A genome-scale metabolic model of Methanococcus maripaludis S2 for CO2 capture and conversion to methane

Unraveling interspecies cross-feeding during anaerobic lignin degradation for bioenergy applications

Lignin, a major component of plant biomass, remains underutilized for renewable biofuels due to its complex and heterogeneous structure. Although investigations into depolymerizing lignin using fungi are well-established, studies of microbial pathways that enable anaerobic lignin breakdown linked with methanogenesis are limited. Through an enrichment cultivation approach with inoculation of freshwater sediment, we enriched a microbial community capable of producing methane during anaerobic lignin degradation. We reconstructed the near-complete population genomes of key lignin degraders and methanogens using metagenome-assembled genomes finally selected in this study (MAGs; 92 bacterial and 4 archaeal MAGs affiliated into 45 and 2 taxonomic groups, respectively). This study provides genetic evidence of microbial interdependence in conversion of lignin to methane in a syntrophic community. Metagenomic analysis revealed metabolic linkages, with lignin-hydrolyzing and/or fermentative bacteria such as the genera Alkalibaculum and Propionispora transforming lignin breakdown products into compounds such as acetate to feed methanogens (two archaeal MAGs classified into the genus Methanosarcina or UBA6 of the family Methanomassiliicoccaceae). Understanding the synergistic relationships between microbes that convert lignin could inform strategies for producing renewable bioenergy and treating aromatic-contaminated environments through anaerobic biodegradation processes. Overall, this study offers fundamental insights into complex community-level anaerobic lignin metabolism, highlighting hitherto unknown players, interactions, and pathways in this biotechnologically valuable process.

An integrated systems biology approach reveals differences in formate metabolism in the genus Methanothermobacter

Methanogenesis allows methanogenic archaea to generate cellular energy for their growth while producing methane. Thermophilic hydrogenotrophic species of the genus Methanothermobacter have been recognized as robust biocatalysts for a circular carbon economy and are already applied in power-to-gas technology with biomethanation, which is a platform to store renewable energy and utilize captured carbon dioxide. Here, we generated curated genome-scale metabolic reconstructions for three Methanothermobacter strains and investigated differences in the growth performance of these same strains in chemostat bioreactor experiments with hydrogen and carbon dioxide or formate as substrates. Using an integrated systems biology approach, we identified differences in formate anabolism between the strains and revealed that formate anabolism influences the diversion of carbon between biomass and methane. This finding, together with the omics datasets and the metabolic models we generated, can be implemented for biotechnological applications of Methanothermobacter in power-to-gas technology, and as a perspective, for value-added chemical production.

A predicted CRISPR-mediated symbiosis between uncultivated archaea

CRISPR-Cas systems defend prokaryotic cells from invasive DNA of viruses, plasmids and other mobile genetic elements. Here, we show using metagenomics, metatranscriptomics and single-cell genomics that CRISPR systems of widespread, uncultivated archaea can also target chromosomal DNA of archaeal episymbionts of the DPANN superphylum. Using meta-omics datasets from Crystal Geyser and Horonobe Underground Research Laboratory, we find that CRISPR spacers of the hosts Candidatus Altiarchaeum crystalense and Ca. A. horonobense, respectively, match putative essential genes in their episymbionts' genomes of the genus Ca. Huberiarchaeum and that some of these spacers are expressed in situ. Metabolic interaction modelling also reveals complementation between host-episymbiont systems, on the basis of which we propose that episymbionts are either parasitic or mutualistic depending on the genotype of the host. By expanding our analysis to 7,012 archaeal genomes, we suggest that CRISPR-Cas targeting of genomes associated with symbiotic archaea evolved independently in various archaeal lineages.

Methyl-Based Methanogenesis: an Ecological and Genomic Review

Methyl-based methanogenesis is one of three broad categories of archaeal anaerobic methanogenesis, including both the methyl dismutation (methylotrophic) pathway and the methyl-reducing (also known as hydrogen-dependent methylotrophic) pathway. Methyl-based methanogenesis is increasingly recognized as an important source of methane in a variety of environments. Here, we provide an overview of methyl-based methanogenesis research, including the conditions under which methyl-based methanogenesis can be a dominant source of methane emissions, experimental methods for distinguishing different pathways of methane production, molecular details of the biochemical pathways involved, and the genes and organisms involved in these processes. We also identify the current gaps in knowledge and present a genomic and metagenomic survey of methyl-based methanogenesis genes, highlighting the diversity of methyl-based methanogens at multiple taxonomic levels and the widespread distribution of known methyl-based methanogenesis genes and families across different environments.

CRISPR-Cas9 Toolkit for Genome Editing in an Autotrophic CO2-Fixing Methanogenic Archaeon

The CRISPR-Cas9 system is a robust genome editing tool that is widely applied in eukaryotes and bacteria. However, use of this technique has only been developed for one species of Archaea, a domain of life ranking in parallel with Eukarya and Bacteria. In this study, we applied the CRISPR-Cas9 genome editing technique to Methanococcus maripaludis, an autotrophic and hydrogenotrophic methanogenic archaeon with a remarkably polyploid genome comprising up to ~55 chromosomal copies per cell. An editing plasmid was designed that encodes small guide RNA (sgRNA), Cas9 protein and an ~1-kb repair template (donor). Highly efficient (75% to 100%) and precise genome editing was achieved following one-step transformation. Significantly, the Cas9-based system efficiently deleted one or two genes and a large DNA fragment (~9 kb) and even synchronously deleted 13 genes located at three loci in all chromosomal copies of M. maripaludis. Moreover, precise in situ genome modifications, such as gene tagging and multiple- and even single-nucleotide mutagenesis, were also introduced with high efficiency. Further, as a proof of concept, precise mutagenesis at the nucleotide level allowed the engineering of both transcriptional and translational activities. Mutations were introduced into an archaeal promoter BRE (transcription factor B [TFB] recognition element), a terminator U-tract region, and a gene coding region. Stop codon introduction into a gene through single-nucleotide substitution shut down its expression, providing an alternative strategy for gene inactivation. In conclusion, the robust CRISPR-Cas9 genetic toolkit developed in this investigation greatly facilitates the application of M. maripaludis as a model system in the study of archaeal biology and biotechnology development, particularly CO2-based biotechnologies. IMPORTANCE Archaea are prokaryotes with intriguing biological characteristics. They possess bacterial cell structures but eukaryotic homologous information processing machinery and eukaryotic featured proteins. Archaea also display excellent adaptability to extreme environments and play pivotal roles in ecological processes, thus exhibiting valuable biotechnological potential. However, the in-depth understanding and practical application of archaea are much lagging, because only a minority of pure cultures are available, and even worse, very few can be genetically manipulated. This work developed CRISPR-Cas9-based genome editing technology in Methanococcus maripaludis, a CO2-fixing methanogenic archaeon. The CRISPR-Cas9 approach developed in this study provides an elegant and efficient genome editing toolkit that can be applied in the knockout of single or multiple genes, in situ gene tagging, multiple- or single-nucleotide mutagenesis, and inactivation of gene expression by introduction of stop codons. The successful development of the CRISPR-Cas9 toolkit will facilitate the application of M. maripaludis in archaeal biology research and biotechnology development, particularly CO2-derived biotechnologies.

Genome-Scale Metabolic Modeling Enables In-Depth Understanding of Big Data

Genome-scale metabolic models (GEMs) enable the mathematical simulation of the metabolism of archaea, bacteria, and eukaryotic organisms. GEMs quantitatively define a relationship between genotype and phenotype by contextualizing different types of Big Data (e.g., genomics, metabolomics, and transcriptomics). In this review, we analyze the available Big Data useful for metabolic modeling and compile the available GEM reconstruction tools that integrate Big Data. We also discuss recent applications in industry and research that include predicting phenotypes, elucidating metabolic pathways, producing industry-relevant chemicals, identifying drug targets, and generating knowledge to better understand host-associated diseases. In addition to the up-to-date review of GEMs currently available, we assessed a plethora of tools for developing new GEMs that include macromolecular expression and dynamic resolution. Finally, we provide a perspective in emerging areas, such as annotation, data managing, and machine learning, in which GEMs will play a key role in the further utilization of Big Data.

Tuning Gene Expression by Phosphate in the Methanogenic Archaeon Methanococcus maripaludis

Methanococcus maripaludis is a rapidly growing, hydrogenotrophic, and genetically tractable methanogen with unique capabilities to convert formate and CO₂ to CH₄. The existence of genome-scale metabolic models and an established, robust system for both large-scale and continuous cultivation make it amenable for industrial applications. However, the lack of molecular tools for differential gene expression has hindered its application as a microbial cell factory to produce biocatalysts and biochemicals. In this study, a library of differentially regulated promoters was designed and characterized based on the pst promoter, which responds to the inorganic phosphate concentration in the growth medium. Gene expression increases by 4- to 6-fold when the medium phosphate drops to growth-limiting concentrations. Hence, this regulated system decouples growth from heterologous gene expression without the need for adding an inducer. The minimal pst promoter is identified and contains a conserved AT-rich region, a factor B recognition element, and a TATA box for phosphate-dependent regulation. Rational changes to the factor B recognition element and start codon had no significant impact on expression; however, changes to the transcription start site and the 5' untranslated region resulted in the differential protein production with regulation remaining intact. Compared to a previous expression system based upon the histone promoter, this regulated expression system resulted in significant improvements in the expression of a key methanogenic enzyme complex, methyl-coenzyme M reductase, and the potentially toxic arginine methyltransferase MmpX.

Insights into Metatranscriptome, and CAZymes of Buffalo Rumen Supplemented with Blend of Essential Oils

The aim of this study was to investigate the rumen microbial diversity and functionality in buffaloes fed with a blend of essential oils (BEO) using LSD switch over design. The BEO consisting of blend of Trachyspermum copticum (Ajwain) oil, Cymbopogon citratus (lemon grass) oil and Syzygium aromaticum (clove bud) oleoresin mixed in equal proportion, was fed at the rate of 0, 0.75 and 1.5 ml/100 kg of body weight in 0 (control), 0.75 and 1.5 groups, respectively. The metatranscriptomic libraries of the rumen microbiome were represented by 7 domains, 84 phyla, 64 archeal genera and 663 bacterial genera with Bacteroidetes and Firmicutes constituting 80% of phyla abundance irrespective of feeding regime. Methanogenic archaea was represented by 22 phyla with Methanobrevibacter as the major genus. BEO feeding reduced the abundance of Methanococcus and Thermoplasma (P < 0.05) at all levels. The results revealed that the feeding of BEO shifted the archeal and bacterial population at very low magnitude. The study explored the vast diversity of buffalo rumen bacteria and archaea, and the diverse wealth of rumen enzymes (CAZymes), which revealed that a major part of CAZymes comes from the less known rumen microbes indicating alternative paths of fiber degradation along with the very well known ones.

Comparative analysis of differential proteome-wide protein-protein interaction network of Methanobrevibacter ruminantium M1

A proteome-wide protein-protein interaction (PPI) network of Methanobrevibacter ruminantium M1 (MRU), a predominant rumen methanogen, was constructed from its metabolic genes using a gene neighborhood algorithm and then compared with closely related rumen methanogens Using proteome-wide PPI approach, we constructed network encompassed 2194 edges and 637 nodes interacting with 634 genes. Network quality and robustness of functional modules were assessed with gene ontology terms. A structure-function-metabolism mapping for each protein has been carried out with efforts to extract experimental PPI concomitant information from the literature. The results of our study revealed that some topological properties of its network were robust for sharing homologous protein interactions across heterotrophic and hydrogenotrophic methanogens. MRU proteome has shown to establish many PPI sub-networks for associated metabolic subsystems required to survive in the rumen environment. MRU genome found to share interacting proteins from its PPI network involved in specific metabolic subsystems distinct to heterotrophic and hydrogenotrophic methanogens. Across these proteomes, the interacting proteins from differential PPI networks were shared in common for the biosynthesis of amino acids, nucleosides, and nucleotides and energy metabolism in which more fractions of protein pairs shared with Methanosarcina acetivorans. Our comparative study expedites our knowledge to understand a complex proteome network associated with typical metabolic subsystems of MRU and to improve its genome-scale reconstruction in the future.

The GC Content as a Main Factor Shaping the Amino Acid Usage During Bacterial Evolution Process

Understanding how proteins evolve is important, and the order of amino acids being recruited into the genetic codons was found to be an important factor shaping the amino acid composition of proteins. The latest work about the last universal common ancestor (LUCA) makes it possible to determine the potential factors shaping amino acid compositions during evolution. Those LUCA genes/proteins from Methanococcus maripaludis S2, which is one of the possible LUCA, were investigated. The evolutionary rates of these genes positively correlate with GC contents with P-value significantly lower than 0.05 for 94% homologous genes. Linear regression results showed that compositions of amino acids coded by GC-rich codons positively contribute to the evolutionary rates, while these amino acids tend to be gained in GC-rich organisms according to our results. The first principal component correlates with the GC content very well. The ratios of amino acids of the LUCA proteins coded by GC rich codons positively correlate with the GC content of different bacteria genomes, while the ratios of amino acids coded by AT rich codons negatively correlate with the increase of GC content of genomes. Next, we found that the recruitment order does correlate with the amino acid compositions, but gain and loss in codons showed newly recruited amino acids are not significantly increased along with the evolution. Thus, we conclude that GC content is a primary factor shaping amino acid compositions. GC content shapes amino acid composition to trade off the cost of amino acids with bases, which could be caused by the energy efficiency.

Rare Biosphere Archaea Assimilate Acetate in Precambrian Terrestrial Subsurface at 2.2 km Depth

The deep biosphere contains a large portion of the total microbial communities on Earth, but little is known about the carbon sources that support deep life. In this study, we used Stable Isotope Probing (SIP) and high throughput amplicon sequencing to identify the acetate assimilating microbial communities at 2260 m depth in the bedrock of Outokumpu, Finland. The long-term and short-term effects of acetate on the microbial communities were assessed by DNA-targeted SIP and RNA targeted cell activation. The microbial communities reacted within hours to the amended acetate. Archaeal taxa representing the rare biosphere at 2260 m depth were identified and linked to the cycling of acetate, and were shown to have an impact on the functions and activity of the microbial communities in general through small key carbon compounds. The major archaeal lineages identified to assimilate acetate and metabolites derived from the labelled acetate were Methanosarcina spp., Methanococcus spp., Methanolobus spp., and unclassified Methanosarcinaceae. These archaea have previously been detected in the Outokumpu deep subsurface as minor groups. Nevertheless, their involvement in the assimilation of acetate and secretion of metabolites derived from acetate indicated an important role in the supporting of the whole community in the deep subsurface, where carbon sources are limited.

Methanobacterium formicicum as a target rumen methanogen for the development of new methane mitigation interventions: A review

Methanobacterium formicicum (Methanobacteriaceae family) is an endosymbiotic methanogenic Archaean found in the digestive tracts of ruminants and elsewhere. It has been significantly implicated in global CH₄ emission during enteric fermentation processes. In this review, we discuss current genomic and metabolic aspects of this microorganism for the purpose of the discovery of novel veterinary therapeutics. This microorganism encompasses a typical H₂ scavenging system, which facilitates a metabolic symbiosis across the H₂ producing cellulolytic bacteria and fumarate reducing bacteria. To date, five genome-scale metabolic models (iAF692, iMG746, iMB745, iVS941 and iMM518) have been developed. These metabolic reconstructions revealed the cellular and metabolic behaviors of methanogenic archaea. The characteristics of its symbiotic behavior and metabolic crosstalk with competitive rumen anaerobes support understanding of the physiological function and metabolic fate of shared metabolites in the rumen ecosystem. Thus, systems biological characterization of this microorganism may provide a new insight to realize its metabolic significance for the development of a healthy microbiota in ruminants. An in-depth knowledge of this microorganism may allow us to ensure a long term sustainability of ruminant-based agriculture.

The physiological effect of heavy metals and volatile fatty acids on Methanococcus maripaludis S2

BACKGROUND

Methanogenic archaea are of importance to the global C-cycle and to biological methane (CH₄) production through anaerobic digestion and pure culture. Here, the individual and combined effects of copper (Cu), zinc (Zn), acetate, and propionate on the metabolism of the autotrophic, hydrogenotrophic methanogen Methanococcus maripaludis S2 were investigated. Cu, Zn, acetate, and propionate may interfere directly and indirectly with the acetyl-CoA synthesis and biological CH₄ production. Thus, these compounds can compromise or improve the performance of M. maripaludis, an organism which can be applied as biocatalyst in the carbon dioxide (CO₂)-based biological CH₄ production (CO₂-BMP) process or of methanogenic organisms applied in anaerobic digestion.

RESULTS

Here, we show that Cu concentration of 1.9 µmol L^-1 reduced growth of M. maripaludis, whereas 4.4 and 6.3 µmol L^-1 of Cu even further retarded biomass production. However, 1.0 mmol L^-1 of Zn enhanced growth, but at Zn concentrations > 2.4 mmol L^-1 no growth could be observed. When both, Cu and Zn, were supplemented to the medium, growth and CH₄ production could even be observed at the highest tested concentration of Cu (6.3 µmol L^-1). Hence, it seems that the addition of 1 mmol L^-1 of Zn enhanced the ability of M. maripaludis to counteract the toxic effect of Cu. The physiological effect to rising concentrations of acetate (12.2, 60.9, 121.9 mmol L^-1) and/or propionate (10.3, 52.0, 104.1 mmol L^-1) was also investigated. When instead of acetate 10.3 mmol L^-1 propionate was provided in the growth medium, M. maripaludis could grow without reduction of the specific growth rate (µ) or the specific CH₄ productivity (qCH₄). A combination of inorganic and/or organic compounds resulted in an increase of µ and qCH₄ for Zn/Cu and Zn/acetate beyond the values that were observed if only the individual concentrations of Zn, Cu, acetate were used.

CONCLUSIONS

Our study sheds light on the physiological effect of VFAs and heavy metals on M. maripaludis. Differently from µ and qCH₄, MER was not influenced by the presence of these compounds. This indicated that each of these compounds directly interacted with the C-fixation machinery of M. maripaludis. Until now, the uptake of VFAs other than acetate was not considered to enhance growth and CH₄ production of methanogens. The finding of propionate uptake by M. maripaludis is important for the interpretation of VFA cycling in anaerobic microenvironments. Due to the importance of methanogens in natural and artificial anaerobic environments, our results help to enhance the understanding the physiological and biotechnological importance with respect to anaerobic digestion, anaerobic wastewater treatment, and CO₂-BMP. Finally, we propose a possible mechanism for acetate uptake into M. maripaludis supported by in silico analyses.

Constraint-based metabolic modelling of marine microbes and communities

Constraint-based metabolic modelling (CBMM) consists in the use of computational methods and tools to perform genome-scale simulations and predict metabolic features at the whole cellular level. This approach is rapidly expanding in microbiology, as it combines reliable predictive abilities with conceptually and technically simple frameworks. Among the possible outcomes of CBMM, the capability to i) guide a focused planning of metabolic engineering experiments and ii) provide a system-level understanding of (single or community-level) microbial metabolic circuits also represent primary aims in present-day marine microbiology. In this work we briefly introduce the theoretical formulation behind CBMM and then review the most recent and effective case studies of CBMM of marine microbes and communities. Also, the emerging challenges and possibilities in the use of such methodologies in the context of marine microbiology/biotechnology are discussed. As the potential applications of CBMM have a very broad range, the topics presented in this review span over a large plethora of fields such as ecology, biotechnology and evolution.

IMGMD: A platform for the integration and standardisation of In silico Microbial Genome-scale Metabolic Models

Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.

Genome-Scale Metabolic Modeling of Archaea Lends Insight into Diversity of Metabolic Function

Decades of biochemical, bioinformatic, and sequencing data are currently being systematically compiled into genome-scale metabolic reconstructions (GEMs). Such reconstructions are knowledge-bases useful for engineering, modeling, and comparative analysis. Here we review the fifteen GEMs of archaeal species that have been constructed to date. They represent primarily members of the Euryarchaeota with three-quarters comprising representative of methanogens. Unlike other reviews on GEMs, we specially focus on archaea. We briefly review the GEM construction process and the genealogy of the archaeal models. The major insights gained during the construction of these models are then reviewed with specific focus on novel metabolic pathway predictions and growth characteristics. Metabolic pathway usage is discussed in the context of the composition of each organism's biomass and their specific energy and growth requirements. We show how the metabolic models can be used to study the evolution of metabolism in archaea. Conservation of particular metabolic pathways can be studied by comparing reactions using the genes associated with their enzymes. This demonstrates the utility of GEMs to evolutionary studies, far beyond their original purpose of metabolic modeling; however, much needs to be done before archaeal models are as extensively complete as those for bacteria.

Exploring Hydrogenotrophic Methanogenesis: a Genome Scale Metabolic Reconstruction of Methanococcus maripaludis

Hydrogenotrophic methanogenesis occurs in multiple environments, ranging from the intestinal tracts of animals to anaerobic sediments and hot springs. Energy conservation in hydrogenotrophic methanogens was long a mystery; only within the last decade was it reported that net energy conservation for growth depends on electron bifurcation. In this work, we focus on Methanococcus maripaludis, a well-studied hydrogenotrophic marine methanogen. To better understand hydrogenotrophic methanogenesis and compare it with methylotrophic methanogenesis that utilizes oxidative phosphorylation rather than electron bifurcation, we have built iMR539, a genome scale metabolic reconstruction that accounts for 539 of the 1,722 protein-coding genes of M. maripaludis strain S2. Our reconstructed metabolic network uses recent literature to not only represent the central electron bifurcation reaction but also incorporate vital biosynthesis and assimilation pathways, including unique cofactor and coenzyme syntheses. We show that our model accurately predicts experimental growth and gene knockout data, with 93% accuracy and a Matthews correlation coefficient of 0.78. Furthermore, we use our metabolic network reconstruction to probe the implications of electron bifurcation by showing its essentiality, as well as investigating the infeasibility of aceticlastic methanogenesis in the network. Additionally, we demonstrate a method of applying thermodynamic constraints to a metabolic model to quickly estimate overall free-energy changes between what comes in and out of the cell. Finally, we describe a novel reconstruction-specific computational toolbox we created to improve usability. Together, our results provide a computational network for exploring hydrogenotrophic methanogenesis and confirm the importance of electron bifurcation in this process.

IMPORTANCE

Understanding and applying hydrogenotrophic methanogenesis is a promising avenue for developing new bioenergy technologies around methane gas. Although a significant portion of biological methane is generated through this environmentally ubiquitous pathway, existing methanogen models portray the more traditional energy conservation mechanisms that are found in other methanogens. We have constructed a genome scale metabolic network of Methanococcus maripaludis that explicitly accounts for all major reactions involved in hydrogenotrophic methanogenesis. Our reconstruction demonstrates the importance of electron bifurcation in central metabolism, providing both a window into hydrogenotrophic methanogenesis and a hypothesis-generating platform to fuel metabolic engineering efforts.

Genome-scale reconstruction of the metabolic network in Pseudomonas stutzeri A1501

Pseudomonas stutzeri A1501 is an endophytic bacterium capable of nitrogen fixation. This strain has been isolated from the rice rhizosphere and provides the plant with fixed nitrogen and phytohormones. These interesting features encouraged us to study the metabolism of this microorganism at the systems-level. In this work, we present the first genome-scale metabolic model (iPB890) for P. stutzeri, involving 890 genes, 1135 reactions, and 813 metabolites. A combination of automatic and manual approaches was used in the reconstruction process. Briefly, using the metabolic networks of Pseudomonas aeruginosa and Pseudomonas putida as templates, a draft metabolic network of P. stutzeri was reconstructed. Then, the draft network was driven through an iterative and curative process of gap filling. In the next step, the model was evaluated using different experimental data such as specific growth rate, Biolog substrate utilization data and other experimental observations. In most of the evaluation cases, the model was successful in correctly predicting the cellular phenotypes. Thus, we posit that the iPB890 model serves as a suitable platform to explore the metabolism of P. stutzeri.

Engineering the Autotroph Methanococcus maripaludis for Geraniol Production

The rapid autotrophic growth of the methanogenic archaeon Methanococcus maripaludis on H2 and CO2 makes it an attractive microbial chassis to inexpensively produce biochemicals. To explore this potential, a synthetic gene encoding geraniol synthase (GES) derived from Ocimum basilicum was cloned into a M. maripaludis expression vector under selection for puromycin resistance. Recombinant expression of GES in M. maripaludis during autotrophic growth on H2/CO2 or formate yielded geraniol at 2.8 and 4.0 mg g(-1) of dry weight, respectively. The yield of geraniol decreased 2-3-fold when organic carbon sources were added to stimulate heterotrophic growth. In the absence of puromycin, geraniol production during autotrophic growth on formate increased to 4.6 mg g(-1) of dry weight. A conceptual model centered on the autotrophic acetyl coenzyme A biosynthetic pathway identified strategies to divert more autotrophic carbon flux to geraniol production.

Metabolic processes of Methanococcus maripaludis and potential applications

Methanococcus maripaludis is a rapidly growing, fully sequenced, genetically tractable model organism among hydrogenotrophic methanogens. It has the ability to convert CO2 and H2 into a useful cleaner energy fuel (CH4). In fact, this conversion enhances in the presence of free nitrogen as the sole nitrogen source due to prolonged cell growth. Given the global importance of GHG emissions and climate change, diazotrophy can be attractive for carbon capture and utilization applications from appropriately treated flue gases, where surplus hydrogen is available from renewable electricity sources. In addition, M. maripaludis can be engineered to produce other useful products such as terpenoids, hydrogen, methanol, etc. M. maripaludis with its unique abilities has the potential to be a workhorse like Escherichia coli and S. cerevisiae for fundamental and experimental biotechnology studies. More than 100 experimental studies have explored different specific aspects of the biochemistry and genetics of CO2 and N2 fixation by M. maripaludis. Its genome-scale metabolic model (iMM518) also exists to study genetic perturbations and complex biological interactions. However, a comprehensive review describing its cell structure, metabolic processes, and methanogenesis is still lacking in the literature. This review fills this crucial gap. Specifically, it integrates distributed information from the literature to provide a complete and detailed view for metabolic processes such as acetyl-CoA synthesis, pyruvate synthesis, glycolysis/gluconeogenesis, reductive tricarboxylic acid (RTCA) cycle, non-oxidative pentose phosphate pathway (NOPPP), nitrogen metabolism, amino acid metabolism, and nucleotide biosynthesis. It discusses energy production via methanogenesis and its relation to metabolism. Furthermore, it reviews taxonomy, cell structure, culture/storage conditions, molecular biology tools, genome-scale models, and potential industrial and environmental applications. Through the discussion, it develops new insights and hypotheses from experimental and modeling observations, and identifies opportunities for further research and applications.

Flux measurements and maintenance energy for carbon dioxide utilization by Methanococcus maripaludis

BACKGROUND

The rapidly growing mesophilic methanogen Methanococcus maripaludis S2 has a unique ability to consume both CO2 and N2, the main components of a flue gas, and produce methane with H2 as the electron donor. The existing literature lacks experimental measurements of CO2 and H2 uptake rates and CH4 production rates on M. maripaludis. Furthermore, it lacks estimates of maintenance energies for use with genome-scale models. In this paper, we performed batch culture experiments on M. maripaludis S2 using CO2 as the sole carbon substrate to quantify three key extracellular fluxes (CO2, H2, and CH4) along with specific growth rates. For precise computation of these fluxes from experimental measurements, we developed a systematic process simulation approach. Then, using an existing genome-scale model, we proposed an optimization procedure to estimate maintenance energy parameters: growth associated maintenance (GAM) and non-growth associated maintenance (NGAM).

RESULTS

The measured extracellular fluxes for M. maripaludis showed excellent agreement with in silico predictions from a validated genome-scale model (iMM518) for NGAM = 7.836 mmol/gDCW/h and GAM = 27.14 mmol/gDCW. M. maripaludis achieved a CO2 to CH4 conversion yield of 70-95 % and a growth yield of 3.549 ± 0.149 g DCW/mol CH4 during the exponential phase. The ATP gain of 0.35 molATP/molCH4 for M. maripaludis, computed using NGAM, is in the acceptable range of 0.3-0.7 mol ATP/molCH4 reported for methanogens. Interestingly, the uptake distribution of amino acids, quantified using iMM518, confirmed alanine to be the most preferred amino acids for growth and methanogenesis.

CONCLUSIONS

This is the first study to report experimental gas consumption and production rates for the growth of M. maripaludis on CO2 and H2 in minimal media. A systematic process simulation and optimization procedure was successfully developed to precisely quantify extracellular fluxes along with cell growth and maintenance energy parameters. Our growth yields, ATP gain, and energy parameters fall within acceptable ranges known in the literature for hydrogenotrophic methanogens.

Acidogenic fermentation of food waste for volatile fatty acid production with co-generation of biohydrogen

Fermentation experiments were designed to elucidate the functional role of the redox microenvironment on volatile fatty acid (VFA, short chain carboxylic acid) production and co-generation of biohydrogen (H2). Higher VFA productivity was observed at pH 10 operation (6.3g/l) followed by pH 9, pH 6, pH 5, pH 7, pH 8 and pH 11 (3.5 g/l). High degree of acidification, good system buffering capacity along with co-generation of higher H2 production from food waste was also noticed at alkaline condition. Experiments illustrated the role of initial pH on carboxylic acids synthesis. Alkaline redox conditions assist solubilization of carbohydrates, protein and fats and also suppress the growth of methanogens. Among the carboxylic acids, acetate fraction was higher at alkaline condition than corresponding neutral or acidic operations. Integrated process of VFA production from waste with co-generation of H2 can be considered as a green and sustainable platform for value-addition.

Perturbation Experiments: Approaches for Metabolic Pathway Analysis in Bioreactors

In the last decades, targeted metabolic engineering of microbial cells has become one of the major tools in bioprocess design and optimization. For successful application, a detailed knowledge is necessary about the relevant metabolic pathways and their regulation inside the cells. Since in vitro experiments cannot display process conditions and behavior properly, process data about the cells' metabolic state have to be collected in vivo. For this purpose, special techniques and methods are necessary. Therefore, most techniques enabling in vivo characterization of metabolic pathways rely on perturbation experiments, which can be divided into dynamic and steady-state approaches. To avoid any process disturbance, approaches which enable perturbation of cell metabolism in parallel to the continuing production process are reasonable. Furthermore, the fast dynamics of microbial production processes amplifies the need of parallelized data generation. These points motivate the development of a parallelized approach for multiple metabolic perturbation experiments outside the operating production reactor. An appropriate approach for in vivo characterization of metabolic pathways is presented and applied exemplarily to a microbial L-phenylalanine production process on a 15 L-scale.