Dataset Information

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

ABSTRACT: The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters. Microbial communities were analyzed regarding their taxonomic composition, functional potential, as well as functions expressed on the proteome level. Different abundances of genes and enzymes related to the biogas process could be mostly attributed to different process parameters. Individual MAGs exhibiting different abundances in the digesters were studied in detail, and their roles in the hydrolysis, acidogenesis and acetogenesis steps of anaerobic digestion could be assigned. Methanoculleus thermohydrogenotrophicum was an active hydrogenotrophic methanogen in all three digesters, whereas Methanothermobacter wolfeii was more prevalent at higher process temperatures. Further analysis focused on MAGs, which were abundant in all digesters, indicating their potential to ensure biogas process stability. The most prevalent MAG belonged to the class Limnochordia; this MAG was ubiquitous in all three digesters and exhibited activity in numerous pathways related to different steps of AD.

SUBMITTER: Hassa J

PROVIDER: S-EPMC10608942 | biostudies-literature | 2023 Sep

REPOSITORIES: biostudies-literature

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Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

Hassa Julia J Tubbesing Tom Jonas TJ Maus Irena I Heyer Robert R Benndorf Dirk D Effenberger Mathias M Henke Christian C Osterholz Benedikt B Beckstette Michael M Pühler Alfred A Sczyrba Alexander A Schlüter Andreas A

Microorganisms 20230927 10

The current focus on renewable energy in global policy highlights the importance of methane production from biomass through anaerobic digestion (AD). To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies become more important. In this study, metagenomes and metaproteomes were used for metagenomically assembled genome (MAG)-centric analyses to investigate a full-scale biogas plant consisting of three differentially operated digesters. Microb ...[more]

PMID: 37894070

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Project description:Current developments have led to a reconsidering of energy policy in many countries with the aim of increasing the share of renewable energies in the energy supply, where the anaerobic digestion (AD) of biomass to produce methane also plays an important role. To improve biomass digestion while ensuring overall process stability, microbiome-based management strategies became more important. By applying combined metagenome and metaproteome, as well as metagenomically assembled genome (MAG)-centric analyses, it is possible to determine not only the functional potential but also the expressed functions of the entire microbial community and also individual MAGs. This approach was used in this study for the production-scale biogas plant 35 (BP35) consisting of three digesters which were operated differently regarding process temperatures, feedstocks and other process parameters. Different process conditions were hypothesized to result in specific microbiome adaptations and differentially abundant metabolic functions in the digesters. Based on metagenomic single-read analyses, several taxa residing in the three digesters of BP35 were shown to correlate with the corresponding substrates and temperatures. In particular, the genus Defluviitoga showed the strongest correlation to the process temperature and the genus Acetomicrobium featured a direct correlation to the concentartions of different acids including acetic acid. Analysis of the functional potential and expressed functions of the entire microbial community of the three digesters revealed that the genes and key enzymes relevant for the biogas process were present and also expressed. Differences between the abundances of certain genes and expressed enzymes could be related to the specific parameters of the corresponding digesters. Regarding the biogas related metabolic pathways, MAG-centric metagenomics and metaproteomics indicated the functional potential and the actual expressed metabolic functions of certain MAGs that are differentially abundant in the three digesters. These MAGs, belonging to the phylum Firmicutes, the class Bacilli and the orders Caldicoprobacterales and Bacteroidales showed a specific metabolic activity within the three digesters and have important roles in the hydrolysis, acidogenesis or acetogenesis of the anaerobic digestion process. An archaeal MAG assigned to the species Methanothermobacter wolfeii was the most abundant and highly active hydrogenotrophic methanogen in digester 3 featuring an operation temperature of 54 °C. Beside the MAGs that were differentially abundant in the three digesters, also MAGs which were more evenly distributed were analyzed. The most abundant and highly active MAG in all digesters belongs to the class Limnochordia and was shown to be ubiquitous in all three digesters and exhibit activity in a variety of pathways representing hydrolysis as well as the acido- and acetogenesis steps of the biogas process. Other MAGs assigned to the phylum Firmicutes, genus Acetomicrobium and the hydrogenotrophic species Methanoculleus thermohydrogenotrophicum were also shown to be more evenly distributed and active in the three digesters. Corresponding taxa appeared to be more resilient to the different process parameters of the three digesters, and therefore, may support a stable biogas process. Overall, the combined metagenome and metaproteome analysis of biogas digesters helps to gain deeper insights into the composition of the whole microbial community, biogas related pathways and their expression, which could contribute to an improved microbiome-based process management in the future.

Project description:In this work, two BONCAT enrichment techniques were evaluated against a conventional untargeted metaproteomics approach for their ability to enrich the SIP signal of SAOB in metaproteomics data from an anaerobic microbiome. The first BONCAT enrichment was based on sorting active cells using fluorescent activated cell sorting (FACS) prior to protein extraction for mass spectrometry. The second BONCAT technique involved protein extraction from bulk biomass followed by purification of newly-translated proteins using click chemistry and a biotin-streptavidin bead pulldown assay prior to preparation for mass spectrometry. We found that both of these techniques improved detection of a highly-active and low-abundance syntrophic bacterium that was responsible for significant acetate turnover within the study full-scale biogas facility. The BONCAT-SIP approaches described here therefore represent a powerful toolbox for unraveling the contributions of active microorganisms to microbial communities--a facet of microbial ecology that holds great potential for improving our comprehension of the untapped metabolic potentials contained within microbiomes. Mass spectra data were processed using quantms v1.3.1 of the nf-core collection of workflows, utilizing reproducible software environments from the Bioconda and Biocontainers projects and tools from OpenMS v3.2.0. The workflow was executed with Nextflow v24.04.4. Both 12C-acetate (non-SIP) and 13C-acetate (SIP) samples from all metaproteomic methods were treated identically for peptide identification. Mass spectra were searched against the metagenome-derived protein database using both MSGF+ v2021.03.22 and Comet v2023.01. A target-decoy competition strategy was employed to estimate the rate of false positive peptide-spectrum matches (PSMs). Mass tolerances were set to 5 ppm for precursor (peptide) ions and 0.03 Da for fragment ions. Up to two missed cleavages were allowed and peptide termini were required to match the tryptic cleavage conditions fully. The precursor charge was limited to 2-4 and the peptide length was limited to 6-40. The PSMs were then rescored using Percolator v3.05.0. The two search engine results were combined by retaining only the peptide sequence with the highest E-value for each spectrum and the consensus list of PSMs was filtered with a false discovery rate (FDR) threshold of 10% to reduce decoy and false positive matches. Quantification of peptides was performed on the 12C-acetate (non-SIP) samples using the OpenMS tool, proteomicsLFQ. Peptide intensities were scaled such that the median peptide intensity in every sample was equal. The peptides are then evaluated for uniqueness and used for protein inference. The quantification results were filtered with a protein FDR of 1% and a PSM FDR of 1%. Detection of isotopically labeled peptides in the labeled condition (13C-acetate) was performed using MetaProSIP v2.3.0 as implemented in OpenMS v2.8.0 in a KNIME Analytics Platform v4.6.3 workflow. The unlabeled condition (12C-acetate) paired samples were used to identify coeluting isotopologues in the labeled condition (13C-acetate).

Project description:Bovine mastitis is a multi-etiological and complex disease, resulting in serious economic consequences for dairy farmers and industry. In recent years, the microbiological evaluation of raw milk has been investigated in-depth using next-generation sequencing approaches such as metataxonomic analysis. Despite this, host DNA is a major concern in the shotgun metagenomic sequencing of microbial communities in milk samples, and it represents a big challenge. In this study, we aimed to evaluate different methods for host DNA depletion and/or microbial DNA enrichment and assess the use of PCR-based whole genome amplification in milk samples with high somatic cell count (SCC) by using short- and long-read sequencing technologies. Our results evidenced that DNA extraction performed differently in terms of host DNA removal, impacting metagenome composition and functional profiles.. Moreover, the ratio of SCC/bacteria ultimately impacts microbial DNA yield, and samples with low SCC (SCC below 100,000 cells/mL) are the most problematic. When milk samples with high SCC (SCC above 200,000 cells/mL) underwent multiple-displacement amplification (MDA), we successfully recovered high-quality metagenome-assembled genomes (MAGs), and long-read sequencing was feasible even for samples with low DNA concentration. By associating MDA and short-read sequencing, we recovered two times more MAGs than in untreated samples, and an ongoing co-infection not reported by traditional methods was detected for mastitis pathogen. Overall, this new approach will improve the detection of mastitis-associated microorganisms and make it possible to examine host-microbiome interactions in bovine mastitis.IMPORTANCENext-generation sequencing technologies have been widely used to gain new insights into the diversity of the microbial community of milk samples and dairy products for different purposes such as microbial safety, profiling of starter cultures, and host-microbiome interactions. Milk is a complex food matrix, and additionally, the presence of host nucleic acid sequences is considered a contaminant in untargeted high-throughput sequencing studies. Therefore, genomic-centric metagenomic studies of milk samples focusing on the health-disease status in dairy cattle are still scarce, which makes it difficult to evaluate the microbial ecophysiology of bovine hindmilk. This study provides an alternative method for genome-centric metagenome studies applied to hindmilk samples with high somatic cell content, which is indispensable to examining host-microbiome interactions in bovine mastitis.

Project description:BackgroundDecomposition of biomass for biogas production can be practiced under wet and dry fermentation conditions. In contrast to the dry fermentation technology, wet fermentation is characterized by a high liquid content and a relatively low total solid content. In this study, the composition and functional potential of a biogas-producing microbial community in an agricultural biogas reactor operating under wet fermentation conditions was analyzed by a metagenomic approach applying 454-pyrosequencing. The obtained metagenomic dataset and corresponding 16S rRNA gene amplicon sequences were compared to the previously sequenced comparable metagenome from a dry fermentation process, meeting explicitly identical boundary conditions regarding sample and community DNA preparation, sequencing technology, processing of sequence reads and data analyses by bioinformatics tools.ResultsHigh-throughput metagenome sequencing of community DNA from the wet fermentation process applying the pyrosequencing approach resulted in 1,532,780 reads, with an average read length of 397 bp, accounting for approximately 594 million bases of sequence information in total. Taxonomic comparison of the communities from wet and dry fermentation revealed similar microbial profiles with Bacteria being the predominant superkingdom, while the superkingdom Archaea was less abundant. In both biogas plants, the bacterial phyla Firmicutes, Bacteroidetes, Spirochaetes and Proteobacteria were identified with descending frequencies. Within the archaeal superkingdom, the phylum Euryarchaeota was most abundant with the dominant class Methanomicrobia. Functional profiles of the communities revealed that environmental gene tags representing methanogenesis enzymes were present in both biogas plants in comparable frequencies. 16S rRNA gene amplicon high-throughput sequencing disclosed differences in the sub-communities comprising methanogenic Archaea between both processes. Fragment recruitments of metagenomic reads to the reference genome of the archaeon Methanoculleus bourgensis MS2(T) revealed that dominant methanogens within the dry fermentation process were highly related to the reference.ConclusionsAlthough process parameters, substrates and technology differ between the wet and dry biogas fermentations analyzed in this study, community profiles are very similar at least at higher taxonomic ranks, illustrating that core community taxa perform key functions in biomass decomposition and methane synthesis. Regarding methanogenesis, Archaea highly related to the type strain M. bourgensis MS2(T) dominate the dry fermentation process, suggesting the adaptation of members belonging to this species to specific fermentation process parameters.

Dataset Information

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

Publications

Uncovering Microbiome Adaptations in a Full-Scale Biogas Plant: Insights from MAG-Centric Metagenomics and Metaproteomics.

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