Exploring biodiversity for cellulosic biofuel production

Uses of Multi-Objective Flux Analysis for Optimization of Microbial Production of Secondary Metabolites

Secondary metabolites are not essential for the growth of microorganisms, but they play a critical role in how microbes interact with their surroundings. In addition to this important ecological role, secondary metabolites also have a variety of agricultural, medicinal, and industrial uses, and thus the examination of secondary metabolism of plants and microbes is a growing scientific field. While the chemical production of certain secondary metabolites is possible, industrial-scale microbial production is a green and economically attractive alternative. This is even more true, given the advances in bioengineering that allow us to alter the workings of microbes in order to increase their production of compounds of interest. This type of engineering requires detailed knowledge of the "chassis" organism's metabolism. Since the resources and the catalytic capacity of enzymes in microbes is finite, it is important to examine the tradeoffs between various bioprocesses in an engineered system and alter its working in a manner that minimally perturbs the robustness of the system while allowing for the maximum production of a product of interest. The in silico multi-objective analysis of metabolism using genome-scale models is an ideal method for such examinations.

Role of metagenomics in prospecting novel endoglucanases, accentuating functional metagenomics approach in second-generation biofuel production: a review

As the fossil fuel reserves are depleting rapidly, there is a need for alternate fuels to meet the day to day mounting energy demands. As fossil fuel started depleting, a quest for alternate forms of fuel was initiated and biofuel is one of its promising outcomes. First-generation biofuels are made from edible sources like vegetable oils, starch, and sugars. Second-generation biofuels (SGB) are derived from lignocellulosic crops and the third-generation involves algae for biofuel production. Technical challenges in the production of SGB are hampering its commercialization. Advanced molecular technologies like metagenomics can help in the discovery of novel lignocellulosic biomass-degrading enzymes for commercialization and industrial production of SGB. This review discusses the metagenomic outcomes to enlighten the importance of unexplored habitats for novel cellulolytic gene mining. It also emphasizes the potential of different metagenomic approaches to explore the uncultivable cellulose-degrading microbiome as well as cellulolytic enzymes associated with them. This review also includes effective pre-treatment technology and consolidated bioprocessing for efficient biofuel production.

Glycosylation effects on the structure and dynamics of a full-length Cel7A cellulase

Fungi cellulases are used to degrade cellulose-containing biomass for bioethanol production. Industrial cellulases such as Cel7A from Trichoderma reesei (TrCel7A) are critical in this process. Thus, the understanding of structure and dynamics is crucial for engineering variants with improved cellulolytic activity. This cellulase consists of two domains connected by a flexible and highly glycosylated linker. However, the linker flexibility has hindered the determination of Cel7A complete structure. Herein, based on atomic and sparse data, we applied integrative modelling to build a model of the complete enzyme structure. Next, through simulations, we studied the glycosylation effects on the structure and dynamics of a solubilized TrCel7A. Essential dynamics analysis showed that O-glycosylation in the linker led to the stabilization of protein overall dynamics. O-linked glycans seem to restrict protein dihedral angles distribution in this region, selecting more elongated conformations. Besides the reduced flexibility, functional interdomain motions occurred in a more concerted way in the glycosylated system. In contrast, in the absence of glycosylation, we observed vast conformational plasticity with the functional domains frequently collapsing. We report here evidence that targeting Cel7A linker flexibility by point mutations including modification of glycosylation sites could be a promising design strategy to improve cellulase activity.

Molecular cloning, expression, and characterization of four novel thermo-alkaliphilic enzymes retrieved from a metagenomic library

BACKGROUND

Enzyme discovery is a promising approach to aid in the deconstruction of recalcitrant plant biomass in an industrial process. Novel enzymes can be readily discovered by applying metagenomics on whole microbiomes. Our goal was to select, examine, and characterize eight novel glycoside hydrolases that were previously detected in metagenomic libraries, to serve biotechnological applications with high performance.

RESULTS

Here, eight glycosyl hydrolase family candidate genes were selected from metagenomes of wheat straw-degrading microbial consortia using molecular cloning and subsequent gene expression studies in Escherichia coli. Four of the eight enzymes had significant activities on either pNP-β-d-galactopyranoside, pNP-β-d-xylopyranoside, pNP-α-l-arabinopyranoside or pNP-α-d-glucopyranoside. These proteins, denoted as proteins 1, 2, 5 and 6, were his-tag purified and their nature and activities further characterized using molecular and activity screens with the pNP-labeled substrates. Proteins 1 and 2 showed high homologies with (1) a β-galactosidase (74%) and (2) a β-xylosidase (84%), whereas the remaining two (5 and 6) were homologous with proteins reported as a diguanylate cyclase and an aquaporin, respectively. The β-galactosidase- and β-xylosidase-like proteins 1 and 2 were confirmed as being responsible for previously found thermo-alkaliphilic glycosidase activities of extracts of E. coli carrying the respective source fosmids. Remarkably, the β-xylosidase-like protein 2 showed activities with both pNP-Xyl and pNP-Ara in the temperature range 40-50 °C and pH range 8.0-10.0. Moreover, proteins 5 and 6 showed thermotolerant α-glucosidase activity at pH 10.0. In silico structure prediction of protein 5 revealed the presence of a potential "GGDEF" catalytic site, encoding α-glucosidase activity, whereas that of protein 6 showed a "GDSL" site, encoding a 'new family' α-glucosidase activity.

CONCLUSION

Using a rational screening approach, we identified and characterized four thermo-alkaliphilic glycosyl hydrolases that have the potential to serve as constituents of enzyme cocktails that produce sugars from lignocellulosic plant remains.

Efficient whole-cell-catalyzing cellulose saccharification using engineered Clostridium thermocellum

BACKGROUND

Cost-efficient saccharification is one of the main bottlenecks for industrial lignocellulose conversion. Clostridium thermocellum naturally degrades lignocellulose efficiently using the cellulosome, a multiprotein supermolecular complex, and thus can be potentially used as a low-cost catalyst for lignocellulose saccharification. The industrial use of C. thermocellum is restrained due largely to the inhibition of the hydrolysate cellobiose to its cellulosome. Although the supplementation of beta-glucosidase may solve the problem, the production of the enzymes greatly complicates the process and may also increase the cost of saccharification.

RESULTS

To conquer the feedback inhibition and establish an efficient whole-cell catalyst for highly efficient cellulose saccharification, we constructed a recombinant strain of C. thermocellum ∆pyrF::CaBglA which produced a secretory exoglucanase CelS-bearing heterologous BGL using a newly developed seamless genome editing system. Without the extra addition of enzymes, the relative saccharification level of ∆pyrF::CaBglA was stimulated by over twofolds compared to its parent strain ∆pyrF through a two-stage saccharification process with 100 g/L Avicel as the carbon source. The production of reducing sugars and the relative saccharification level were further enhanced to 490 mM and 79.4%, respectively, with increased cell density.

CONCLUSIONS

The high cellulose-degrading ability and sugar productivity suggested that the whole-cell-catalysis strategy for cellulose saccharification is promising, and the C. thermocellum strain ∆pyrF::CaBglA could be potentially used as an efficient whole-cell catalyst for industrial cellulose saccharification.

Covalently anchored sulfamic acid on cellulose as heterogeneous solid acid catalyst for the synthesis of structurally symmetrical and unsymmetrical 1,4-dihydropyridine derivatives

A novel heterogeneous solid acid catalyst has been prepared by covalent grafting of chlorosulphonic acid on amino-functionalized cellulose (Cell–Pr-NHSO₃H).

A multi-substrate approach for functional metagenomics-based screening for (hemi)cellulases in two wheat straw-degrading microbial consortia unveils novel thermoalkaliphilic enzymes

BACKGROUND

Functional metagenomics is a promising strategy for the exploration of the biocatalytic potential of microbiomes in order to uncover novel enzymes for industrial processes (e.g. biorefining or bleaching pulp). Most current methodologies used to screen for enzymes involved in plant biomass degradation are based on the use of single substrates. Moreover, highly diverse environments are used as metagenomic sources. However, such methods suffer from low hit rates of positive clones and hence the discovery of novel enzymatic activities from metagenomes has been hampered.

RESULTS

Here, we constructed fosmid libraries from two wheat straw-degrading microbial consortia, denoted RWS (bred on untreated wheat straw) and TWS (bred on heat-treated wheat straw). Approximately 22,000 clones from each library were screened for (hemi)cellulose-degrading enzymes using a multi-chromogenic substrate approach. The screens yielded 71 positive clones for both libraries, giving hit rates of 1:440 and 1:1,047 for RWS and TWS, respectively. Seven clones (NT2-2, T5-5, NT18-17, T4-1, 10BT, NT18-21 and T17-2) were selected for sequence analyses. Their inserts revealed the presence of 18 genes encoding enzymes belonging to twelve different glycosyl hydrolase families (GH2, GH3, GH13, GH17, GH20, GH27, GH32, GH39, GH53, GH58, GH65 and GH109). These encompassed several carbohydrate-active gene clusters traceable mainly to Klebsiella related species. Detailed functional analyses showed that clone NT2-2 (containing a beta-galactosidase of ~116 kDa) had highest enzymatic activity at 55 °C and pH 9.0. Additionally, clone T5-5 (containing a beta-xylosidase of ~86 kDa) showed > 90% of enzymatic activity at 55 °C and pH 10.0.

CONCLUSIONS

This study employed a high-throughput method for rapid screening of fosmid metagenomic libraries for (hemi)cellulose-degrading enzymes. The approach, consisting of screens on multi-substrates coupled to further analyses, revealed high hit rates, as compared with recent other studies. Two clones, 10BT and T4-1, required the presence of multiple substrates for detectable activity, indicating a new avenue in library activity screening. Finally, clones NT2-2, T5-5 and NT18-17 were found to encode putative novel thermo-alkaline enzymes, which could represent a starting point for further biotechnological applications.

Genome-scale modelling of microbial metabolism with temporal and spatial resolution

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated.

Family 46 Carbohydrate-binding Modules Contribute to the Enzymatic Hydrolysis of Xyloglucan and β-1,3-1,4-Glucans through Distinct Mechanisms

Structural carbohydrates comprise an extraordinary source of energy that remains poorly utilized by the biofuel sector as enzymes have restricted access to their substrates within the intricacy of plant cell walls. Carbohydrate active enzymes (CAZYmes) that target recalcitrant polysaccharides are modular enzymes containing noncatalytic carbohydrate-binding modules (CBMs) that direct enzymes to their cognate substrate, thus potentiating catalysis. In general, CBMs are functionally and structurally autonomous from their associated catalytic domains from which they are separated through flexible linker sequences. Here, we show that a C-terminal CBM46 derived from BhCel5B, a Bacillus halodurans endoglucanase, does not interact with β-glucans independently but, uniquely, acts cooperatively with the catalytic domain of the enzyme in substrate recognition. The structure of BhCBM46 revealed a β-sandwich fold that abuts onto the region of the substrate binding cleft upstream of the active site. BhCBM46 as a discrete entity is unable to bind to β-glucans. Removal of BhCBM46 from BhCel5B, however, abrogates binding to β-1,3-1,4-glucans while substantially decreasing the affinity for decorated β-1,4-glucan homopolymers such as xyloglucan. The CBM46 was shown to contribute to xyloglucan hydrolysis only in the context of intact plant cell walls, but it potentiates enzymatic activity against purified β-1,3-1,4-glucans in solution or within the cell wall. This report reveals the mechanism by which a CBM can promote enzyme activity through direct interaction with the substrate or by targeting regions of the plant cell wall where the target glucan is abundant.

Crystallization and preliminary X-ray diffraction analysis of a trimodular endo-β-1,4-glucanase (Cel5B) from Bacillus halodurans

Cellulases catalyze the hydrolysis of cellulose, the major constituent of plant biomass and the most abundant organic polymer on earth. Cellulases are modular enzymes containing catalytic domains connected, via linker sequences, to noncatalytic carbohydrate-binding modules (CBMs). A putative modular endo-β-1,4-glucanase (BhCel5B) is encoded at locus BH0603 in the genome of Bacillus halodurans. It is composed of an N-terminal glycoside hydrolase family 5 catalytic module (GH5) followed by an immunoglobulin-like module and a C-terminal family 46 CBM (BhCBM46). Here, the crystallization and preliminary X-ray diffraction analysis of the trimodular BhCel5B are reported. The crystals of BhCel5B belonged to the orthorhombic space group P2121 2 and data were processed to a resolution of 1.64 Å. A molecular-replacement solution has been found.

Characterization of five β-glycoside hydrolases from Cellulomonas fimi ATCC 484

The Gram-positive bacterium Cellulomonas fimi produces a large array of carbohydrate-active enzymes. Analysis of the collection of carbohydrate-active enzymes from the recent genome sequence of C. fimi ATCC 484 shows a large number of uncharacterized genes for glycoside hydrolase (GH) enzymes potentially involved in biomass utilization. To investigate the enzymatic activity of potential β-glucosidases in C. fimi, genes encoding several GH3 enzymes and one GH1 enzyme were cloned and recombinant proteins were expressed in Escherichia coli. Biochemical analysis of these proteins revealed that the enzymes exhibited different substrate specificities for para-nitrophenol-linked substrates (pNP), disaccharides, and oligosaccharides. Celf_2726 encoded a bifunctional enzyme with β-d-xylopyranosidase and α-l-arabinofuranosidase activities, based on pNP-linked substrates (CfXyl3A). Celf_0140 encoded a β-d-glucosidase with activity on β-1,3- and β-1,6-linked glucosyl disaccharides as well as pNP-β-Glc (CfBgl3A). Celf_0468 encoded a β-d-glucosidase with hydrolysis of pNP-β-Glc and hydrolysis/transglycosylation activities only on β-1,6-linked glucosyl disaccharide (CfBgl3B). Celf_3372 encoded a GH3 family member with broad aryl-β-d-glycosidase substrate specificity. Celf_2783 encoded the GH1 family member (CfBgl1), which was found to hydrolyze pNP-β-Glc/Fuc/Gal, as well as cellotetraose and cellopentaose. CfBgl1 also had good activity on β-1,2- and β-1,3-linked disaccharides but had only very weak activity on β-1,4/6-linked glucose.

Designing novel cellulase systems through agent-based modeling and global sensitivity analysis

Experimental techniques allow engineering of biological systems to modify functionality; however, there still remains a need to develop tools to prioritize targets for modification. In this study, agent-based modeling (ABM) was used to build stochastic models of complexed and non-complexed cellulose hydrolysis, including enzymatic mechanisms for endoglucanase, exoglucanase, and β-glucosidase activity. Modeling results were consistent with experimental observations of higher efficiency in complexed systems than non-complexed systems and established relationships between specific cellulolytic mechanisms and overall efficiency. Global sensitivity analysis (GSA) of model results identified key parameters for improving overall cellulose hydrolysis efficiency including: (1) the cellulase half-life, (2) the exoglucanase activity, and (3) the cellulase composition. Overall, the following parameters were found to significantly influence cellulose consumption in a consolidated bioprocess (CBP): (1) the glucose uptake rate of the culture, (2) the bacterial cell concentration, and (3) the nature of the cellulase enzyme system (complexed or non-complexed). Broadly, these results demonstrate the utility of combining modeling and sensitivity analysis to identify key parameters and/or targets for experimental improvement.

Inference of phenotype-defining functional modules of protein families for microbial plant biomass degraders

BACKGROUND

Efficient industrial processes for converting plant lignocellulosic materials into biofuels are a key to global efforts to come up with alternative energy sources to fossil fuels. Novel cellulolytic enzymes have been discovered in microbial genomes and metagenomes of microbial communities. However, the identification of relevant genes without known homologs, and the elucidation of the lignocellulolytic pathways and protein complexes for different microorganisms remain challenging.

RESULTS

We describe a new computational method for the targeted discovery of functional modules of plant biomass-degrading protein families, based on their co-occurrence patterns across genomes and metagenome datasets, and the strength of association of these modules with the genomes of known degraders. From approximately 6.4 million family annotations for 2,884 microbial genomes, and 332 taxonomic bins from 18 metagenomes, we identified 5 functional modules that are distinctive for plant biomass degraders, which we term "plant biomass degradation modules" (PDMs). These modules incorporate protein families involved in the degradation of cellulose, hemicelluloses, and pectins, structural components of the cellulosome, and additional families with potential functions in plant biomass degradation. The PDMs were linked to 81 gene clusters in genomes of known lignocellulose degraders, including previously described clusters of lignocellulolytic genes. On average, 70% of the families of each PDM were found to map to gene clusters in known degraders, which served as an additional confirmation of their functional relationships. The presence of a PDM in a genome or taxonomic metagenome bin furthermore allowed us to accurately predict the ability of any particular organism to degrade plant biomass. For 15 draft genomes of a cow rumen metagenome, we used cross-referencing to confirmed cellulolytic enzymes to validate that the PDMs identified plant biomass degraders within a complex microbial community.

CONCLUSIONS

Functional modules of protein families that are involved in different aspects of plant cell wall degradation can be inferred from co-occurrence patterns across (meta-)genomes with a probabilistic topic model. PDMs represent a new resource of protein families and candidate genes implicated in microbial plant biomass degradation. They can also be used to predict the plant biomass degradation ability for a genome or taxonomic bin. The method is also suitable for characterizing other microbial phenotypes.

Dynamic metabolic modeling of a microaerobic yeast co-culture: predicting and optimizing ethanol production from glucose/xylose mixtures

BACKGROUND

A key step in any process that converts lignocellulose to biofuels is the efficient fermentation of both hexose and pentose sugars. The co-culture of respiratory-deficient Saccharomyces cerevisiae and wild-type Scheffersomyces stipitis has been identified as a promising system for microaerobic ethanol production because S. cerevisiae only consumes glucose while S. stipitis efficiently converts xylose to ethanol.

RESULTS

To better predict how these two yeasts behave in batch co-culture and to optimize system performance, a dynamic flux balance model describing co-culture metabolism was developed from genome-scale metabolic reconstructions of the individual organisms. First a dynamic model was developed for each organism by estimating substrate uptake kinetic parameters from batch pure culture data and evaluating model extensibility to different microaerobic growth conditions. The co-culture model was constructed by combining the two individual models assuming a cellular objective of total growth rate maximization. To obtain accurate predictions of batch co-culture data collected at different microaerobic conditions, the S. cerevisiae maximum glucose uptake rate was reduced from its pure culture value to account for more efficient S. stipitis glucose uptake in co-culture. The dynamic co-culture model was used to predict the inoculum concentration and aeration level that maximized batch ethanol productivity. The model predictions were validated with batch co-culture experiments performed at the optimal conditions. Furthermore, the dynamic model was used to predict how engineered improvements to the S. stipitis xylose transport system could improve co-culture ethanol production.

CONCLUSIONS

These results demonstrate the utility of the dynamic co-culture metabolic model for guiding process and metabolic engineering efforts aimed at increasing microaerobic ethanol production from glucose/xylose mixtures.

The role of synthetic biology in the design of microbial cell factories for biofuel production

Insecurity in the supply of fossil fuels, volatile fuel prices, and major concerns regarding climate change have sparked renewed interest in the production of fuels from renewable resources. Because of this, the use of biodiesel has grown dramatically during the last few years and is expected to increase even further in the future. Biodiesel production through the use of microbial systems has marked a turning point in the field of biofuels since it is emerging as an attractive alternative to conventional technology. Recent progress in synthetic biology has accelerated the ability to analyze, construct, and/or redesign microbial metabolic pathways with unprecedented precision, in order to permit biofuel production that is amenable to industrial applications. The review presented here focuses specifically on the role of synthetic biology in the design of microbial cell factories for efficient production of biodiesel.

Laboratory evolution and multi-platform genome re-sequencing of the cellulolytic actinobacterium Thermobifida fusca

Biological utilization of cellulose is a complex process involving the coordinated expression of different cellulases, often in a synergistic manner. One possible means of inducing an organism-level change in cellulase activity is to use laboratory adaptive evolution. In this study, evolved strains of the cellulolytic actinobacterium, Thermobifida fusca, were generated for two different scenarios: continuous exposure to cellobiose (strain muC) or alternating exposure to cellobiose and glucose (strain muS). These environmental conditions produced a phenotype specialized for growth on cellobiose (muC) and an adaptable, generalist phenotype (muS). Characterization of cellular phenotypes and whole genome re-sequencing were conducted for both the muC and muS strains. Phenotypically, the muC strain showed decreased cell yield over the course of evolution concurrent with decreased cellulase activity, increased intracellular ATP concentrations, and higher end-product secretions. The muS strain increased its cell yield for growth on glucose and exhibited a more generalist phenotype with higher cellulase activity and growth capabilities on different substrates. Whole genome re-sequencing identified 48 errors in the reference genome and 18 and 14 point mutations in the muC and muS strains, respectively. Among these mutations, the site mutation of Tfu_1867 was found to contribute the specialist phenotype and the site mutation of Tfu_0423 was found to contribute the generalist phenotype. By conducting and characterizing evolution experiments on Thermobifida fusca, we were able to show that evolutionary changes balance ATP energetic considerations with cellulase activity. Increased cellulase activity is achieved in stress environments (switching carbon sources), otherwise cellulase activity is minimized to conserve ATP.

Applications of systems biology towards microbial fuel production

Harnessing the immense natural diversity of biological functions for economical production of fuel has enormous potential benefits. Inevitably, however, the native capabilities for any given organism must be modified to increase the productivity or efficiency of a biofuel bioprocess. From a broad perspective, the challenge is to sufficiently understand the details of cellular functionality to be able to prospectively predict and modify the cellular function of a microorganism. Recent advances in experimental and computational systems biology approaches can be used to better understand cellular level function and guide future experiments. With pressure to quickly develop viable, renewable biofuel processes a balance must be maintained between obtaining depth of biological knowledge and applying that knowledge.

Metabolic engineering of Clostridium cellulolyticum for production of isobutanol from cellulose

Producing biofuels directly from cellulose, known as consolidated bioprocessing, is believed to reduce costs substantially compared to a process in which cellulose degradation and fermentation to fuel are accomplished in separate steps. Here we present a metabolic engineering example for the development of a Clostridium cellulolyticum strain for isobutanol synthesis directly from cellulose. This strategy exploits the host's natural cellulolytic activity and the amino acid biosynthesis pathway and diverts its 2-keto acid intermediates toward alcohol synthesis. Specifically, we have demonstrated the first production of isobutanol to approximately 660 mg/liter from crystalline cellulose by using this microorganism.