Metabolic modeling of clostridia: current developments and applications

Effects of orphan histidine kinases on clostridial sporulation progression and metabolism

Solventogenesis and sporulation of clostridia are the main responsive adaptations to the acidic environment during acetone-butanol-ethanol (ABE) fermentation. It was hypothesized that five orphan histidine kinases (HKs) including Cac3319, Cac0323, Cac0903, Cac2730, and Cac0437 determined the cell fates between sporulation and solventogenesis. In this study, the comparative genomic analysis revealed that a mutation in cac0437 appeared to contribute to the nonsporulating feature of ATCC 55025. Hence, the individual and interactive roles of five HKs in regulating cell growth, metabolism, and sporulation were investigated. The fermentation results of mutants with different HK expression levels suggested that cac3319 and cac0437 played critical roles in regulating sporulation and acids and butanol biosynthesis. Morphological analysis revealed that cac3319 knockout abolished sporulation (Stage 0) whereas cac3319 overexpression promoted spore development (Stage VII), and cac0437 knockout initiated but blocked sporulation before Stage II, indicating the progression of sporulation was altered through engineering HKs. By combinatorial HKs knockout, the interactive effects between two different HKs were investigated. This study elucidated the regulatory roles of HKs in clostridial differentiation and demonstrated that HK engineering can be effectively used to control sporulation and enhance butanol biosynthesis.

Towards continuous industrial bioprocessing with solventogenic and acetogenic clostridia: challenges, progress and perspectives

The sustainable production of solvents from above ground carbon is highly desired. Several clostridia naturally produce solvents and use a variety of renewable and waste-derived substrates such as lignocellulosic biomass and gas mixtures containing H2/CO2 or CO. To enable economically viable production of solvents and biofuels such as ethanol and butanol, the high productivity of continuous bioprocesses is needed. While the first industrial-scale gas fermentation facility operates continuously, the acetone-butanol-ethanol (ABE) fermentation is traditionally operated in batch mode. This review highlights the benefits of continuous bioprocessing for solvent production and underlines the progress made towards its establishment. Based on metabolic capabilities of solvent producing clostridia, we discuss recent advances in systems-level understanding and genome engineering. On the process side, we focus on innovative fermentation methods and integrated product recovery to overcome the limitations of the classical one-stage chemostat and give an overview of the current industrial bioproduction of solvents.

Baicalin-Copper Complex Modulates Gut Microbiota, Inflammatory Responses, and Hormone Secretion in DON-Challenged Piglets

Simple Summary

Deoxynivalenol (DON) is the most common mycotoxin contaminant in the agriculture industry worldwide. Copper is very efficacious in promoting growth performance and improving feed remuneration, and baicalin may alleviate oxidative stress and inflammatory responses in humans and animals. We speculated that the combined effect of baicalin and copper would have some effect in DON-challenged piglets. The present study examined the effects of a baicalin-copper complex on inflammatory responses, hormone secretion, and gut microbiota in DON challenged piglets. These findings provide new application prospects in piglets involving the combination of baicalin and copper.

Abstract

The present experiment assessed the inflammatory responses, hormone secretion, and gut microbiota of weanling piglets administered baicalin-copper complex (BCU) or deoxynivalenol (DON) supplementation diets. Twenty-eight piglets were randomly assigned to four groups: control diet (Con group), a 4 mg DON/kg diet (DON group), a 5 g BCU/kg diet (BCU group), a 5 g BCU + 4 mg DON/kg diet (DBCU group). After 14 days, the results showed that dietary BCU supplementation remarkably increased the relative abundance of Clostrium bornimense and decreased the relative abundance of Lactobacillus in the DBCU group (p < 0.05). BCU decreased the serum concentration of IgG, IL-2, IFN-γ, and IgA in DON treated piglets (p < 0.05), and promoted the serum concentration of IL-1β, IgG, IL-2, IFN-γ, IgA, IL-6, IgM, and TNFα in normal piglets (p < 0.05). BCU increased the concentrations of serum IGF1, insulin, NPY, GLP-1, and GH, and decreased the concentrations of serum somatostatin in no DON treated piglets (p < 0.05). Dietary BCU supplementation significantly promoted the secretion of somatostatin, and inhibited the secretion of leptin in piglets challenged with DON (p < 0.05). BCU regulated the expression of food intake-related genes in the hypothalamus and pituitary of piglets. Collectively, dietary BCU supplementation alleviated inflammatory responses and regulated the secretion of appetite-regulating hormones and growth-axis hormones in DON challenged piglets, which was closely linked to changes of intestinal microbes.

Development of a Genome-Scale Metabolic Model of Clostridium thermocellum and Its Applications for Integration of Multi-Omics Datasets and Computational Strain Design

Solving environmental and social challenges such as climate change requires a shift from our current non-renewable manufacturing model to a sustainable bioeconomy. To lower carbon emissions in the production of fuels and chemicals, plant biomass feedstocks can replace petroleum using microorganisms as biocatalysts. The anaerobic thermophile Clostridium thermocellum is a promising bacterium for bioconversion due to its capability to efficiently degrade lignocellulosic biomass. However, the complex metabolism of C. thermocellum is not fully understood, hindering metabolic engineering to achieve high titers, rates, and yields of targeted molecules. In this study, we developed an updated genome-scale metabolic model of C. thermocellum that accounts for recent metabolic findings, has improved prediction accuracy, and is standard-conformant to ensure easy reproducibility. We illustrated two applications of the developed model. We first formulated a multi-omics integration protocol and used it to understand redox metabolism and potential bottlenecks in biofuel (e.g., ethanol) production in C. thermocellum. Second, we used the metabolic model to design modular cells for efficient production of alcohols and esters with broad applications as flavors, fragrances, solvents, and fuels. The proposed designs not only feature intuitive push-and-pull metabolic engineering strategies, but also present novel manipulations around important central metabolic branch-points. We anticipate the developed genome-scale metabolic model will provide a useful tool for system analysis of C. thermocellum metabolism to fundamentally understand its physiology and guide metabolic engineering strategies to rapidly generate modular production strains for effective biosynthesis of biofuels and biochemicals from lignocellulosic biomass.

Recent advancement on biological technologies and strategies for resource recovery from swine wastewater

Swine wastewater is categorized as one of the agricultural wastewater with high contents of organics and nutrients including nitrogen and phosphorus, which may lead to eutrophication in the environment. Insufficient technologies to remove those nutrients could lead to environmental problems after discharge. Several physical and chemical methods have been applied to treat the swine wastewater, but biological treatments are considered as the promising methods due to the cost effectiveness and performance efficiency along with the production of valuable products and bioenergies. This review summarizes the characteristics of swine wastewaters in the beginning, and briefly describes the current issues on the treatments of swine wastewaters. Several biological techniques, such as anaerobic digestion, A/O process, microbial fuel cells, and microalgae cultivations, and their future aspects will be addressed. Finally, the potentials to reutilize biomass produced during the treatment processes are also presented under the consideration of circular economy.

Metagenomic Insights Into a Cellulose-Rich Niche Reveal Microbial Cooperation in Cellulose Degradation

Background

Cellulose is the most abundant organic polymer mainly produced by plants in nature. It is insoluble and highly resistant to enzymatic hydrolysis. Cellulolytic microorganisms that are capable of producing a battery of related enzymes play an important role in recycling cellulose-rich plant biomass. Effective cellulose degradation by multiple synergic microorganisms has been observed within a defined microbial consortium in the lab culture. Metagenomic analysis may enable us to understand how microbes cooperate in cellulose degradation in a more complex microbial free-living ecosystem in nature.

Results

Here we investigated a typical cellulose-rich and alkaline niche where constituent microbes survive through inter-genera cooperation in cellulose utilization. The niche has been generated in an ancient paper-making plant, which has served as an isolated habitat for over 7 centuries. Combined amplicon-based sequencing of 16S rRNA genes and metagenomic sequencing, our analyses showed a microbial composition with 6 dominant genera including Cloacibacterium, Paludibacter, Exiguobacterium, Acetivibrio, Tolumonas, and Clostridium in this cellulose-rich niche; the composition is distinct from other cellulose-rich niches including a modern paper mill, bamboo soil, wild giant panda guts, and termite hindguts. In total, 11,676 genes of 96 glucoside hydrolase (GH) families, as well as 1,744 genes of carbohydrate transporters were identified, and modeling analysis of two representative genes suggested that these glucoside hydrolases likely evolved to adapt to alkaline environments. Further reconstruction of the microbial draft genomes by binning the assembled contigs predicted a mutualistic interaction between the dominant microbes regarding the cellulolytic process in the niche, with Paludibacter and Clostridium acting as helpers that produce endoglucanases, and Cloacibacterium, Exiguobacterium, Acetivibrio, and Tolumonas being beneficiaries that cross-feed on the cellodextrins by oligosaccharide uptake.

Conclusion

The analysis of the key genes involved in cellulose degradation and reconstruction of the microbial draft genomes by binning the assembled contigs predicted a mutualistic interaction based on public goods regarding the cellulolytic process in the niche, suggesting that in the studied microbial consortium, free-living bacteria likely survive on each other by acquisition and exchange of metabolites. Knowledge gained from this study will facilitate the design of complex microbial communities with a better performance in industrial bioprocesses.

Secretomic analyses of Ruminiclostridium papyrosolvens reveal its enzymatic basis for lignocellulose degradation

BACKGROUND

Efficient biotechnological conversion of lignocellulosic biomass to valuable products, such as transportation biofuels, is ecologically attractive, yet requires substantially improved mechanistic understanding and optimization to become economically feasible. Cellulolytic clostridia, such as Ruminiclostridium papyrosolvens (previously Clostridium papyrosolvens), produce a wide variety of carbohydrate-active enzymes (CAZymes) including extracellular multienzyme complexes-cellulosomes with different specificities for enhanced cellulosic biomass degradation. Identification of the secretory components, especially CAZymes, during bacterial growth on lignocellulose and their influence on bacterial catalytic capabilities provide insight into construction of potent cellulase systems of cell factories tuned or optimized for the targeted substrate by matching the type and abundance of enzymes and corresponding transporters.

RESULTS

In this study, we firstly predicted a total of 174 putative CAZymes from the genome of R. papyrosolvens, including 74 cellulosomal components. To explore profile of secreted proteins involved in lignocellulose degradation, we compared the secretomes of R. papyrosolvens grown on different substrates using label-free quantitative proteomics. CAZymes, extracellular solute-binding proteins (SBPs) of transport systems and proteins involved in spore formation were enriched in the secretome of corn stover for lignocellulose degradation. Furthermore, compared with free CAZymes, complex CAZymes (cellulosomal components) had larger fluctuations in variety and abundance of enzymes among four carbon sources. In particular, cellulosomal proteins encoded by the cip-cel operon and the xyl-doc gene cluster had the highest abundance with corn stover as substrate. Analysis of differential expression of CAZymes revealed a substrate-dependent secretion pattern of CAZymes, which was consistent with their catalytic activity from each secretome determined on different cellulosic substrates. The results suggest that the expression of CAZymes is regulated by the type of substrate in the growth medium.

CONCLUSIONS

In the present study, our results demonstrated the complexity of the lignocellulose degradation systems of R. papyrosolvens and showed the potency of its biomass degradation activity. Differential proteomic analyses and activity assays of CAZymes secreted by R. papyrosolvens suggested a distinct environment-sensing strategy for cellulose utilization in which R. papyrosolvens modulated the composition of the CAZymes, especially cellulosome, according to the degradation state of its natural substrate.

Clostridium butyricum population balance model: Predicting dynamic metabolic flux distributions using an objective function related to extracellular glycerol content

BACKGROUND

Extensive experimentation has been conducted to increment 1,3-propanediol (PDO) production using Clostridium butyricum cultures in glycerol, but computational predictions are limited. Previously, we reconstructed the genome-scale metabolic (GSM) model iCbu641, the first such model of a PDO-producing Clostridium strain, which was validated at steady state using flux balance analysis (FBA). However, the prediction ability of FBA is limited for batch and fed-batch cultures, which are the most often employed industrial processes.

RESULTS

We used the iCbu641 GSM model to develop a dynamic flux balance analysis (DFBA) approach to predict the PDO production of the Colombian strain Clostridium sp IBUN 158B. First, we compared the predictions of the dynamic optimization approach (DOA), static optimization approach (SOA), and direct approach (DA). We found no differences between approaches, but the DOA simulation duration was nearly 5000 times that of the SOA and DA simulations. Experimental results at glycerol limitation and glycerol excess allowed for validating dynamic predictions of growth, glycerol consumption, and PDO formation. These results indicated a 4.4% error in PDO prediction and therefore validated the previously proposed objective functions. We performed two global sensitivity analyses, finding that the kinetic input parameters of glycerol uptake flux had the most significant effect on PDO predictions. The other input parameters evaluated during global sensitivity analysis were biomass composition (precursors and macromolecules), death constants, and the kinetic parameters of acetic acid secretion flux. These last input parameters, all obtained from other Clostridium butyricum cultures, were used to develop a population balance model (PBM). Finally, we simulated fed-batch cultures, predicting a final PDO production near to 66 g/L, almost three times the PDO predicted in the best batch culture.

CONCLUSIONS

We developed and validated a dynamic approach to predict PDO production using the iCbu641 GSM model and the previously proposed objective functions. This validated approach was used to propose a population model and then an increment in predictions of PDO production through fed-batch cultures. Therefore, this dynamic model could predict different scenarios, including its integration into downstream processes to predict technical-economic feasibilities and reducing the time and costs associated with experimentation.

Human gut microbe co-cultures have greater potential than monocultures for food waste remediation to commodity chemicals

Food waste represents an underutilized resource for commodity chemical generation. Constituents of the human gut microbiota that are already adapted to a food waste stream could be repurposed for useful chemical production. Industrial fermentations utilizing these microbes maintain organisms in isolation; however, microbial consortia offer an attractive alternative to monocultures in that metabolic interactions may result in more efficient processes with higher yields. Here we computationally assess the ability of co-cultures vs. monocultures to anaerobically convert a Western diet to commodity chemicals. The combination of genome-scale metabolic models with flux-balance analysis predicts that every organism analyzed can benefit from interactions with another microbe, as evidenced by increased biomass fluxes in co-culture vs. monoculture. Furthermore, microbe combinations result in emergent or increased commodity chemical production including butanol, methane, formaldehyde, propionate, hydrogen gas, and urea. These overproducing co-cultures are enriched for mutualistic and commensal interactions. Using Clostridium beijerinckii co-cultures as representative examples, models predict cross-fed metabolites will simultaneously modify multiple internal pathways, evident by different internal metabolic network structures. Differences in degree and betweenness centrality of hub precursor metabolites were correlated to C. beijerinckii metabolic outputs, and thus demonstrate the potential of co-cultures to differentially direct metabolisms to useful products.

Microbial Methylotrophic Metabolism: Recent Metabolic Modeling Efforts and Their Applications In Industrial Biotechnology

Developing methylotrophic bacteria into cell factories that meet the chemical demand of the future could be both economical and environmentally friendly. Methane is not only an abundant, low-cost resource but also a potent greenhouse gas, the capture of which could help to reduce greenhouse gas emissions. Rational strain design workflows rely on the availability of carefully combined knowledge often in the form of genome-scale metabolic models to construct high-producer organisms. In this review, the authors present the most recent genome-scale metabolic models in aerobic methylotrophy and their applications. Further, the authors present models for the study of anaerobic methanotrophy through reverse methanogenesis and suggest organisms that may be of interest for expanding one-carbon industrial biotechnology. Metabolic models of methylotrophs are scarce, yet they are important first steps toward rational strain-design in these organisms.

Genome-scale metabolic reconstruction and analysis for Clostridium kluyveri

Clostridium kluyveri is an anaerobic microorganism that is well-known for producing butyrate and hexanoate using ethanol and acetate. It is also an important bacterium in the production of Chinese strong flavour baijiu (SFB). To obtain a comprehensive understanding of its metabolism, a curated genome-scale metabolic model (GSMM) of C. kluyveri, including 708 genes, 994 reactions, and 804 metabolites, was constructed and named iCKL708. This model was used to simulate the growth of C. kluyveri on different carbon substrates and the results agreed well with the experimental data. The butyrate, pentanoate, and hexanoate biosynthesis pathways were also elucidated. Flux balance analysis indicated that the ratio of ethanol to acetate, as well as the uptake rate of carbon dioxide, affected hexanoate production. The GSMM iCKL708 described here provides a platform to further our understanding and exploration of the metabolic potential of C. kluyveri.

Progress towards platform chemical production using Clostridium autoethanogenum

Since 2013, there has been an explosion in the number of research articles published on Clostridium autoethanogenum, an acetogen capable of producing platform chemicals such as ethanol and 2,3-butanediol from greenhouse gases. However, no review focusing solely on C. autoethanogenum has appeared in the literature. This review outlines the research conducted into this organism in three broad categories (Enzymology, Genetics, and Systems Biology) and suggestions for future research are offered.

Diversity, Function, and Application of Clostridium in Chinese Strong Flavor Baijiu Ecosystem: A Review

Baijiu is a Chinese traditional distilled liquor with an annual yield over 13.12 million tons. Strong flavor baijiu (SFB) also called Luzhou-flavor liquor, takes account for > 70% of the total baijiu produced. SFB is produced by an open solid fermentation process with a complex microbial ecosystem. Clostridium is one of the most important microorganisms for the formation of the main flavor compounds of SFB, such as ethyl caproate. In this paper, we review current research progress on the Clostridium in the SFB ecosystem, focusing on the species diversity, physiological and metabolic features along with interspecies interactions. Systems biology approaches for the study of Clostridium from SFB ecosystems were discussed and explored. Furthermore, current applications of Clostridium in SFB production were discussed.

PRACTICAL APPLICATION

Strong flavor baijiu (SFB) accounts for more than 70% of total yield of Chinese baijiu, which exists for hundreds of years. Clostridium is common in SFB ecosystem and identified to be one of main contributors of flavor compounds in SFB. Study on the Clostridium from SFB ecosystem is not only helpful for the understanding of flavor compounds formation mechanism, but also the improvement of SFB quality. This study focuses on the current researches on the Clostridium species in SFB ecosystem, including the species diversity, physiological and metabolic features, and applications.

H2 drives metabolic rearrangements in gas-fermenting Clostridium autoethanogenum

BACKGROUND

The global demand for affordable carbon has never been stronger, and there is an imperative in many industrial processes to use waste streams to make products. Gas-fermenting acetogens offer a potential solution and several commercial gas fermentation plants are currently under construction. As energy limits acetogen metabolism, supply of H₂ should diminish substrate loss to CO₂ and facilitate production of reduced and energy-intensive products. However, the effects of H₂ supply on CO-grown acetogens have yet to be experimentally quantified under controlled growth conditions.

RESULTS

Here, we quantify the effects of H₂ supplementation by comparing growth on CO, syngas, and a high-H₂ CO gas mix using chemostat cultures of Clostridium autoethanogenum. Cultures were characterised at the molecular level using metabolomics, proteomics, gas analysis, and a genome-scale metabolic model. CO-limited chemostats operated at two steady-state biomass concentrations facilitated co-utilisation of CO and H₂. We show that H₂ supply strongly impacts carbon distribution with a fourfold reduction in substrate loss as CO₂ (61% vs. 17%) and a proportional increase of flux to ethanol (15% vs. 61%). Notably, H₂ supplementation lowers the molar acetate/ethanol ratio by fivefold. At the molecular level, quantitative proteome analysis showed no obvious changes leading to these metabolic rearrangements suggesting the involvement of post-translational regulation. Metabolic modelling showed that H₂ availability provided reducing power via H₂ oxidation and saved redox as cells reduced all the CO₂ to formate directly using H₂ in the Wood-Ljungdahl pathway. Modelling further indicated that the methylene-THF reductase reaction was ferredoxin reducing under all conditions. In combination with proteomics, modelling also showed that ethanol was synthesised through the acetaldehyde:ferredoxin oxidoreductase (AOR) activity.

CONCLUSIONS

Our quantitative molecular analysis revealed that H₂ drives rearrangements at several layers of metabolism and provides novel links between carbon, energy, and redox metabolism advancing our understanding of energy conservation in acetogens. We conclude that H₂ supply can substantially increase the efficiency of gas fermentation and thus the feed gas composition can be considered an important factor in developing gas fermentation-based bioprocesses.

A review of computational tools for design and reconstruction of metabolic pathways

Metabolic pathways reflect an organism's chemical repertoire and hence their elucidation and design have been a primary goal in metabolic engineering. Various computational methods have been developed to design novel metabolic pathways while taking into account several prerequisites such as pathway stoichiometry, thermodynamics, host compatibility, and enzyme availability. The choice of the method is often determined by the nature of the metabolites of interest and preferred host organism, along with computational complexity and availability of software tools. In this paper, we review different computational approaches used to design metabolic pathways based on the reaction network representation of the database (i.e., graph or stoichiometric matrix) and the search algorithm (i.e., graph search, flux balance analysis, or retrosynthetic search). We also put forth a systematic workflow that can be implemented in projects requiring pathway design and highlight current limitations and obstacles in computational pathway design.

Clostridium butyricum maximizes growth while minimizing enzyme usage and ATP production: metabolic flux distribution of a strain cultured in glycerol

BACKGROUND

The increase in glycerol obtained as a byproduct of biodiesel has encouraged the production of new industrial products, such as 1,3-propanediol (PDO), using biotechnological transformation via bacteria like Clostridium butyricum. However, despite the increasing role of Clostridium butyricum as a bio-production platform, its metabolism remains poorly modeled.

RESULTS

We reconstructed iCbu641, the first genome-scale metabolic (GSM) model of a PDO producer Clostridium strain, which included 641 genes, 365 enzymes, 891 reactions, and 701 metabolites. We found an enzyme expression prediction of nearly 84% after comparison of proteomic data with flux distribution estimation using flux balance analysis (FBA). The remaining 16% corresponded to enzymes directionally coupled to growth, according to flux coupling findings (FCF). The fermentation data validation also revealed different phenotype states that depended on culture media conditions; for example, Clostridium maximizes its biomass yield per enzyme usage under glycerol limitation. By contrast, under glycerol excess conditions, Clostridium grows sub-optimally, maximizing biomass yield while minimizing both enzyme usage and ATP production. We further evaluated perturbations in the GSM model through enzyme deletions and variations in biomass composition. The GSM predictions showed no significant increase in PDO production, suggesting a robustness to perturbations in the GSM model. We used the experimental results to predict that co-fermentation was a better alternative than iCbu641 perturbations for improving PDO yields.

CONCLUSIONS

The agreement between the predicted and experimental values allows the use of the GSM model constructed for the PDO-producing Clostridium strain to propose new scenarios for PDO production, such as dynamic simulations, thereby reducing the time and costs associated with experimentation.

Maintenance of ATP Homeostasis Triggers Metabolic Shifts in Gas-Fermenting Acetogens

Acetogens are promising cell factories for producing fuels and chemicals from waste feedstocks via gas fermentation, but quantitative characterization of carbon, energy, and redox metabolism is required to guide their rational metabolic engineering. Here, we explore acetogen gas fermentation using physiological, metabolomics, and transcriptomics data for Clostridium autoethanogenum steady-state chemostat cultures grown on syngas at various gas-liquid mass transfer rates. We observe that C. autoethanogenum shifts from acetate to ethanol production to maintain ATP homeostasis at higher biomass concentrations but reaches a limit at a molar acetate/ethanol ratio of ∼1. This regulatory mechanism eventually leads to depletion of the intracellular acetyl-CoA pool and collapse of metabolism. We accurately predict growth phenotypes using a genome-scale metabolic model. Modeling revealed that the methylene-THF reductase reaction was ferredoxin reducing. This work provides a reference dataset to advance the understanding and engineering of arguably the first carbon fixation pathway on Earth.

Development of a core Clostridium thermocellum kinetic metabolic model consistent with multiple genetic perturbations

BACKGROUND

Clostridium thermocellum is a Gram-positive anaerobe with the ability to hydrolyze and metabolize cellulose into biofuels such as ethanol, making it an attractive candidate for consolidated bioprocessing (CBP). At present, metabolic engineering in C. thermocellum is hindered due to the incomplete description of its metabolic repertoire and regulation within a predictive metabolic model. Genome-scale metabolic (GSM) models augmented with kinetic models of metabolism have been shown to be effective at recapitulating perturbed metabolic phenotypes.

RESULTS

In this effort, we first update a second-generation genome-scale metabolic model (iCth446) for C. thermocellum by correcting cofactor dependencies, restoring elemental and charge balances, and updating GAM and NGAM values to improve phenotype predictions. The iCth446 model is next used as a scaffold to develop a core kinetic model (k-ctherm118) of the C. thermocellum central metabolism using the Ensemble Modeling (EM) paradigm. Model parameterization is carried out by simultaneously imposing fermentation yield data in lactate, malate, acetate, and hydrogen production pathways for 19 measured metabolites spanning a library of 19 distinct single and multiple gene knockout mutants along with 18 intracellular metabolite concentration data for a Δgldh mutant and ten experimentally measured Michaelis-Menten kinetic parameters.

CONCLUSIONS

The k-ctherm118 model captures significant metabolic changes caused by (1) nitrogen limitation leading to increased yields for lactate, pyruvate, and amino acids, and (2) ethanol stress causing an increase in intracellular sugar phosphate concentrations (~1.5-fold) due to upregulation of cofactor pools. Robustness analysis of k-ctherm118 alludes to the presence of a secondary activity of ketol-acid reductoisomerase and possible regulation by valine and/or leucine pool levels. In addition, cross-validation and robustness analysis allude to missing elements in k-ctherm118 and suggest additional experiments to improve kinetic model prediction fidelity. Overall, the study quantitatively assesses the advantages of EM-based kinetic modeling towards improved prediction of C. thermocellum metabolism and develops a predictive kinetic model which can be used to design biofuel-overproducing strains.

Genome Editing in Clostridium saccharoperbutylacetonicum N1-4 with the CRISPR-Cas9 System

Clostridium saccharoperbutylacetonicum N1-4 is well known as a hyper-butanol-producing strain. However, the lack of genetic engineering tools hinders further elucidation of its solvent production mechanism and development of more robust strains. In this study, we set out to develop an efficient genome engineering system for this microorganism based on the clustered regularly interspaced short palindromic repeats (CRISPR) and CRISPR-associated 9 (CRISPR-Cas9) system. First, the functionality of the CRISPR-Cas9 system previously customized for Clostridium beijerinckii was evaluated in C. saccharoperbutylacetonicum by targeting pta and buk, two essential genes for acetate and butyrate production, respectively. pta and buk single and double deletion mutants were successfully obtained based on this system. However, the genome engineering efficiency was rather low (the mutation rate is <20%). Therefore, the efficiency was further optimized by evaluating various promoters for guide RNA (gRNA) expression. With promoter P _J23119 , we achieved a mutation rate of 75% for pta deletion without serial subculturing as suggested previously for C. beijerinckii Thus, this developed CRISPR-Cas9 system is highly desirable for efficient genome editing in C. saccharoperbutylacetonicum Batch fermentation results revealed that both the acid and solvent production profiles were altered due to the disruption of acid production pathways; however, neither acetate nor butyrate production was eliminated with the deletion of the corresponding gene. The butanol production, yield, and selectivity were improved in mutants, depending on the fermentation medium. In the pta buk double deletion mutant, the butanol production in P2 medium reached 19.0 g/liter, which is one of the highest levels ever reported from batch fermentations.IMPORTANCE An efficient CRISPR-Cas9 genome engineering system was developed for C. saccharoperbutylacetonicum N1-4. This paves the way for elucidating the solvent production mechanism in this hyper-butanol-producing microorganism and developing strains with desirable butanol-producing features. This tool can be easily adapted for use in closely related microorganisms. As also reported by others, here we demonstrated with solid data that the highly efficient expression of gRNA is the key factor determining the efficiency of CRISPR-Cas9 for genome editing. The protocol developed in this study can provide essential references for other researchers who work in the areas of metabolic engineering and synthetic biology. The developed mutants can be used as excellent starting strains for development of more robust ones for desirable solvent production.

Arginine deiminase pathway provides ATP and boosts growth of the gas-fermenting acetogen Clostridium autoethanogenum

Acetogens are attractive organisms for the production of chemicals and fuels from inexpensive and non-food feedstocks such as syngas (CO, CO₂ and H₂). Expanding their product spectrum beyond native compounds is dictated by energetics, particularly ATP availability. Acetogens have evolved sophisticated strategies to conserve energy from reduction potential differences between major redox couples, however, this coupling is sensitive to small changes in thermodynamic equilibria. To accelerate the development of strains for energy-intensive products from gases, we used a genome-scale metabolic model (GEM) to explore alternative ATP-generating pathways in the gas-fermenting acetogen Clostridium autoethanogenum. Shadow price analysis revealed a preference of C. autoethanogenum for nine amino acids. This prediction was experimentally confirmed under heterotrophic conditions. Subsequent in silico simulations identified arginine (ARG) as a key enhancer for growth. Predictions were experimentally validated, and faster growth was measured in media containing ARG (t_D~4h) compared to growth on yeast extract (t_D~9h). The growth-boosting effect of ARG was confirmed during autotrophic growth. Metabolic modelling and experiments showed that acetate production is nearly abolished and fast growth is realised by a three-fold increase in ATP production through the arginine deiminase (ADI) pathway. The involvement of the ADI pathway was confirmed by metabolomics and RNA-sequencing which revealed a ~500-fold up-regulation of the ADI pathway with an unexpected down-regulation of the Wood-Ljungdahl pathway. The data presented here offer a potential route for supplying cells with ATP, while demonstrating the usefulness of metabolic modelling for the discovery of native pathways for stimulating growth or enhancing energy availability.

Mathematical modelling of clostridial acetone-butanol-ethanol fermentation

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the ‘evolution’ of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists.

Metabolite labelling reveals hierarchies in Clostridium acetobutylicum that selectively channel carbons from sugar mixtures towards biofuel precursors

Clostridial fermentation of cellulose and hemicellulose relies on the cellular physiology controlling the metabolism of the cellulosic hexose sugar (glucose) with respect to the hemicellulosic pentose sugars (xylose and arabinose) and the hemicellulosic hexose sugars (galactose and mannose). Here, liquid chromatography–mass spectrometry and stable isotope tracers in Clostridium acetobutylicum were applied to investigate the metabolic hierarchy of glucose relative to the different hemicellulosic sugars towards two important biofuel precursors, acetyl‐coenzyme A and butyryl‐coenzyme A. The findings revealed constitutive metabolic hierarchies in C. acetobutylicum that facilitate (i) selective investment of hemicellulosic pentoses towards ribonucleotide biosynthesis without substantial investment into biofuel production and (ii) selective contribution of hemicellulosic hexoses through the glycolytic pathway towards biofuel precursors. Long‐term isotopic enrichment demonstrated incorporation of both pentose sugars into pentose‐phosphates and ribonucleotides in the presence of glucose. Kinetic labelling data, however, showed that xylose was not routed towards the biofuel precursors but there was minor contribution from arabinose. Glucose hierarchy over the hemicellulosic hexoses was substrate‐dependent. Kinetic labelling of hexose‐phosphates and triose‐phosphates indicated that mannose was assimilated but not galactose. Labelling of both biofuel precursors confirmed this metabolic preference. These results highlight important metabolic considerations in the accounting of clostridial mixed‐sugar utilization.

Recent applications of metabolomics to advance microbial biofuel production

Biofuel production from plant biomass is a promising source of renewable energy [1]. However, efficient biofuel production involves the complex task of engineering high-performance microorganisms, which requires detailed knowledge of metabolic function and regulation. This review highlights the potential of mass-spectrometry-based metabolomic analysis to guide rational engineering of biofuel-producing microbes. We discuss recent studies that apply knowledge gained from metabolomic analyses to increase the productivity of engineered pathways, characterize the metabolism of emerging biofuel producers, generate novel bioproducts, enable utilization of lignocellulosic feedstock, and improve the stress tolerance of biofuel producers.

Exploring complex cellular phenotypes and model-guided strain design with a novel genome-scale metabolic model of Clostridium thermocellum DSM 1313 implementing an adjustable cellulosome

BACKGROUND

Clostridium thermocellum is a gram-positive thermophile that can directly convert lignocellulosic material into biofuels. The metabolism of C. thermocellum contains many branches and redundancies which limit biofuel production, and typical genetic techniques are time-consuming. Further, the genome sequence of a genetically tractable strain C. thermocellum DSM 1313 has been recently sequenced and annotated. Therefore, developing a comprehensive, predictive, genome-scale metabolic model of DSM 1313 is desired for elucidating its complex phenotypes and facilitating model-guided metabolic engineering.

RESULTS

We constructed a genome-scale metabolic model iAT601 for DSM 1313 using the KEGG database as a scaffold and an extensive literature review and bioinformatic analysis for model refinement. Next, we used several sets of experimental data to train the model, e.g., estimation of the ATP requirement for growth-associated maintenance (13.5 mmol ATP/g DCW/h) and cellulosome synthesis (57 mmol ATP/g cellulosome/h). Using our tuned model, we investigated the effect of cellodextrin lengths on cell yields, and could predict in silico experimentally observed differences in cell yield based on which cellodextrin species is assimilated. We further employed our tuned model to analyze the experimentally observed differences in fermentation profiles (i.e., the ethanol to acetate ratio) between cellobiose- and cellulose-grown cultures and infer regulatory mechanisms to explain the phenotypic differences. Finally, we used the model to design over 250 genetic modification strategies with the potential to optimize ethanol production, 6155 for hydrogen production, and 28 for isobutanol production.

CONCLUSIONS

Our developed genome-scale model iAT601 is capable of accurately predicting complex cellular phenotypes under a variety of conditions and serves as a high-quality platform for model-guided strain design and metabolic engineering to produce industrial biofuels and chemicals of interest.

Industrial production of acetone and butanol by fermentation-100 years later

Microbial production of acetone and butanol was one of the first large-scale industrial fermentation processes of global importance. During the first part of the 20th century, it was indeed the second largest fermentation process, superseded in importance only by the ethanol fermentation. After a rapid decline after the 1950s, acetone-butanol-ethanol (ABE) fermentation has recently gained renewed interest in the context of biorefinery approaches for the production of fuels and chemicals from renewable resources. The availability of new methods and knowledge opens many new doors for industrial microbiology, and a comprehensive view on this process is worthwhile due to the new interest. This thematic issue of FEMS Microbiology Letters, dedicated to the 100th anniversary of the first industrial exploitation of Chaim Weizmann's ABE fermentation process, covers the main aspects of old and new developments, thereby outlining a model development in biotechnology. All major aspects of industrial microbiology are exemplified by this single process. This includes new technologies, such as the latest developments in metabolic engineering, the exploitation of biodiversity and discoveries of new regulatory systems such as for microbial stress tolerance, as well as technological aspects, such as bio- and down-stream processing.

Industrial production of acetone and butanol by fermentation—100 years later.