic cycle, in the cellulases preparations suggest that these auxiliary activity proteins are capable of boosting the hydrolytic potential of core cellulases and can reduce the total protein loading rate, as low amount of LPMOs addition can result in the enhanced release of monomeric sugars (Singhania et al., 2021). However, the challenge is still to screen the best potential LPMO candidate for to be a part of cocktail as the recent data suggest that the number of LPMO genes annotated in thermophilic fungal strains may be as high as 31 (Myceliophthora sepedonium ATCC 9787, https://gb.fungalgenomics.ca/portal/). In addition, the reports on synergistic interaction of hemicellulases (e.g. endo-xylanases, xylosidases and exo-xylanases) and accessory enzymes (e.g. esterases and arabinofuranosidases) with core cellulases also suggests their importance to reduce the enzyme loading rate and obtain higher hydrolytic performance of the enzymatic cocktails (Boyce and Walsh, 2018; Mkabayi et al., 2020). In order to know the exact amount of the auxiliary/accessory enzyme required for custom designing efficient mixture of enzymes for a particular pre-treated substrate (Du et al., 2020) different studies have been conducted using statistical models simplex lattice, Box Behnken, composite designs to arrive at optimal levels (Badhan et al., 2014; Santa Rosa et al., 2021). These tailored enzymatic cocktails are able to hydrolyse lignocellulosic biomass (LCB) at lower protein loading rate/g of glucan, and efficiently convert LCB into monomeric sugars in shorter hydrolytic period (Du et al., 2020).

In this study, different auxiliary and accessory activity recombinant proteins derived from indigenous thermophilic/thermotolerant fungal strains Malbranchea cinnamomea CM-10T (LPMOs: PMO9A_MALCI and PMO9D_MALCI; xylanases: XYN10A_MALCI and XYN11A_MALCI), Scytalidium thermophilum CM-4T (LPMO: PMO9D_SCYTH; feruloyl esterase: FAED_SCYTH; β-xylosidase: XYL43B_SCYTH) and Aspergillus terreus 9DR (LPMOs: PMO_08942 and PMO_07920) and heterologously expressed in the methylotrophic yeast Pichia pastoris X33 were evaluated to improve the hydrolytic potential of present state of a commercial cellulase Cellic CTec3 during the hydrolysis of bio-refinery relevant acid pre-treated unwashed rice straw slurry. After determining the best dosage of recombinant protein to be added with Cellic CTec3, the simple-lattice mixture designing study was conducted to design an efficient enzymatic cocktail containing Cellic CTec3 and recombinant proteins mixture (PMO9D_SCYTH, XYL43B_SCYTH and FAED_SCYTH).

2.1 Auxiliary and accessory activity enzymes production

Five auxiliary activity enzymes (AA9 proteins), derived from Malbranchea cinnamomea CM-10T (PMO9A_MALCI and PMO9D_MALCI), Aspergillus terreus 9DR (PMO_08942 and PMO_07920) and Scytalidium thermophilum CM-4T (PMO9D_SCYTH), and four accessory activity enzymes derived from M. cinnamomea CM-10T (xylanases: XYN11A_MALCI and XYN10A_MALCI) and S. thermophilum CM-4T (feruloyl esterase, FAED_SCYTH and β-xylosidase, XYL43B_SCYTH) were cloned using pPICZαA vector and heterologously expressed in the methylotrophic yeast Pichia pastoris X33 by sustained induction of AOX1 promoter in presence of 1% methanol (Basotra et al., 2018; Basotra et al., 2019; Agrawal et al., 2020a, Agrawal et al., 2020b, Agrawal et al., 2021). The culture supernatants (100 ml) obtained were subjected to overnight precipitation with 80% (v/v) ice cold acetone at 4° C (Basotra et al., 2018) followed by centrifugation (10,000×g; 20 min). The resultant precipitates were dissolved in 10 ml acetate buffer (50 mM; pH 5.0 ± 0.2). The activity of the crude as well as concentrated samples of the recombinant GH10 & GH11, AA9s, CE1 and GH43 clones were assayed using birchwood xylan (0.5% w/v; Sigma-Aldrich, USA), carboxymethyl cellulose (CMC; 1% w/v; Sigma-Aldrich, USA), p-nitrophenol-ferulate (pNPF; 3 mM; Sigma-Aldrich, USA) and p-nitrophenol-xylopyranoside (pNPX; 3 mM; Sigma-Aldrich, USA) as substrates, respectively. The protein content of the crude as well as concentrated samples was determined using DC protein assay kit (BioRad, USA). The characteristics of these recombinant enzymes are summarized in Table 1.

Table 1

Characteristics of auxiliary and accessory enzymes used in this study
	Recombinant protein	Gene source	CAZy family	M_w	T_opt	pH_opt	Reference
1.	XYN11A_MALCI	Malbranchea cinnamomea CM-10T	GH11	28 kDa	70° C	7.0	Basotra et al., 2018
2.	XYN10A_MALCI		GH10	-	-	-	Basotra et al., 2018
3.	PMO9A_MALCI		AA9	27 kDa	60° C	9.0	Basotra et al., 2019
4.	PMO9D_MALCI		AA9	20 kDa	50° C	9.0	Agrawal et al., 2020b
5.	PMO_08942	Aspergillus terreus 9DR	AA9	29 kDa	50° C	5.0	Agrawal et al., 2020a
6.	PMO_07920	Aspergillus terreus 9DR	AA9	40 kDa	50° C	7.0	Agrawal et al., 2020a
7.	PMO9D_SCYTH	Scytalidium thermophilum CM-4T	AA9	27 kDa	60° C	7.0	Agrawal et al., 2020b
8.	FAED_SCYTH		CE1	31 kDa	60° C	6.0	Agrawal et al., 2021
9.	XYL43B_SCYTH		GH43	40 kDa	50° C	7.0	Agrawal et al., 2021

2.2 Saccharification reaction setup, pre-treated substrate and the benchmark enzyme

The saccharification reactions were carried out in screw-capped glass vials (15 ml), containing 1 ml reaction mixture comprising pre-treated substrate slurry (0.17 g substrate on dry weight basis, i.e., 17% substrate loading rate) and 100 µl of Cellic CTec3 (~ 2.3 mg protein/g substrate or ~ 2.3 FPU/g substrate) as lignocellulolytic enzyme, under shaking condition (200 rpm) at 50° C, for 72 h. The acid pre-treated unwashed rice straw slurry (pH 2.3 ± 0.2) was provided by Praj Industries (Pune, Maharashtra, India) and Indian Oil Corporation Ltd. (IOCL, New Delhi, India), and the pH of pre-treated rice straw slurry was adjusted to (5.0 ± 0.2) using aqueous ammonia solution (25% v/v) (Sharma et al., 2021). The benchmark lignocellulolytic enzyme used in this study was a commercial cellulase preparation Cellic CTec3 (Novozyme™) procured from our collaborators. Cellic CTec3 used in this study was assayed to contain 315.68 ± 0.54 U ml^− 1 FPU and 314.22 ± 0.68 mg ml^− 1 protein (Liang, 2015). After hydrolysis, the amount of released glucose and total reducing sugars during hydrolysis were analysed using GOD-POD kit (ARKRAY Healthcare Pvt. Ltd.) and DNS method, respectively (Basotra et al., 2018). The unwashed acid pre-treated rice straw slurry substrate PRAJ and IOCL, after adjustment of pH were found to contain 57.50 and 39.29 g L^− 1 of reducing sugars of which 10.71 and 7.28 g L^− 1 were in the form of glucose, respectively.

2.3 Effect of increasing dosages of recombinant proteins on hydrolysis

The auxiliary and accessory activity proteins were evaluated for their synergistic effect by preparing blends with Cellic CTec3. The blend cocktails were prepared by replacing one part of benchmark enzyme (Cellic CTec3) with recombinant proteins (9:1 ratios). The selected recombinant proteins (XYN11A_MALCI, PMO9A_MALCI, PMO9D_SCYTH, FAED_SCYTH and XYL43B_SCYTH) that were found to enhance the saccharification appreciably were supplemented at different levels (10, 15, 20 and 25 µl) to Cellic CTec3 (100 µl), and these formulated cocktails were evaluated to hydrolyse pre-treated rice straw slurries. The reactions carried out using 100 µl of Cellic CTec3 (~ 2.3 mg protein/g substrate) were taken as control.

2.4 Statistical design

Simplex-lattice mixture designing (SLMD) study was carried out using three selected recombinant proteins i.e., PMO9D_SCYTH (A), XYL43B_SCYTH (B) and FAED_SCYTH (C) at low (0 µl) and high (20 µl) levels of addition. The mixture components (A, B and C), taken as independent variable (0 and + 1), were evaluated on the basis of their potential to release glucose and total reducing sugars from the acid pre-treated unwashed rice straw slurries (obtained from PRAJ Industries and IOCL) when added to Cellic CTec3 (benchmark enzyme). The proportions of the components were taken as the sum (A + B + C) of 20 µl. These levels and experimental design in terms of coded and actual values of the three independent components: PMO9D_SCYTH, XYL43B_SCYTH and FAED_SCYTH, was studied using 13 mixture combinations with replicates of centre and vertex points that are presented in Table 2. The statistical analysis was conducted using Stat-Ease software (Design-Expert v13.0.4.0, Stat-Ease Inc., Minneapolis) that was also used for the computation of results and response surface graphs preparation. The dependant variables (responses), glucose and total reducing sugars (TRS) released (mg/ml) during the hydrolysis of lignocellulosic biomass (PRAJ and IOCL), were analysed and the fitted model (special quartic) was subjected to the analysis of variance (ANOVA) to determine the significance (p < 0.001), coefficient of determination (R²) and lack of fit of the proposed model.

Table 2

Simplex lattice mixture design (SLMD) for the formulation of auxiliary/accessory activity enzyme cocktail
Mixtures		Independent components
Mixtures		A	B	C	A: PMO9D_SCYTH (µl)	B: XYL43B_SCYTH (µl)	C: FAED_SCYTH (µl)
Std	Run	Coded values			Actual values
1	7	1.000	0.000	0.000	20	0	0
2	3	0.000	1.000	0.000	0	20	0
3	10	0.000	0.000	1.000	0	0	20
4	8	0.667	0.334	0.000	13.33	6.67	0
5	17	0.667	0.000	0.334	13.33	0	6.67
6	4	0.334	0.667	0.000	6.67	13.33	0
7	12	0.334	0.334	0.333	6.67	6.67	6.66
8	11	0.334	0.000	0.667	6.67	0	13.33
9	1	0.000	0.667	0.334	0	13.33	6.67
10	2	0.000	0.334	0.667	0	6.67	13.33
11	5	0.667	0.167	0.167	13.33	3.34	3.33
12	15	0.167	0.667	0.167	3.34	13.33	3.33
13	6	0.167	0.167	0.667	3.34	3.33	13.33
14	16	1.000	0.000	0.000	20	0	0
15	9	0.000	1.000	0.000	0	20	0
16	14	0.000	0.000	1.000	0	0	20
17	13	0.334	0.334	0.333	6.67	6.67	6.66

The following polynomial equation of function x_i was fitted for each factor assessed at each experimental point. The polynomial model equation for special quartic model was:

ϒ = β₁ A + β₂ B + β₃ C + β₁₂ AB + β₁₃ AC + β₂₃ BC + β₁₁₂₃ A²BC + β₁₂₂₃ AB²C + β₁₂₃₃ ABC²

Where ϒ is the response variable; β₁, β₂, β₃, β₁₂, β₁₃, β₂₃, β₁₁₂₃, β₁₂₂₃ and β₁₂₃₃ are constant coefficients for linear blending portion (β₁, β₂ and β₃) and non-linear blending between component pairs (β₁₂, β₁₃, β₂₃, β₁₁₂₃, β₁₂₂₃ and β₁₂₃₃) term produced for the prediction models of processing components. The non-linear components are responsible for the arising of curvature due to either synergistic or antagonistic blending between components pairs.

The formulated auxiliary/accessory activity enzyme mixtures (20 µl of each) were added to 100 µl of Cellic CTec3 (~ 2.3 mg protein/g substrate) and the resultant cocktail was used for the hydrolysis of acid pre-treated unwashed rice straw slurries (PRAJ and IOCL). In addition to the blends containing above mentioned mixtures with Cellic CTec3 (~ 2.3 mg protein/g substrate), the hydrolysis reactions were also carried out using the 120 µl of Cellic CTec3 (~ 2.76 mg protein/g substrate) to evaluate the performance of formulated enzymes blends over the commercial cellulase preparation.

3.1 Evaluating the potential of Auxiliary and accessory activity enzymes for enhancing the efficacy of Cellic CTec3

Different auxiliary and accessory activity enzymes (Table 3) were produced using BMMY (buffered methanol complex medium) under sustained induction of AOX1 promoter using 1% (v/v) methanol that was fed at 24 h interval up to 120 h. The cells were separated thereafter and resultant crude supernatants were concentrated. The enzymatic activity of the crude and concentrated samples was determined against their model substrate and the protein content was measured using Folin-Ciocalteu reagent (Table 3). The hydrolytic studies carried out with Cellic CTec3 by replacing one part of benchmark enzyme (Cellic CTec3) with recombinant protein (9:1 ratios) showed enhanced hydrolytic potential of recombinant proteins as compared to the control reactions carried out using Cellic CTec3 alone (10 parts; ~2.3 mg protein/g substrate). The recombinant proteins feruloyl esterase (FAED_SCYTH), LPMO (PMO9D_SCYTH), xylanase (XYL11A_MALCI), β-xylosidase (XYL43B_SCYTH) and LPMO (PMO9A_MALCI) showed significant improvement in the release of glucose by 11.78, 7.60, 10.39, 7.20 and 7.60%, respectively, when acid pre-treated rice straw slurry (provided by PRAJ Industries) was used as substrate (Fig. 1a) with corresponding enhanced release of total reducing sugars by 14.72, 14.32, 18.89, 7.76 and 11.74%, respectively (Fig. 1b). Similarly, the recombinant proteins FAED_SCYTH, PMO9D_SCYTH, XYL11A_MALCI, XYL43B_SCYTH and PMO9A_MALCI resulted in enhanced glucan conversion by 17.64, 15.48, 12.85, 12.07 and 10.68% (respectively) using pre-treated rice straw slurry provided by IOCL (Fig. 2a & b).

Table 3

Enzymatic activity and protein content in the samples
Recombinant protein	Model substrate	Enzyme activity (U ml^− 1)		Protein (mg ml^− 1)
Recombinant protein	Model substrate	Crude sample	Concentrated sample	Crude sample	Concentrated sample
XYN11A_MALCI	Birchwood xylan	32.94 ± 0.03	288.10 ± 0.22	2.89 ± 0.02	15.94 ± 0.06
XYN10A_MALCI	Birchwood xylan	3.78 ± 0.09	32.17 ± 0.13	2.66 ± 0.06	15.21 ± 0.07
PMO9A_MALCI	carboxymethyl cellulose	0.66 ± 0.02	4.20 ± 0.01	2.82 ± 0.04	17.57 ± 0.09
PMO9D_MALCI		0.65 ± 0.01	4.11 ± 0.02	2.69 ± 0.04	17.39 ± 0.03
PMO_08942		0.75 ± 0.03	5.90 ± 0.01	2.67 ± 0.06	15.71 ± 0.11
PMO_07920		0.59 ± 0.03	4.10 ± 0.01	2.74 ± 0.07	16.60 ± 0.14
PMO9D_SCYTH		0.73 ± 0.002	5.23 ± 0.02	2.78 ± 0.02	16.14 ± 0.11
FAED_SCYTH	p-nitrophenol-ferulate	0.019 ± 0.005	0.16 ± 0.007	2.07 ± 0.02	8.52 ± 0.07
XYL43B_SCYTH	p-nitrophenol-xylopyranoside	1.01 ± 0.01	7.84 ± 0.03	2.63 ± 0.04	10.34 ± 0.05

3.2 Effect of spiking Cellic CTec3 with increasing dosage of recombinant proteins on hydrolysis

The effect of spiking Cellic CTec3 with increasing dosages of recombinant proteins (10–25 µl) were investigated in order to determine the optimal amount of recombinant protein to be added during the hydrolysis process of unwashed acid pre-treated rice straw slurry at substrate loading rate of 17% (~ 8.67% glucan loading). The spiking of Cellic CTec3 (100 µl, ~ 2.3 mg protein/g substrate) with selected recombinant proteins XYL11A_MALCI, PMO9A_MALCI, PMO9D_SCYTH, FAED_SCYTH and XYL43B_SCYTH (10–25 µl) resulted in the enhanced glucan conversion and the total reducing sugars release from the unwashed pre-treated rice straw slurry obtained from PRAJ Industries and IOCL (Figs. 3 & 4) when compared to the hydrolysis carried out using Cellic CTec3 as control. The blending of Cellic CTec3 with 20 µl of recombinant xylanase (XYL11A_MALCI) led to an enhanced glucan conversion (by 10.92 and 13.83%) from pre-treated rice straw slurry from PRAJ and IOCL substrate, respectively; and blending of 25 µl of XYL11A_MALCI resulted in maximum enhanced release of total reducing sugars (by 18.14 and 11.20%) from PRAJ and IOCL substrates, respectively. As compared to the xylanase XYL11A_MALCI derived from M. cinnamomea CM-10T (Basotra et al., 2018), the recombinant LPMO protein PMO9A_MALCI (Basotra et al., 2019) enhanced the efficacy of Cellic CTec3 more efficiently and the spiking of PMO9A_MALCI (20 µl) resulted in the maximum enhanced glucan conversion (by 15.09 and 13.26%) from PRAJ and IOCL substrate (respectively) with corresponding increase in total reducing sugars release of 22.34 and 11.34% from PRAJ and IOCL substrate, respectively.

The recombinant LPMO, β-xylosidase and feruloyl esterase proteins derived from thermophilic fungus S. thermophilum CM-4T were found to enhance the hydrolytic capability of Cellic CTec3 more efficiently when compared proteins derived from M. cinnamomea CM-10T. The addition of 20 µl of recombinant LPMO protein (PMO9D_SCYTH) resulted in enhanced glucan conversion (32.96%) followed by feruloyl esterase FAED_SCYTH (27.99%) during hydrolysis of rice straw slurry (PRAJ). The blending of 25 µl of β-xylosidase XYL43B_SCYTH resulted in maximal enhanced glucan conversion (24.82%). In terms of total reducing sugars, the spiking of PMO9D_SCYTH (20 µl) resulted in 27.30% improved hydrolysis of rice straw slurry (PRAJ Industries). Similarly, blending of Cellic CTec3 with 20 µl of β-xylosidase XYL43B_SCYTH resulted in 27.87% enhanced release of total reducing sugars, followed by FAED_SCYTH (25.01%) from PRAJ substrate.

In the case of rice straw slurry obtained from IOCL, the blending of Cellic CTec3 with 20 µl of feruloyl esterase (FAED_SCYTH), β-xylosidase (XYL43B_SCYTH), LPMO (PMO9D_SCYTH) resulted in maximal enhanced glucan conversion by 23.27, 22.28 and 19.18%, respectively. However, maximum improvement in total reducing sugar release by 22.40, 19.08 and 13.14% were obtained when 25, 15 and 20 µl of XYL43B_SCYTH, FAED_SCYTH and PMO9D_SCYTH were added to Cellic CTec3, respectively.

3.3 Formulation of multi-component cocktails

The multi-component cocktails comprising Cellic CTec3 and recombinant proteins LPMO (PMO9D_SCYTH), β-xylosidase (XYL43B_SCYTH) and feruloyl esterase (FAED_SCYTH) were formulated using simplex-lattice mixture design for the saccharification of acid pre-treated unwashed rice straw slurry obtained from PRAJ Industries and IOCL (Table 2). The efficacy of these formulated enzyme cocktails were evaluated on the basis of amount of total reducing sugars (TRS) and glucose released in the hydrolysate during 72 h of saccharification. The experimental simplex-lattice mixture design was based on three independent variables PMO9D_SCYTH (A), XYL43B_SCYTH (B) and FAED_SCYTH (C) at low (0 µl) and high (20 µl) levels selected on the basis of results obtained during addition of increasing dosages of recombinant proteins with Cellic CTec3. The actual and predicted values of the responses are given in Table 4. The R² (coefficient of determination) values obtained after statistical analysis for glucose and TRS release from substrate provided by PRAJ Industries and IOCL were 0.9932, 0.9816, 0.9851 and 0.9918, respectively. The results in Table 5 showing the ANOVA regression analysis of the proposed model, and the high values of R² obtained indicated to a strong correlation between actual and the predicted values suggesting that the proposed model is significant (P_model < 0.0001). The predicted R² values of the responses are in reasonable agreement with the adjusted R² values; i.e. the difference is less than 0.2. The Adeq Precision values (signal to noise ratio) for glucose/TRS release from substrate provided by PRAJ Industries/IOCL was 33.19, 21.33, 24.21 and 39.09, respectively; which were more than the desired ratio (4.0). This pattern of high adeq precision values further supports the accuracy of proposed model (Montgomery, 2017).

Table 4

Actual and predicted values of the sugars obtained after hydrolysis of acid pre-treated unwashed rice straw slurry provided by PRAJ Industries and IOCL using multi-component enzyme cocktails formulated using simplex-lattice mixture designing
		PRAJ Industries				IOCL
Std	Run	Response 1		Response 2		Response 3		Response 4
		Glucose (mg ml^− 1)		TRS (mg ml^− 1)		Glucose (mg ml^− 1)		TRS (mg ml^− 1)
				AV	PV	AV	PV	AV	PV	AV	PV
1	7	57.25	57.15	125.09	125.34	65.90	65.48	113.04	113.50
2	3	55.11	55.17	124.99	125.53	65.10	65.45	120.11	120.47
3	10	56.11	56.18	124.10	124.44	66.96	66.58	117.92	117.51
4	8	60.84	60.93	126.89	126.94	67.83	67.91	115.93	115.86
5	17	62.10	62.09	128.18	128.06	67.70	67.79	116.63	116.65
6	4	60.31	60.27	127.09	127.00	67.96	67.90	118.12	118.18
7	12	64.30	65.19	131.27	131.50	70.09	70.09	122.80	122.84
8	11	61.71	61.76	127.68	127.76	68.23	68.16	118.02	117.99
9	1	63.10	63.09	128.88	128.64	68.96	68.95	119.81	120.00
10	2	63.37	63.42	128.08	128.28	69.29	69.32	119.22	119.02
11	5	63.44	63.33	129.87	129.97	67.50	67.46	117.72	117.74
12	15	61.24	61.13	127.48	127.58	68.63	68.59	118.52	118.54
13	6	64.17	64.06	130.27	130.37	70.69	70.65	124.60	124.62
14	16	57.05	57.15	125.59	125.34	65.10	65.48	113.94	113.50
15	9	55.18	55.17	125.99	125.53	65.77	65.45	120.91	120.47
16	14	56.25	56.18	124.89	124.44	66.17	66.58	117.03	117.51
17	13	65.90	65.19	131.87	131.50	70.03	70.09	122.90	122.84
Actual values (AV); predicted values (PV); TRS: total reducing sugars.

Table 5

ANOVA table showing regression analysis of the proposed model for the formulation of multi-component enzymes cocktails
	Acid pre-treated unwashed rice straw slurry (17% substrate loading rate)
	PRAJ Industries				IOCL
	Glucose (mg/ml)		TRS (mg/ml)		Glucose (mg/ml)		TRS (mg/ml)
F-value	145.46		65.74		53.51		121.31
Prob > F	< 0.0001		< 0.0001		< 0.0001		< 0.0001
Model	Significant		Significant		Significant		Significant
	F-value	Prob > F	F-value	Prob > F	F-value	Prob > F	F-value	Prob > F
Linear Mixture	13.94	0.0025	0.0441	0.9571	21.63	0.0006	200.66	< 0.0001
AB	153.87	< 0.0001	19.75	0.0022	71.85	< 0.0001	0.0153	0.9045
AC	216.52	< 0.0001	76.5	< 0.0001	45.79	0.0001	29.26	0.0006
BC	449.69	< 0.0001	101.18	< 0.0001	117.39	< 0.0001	2.43	0.1578
A²BC	4.36	0.0702	16.06	0.0039	9.17	0.0163	0.6974	0.4279
AB²C	12.34	0.0079	11.52	0.0094	0.4412	0.5252	29.89	0.0006
ABC²	4.79	0.06	18.93	0.0024	24.56	0.0011	203.89	< 0.0001
R²	0.9932		0.9850		0.9817		0.9918
Adj. R²	0.9863		0.9700		0.9633		0.9836
Lack of Fit	Not Significant		Not Significant		Not Significant		Not Significant
Probability value of Fisher’s variance ratio (Prob > F); coefficient of determination (R²); Interactive effect of the components (A²BC, AB²C, ABC²); the amount of recombinant proteins PMO9D_SCYTH, XYL43B_SCYTH and FAED_SCYTH added (µl) in the enzyme cocktails are represented by independent variables A, B and C, respectively; TRS: total reducing sugars.

The iso-response values (contour and 3D surface plots) between PMO9D_SCYTH (A), XYL43B_SCYTH (B), and FAED_SCYTH (C) depicts that maximum amount of glucose (65.90 mg ml^− 1, Fig. 5a) and total reducing sugars (131.87 mg ml^− 1, Fig. 5b), corresponding to release of 55.24 and 74.38 mg ml^− 1 of glucose and total reducing sugars, respectively, after subtracting the sugars present in the slurry; were present in the hydrolysate obtained after saccharification of acid pre-treated rice straw slurry obtained from PRAJ Industries with the enzyme cocktail containing Cellic CTec3 (100 µl, ~ 2.3 mg protein or FPU/g substrate) and recombinant proteins mixture (20 µl) comprising PMO9D_SCYTH (33.4%), XYL43B_SCYTH (33.4%) and FAED_SCYTH (33.3%). This enzyme cocktail resulted in the 1.36 and 1.14 folds higher glucose and total reducing sugars release respectively, as compared to the control hydrolytic reactions carried out using Cellic CTec3 alone (120 µl, ~ 2.76 mg protein/g substrate); followed by the mixture containing PMO9D_SCYTH (16.7%), XYL43B_SCYTH (16.7%) and FAED_SCYTH (66.7%) that resulted in 1.33 and 1.12 higher glucose and total reducing sugars release (respectively; run 6), as compared to the control hydrolytic reactions. The polynomial model for both the responses are:

ϒ₁ = 57.15 A + 55.17 B + 56.18 C + 19.96 AB + 23.68 AC + 34.13 BC + 83.73 A²BC + 87.76 ABC²

ϒ₂ = 125.34 A + 125.53 B + 124.44 C + 6.91 AB + 13.61 AC + 15.65 BC + 155.32 A²BC + 168.65 ABC²

Where, ϒ₁ represents the amount of glucose (mg ml^− 1) and ϒ₂ represents the amount of total reducing sugars (mg ml^− 1) obtained from the acid pre-treated unwashed rice straw slurry obtained from PRAJ Industries.

In the case of the acid pre-treated unwashed rice straw slurry obtained from IOCL, the maximum amount of glucose (70.69 mg ml^− 1, Fig. 6a) and total reducing sugars (124.60 mg ml^− 1, Fig. 6b), corresponding to 64.95 and 89.26 mg ml^− 1, after subtracting sugars present in the slurry; were found to be present in the hydrolysate obtained after saccharification with enzyme cocktail containing Cellic CTec3 (100 µl, ~ 2.3 mg protein/g substrate) and the recombinant proteins mixture (20 µl) comprising PMO9D_SCYTH (16.7%), XYL43B_SCYTH (16.7%) and FAED_SCYTH (66.7%). This enzyme cocktail resulted in the 1.19 and 1.13 folds higher glucose and total reducing sugars release (respectively), as compared to the control hydrolytic reactions carried out using Cellic CTec3 alone (120 µl, ~ 2.76 mg protein/g substrate); followed by mixture containing PMO9D_SCYTH (33.4%), XYL43B_SCYTH (33.4%) and FAED_SCYTH (33.3%) resulting in 1.18 and 1.11 higher glucose and total reducing sugars release (respectively; run 13), as compared to the control hydrolytic reactions. The polynomial model for both the responses are:

ϒ₃ = 65.48 A + 65.45 B + 66.58 C + 10.97 AB + 8.76 AC + 14.03 BC + 159.84 ABC²

ϒ₄ = 113.50 A + 120.47 B + 117.51 C + 0.1873 AB + 8.18 AC + 2.36 BC + 31.47 A²BC + 538.15 ABC²

Where, ϒ₃ represents the amount of glucose (mg ml^− 1) and ϒ₄ represents the amount of total reducing sugars (mg ml^− 1) obtained from the acid pre-treated unwashed rice straw slurry provided by IOCL.

The results (Fig. ESM1 & ESM2) showing the relative increase (%) of the glucose and total reducing sugars release during hydrolysis from the unwashed acid pre-treated rice straw slurry obtained from PRAJ Industries and IOCL, respectively; compared to the saccharification carried out using benchmark control Cellic CTec3 (120 µl, ~ 2.76 mg protein/g substrate). The LPMO protein PMO9D_SCYTH alone (run 7 and 16) resulted in ~ 24.14 and 16.68% improved glucan conversion from the slurry obtained from PRAJ Industries and IOCL, respectively. The β-xylosidase protein XYL43B_SCYTH alone (run 3 and 9) resulted in 18.46 and 16.51% improved glucan conversion from the slurry obtained from PRAJ Industries and IOCL, respectively. The feruloyl esterase protein FAED_SCYTH alone (run 10 and 14) resulted in 21.12 and 14.96% improved glucan conversion from the slurry obtained from PRAJ Industries and IOCL, respectively. The spiking of LPMO PMO9D_SCYTH alone with Cellic CTec3 was observed to show maximal synergistic effect as it resulted in relatively high release of glucose and total reducing sugars from the slurry provided by PRAJ Industries, when compared to the spiking of XYL43B_SCYTH and FAED_SCYTH alone.

In the case of slurry obtained from IOCL, spiking of Cellic CTec3 with feruloyl esterase FAED_SCYTH resulted in maximum improvement in glucose release and β-xylosidase XYL43B_SCYTH alone resulted in maximum improvement in the release of total reducing sugars. Among the mixtures containing combinations of two recombinant proteins in different proportions (run 1, 2, 4, 8, 11 and 17), the mixture of XYL43B_SCYTH (33.4%) and FAED_SCYTH (66.7%) resulted in maximum improvement (40.46 and 18.64%) of glucose release from the slurry obtained from PRAJ Industries and IOCL, respectively; and the mixture containing combination of XYL43B_SCYTH (66.7%) and FAED_SCYTH (33.4%) resulted in maximum improvement (23.21 and 13.52%) of total reducing sugars release from the slurry obtained from PRAJ Industries and IOCL, respectively. These results obtained showing the maximum synergy among these two recombinant proteins when in mixture used with Cellic CTec3. The mixtures containing all the three recombinant proteins in different proportions (run 5, 6, 12, 13, and 15), the mixture containing PMO9D_SCYTH (33.4%), XYL43B_SCYTH (33.4%) and FAED_SCYTH (33.3%) resulted in maximum improvement (47.2 and 28.36%) of total reducing sugars and glucose release from the slurry obtained from PRAJ Industries, respectively; and the mixture containing PMO9D_SCYTH (16.7%), XYL43B_SCYTH (16.7%) and FAED_SCYTH (66.7%) resulted in maximum improvement (21.25 and 19.95%) of total reducing sugars and glucose release from the slurry obtained from IOCL Industries, respectively. Enzymatic formulations containing mixture of all the three recombinant proteins (PMO9D_SCYTH, XYL43B_SCYTH and FAED_SCYTH) spiked with Cellic CTec3 have the maximum synergistic effect and also found to be specific for their substrates and showed the overall maximum improvement in hydrolysis for their respective substrate. This showed that these enzymatic formulations are substrate specific and mixture of all the three recombinant proteins (PMO9D_SCYTH, XYL43B_SCYTH and FAED_SCYTH) spiked with Cellic CTec3 has the maximum synergistic effect. The formulated multicomponent enzymatic cocktails resulted in 70.39 and 84.46% saccharification efficiency (glucan and xylan) of unwashed acid pre-treated rice straw slurry obtained from PRAJ Industries and IOCL, respectively, and 57.34 and 67.42% saccharification efficiency (glucan) of unwashed acid pre-treated rice straw slurry obtained from PRAJ Industries and IOCL, respectively.

The optimized mixture of endoglucanase II, cellobiohydrolase I and β-glucosidase I (from Penicillium oxalicum) was formulated using the simplex lattice mixture design method for the hydrolysis of six different cellulosic materials by Du and co-workers (2020), and they found that to achieve optimum saccharification of each biomass a specific enzyme mixture was required (depending on both lignocellulosic material as well as pre-treatment method used). The newly marketed enzymatic formulations are now incorporated with different auxiliary and accessory activity proteins to enhance their performance for cellulosic hydrolysis and Hu et al, (2015) showed in their study that the incorporation of a LPMO (Thermoascus aurantiacus AA9 protein, Novozymes) and GH10 xylanase (purified from HTec, Novozymes) in optimized mixture with Celluclast 1.5 L (Novozymes) during the hydrolysis of steam pre-treated poplar resulted in the similar cellulosic hydrolytic efficiency as Cellic CTec2 at 2% substrate loading rate, and also found the similar pattern at 10 and 20% of substrate loading rate; but to achieve the overall > 80% similar saccharification efficiency, high protein loading rate of 10 to 30 and 60 mg/g substrate for the hydrolysis at 2, 10 and 20% substrate loading rate, respectively, was required. In the current study ~ 70% and > 80 of saccharification efficiency (in terms of total sugars) was achieved on the slurry provided by PRAJ Industries and IOCL, respectively; by loading ~ 4.06 mg/g of protein loading and 17% substrate loading rate. For the hydrolysis of ammonia fiber expansion (AFEX) pre-treated corn stover, an in-house enzyme cocktails was formulated using both fungal cellulases (CBH I, CBH II, EG I and βG) as well as bacterial hemicellulases (LX3, LX4, LArb, LaGl and LbX) and optimized formulation (at ~ 20 mg/g glucan loading rate) resulted in 80 and 70% more glucose and xylose yield, respectively, as compared to commercial cellulase preparation Accellerase™ 1000 (Genencor, NY, USA) (Gao et al., 2011). Recently, Nwamba et al., (2021) demonstrated that the initial loading of 8% substrate and then additional 4–4% substrate feeding at 6, 18 and 24 h (making total to 20%), and the mixture containing combined optimized additives (PEG 8000, Tween 80 and BSA) and accessory enzymes (β-glucosidase and endoxylanase) with new cellulase preparation LT4 (Qingdao Vland Biotech Inc., China) at low enzyme loading (2 mg protein/g substrate) resulted in the 83% glucose and 158 g L^− 1 total sugars yield from alkali-catalyzed atmospheric glycerol organosolv pre-treated sugarcane bagasse. The minimal enzyme cocktails formulated using quadratic design (MODDE Design of Experiments software) for hydrolysis of sulfite-pulped Norway spruce and sugarcane bagasse was developed by Chylenski and co-workers (2017) using purified GHs (TrCel7B, TrCel7A and TrCel6A; Trichoderma reesei QM 9414) and purified commercial β-glucosidase AnCel3A (E-BGLUC; Megazyme, Ireland) and Streptomyces coelicolor protein (ScLPMO10C). They also found that the formulated enzymatic cocktails are specific for their substrate as the cocktail containing TrCel7A (28%), TrCel7B (48%), TrCel6A (17%) and AnCel3A (7%) was found optimum for the maximum hydrolysis yield (82.3% of glucan) from sulfite-pulped Norway spruce (at 8 mg protein loading/g glucan) and the cocktail containing TrCel7A (28%), TrCel7B (30%), TrCel6A (30%), AnCel3A (8%) and ScLPMO10C (5%) was found optimum for the maximum hydrolysis yield (80.5% of glucan) from the sulfite-pulped sugarcane bagasse (at 8 mg protein loading/g glucan). The incorporation of LPMO protein in enzyme mixture was also found to be substrate specific as the cocktail optimized for sulfite-pulped Norway spruce didn’t contain bacterial LPMO ScLPMO10C.

Custom designing of multicomponent enzymatic formulations, optimized specifically for a particular pre-treated substrate, are more suitable to achieve higher saccharification efficiency at minimum protein loading rate as compared to a general enzymatic cocktail. The auxiliary activity proteins (AA9s) in combination with accessory activity proteins (GH43 and CE1) blended with commercially available high priced cellulase preparations (Cellic CTec3) have potential to achieve higher saccharification efficiency at much lower protein loading rate even at higher substrate loading rates.

Author Contribution

D.A. performed the experimental work and sample preparation and characterization, original draft preparation and final editing of the manuscript. Y.R., N.B. and A.T. carried out the formal analysis of the manuscript. S.P. provided the substrates and carried out the formal analysis of the manuscript. B.S.C. took care of the conceptualization, supervision and funding acquisition.

Acknowledgements

This research work was supported by Department of Biotechnology [BT/PR31115/PBD/26/766/2019] project entitled “Novel concepts for developing efficient cellulolytic cocktail for hydrolysis of bio-refinery relevant pre-treated lignocellulosics” and [BT/PR15271/PBD/26/509/2015] project entitled “Bioprospecting for novel lignocellulolytic gylcosyl hydrolases and auxiliary enzymes from diverse thermophilic fungal strains using proteome based approaches” to corresponding author, are duly acknowledged.

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Multi-component cocktail designing to develop a cost effective second generation bioconversion technology

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Highlights

1. Introduction

2. Material and Methods

2.1 Auxiliary and accessory activity enzymes production

2.2 Saccharification reaction setup, pre-treated substrate and the benchmark enzyme

2.3 Effect of increasing dosages of recombinant proteins on hydrolysis

2.4 Statistical design

3. Results

3.2 Effect of spiking Cellic CTec3 with increasing dosage of recombinant proteins on hydrolysis

3.3 Formulation of multi-component cocktails

4. Discussion

5. Conclusions

Declarations

Author Contribution

Acknowledgements

References

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