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

Basile, Arianna; Kovalovszki, Adam; Zampieri, Guido; Rossi, Alessandro; Angelidaki, Irini; Valle, Giorgio; Treu, Laura

doi:10.1016/j.ymben.2020.08.013

Cited by 61 publications

(51 citation statements)

References 75 publications

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“…Preference for specific substrates can be determined based on many different indicators, one being for sure the possibility to degrade a specific compound, but also syntrophic behaviors determined by compounds exchange between microbes are involved in shaping the structure of the microbiomes [ 51 ]. For this reason, it is expected that only a part of the “specialized microbes” is able to directly utilize the substrate provided; other species probably rely on the chemical compounds released.…”

Section: Discussionmentioning

confidence: 99%

“…To understand metabolic networks in AD microbiomes, the metagenomic studies focus on analysis of the microbiomes’ composition, description of interactions within microbial communities, and assignment of functions in AD steps to specific groups of microbes [ 37 , 51 – 55 ]. Metagenomic approaches show interdependencies between microbial communities and the type of feedstock, the C:N ratio, the operating conditions such as temperature, pH, bioreactor construction, organics loading rate, hydraulic retention time, etc.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Evaluation of acidogenesis products’ effect on biogas production performed with metagenomics and isotopic approaches

Detman

Bucha

Treu

et al. 2021

Biotechnol Biofuels

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Background During the acetogenic step of anaerobic digestion, the products of acidogenesis are oxidized to substrates for methanogenesis: hydrogen, carbon dioxide and acetate. Acetogenesis and methanogenesis are highly interconnected processes due to the syntrophic associations between acetogenic bacteria and hydrogenotrophic methanogens, allowing the whole process to become thermodynamically favorable. The aim of this study is to determine the influence of the dominant acidic products on the metabolic pathways of methane formation and to find a core microbiome and substrate-specific species in a mixed biogas-producing system. Results Four methane-producing microbial communities were fed with artificial media having one dominant component, respectively, lactate, butyrate, propionate and acetate, for 896 days in 3.5-L Up-flow Anaerobic Sludge Blanket (UASB) bioreactors. All the microbial communities showed moderately different methane production and utilization of the substrates. Analyses of stable carbon isotope composition of the fermentation gas and the substrates showed differences in average values of δ13C(CH4) and δ13C(CO2) revealing that acetate and lactate strongly favored the acetotrophic pathway, while butyrate and propionate favored the hydrogenotrophic pathway of methane formation. Genome-centric metagenomic analysis recovered 234 Metagenome Assembled Genomes (MAGs), including 31 archaeal and 203 bacterial species, mostly unknown and uncultivable. MAGs accounted for 54%–67% of the entire microbial community (depending on the bioreactor) and evidenced that the microbiome is extremely complex in terms of the number of species. The core microbiome was composed of Methanothrix soehngenii (the most abundant), Methanoculleus sp., unknown Bacteroidales and Spirochaetaceae. Relative abundance analysis of all the samples revealed microbes having substrate preferences. Substrate-specific species were mostly unknown and not predominant in the microbial communities. Conclusions In this experimental system, the dominant fermentation products subjected to methanogenesis moderately modified the final effect of bioreactor performance. At the molecular level, a different contribution of acetotrophic and hydrogenotrophic pathways for methane production, a very high level of new species recovered, and a moderate variability in microbial composition depending on substrate availability were evidenced. Propionate was not a factor ceasing methane production. All these findings are relevant because lactate, acetate, propionate and butyrate are the universal products of acidogenesis, regardless of feedstock.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluation of acidogenesis products’ effect on biogas production performed with metagenomics and isotopic approaches

Detman

Bucha

Treu

et al. 2021

Biotechnol Biofuels

Self Cite

View full text Add to dashboard Cite

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“…Complex microbial communities play an important role in human physiology and environmental processes [1][2][3][4][5][6][7]. Genome-scale metabolic network reconstructions (GENREs) have been shown to model the functional capabilities of microbes and their interactions in communities [8][9][10][11]. A GENRE is a constraint-based model structure that enables the combination of various forms of biological data to gain an improved mechanistic understanding of metabolism [12].…”

Section: Introductionmentioning

confidence: 99%

Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions

et al. 2022

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Genome-scale metabolic network reconstructions (GENREs) are valuable tools for understanding microbial metabolism. The process of automatically generating GENREs includes identifying metabolic reactions supported by sufficient genomic evidence to generate a draft metabolic network. The draft GENRE is then gapfilled with additional reactions in order to recapitulate specific growth phenotypes as indicated with associated experimental data. Previous methods have implemented absolute mapping thresholds for the reactions automatically included in draft GENREs; however, there is growing evidence that integrating annotation evidence in a continuous form can improve model accuracy. There is a need for flexibility in the structure of GENREs to better account for uncertainty in biological data, unknown regulatory mechanisms, and context-specificity associated with data inputs. To address this issue, we present a novel method that provides a framework for quantifying combined genomic, biochemical, and phenotypic evidence for each biochemical reaction during automated GENRE construction. Our method, Constraint-based Analysis Yielding reaction Usage across metabolic Networks (CANYUNs), generates accurate GENREs with a quantitative metric for the cumulative evidence for each reaction included in the network. The structuring of CANYUNs allows for the simultaneous integration of three data inputs while maintaining all supporting evidence for biochemical reactions that may be active in an organism. CANYUNs is designed to maximize the utility of experimental and annotation datasets and to ultimately assist in the curation of the reference datasets used for the automatic construction of metabolic networks. We validated CANYUNs by generating an E. coli K-12 model and compared it to the manually curated reconstruction iML1515. Finally, we demonstrated the use of CANYUNs to build a model by generating an E. coli Nissle CANYUNs model using novel phenotypic data that we collected. This method may address key challenges for the procedural construction of metabolic networks by leveraging uncertainty and redundancy in biological data.

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“…Attempts of mechanistic links between diet or inter-species interactions with microbiota composition and dynamics lead to development of gut species genome-scale metabolic models 15 . GEnome-scale Metabolic models (GEMs) allow assessing species nutritional requirements 16 and their interactions in the human gut as well as in diverse environmental communities [17][18][19] . The current paradigm of metabolic modeling typically relies on mapping identified taxa to their closest reference genomes.…”

Section: Introductionmentioning

confidence: 99%

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes

Zorrilla

Patil

Zelezniak

2021

Preprint

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Advances in genome-resolved metagenomic analysis of complex microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts still tend to rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end highly scalable pipeline enabling metabolic modeling of multi-species communities directly from metagenomic samples. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from metagenome assembled genomes to community level flux balance simulations. To demonstrate the capabilities of the metaGEM pipeline, we analyzed 483 samples spanning lab culture, human gut, plant associated, soil, and ocean metagenomes, to reconstruct over 14 000 prokaryotic GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to the GEMs reconstructed from reference genomes. We further demonstrate that metagenomic GEMs capture intraspecies metabolic diversity by identifying the differences between pathogenicity levels of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, our pipeline enables simulation-ready metabolic model reconstruction directly from individual metagenomes, provides a resource of all reconstructed metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.

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

Cited by 61 publications

References 75 publications

Evaluation of acidogenesis products’ effect on biogas production performed with metagenomics and isotopic approaches

Evaluation of acidogenesis products’ effect on biogas production performed with metagenomics and isotopic approaches

Quantifying cumulative phenotypic and genomic evidence for procedural generation of metabolic network reconstructions

metaGEM: reconstruction of genome scale metabolic models directly from metagenomes

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