A unified compendium of prokaryotic and viral genomes from over 300 anaerobic digestion microbiomes.

BACKGROUND: The anaerobic digestion process degrades organic matter into simpler compounds and occurs in strictly anaerobic and microaerophilic environments. The process is carried out by a diverse community of microorganisms where each species has a unique role and it has relevant biotechnological applications since it is used for biogas production. Some aspects of the microbiome, including its interaction with phages, remains still unclear: a better comprehension of the community composition and role of each species is crucial for a cured understanding of the carbon cycle in anaerobic systems and improving biogas production. RESULTS: The primary objective of this study was to expand our understanding on the anaerobic digestion microbiome by jointly analyzing its prokaryotic and viral components. By integrating 192 additional datasets into a previous metagenomic database, the binning process generated 11,831 metagenome-assembled genomes from 314 metagenome samples published between 2014 and 2022, belonging to 4,568 non-redundant species based on ANI calculation and quality verification. CRISPR analysis on these genomes identified 76 archaeal genomes with active phage interactions. Moreover, single-nucleotide variants further pointed to archaea as the most critical members of the community. Among the MAGs, two methanogenic archaea, Methanothrix sp. 43zhSC_152 and Methanoculleus sp. 52maCN_3230, had the highest number of SNVs, with the latter having almost double the density of most other MAGs. CONCLUSIONS: This study offers a more comprehensive understanding of microbial community structures that thrive at different temperatures. The findings revealed that the fraction of archaeal species characterized at the genome level and reported in public databases is higher than that of bacteria, although still quite limited. The identification of shared spacers between phages and microbes implies a history of phage-bacterial interactions, and specifically lysogenic infections. A significant number of SNVs were identified, primarily comprising synonymous and nonsynonymous variants. Together, the findings indicate that methanogenic archaea are subject to intense selective pressure and suggest that genomic variants play a critical role in the anaerobic digestion process. Overall, this study provides a more balanced and diverse representation of the anaerobic digestion microbiota in terms of geographic location, temperature range and feedstock utilization.

APOLLO: A genome-scale metabolic reconstruction resource of 247,092 diverse human microbes spanning multiple continents, age groups, and body sites.

Computational modelling of microbiome metabolism has proved instrumental to catalyse our understanding of diet-host-microbiome-disease interactions through the interrogation of mechanistic, strain- and molecule-resolved metabolic models. We present APOLLO, a resource of 247,092 human microbial genome-scale metabolic reconstructions spanning 19 phyla and accounting for microbial genomes from 34 countries, all age groups, and five body sites. We explored the metabolic potential of the reconstructed strains and developed a machine learning classifier able to predict with high accuracy the taxonomic strain assignments. We also built 14,451 sample-specific microbial community models, which could be stratified by body site, age, and disease states. Finally, we predicted faecal metabolites enriched or depleted in gut microbiomes of people with Crohn's disease, Parkinson disease, and undernourished children. APOLLO is compatible with the human whole-body models, and thus, provide unprecedented opportunities for systems-level modelling of personalised host-microbiome co-metabolism. APOLLO will be freely available under https://www.vmh.life/.

Modelling of microbial interactions in anaerobic digestion: from black to glass box.

Anaerobic and microaerophilic environments are pervasive in nature, providing essential contributions to the maintenance of human health, biogeochemical cycles and the Earth's climate. These ecological niches are characterised by low free oxygen and oxidants, or lack thereof. Under these conditions, interactions between species are essential for supporting the growth of syntrophic species and maintaining thermodynamic feasibility of anaerobic fermentation. Kinetic models provide a simplified view of complex metabolic networks, while genome-scale metabolic models and flux-balance analysis (FBA) aim to unravel these systems as a whole. The target of this review is to outline the main similarities, differences and challenges associated with kinetic and metabolic modelling, and describe state-of-the-art modelling practices for studying syntrophies in the anaerobic digestion (AD) case study.

Longitudinal flux balance analyses of a patient with episodic colonic inflammation reveals microbiome metabolic dynamics.

We report the first use of constraint-based microbial community modeling on a single individual with episodic inflammation of the gastrointestinal tract, who has a well documented set of colonic inflammatory biomarkers, as well as metagenomically-sequenced fecal time series covering seven dates over 16 months. Between the first two time steps the individual was treated with both steroids and antibiotics. Our methodology enabled us to identify numerous time-correlated microbial species and metabolites. We found that the individual's dynamical microbial ecology in the disease state led to time-varying in silico overproduction, compared to healthy controls, of more than 24 biologically important metabolites, including methane, thiamine, formaldehyde, trimethylamine N-oxide, folic acid, serotonin, histamine, and tryptamine. The microbe-metabolite contribution analysis revealed that some Dialister species changed metabolic pathways according to the inflammation phases. At the first time point, characterized by the highest levels of serum (complex reactive protein) and fecal (calprotectin) inflammation biomarkers, they produced L-serine or formate. The production of the compounds, through a cascade effect, was mediated by the interaction with pathogenic Escherichia coli strains and Desulfovibrio piger. We integrated the microbial community metabolic models of each time point with a male whole-body, organ-resolved model of human metabolism to track the metabolic consequences of dysbiosis at different body sites. The presence of D. piger in the gut microbiome influenced the sulfur metabolism with a domino effect affecting the liver. These results revealed large longitudinal variations in an individual's gut microbiome ecology and metabolite production, potentially impacting other organs in the body. Future simulations with more time points from an individual could permit us to assess how external drivers, such as diet change or medical interventions, drive microbial community dynamics.

A new metabolic model of Drosophila melanogaster and the integrative analysis of Parkinson's disease.

High conservation of the disease-associated genes between flies and humans facilitates the common use of Drosophila melanogaster to study metabolic disorders under controlled laboratory conditions. However, metabolic modeling studies are highly limited for this organism. We here report a comprehensively curated genome-scale metabolic network model of Drosophila using an orthology-based approach. The gene coverage and metabolic information of the draft model derived from a reference human model were expanded via Drosophila-specific KEGG and MetaCyc databases, with several curation steps to avoid metabolic redundancy and stoichiometric inconsistency. Furthermore, we performed literature-based curations to improve gene-reaction associations, subcellular metabolite locations, and various metabolic pathways. The performance of the resulting Drosophila model (8,230 reactions, 6,990 metabolites, and 2,388 genes), iDrosophila1 (https://github.com/SysBioGTU/iDrosophila), was assessed using flux balance analysis in comparison with the other currently available fly models leading to superior or comparable results. We also evaluated the transcriptome-based prediction capacity of iDrosophila1, where differential metabolic pathways during Parkinson's disease could be successfully elucidated. Overall, iDrosophila1 is promising to investigate system-level metabolic alterations in response to genetic and environmental perturbations.

Analysis of the anaerobic digestion metagenome under environmental stresses stimulating prophage induction.

BACKGROUND: The viral community has the potential to influence the structure of the microbiome and thus the yield of the anaerobic digestion process. However, the virome composition in anaerobic digestion is still under-investigated. A viral induction experiment was conducted on separate batches undergoing a series of DNA-damaging stresses, in order to coerce temperate viruses to enter the lytic cycle. RESULTS: The sequencing of the metagenome revealed a viral community almost entirely composed of tailed bacteriophages of the order Caudovirales. Following a binning procedure 1,092 viral and 120 prokaryotic genomes were reconstructed, 64 of which included an integrated prophage in their sequence. Clustering of coverage profiles revealed the presence of species, both viral and microbial, sharing similar reactions to shocks. A group of viral genomes, which increase under organic overload and decrease under basic pH, uniquely encode the yopX gene, which is involved in the induction of temperate prophages. Moreover, the in-silico functional analysis revealed an enrichment of sialidases in viral genomes. These genes are associated with tail proteins and, as such, are hypothesised to be involved in the interaction with the host. Archaea registered the most pronounced changes in relation to shocks and featured behaviours not shared with other species. Subsequently, data from 123 different samples of the global anaerobic digestion database was used to determine coverage profiles of host and viral genomes on a broader scale. CONCLUSIONS: Viruses are key components in anaerobic digestion environments, shaping the microbial guilds which drive the methanogenesis process. In turn, environmental conditions are pivotal in shaping the viral community and the rate of induction of temperate viruses. This study provides an initial insight into the complexity of the anaerobic digestion virome and its relation with the microbial community and the diverse environmental parameters. Video Abstract.

Integrating metagenomic binning with flux balance analysis to unravel syntrophies in anaerobic CO2 methanation.

BACKGROUND: Carbon fixation through biological methanation has emerged as a promising technology to produce renewable energy in the context of the circular economy. The anaerobic digestion microbiome is the fundamental biological system operating biogas upgrading and is paramount in power-to-gas conversion. Carbon dioxide (CO2) methanation is frequently performed by microbiota attached to solid supports generating biofilms. Despite the apparent simplicity of the microbial community involved in biogas upgrading, the dynamics behind most of the interspecies interaction remain obscure. To understand the role of the microbial species in CO2 fixation, the biofilm generated during the biogas upgrading process has been selected as a case study. The present work investigates via genome-centric metagenomics, based on a hybrid Nanopore-Illumina approach the biofilm developed on the diffusion devices of four ex situ biogas upgrading reactors. Moreover, genome-guided metabolic reconstruction and flux balance analysis were used to propose a biological role for the dominant microbes. RESULTS: The combined microbiome was composed of 59 species, with five being dominant (> 70% of total abundance); the metagenome-assembled genomes representing these species were refined to reach a high level of completeness. Genome-guided metabolic analysis appointed Firmicutes sp. GSMM966 as the main responsible for biofilm formation. Additionally, species interactions were investigated considering their co-occurrence in 134 samples, and in terms of metabolic exchanges through flux balance simulation in a simplified medium. Some of the most abundant species (e.g., Limnochordia sp. GSMM975) were widespread (~ 67% of tested experiments), while others (e.g., Methanothermobacter wolfeii GSMM957) had a scattered distribution. Genome-scale metabolic models of the microbial community were built with boundary conditions taken from the biochemical data and showed the presence of a flexible interaction network mainly based on hydrogen and carbon dioxide uptake and formate exchange. CONCLUSIONS: Our work investigated the interplay between five dominant species within the biofilm and showed their importance in a large spectrum of anaerobic biogas reactor samples. Flux balance analysis provided a deeper insight into the potential syntrophic interaction between species, especially Limnochordia sp. GSMM975 and Methanothermobacter wolfeii GSMM957. Finally, it suggested species interactions to be based on formate and amino acids exchanges. Video Abstract.

KEMET - A python tool for KEGG Module evaluation and microbial genome annotation expansion.

Background: The rapid accumulation of sequencing data from metagenomic studies is enabling the generation of huge collections of microbial genomes, with new challenges for mapping their functional potential. In particular, metagenome-assembled genomes are typically incomplete and harbor partial gene sequences that can limit their annotation from traditional tools. New scalable solutions are thus needed to facilitate the evaluation of functional potential in microbial genomes. Methods: To resolve annotation gaps in microbial genomes, we developed KEMET, an open-source Python library devised for the analysis of Kyoto Encyclopedia of Genes and Genomes (KEGG) functional units. KEMET focuses on the in-depth analysis of metabolic reaction networks to identify missing orthologs through hidden Markov model profiles. Results: We evaluate the potential of KEMET for expanding functional annotations by simulating the effect of assembly issues on real gene sequences and showing that our approach can identify missing KEGG orthologs. Additionally, we show that recovered gene annotations can sensibly increase the quality of draft genome-scale metabolic models obtained from metagenome-assembled genomes, in some cases reaching the accuracy of models generated from complete genomes. Conclusions: KEMET therefore allows expanding genome annotations by targeted searches for orthologous sequences, enabling a better qualitative and quantitative assessment of metabolic capabilities in novel microbial organisms.

Genome-Scale Metabolic Modeling of the Human Microbiome in the Era of Personalized Medicine.

The human microbiome plays an important role in human health and disease. Meta-omics analyses provide indispensable data for linking changes in microbiome composition and function to disease etiology. Yet, the lack of a mechanistic understanding of, e.g., microbiome-metabolome links hampers the translation of these findings into effective, novel therapeutics. Here, we propose metabolic modeling of microbial communities through constraint-based reconstruction and analysis (COBRA) as a complementary approach to meta-omics analyses. First, we highlight the importance of microbial metabolism in cardiometabolic diseases, inflammatory bowel disease, colorectal cancer, Alzheimer disease, and Parkinson disease. Next, we demonstrate that microbial community modeling can stratify patients and controls, mechanistically link microbes with fecal metabolites altered in disease, and identify host pathways affected by the microbiome. Finally, we outline our vision for COBRA modeling combined with meta-omics analyses and multivariate statistical analyses to inform and guide clinical trials, yield testable hypotheses, and ultimately propose novel dietary and therapeutic interventions.

Genome-Centric Metatranscriptomics Analysis Reveals the Role of Hydrochar in Anaerobic Digestion of Waste Activated Sludge.

Anaerobic digestion (AD) of waste activated sludge (WAS) has been widely used, while it poses problems including low methane yield and production rate. Hydrochar is produced by hydrothermal liquefaction of biomass; however, little is known about the role of hydrochar in promoting AD of WAS. The present study showed that hydrochar increased the methane production rate by 30.8% and yield by 31.4% of hydrothermal pretreated dewatered WAS. Hydrochar increased the methane production rate and yield by enhancing the acidification and methanogenesis processes. Genomic-centric metatranscriptomics were used to identify the metabolic activities and transcriptomic response of individual metagenome-assembled genomes that were enriched by hydrochar. Although Methanosarcina sp. FDU0106 had been shown unable to used H2, it had the complete pathway for the reduction of CO2 to methane. Syntrophomonas sp. FDU0164 expressed genes for extracellular electron transfer via electrically pili, suggesting that Syntrophomonas sp. FDU0164 and Methanosarcina sp. FDU0106 were exchanging electrons via direct interspecies electron transfer. The expression of pili was decreased, indicating that hydrochar could replace its roles. Additionally, Firmicutes sp. FDU0048, Proteiniphilum sp. FDU0082, and Aminobacterium mobile FDU0089 were related to the degradation of organics, which could be related to the enhanced methane yield.

Large-scale sequencing and comparative analysis of oenological Saccharomyces cerevisiae strains supported by nanopore refinement of key genomes.

Saccharomyces cerevisiae has long been part of human activities related to the production of food and wine. The industrial demand for fermented beverages with well-defined and stable characteristics boosted the isolation and selection of strains conferring a distinctive aroma profile to the final product. To uncover variants characterizing oenological strains, the sequencing of 65 new S. cerevisiae isolates, and the comparison with other 503 publicly available genomes were performed. A hybrid approach based on short Illumina and long Oxford Nanopore reads allowed the in-depth investigation of eleven genomes and the identification of putative laterally transferred regions and structural variants. A comparative analysis between clusters of strains belonging to different datasets allowed the identification of novel relevant genetic features including single nucleotide polymorphisms, insertions and structural variants. Detection of oenological single nucleotide variants shed light on the existence of different levels of modulation for the mevalonate pathway relevant for the biosynthesis of aromatic compounds.

Revealing metabolic mechanisms of interaction in the anaerobic digestion microbiome by flux balance analysis.

Anaerobic digestion is a key biological process for renewable energy, yet the mechanistic knowledge on its hidden microbial dynamics is still limited. The present work charted the interaction network in the anaerobic digestion microbiome via the full characterization of pairwise interactions and the associated metabolite exchanges. To this goal, a novel collection of 836 genome-scale metabolic models was built to represent the functional capabilities of bacteria and archaea species derived from genome-centric metagenomics. Dominant microbes were shown to prefer mutualistic, parasitic and commensalistic interactions over neutralism, amensalism and competition, and are more likely to behave as metabolite importers and profiteers of the coexistence. Additionally, external hydrogen injection positively influences microbiome dynamics by promoting commensalism over amensalism. Finally, exchanges of glucogenic amino acids were shown to overcome auxotrophies caused by an incomplete tricarboxylic acid cycle. Our novel strategy predicted the most favourable growth conditions for the microbes, overall suggesting strategies to increasing the biogas production efficiency. In principle, this approach could also be applied to microbial populations of biomedical importance, such as the gut microbiome, to allow a broad inspection of the microbial interplays.

Insights into Ammonia Adaptation and Methanogenic Precursor Oxidation by Genome-Centric Analysis.

Ammonia released from the degradation of protein and/or urea usually leads to suboptimal anaerobic digestion (AD) when N-rich organic waste is used. However, the insights behind the differential ammonia tolerance of anaerobic microbiomes remain an enigma. In this study, the cultivation in synthetic medium with different carbon sources (acetate, methanol, formate, and H2/CO2) shaped a common initial inoculum into four unique ammonia-tolerant syntrophic populations. Specifically, various levels of ammonia tolerance were observed: consortia fed with methanol and H2/CO2 could grow at ammonia levels up to 7.25 g NH+-N/L, whereas the other two groups (formate and acetate) only thrived at 5.25 and 4.25 g NH+-N/L, respectively. Metabolic reconstruction highlighted that this divergent microbiome might be achieved by complementary metabolisms to maximize biomethane recovery from carbon sources, thus indicating the importance of the syntrophic community in the AD of N-rich substrates. Besides, sodium/proton antiporter operon, osmoprotectant/K+ regulator, and osmoprotectant synthesis operon may function as the main drivers of adaptation to the ammonia stress. Moreover, energy from the substrate-level phosphorylation and multiple energy-converting hydrogenases (e.g., Ech and Eha) could aid methanogens to balance the energy request for anabolic activities and contribute to thriving when exposed to high ammonia levels.

New insights into the variability of lactic acid production in Lachancea thermotolerans at the phenotypic and genomic level.

Non-conventional yeasts are increasingly applied in fermented beverage industry to obtain distinctive products with improved quality. Among these yeasts, Lachancea thermotolerans has multiple features of industrial relevance, especially the production of l(+)-lactic acid (LA), useful for the biological acidification of wine and beer. Since few information is available on this peculiar activity, the current study aimed to explore the physiological and genetic variability among L. thermotolerans strains. From a strain collection, mostly isolated from wine, a huge phenotypic diversity was acknowledged and allowed the selection of a high (SOL13) and a low (COLC27) LA producer. Comparative whole-genome sequencing of these two selected strains and the type strain CBS 6340T showed a high similarity in terms of gene content and functional annotation. Notwithstanding, target gene-based analysis revealed variations between high and low producers in the key gene sequences related to LA accumulation. More in-depth investigation of the core promoters and expression analysis of the genes ldh, encoding lactate dehydrogenase, indicated the transcriptional regulation may be the principal cause behind phenotypic differences. These findings highlighted the usefulness of whole-genome sequencing coupled with expression analysis. They provided crucial genetic insights for a deeper investigation of the intraspecific variability in LA production pathway.

New insights from the biogas microbiome by comprehensive genome-resolved metagenomics of nearly 1600 species originating from multiple anaerobic digesters.

BACKGROUND: Microorganisms in biogas reactors are essential for degradation of organic matter and methane production. However, a comprehensive genome-centric comparison, including relevant metadata for each sample, is still needed to identify the globally distributed biogas community members and serve as a reliable repository. RESULTS: Here, 134 publicly available metagenomes derived from different biogas reactors were used to recover 1635 metagenome-assembled genomes (MAGs) representing different biogas bacterial and archaeal species. All genomes were estimated to be > 50% complete and nearly half ≥ 90% complete with ≤ 5% contamination. In most samples, specialized microbial communities were established, while only a few taxa were widespread among the different reactor systems. Metabolic reconstruction of the MAGs enabled the prediction of functional traits related to biomass degradation and methane production from waste biomass. An extensive evaluation of the replication index provided an estimation of the growth dynamics for microbes involved in different steps of the food chain. CONCLUSIONS: The outcome of this study highlights a high flexibility of the biogas microbiome, allowing it to modify its composition and to adapt to the environmental conditions, including temperatures and a wide range of substrates. Our findings enhance our mechanistic understanding of the AD microbiome and substantially extend the existing repository of genomes. The established database represents a relevant resource for future studies related to this engineered ecosystem.

Genomic Comparison of Lactobacillus helveticus Strains Highlights Probiotic Potential.

Lactobacillus helveticus belongs to the large group of lactic acid bacteria (LAB), which are the major players in the fermentation of a wide range of foods. LAB are also present in the human gut, which has often been exploited as a reservoir of potential novel probiotic strains, but several parameters need to be assessed before establishing their safety and potential use for human consumption. In the present study, six L. helveticus strains isolated from natural whey cultures were analyzed for their phenotype and genotype in exopolysaccharide (EPS) production, low pH and bile salt tolerance, bile salt hydrolase (BSH) activity, and antibiotic resistance profile. In addition, a comparative genomic investigation was performed between the six newly sequenced strains and the 51 publicly available genomes of L. helveticus to define the pangenome structure. The results indicate that the newly sequenced strain UC1267 and the deposited strain DSM 20075 can be considered good candidates for gut-adapted strains due to their ability to survive in the presence of 0.2% glycocholic acid (GCA) and 1% taurocholic and taurodeoxycholic acid (TDCA). Moreover, these strains had the highest bile salt deconjugation activity among the tested L. helveticus strains. Considering the safety profile, none of these strains presented antibiotic resistance phenotypically and/or at the genome level. The pangenome analysis revealed genes specific to the new isolates, such as enzymes related to folate biosynthesis in strains UC1266 and UC1267 and an integrated phage in strain UC1035. Finally, the presence of maltose-degrading enzymes and multiple copies of 6-phospho-ß-glucosidase genes in our strains indicates the capability to metabolize sugars other than lactose, which is related solely to dairy niches.