Synergistic functional activity of a landfill microbial consortium in a microplastic-enriched environment.

Plastic pollution of the soil is a global issue of increasing concern, with far-reaching impact on the environment and human health. To fully understand the medium- and long-term impact of plastic dispersal in the environment, it is necessary to define its interaction with the residing microbial communities and the biochemical routes of its degradation and metabolization. However, despite recent attention on this problem, research has largely focussed on microbial functional potential, failing to clearly identify collective adaptation strategies of these communities. Our study combines genome-centric metagenomics and metatranscriptomics to characterise soil microbial communities adapting to high polyethylene and polyethylene terephthalate concentration. The microbiota were sampled from a landfill subject to decades-old plastic contamination and enriched through prolonged cultivation using these microplastics as the only carbon source. This approach aimed to select the microorganisms that best adapt to these specific substrates. As a result, we obtained simplified communities where multiple plastic metabolization pathways are widespread across abundant and rare microbial taxa. Major differences were found in terms of expression, which on average was higher in planktonic microbes than those firmly adhered to plastic, indicating complementary metabolic roles in potential microplastic assimilation. Moreover, metatranscriptomic patterns indicate a high transcriptional level of numerous genes in emerging taxa characterised by a marked accumulation of genomic variants, supporting the hypothesis that plastic metabolization requires an extensive rewiring in energy metabolism and thus provides a strong selective pressure. Altogether, our results provide an improved characterisation of the impact of microplastics derived from common plastics types on terrestrial microbial communities and suggest biotic responses investing contaminated sites as well as potential biotechnological targets for cooperative plastic upcycling.

Autotrophic poly-3-hydroxybutyrate accumulation in Cupriavidus necator for sustainable bioplastic production triggered by nutrient starvation.

Cupriavidus necator is a facultative chemolithoautotrophic bacterium able to convert carbon dioxide into poly-3-hydroxybutyrate. This is highly promising as the conversion process allows the production of sustainable and biodegradable plastics. Poly-3-hydroxybutyrate accumulation is known to be induced by nutrient starvation, but information regarding the optimal stress conditions controlling the process is still heterogeneous and fragmentary. This study presents a comprehensive comparison of the effects of nutrient stress conditions, namely nitrogen, hydrogen, phosphorus, oxygen, and magnesium deprivation, on poly-3-hydroxybutyrate accumulation in C. necator DSM545. Nitrogen starvation exhibited the highest poly-3-hydroxybutyrate accumulation, achieving 54% of total cell dry weight after four days of nutrient stress, and a carbon conversion efficiency of 85%. The gas consumption patterns indicated flexible physiological mechanisms underlying polymer accumulation and depolymerization. These findings provide insights into strategies for efficient carbon conversion into bioplastics, and highlight the key role of C. necator for future industrial-scale applications.

Metapresence: a tool for accurate species detection in metagenomics based on the genome-wide distribution of mapping reads.

Shotgun metagenomics allows comprehensive sampling of the genomic information of microbes in a given environment and is a tool of choice for studying complex microbial systems. Mapping sequencing reads against a set of reference or metagenome-assembled genomes is in principle a simple and powerful approach to define the species-level composition of the microbial community under investigation. However, despite the widespread use of this approach, there is no established way to properly interpret the alignment results, with arbitrary relative abundance thresholds being routinely used to discriminate between present and absent species. Such an approach can be affected by significant biases, especially in the identification of rare species. Therefore, it is important to develop new metrics to overcome these biases. Here, we present Metapresence, a new tool to perform reliable identification of the species in metagenomic samples based on the distribution of mapped reads on the reference genomes. The analysis is based on two metrics describing the breadth of coverage and the genomic distance between consecutive reads. We demonstrate the high precision and wide applicability of the tool using data from various synthetic communities, a real mock community, and the gut microbiome of healthy individuals and antibiotic-associated-diarrhea patients. Overall, our results suggest that the proposed approach has a robust performance in hard-to-analyze microbial communities containing contaminated or closely related genomes in low abundance.IMPORTANCEDespite the prevalent use of genome-centric alignment-based methods to characterize microbial community composition, there lacks a standardized approach for accurately identifying the species within a sample. Currently, arbitrary relative abundance thresholds are commonly employed for this purpose. However, due to the inherent complexity of genome structure and biases associated with genome-centric approaches, this practice tends to be imprecise. Notably, it introduces significant biases, particularly in the identification of rare species. The method presented here addresses these limitations and contributes significantly to overcoming inaccuracies in precisely defining community composition, especially when dealing with rare members.

Deciphering the genetic landscape of enhanced poly-3-hydroxybutyrate production in Synechocystis sp. B12.

BACKGROUND: Microbial biopolymers such as poly-3-hydroxybutyrate (PHB) are emerging as promising alternatives for sustainable production of biodegradable bioplastics. Their promise is heightened by the potential utilisation of photosynthetic organisms, thus exploiting sunlight and carbon dioxide as source of energy and carbon, respectively. The cyanobacterium Synechocystis sp. B12 is an attractive candidate for its superior ability to accumulate high amounts of PHB as well as for its high-light tolerance, which makes it extremely suitable for large-scale cultivation. Beyond its practical applications, B12 serves as an intriguing model for unravelling the molecular mechanisms behind PHB accumulation. RESULTS: Through a multifaceted approach, integrating physiological, genomic and transcriptomic analyses, this work identified genes involved in the upregulation of chlorophyll biosynthesis and phycobilisome degradation as the possible candidates providing Synechocystis sp. B12 an advantage in growth under high-light conditions. Gene expression differences in pentose phosphate pathway and acetyl-CoA metabolism were instead recognised as mainly responsible for the increased Synechocystis sp. B12 PHB production during nitrogen starvation. In both response to strong illumination and PHB accumulation, Synechocystis sp. B12 showed a metabolic modulation similar but more pronounced than the reference strain, yielding in better performances. CONCLUSIONS: Our findings shed light on the molecular mechanisms of PHB biosynthesis, providing valuable insights for optimising the use of Synechocystis in economically viable and sustainable PHB production. In addition, this work supplies crucial knowledge about the metabolic processes involved in production and accumulation of these molecules, which can be seminal for the application to other microorganisms as well.

Carbon monoxide inhibition on acidogenic glucose fermentation and aceticlastic methanogenesis.

Syngas and CO-rich off-gases are key chemical platforms to produce biofuels and bioproducts. From the perspective of optimizing and up-scaling CO co-digestion with organic waste streams, this study aims at assessing and quantifying the inhibitory effects of CO on acidogenic glucose fermentation and aceticlastic methanogenesis. Mesophilic cultures were fed in two sets of batch assays, respectively, with glucose and acetate while being exposed to dissolved CO in equilibrium with partial pressures in the range of 0.25-1.00 atm. Cumulative methane production and microbial monitoring revealed that aceticlastic methanogenic archaea were significantly inhibited (2-20 % of the methane production of CO non-exposed cultures). The acidogenic glucose degrading community was also inhibited by CO, although, thanks to its functional redundancy, shifted its metabolism towards propionate production. Future work should assess the sensitivity of hereby estimated CO inhibition parameters, e.g., on the simulation output of a continuous syngas co-digestion process with organic substrates.

Classification of bioactive peptides: A systematic benchmark of models and encodings.

Bioactive peptides are short amino acid chains possessing biological activity and exerting physiological effects relevant to human health. Despite their therapeutic value, their identification remains a major problem, as it mainly relies on time-consuming in vitro tests. While bioinformatic tools for the identification of bioactive peptides are available, they are focused on specific functional classes and have not been systematically tested on realistic settings. To tackle this problem, bioactive peptide sequences and functions were here gathered from a variety of databases to generate a unified collection of bioactive peptides from microbial fermentation. This collection was organized into nine functional classes including some previously studied and some unexplored such as immunomodulatory, opioid and cardiovascular peptides. Upon assessing their sequence properties, four alternative encoding methods were tested in combination with a multitude of machine learning algorithms, from basic classifiers like logistic regression to advanced algorithms like BERT. Tests on a total of 171 models showed that, while some functions are intrinsically easier to detect, no single combination of classifiers and encoders worked universally well for all classes. For this reason, we unified all the best individual models for each class and generated CICERON (Classification of bIoaCtive pEptides fRom micrObial fermeNtation), a classification tool for the functional classification of peptides. State-of-the-art classifiers were found to underperform on our realistic benchmark dataset compared to the models included in CICERON. Altogether, our work provides a tool for real-world peptide classification and can serve as a benchmark for future model development.

Biological carbon capture from biogas streams: Insights into Cupriavidus necator autotrophic growth and transcriptional profile.

Recycling carbon-rich wastes into high-value platform chemicals through biological processes provides a sustainable alternative to petrochemicals. Cupriavidus necator, known for converting carbon dioxide (CO2) into polyhydroxyalkanoates (PHA) was studied for the first time using biogas streams as the sole carbon source. The bacterium efficiently consumed biogenic CO2 from raw biogas with methane at high concentrations (50%) proving non-toxic. Continuous addition of H2 and O2 enabled growth trends comparable to glucose-based heterotrophic growth. Transcriptomic analysis revealed CO2-adaptated cultures exhibited upregulation of hydrogenases and Calvin cycle enzymes, as well as genes related to electron transport, nutrient uptake, and glyoxylate cycle. Non-adapted samples displayed activation of stress response mechanisms, suggesting potential lags in large-scale processes. These findings showcase the setting of growth parameters for a pioneering biological biogas upgrading strategy, emphasizing the importance of inoculum adaptation for autotrophic growth and providing potential targets for genetic engineering to push PHA yields in future applications.

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.

Decoding Microbial Responses to Ammonia Shock Loads in Biogas Reactors through Metagenomics and Metatranscriptomics.

The presence of elevated ammonia levels is widely recognized as a significant contributor to process inhibition in biogas production, posing a common challenge for biogas plant operators. The present study employed a combination of biochemical, genome-centric metagenomic and metatranscriptomic data to investigate the response of the biogas microbiome to two shock loads induced by single pulses of elevated ammonia concentrations (i.e., 1.5 g NH4+/LR and 5 g NH4+/LR). The analysis revealed a microbial community of high complexity consisting of 364 Metagenome Assembled Genomes (MAGs). The hydrogenotrophic pathway was the primary route for methane production during the entire experiment, confirming its efficiency even at high ammonia concentrations. Additionally, metatranscriptomic analysis uncovered a metabolic shift in the methanogens Methanothrix sp. MA6 and Methanosarcina flavescens MX5, which switched their metabolism from the acetoclastic to the CO2 reduction route during the second shock. Furthermore, multiple genes associated with mechanisms for maintaining osmotic balance in the cell were upregulated, emphasizing the critical role of osmoprotection in the rapid response to the presence of ammonia. Finally, this study offers insights into the transcriptional response of an anaerobic digestion community, specifically focusing on the mechanisms involved in recovering from ammonia-induced stress.

Adaptation of Anaerobic Digestion Microbial Communities to High Ammonium Levels: Insights from Strain-Resolved Metagenomics.

Ammonia release from proteinaceous feedstocks represents the main inhibitor of the anaerobic digestion (AD) process, which can result in a decreased biomethane yield or even complete failure of the process. The present study focused on the adaptation of mesophilic AD communities to a stepwise increase in the concentration of ammonium chloride in synthetic medium with casein used as the carbon source. An adaptation process occurring over more than 20 months allowed batch reactors to reach up to 20 g of NH4+ N/L without collapsing in acidification nor ceasing methane production. To decipher the microbial dynamics occurring during the adaptation and determine the genes mostly exposed to selective pressure, a combination of biochemical and metagenomics analyses was performed, reconstructing the strains of key species and tracking them over time. Subsequently, the adaptive metabolic mechanisms were delineated by following the single nucleotide variants (SNVs) characterizing the strains and prioritizing the associated genes according to their function. An in-depth exploration of the archaeon Methanoculleus bourgensis vb3066 and the putative syntrophic acetate-oxidizing bacteria Acetomicrobium sp. ma133 identified positively selected SNVs on genes involved in stress adaptation. The intraspecies diversity with multiple coexisting strains in a temporal succession pattern allows us to detect the presence of an additional level of diversity within the microbial community beyond the species level.

Magnetite Alters the Metabolic Interaction between Methanogens and Sulfate-Reducing Bacteria.

It is known that the presence of sulfate decreases the methane yield in the anaerobic digestion systems. Sulfate-reducing bacteria can convert sulfate to hydrogen sulfide competing with methanogens for substrates such as H2 and acetate. The present work aims to elucidate the microbial interactions in biogas production and assess the effectiveness of electron-conductive materials in restoring methane production after exposure to high sulfate concentrations. The addition of magnetite led to a higher methane content in the biogas and a sharp decrease in the level of hydrogen sulfide, indicating its beneficial effects. Furthermore, the rate of volatile fatty acid consumption increased, especially for butyrate, propionate, and acetate. Genome-centric metagenomics was performed to explore the main microbial interactions. The interaction between methanogens and sulfate-reducing bacteria was found to be both competitive and cooperative, depending on the methanogenic class. Microbial species assigned to the Methanosarcina genus increased in relative abundance after magnetite addition together with the butyrate oxidizing syntrophic partners, in particular belonging to the Syntrophomonas genus. Additionally, Ruminococcus sp. DTU98 and other species assigned to the Chloroflexi phylum were positively correlated to the presence of sulfate-reducing bacteria, suggesting DIET-based interactions. In conclusion, this study provides new insights into the application of magnetite to enhance the anaerobic digestion performance by removing hydrogen sulfide, fostering DIET-based syntrophic microbial interactions, and unraveling the intricate interplay of competitive and cooperative interactions between methanogens and sulfate-reducing bacteria, influenced by the specific methanogenic group.

Additional glucoamylase genes increase ethanol productivity on rice and potato waste streams by a recombinant amylolytic yeast.

The implementation of consolidated bioprocessing for converting starch to ethanol relies on a robust yeast that produces enough amylases for rapid starch hydrolysis. Furthermore, using low-cost substrates will assist with competitive ethanol prices and support a bioeconomy, especially in developing countries. This paper addresses both challenges with the expression of additional glucoamylase gene copies in an efficient amylolytic strain (Saccharomyces cerevisiae ER T12) derived from the industrial yeast, Ethanol Red™. Recombinant ER T12 was used as a host to increase ethanol productivity during raw starch fermentation; the ER T12.7 variant, selected from various transformants, displayed enhanced raw starch conversion and a 36% higher ethanol concentration than the parental strain after 120 h. Unripe rice, rice bran, potato waste and potato peels were evaluated as alternative starchy substrates to test ER T12.7's fermenting ability. ER T12.7 produced high ethanol yields at significantly improved ethanol productivity, key criteria for its industrial application.

Cupriavidus necator as a platform for polyhydroxyalkanoate production: An overview of strains, metabolism, and modeling approaches.

Cupriavidus necator is a bacterium with a high phenotypic diversity and versatile metabolic capabilities. It has been extensively studied as a model hydrogen oxidizer, as well as a producer of polyhydroxyalkanoates (PHA), plastic-like biopolymers with a high potential to substitute petroleum-based materials. Thanks to its adaptability to diverse metabolic lifestyles and to the ability to accumulate large amounts of PHA, C. necator is employed in many biotechnological processes, with particular focus on PHA production from waste carbon sources. The large availability of genomic information has enabled a characterization of C. necator's metabolism, leading to the establishment of metabolic models which are used to devise and optimize culture conditions and genetic engineering approaches. In this work, the characteristics of available C. necator strains and genomes are reviewed, underlining how a thorough comprehension of the genetic variability of C. necator is lacking and it could be instrumental for wider application of this microorganism. The metabolic paradigms of C. necator and how they are connected to PHA production and accumulation are described, also recapitulating the variety of carbon substrates used for PHA accumulation, highlighting the most promising strategies to increase the yield. Finally, the review describes and critically analyzes currently available genome-scale metabolic models and reduced metabolic network applications commonly employed in the optimization of PHA production. Overall, it appears that the capacity of C. necator of performing CO2 bioconversion to PHA is still underexplored, both in biotechnological applications and in metabolic modeling. However, the accurate characterization of this organism and the efforts in using it for gas fermentation can help tackle this challenging perspective in the future.

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.

Comparative study on packing materials for improved biological methanation in trickle Bed reactors.

Packing materials improve biological methanation efficiency in Trickle Bed Reactors. The present study, which lies in the field of energy production and biotechnology, entailed the evaluation of commercial pelletized activated carbon and Raschig rings as packing materials. The evaluation focused on monitoring process indicators and examining the composition of the microbial community. Activated carbon resulted in enhanced methane purity, achieving a two-fold higher methane percentage than Raschig rings, maintaining a stable pH level within a range of 7-8 and reducing gas retention time from 6 h to 90 min. Additionally, the digestate derived from biogas plant was found to be a sufficient nutrient source for the process. Fermentative species with genes for ß-oxidation, such as Amaricoccus sp. and Caloramator australicus could explain the production of hexanoic and valerate acids during reactor operation. Based on the physical properties of packing materials, the efficiency of biological methanation could be maximized.

An integrated metagenomic model to uncover the cooperation between microbes and magnetic biochar during microplastics degradation in paddy soil.

The free radicals released from the advanced oxidation processes can enhance microplastics degradation, however, the existence of microbes acting synergistically in this process is still uncertain. In this study, magnetic biochar was used to initiate the advanced oxidation process in flooded soil. paddy soil was contaminated with polyethylene and polyvinyl chloride microplastics in a long-term incubation experiment, and subsequently subjected to bioremediation with biochar or magnetic biochar. After incubation, the total organic matter present in the samples containing polyvinyl chloride or polyethylene, and treated with magnetic biochar, significantly increased compared to the control. In the same samples there was an accumulation of "UVA humic" and "protein/phenol-like" substances. The integrated metagenomic investigation revealed that the relative abundance of some key genes involved in fatty acids degradation and in dehalogenation changed in different treatments. Results from genome-centric investigation suggest that a Nocardioides species can cooperate with magnetic biochar in the degradation of microplastics. In addition, a species assigned to the Rhizobium taxon was identified as a candidate in the dehalogenation and in the benzoate metabolism. Overall, our results suggest that cooperation between magnetic biochar and some microbial species involved in microplastic degradation is relevant in determining the fate of microplastics in soil.

Genome-centric metagenomics revealed the effect of pH on the microbiome involved in short-chain fatty acids and ethanol production.

Added-value chemicals production via food waste (FWs) valorization using open-mixed cultures is an emerging approach to replace petrochemical-based compounds. Nevertheless, the effects of operational parameters on the product spectrum remain uncertain given the wide number of co-occurring species and metabolisms. In this study, the identification of 58 metagenome-assembled genomes and their investigation assessed the effect of slight pH variations on microbial dynamics and the corresponding functions when FWs were subjected to anaerobic fermentation (AF) in 1-L continuous stirred tank reactors at 25 °C. The initial pH of 6.5 promoted a microbial community involved in acetate, butyrate and ethanol production, mediated by Bifidobacterium subtile IE007 and Eubacteriaceae IE027 as main species. A slight pH decrease to 6.1 shaped microbial functions that resulted in caproate and H2 production, increasing the relevance of Eubacteriaceae IE037 role. This study elucidated the strong pH effect on product outputs when minimal variations take place in AF.

Unraveling prevalence of homoacetogenesis and methanogenesis pathways due to inhibitors addition.

Three inhibitors targeting different microorganisms, both from Archaea and Bacteria domains, were evaluated for their effect on CO2 biomethanation: sodium ionophore III (ETH2120), carbon monoxide (CO), and sodium 2-bromoethanesulfonate (BES). This study examines how these compounds affect the anaerobic digestion microbiome in a biogas upgrading process. While archaea were observed in all experiments, methane was produced only when adding ETH2120 or CO, not when adding BES, suggesting archaea were in an inactivated state. Methane was produced mainly via methylotrophic methanogenesis from methylamines. Acetate was produced at all conditions, but a slight reduction on acetate production (along with an enhancement on CH4 production) was observed when applying 20 kPa of CO. Effects on CO2 biomethanation were difficult to observe since the inoculum used was from a real biogas upgrading reactor, being this a complex environmental sample. Nevertheless, it must be mentioned that all compounds had effects on the microbial community composition.

Metatranscriptomics-guided genome-scale metabolic modeling of microbial communities.

Multi-omics data integration via mechanistic models of metabolism is a scalable and flexible framework for exploring biological hypotheses in microbial systems. However, although most microorganisms are unculturable, such multi-omics modeling is limited to isolate microbes or simple synthetic communities. Here, we developed an approach for modeling microbial activity and interactions that leverages the reconstruction of metagenome-assembled genomes and associated genome-centric metatranscriptomes. At its core, we designed a method for condition-specific metabolic modeling of microbial communities through the integration of metatranscriptomic data. Using this approach, we explored the behavior of anaerobic digestion consortia driven by hydrogen availability and human gut microbiota dysbiosis associated with Crohn's disease, identifying condition-dependent amino acid requirements in archaeal species and a reduced short-chain fatty acid exchange network associated with disease, respectively. Our approach can be applied to complex microbial communities, allowing a mechanistic contextualization of multi-omics data on a metagenome scale.