Integrative Analyses to Investigate the Link between Microbial Activity and Metabolite Degradation during Anaerobic Digestion

Cardona, Laëtitia; Cao, Kim Anh Lê; Puig‐Castellví, Francesc; Bureau, Chrystelle; Madigou, Céline; Mazéas, Laurent; Chapleur, Olivier

doi:10.1021/acs.jproteome.0c00251

Cited by 17 publications

(8 citation statements)

References 70 publications

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“…For bacteria, members of family D8A‐2 and H 2 ‐producers Coprothermobacteriaceae expressed activity positively related to methanogenic activities during waste fermentation, suggesting that these yet‐to‐be‐cultured anaerobes may play an important role in syntrophic acids oxidation during the later phase of low‐and medium‐load fermentation (day 20 to 45, Figures 3 and 4 , Supplementary Information Figure S4 ). Our hypothesis is well supported by prior reports of highly positive correlation (i) between Coprothermobacteriaceae members and H 2 ‐utilising Hydrogenedentiales [ 50 , 51 ] and (ii) between D8A‐2 and hydrogenotrophic methanogen Methanoculleus [ 52 ]. Thus, precise control of D8A‐2 and Coprothermobacteriacea ’s activity could potentially lead to VFA accumulations during biowaste fermentation and achieve similar effects as BES.…”

Section: Discussionsupporting

confidence: 90%

Microbiome dynamics and products profiles of biowaste fermentation under different organic loads and additives

Zhu,

Li,

2023

Engineering in Life Sciences

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Biowaste fermentation is a promising technology for low‐carbon print bioenergy and biochemical production. Although it is believed that the microbiome determines both the fermentation efficiency and the product profiles of biowastes, the explicit mechanisms of how microbial activity controls fermentation processes remained to be unexplored. The current study investigated the microbiome dynamics and fermentation product profiles of biowaste fermentation under different organic loads (5, 20, and 40 g‐VS/L) and with additives that potentially modulate the fermentation process via methanogenesis inhibition (2‐bromoethanesulfonate) or electron transfer promotion (i.e., reduced iron, magnetite iron, and activated carbon). The overall fermentation products yields were 440, 373 and 208 CH4‐eq/g‐VS for low‐, medium‐ and high‐load fermentation. For low‐ and medium‐load fermentation, volatile fatty acids (VFAs) were first accumulated and were gradually converted to methane. For high‐load fermentation, VFAs were the main fermentation products during the entire fermentation period, accounting for 62% of all products. 16S rRNA‐based analyses showed that both 2‐bromoethanesulfonate addition and increase of organic loads inhibited the activity of methanogens and promoted the activity of distinct VFA‐producing bacterial microbiomes. Moreover, the addition of activated carbon promoted the activity of H2‐producing Bacteroides, homoacetogenic Eubacteriaceae and methanogenic Methanosarcinaceae, whose activity dynamics during the fermentation led to changes in acetate and methane production. The current results unveiled mechanisms of microbiome activity dynamics shaping the biowaste fermentation product profiles and provided the fundamental basis for the development of microbiome‐guided engineering approaches to modulate biowaste fermentation toward high‐value product recovery.

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Section: Discussionsupporting

confidence: 90%

Microbiome dynamics and products profiles of biowaste fermentation under different organic loads and additives

Zhu,

Li,

2023

Engineering in Life Sciences

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“…The presence of specific taxa (amplicon sequencing), proteins (metaproteomics) or metabolites (metabolomics) could explain the outcome of AD, and engineered microbial processes in more detail. For example, the presence (amplicon sequencing) and activity (metaproteomics) of certain methanogens could clarify the key pathways in the AD process (Vanwonterghem et al, 2014), and metabolomics could confirm the degradation of key metabolites (Cardona et al, 2020). Such functional information cannot be deducted from cytometric fingerprints directly.…”

Section: Cytometric Fingerprinting As a Valid Methods To Monitor The Anaerobic Digestion Microbiomementioning

confidence: 99%

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

Vrieze

Heyer

Props

et al. 2021

Preprint

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The anaerobic digestion microbiome has been puzzling us since the dawn of molecular methods for mixed microbial community analysis. Monitoring of the anaerobic digestion microbiome can either take place via a non-targeted holistic evaluation of the microbial community through fingerprinting or by targeted monitoring of selected taxa. Here, we compared four different microbial community fingerprinting methods, i.e., amplicon sequencing, metaproteomics, metabolomics and cytomics, in their ability to characterise the full-scale anaerobic digestion microbiome. Cytometric fingerprinting through cytomics reflects a, for anaerobic digestion, novel, single cell-based approach of direct microbial community fingerprinting by flow cytometry. Three different digester types, i.e., sludge digesters, digesters treating agro-industrial waste and dry anaerobic digesters, each reflected different operational parameters. The α-diversity analysis yielded inconsistent results, especially for richness, across the different methods. In contrast, β-diversity analysis resulted in comparable profiles, even when translated into phyla or functions, with clear separation of the three digester types. In-depth analysis of each method's features i.e., operational taxonomic units, metaproteins, metabolites, and cytometric traits, yielded certain similar features, yet, also some clear differences between the different methods, which was related to the complexity of the anaerobic digestion process. In conclusion, cytometric fingerprinting through flow cytometry is a reliable, fast method for holistic monitoring of the anaerobic digestion microbiome, and the complementary identification of key features through other methods could give rise to a direct interpretation of anaerobic digestion process performance.

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“…The LC-MS metabolomics analysis resulted in 476 features (peak areas relative to putative metabolites), while 1,145 different Operational Taxonomic Units (OTUs, counts representative of microorganisms) were detected in the 16S rRNA metataxonomics analysis. More details about the experimental part can be found in Cardona et al (2020) [28].…”

Section: Tested Datasetsmentioning

confidence: 99%

Rearrangement of incomplete multi-omics datasets combined with ComDim for evaluating replicate cross-platform variability and batch influence

Puig‐Castellví

Bouveresse

Mazéas

et al. 2021

Chemometrics and Intelligent Laboratory Systems

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Integrative Analyses to Investigate the Link between Microbial Activity and Metabolite Degradation during Anaerobic Digestion

Abstract: TitleIntegrative analyses to investigate the link between microbial activity and metabolites degradation during anaerobic digestion

Cited by 17 publications

References 70 publications

Microbiome dynamics and products profiles of biowaste fermentation under different organic loads and additives

Microbiome dynamics and products profiles of biowaste fermentation under different organic loads and additives

Triangulation of microbial fingerprinting in anaerobic digestion reveals consistent fingerprinting profiles

Rearrangement of incomplete multi-omics datasets combined with ComDim for evaluating replicate cross-platform variability and batch influence

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