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Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.

ABSTRACT: BACKGROUND:Methane yield and biogas productivity of biogas plants (BGPs) depend on microbial community structure and function, substrate supply, and general biogas process parameters. So far, however, relatively little is known about correlations between microbial community function and process parameters. To close this knowledge gap, microbial communities of 40 samples from 35 different industrial biogas plants were evaluated by a metaproteomics approach in this study. RESULTS:Liquid chromatography coupled to tandem mass spectrometry (Orbitrap Elite™ Hybrid Ion Trap-Orbitrap Mass Spectrometer) of all 40 samples as triplicate enabled the identification of 3138 different metaproteins belonging to 162 biological processes and 75 different taxonomic orders. The respective database searches were performed against UniProtKB/Swiss-Prot and seven metagenome databases. Subsequent clustering and principal component analysis of these data allowed for the identification of four main clusters associated with mesophile and thermophile process conditions, the use of upflow anaerobic sludge blanket reactors and BGP feeding with sewage sludge. Observations confirm a previous phylogenetic study of the same BGP samples that was based on 16S rRNA gene sequencing by De Vrieze et al. (Water Res 75:312-323, 2015). In particular, we identified similar microbial key players of biogas processes, namely Bacillales, Enterobacteriales, Bacteriodales, Clostridiales, Rhizobiales and Thermoanaerobacteriales as well as Methanobacteriales, Methanosarcinales and Methanococcales. For the elucidation of the main biomass degradation pathways, the most abundant 1 % of metaproteins was assigned to the KEGG map 1200 representing the central carbon metabolism. Additionally, the effect of the process parameters (i) temperature, (ii) organic loading rate (OLR), (iii) total ammonia nitrogen (TAN), and (iv) sludge retention time (SRT) on these pathways was investigated. For example, high TAN correlated with hydrogenotrophic methanogens and bacterial one-carbon metabolism, indicating syntrophic acetate oxidation. CONCLUSIONS:This is the first large-scale metaproteome study of BGPs. Proteotyping of BGPs reveals general correlations between the microbial community structure and its function with process parameters. The monitoring of changes on the level of microbial key functions or even of the microbial community represents a well-directed tool for the identification of process problems and disturbances.Graphical abstractCorrelation between the different orders and process parameter, as well as principle component analysis of all investigated biogas plants based on the identified metaproteins.

SUBMITTER: Heyer R

PROVIDER: S-EPMC4960849 | biostudies-literature | 2016

REPOSITORIES: biostudies-literature

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Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.

Heyer R R Benndorf D D Kohrs F F De Vrieze J J Boon N N Hoffmann M M Rapp E E Schlüter Andreas A Sczyrba Alexander A Reichl U U

Biotechnology for biofuels 20160726

<h4>Background</h4>Methane yield and biogas productivity of biogas plants (BGPs) depend on microbial community structure and function, substrate supply, and general biogas process parameters. So far, however, relatively little is known about correlations between microbial community function and process parameters. To close this knowledge gap, microbial communities of 40 samples from 35 different industrial biogas plants were evaluated by a metaproteomics approach in this study.<h4>Results</h4>Li ...[more]

PMID: 27462366

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Project description:Coumarins are widely found in plants as natural constituents having antimicrobial activity. When considering plants that are rich in coumarins for biogas production, adverse effects on microorganisms driving the anaerobic digestion process are expected. Furthermore, coumarin derivatives, like warfarin, which are used as anticoagulating medicines, are found in wastewater, affecting its treatment. Coumarin, the structure common to all coumarins, inhibits the anaerobic digestion process. However, the details of this inhibition are still elusive. Here, we studied the impact of coumarin on acetogenesis and methanogenesis. First, coumarin was applied at four concentrations between 0.25 and 1 g · liter-1 to pure cultures of the methanogens Methanosarcina barkeri and Methanospirillum hungatei, which resulted in up to 25% less methane production. Acetate production of syntrophic propionate- and butyrate-degrading cultures of Syntrophobacter fumaroxidans and Syntrophomonas wolfei was inhibited by 72% at a coumarin concentration of 1 g · liter-1 Coumarin also inhibited acetogenesis and acetoclastic methanogenesis in a complex biogas reactor microbiome. When a coumarin-adapted microbiome was used, acetogenesis and methanogenesis were not inhibited. According to amplicon sequencing of bacterial 16S rRNA genes and mcrA genes, the communities of the two microbiomes were similar, although Methanoculleus was more abundant and Methanobacterium less abundant in the coumarin-adapted than in the nonadapted microbiome. Our results suggest that well-dosed feeding with coumarin-rich feedstocks to full-scale biogas reactors while keeping the coumarin concentrations below 0.5 g · liter-1 will allow adaptation to coumarins by structural and functional community reorganization and coumarin degradation.IMPORTANCE Coumarins from natural and anthropogenic sources have an inhibitory impact on the anaerobic digestion process. Here, we studied in detail the adverse effects of the model compound coumarin on acetogenesis and methanogenesis, which are two important steps of the anaerobic digestion process. Coumarin concentrations lower than 0.5 g · liter-1 had only a minor impact. Even though similar inhibitory effects can be assumed for coumarin derivatives, little effects on the anaerobic treatment of wastewater are expected where concentrations of coumarin derivatives are lower than 0.5 g · liter-1 However, when full-scale reactors are fed with coumarin-rich feedstocks, the biogas processes might be inhibited. Hence, these feedstocks should be utilized in a well-dosed manner or after adaptation of the microbial community.

Project description:BackgroundPlant cell walls represent the most plentiful renewable organic resource on earth, but due to their heterogeneity, complex structure and partial recalcitrance, their use as biotechnological feedstock is still limited.ResultsIn order to identify efficient enzymes for polysaccharide breakdown, we have carried out functional screening of metagenomic fosmid libraries from biogas fermenter microbial communities grown on sugar beet pulp, an arabinan-rich agricultural residue, or other sources containing microbes that efficiently depolymerize polysaccharides, using CPH (chromogenic polysaccharide hydrogel) or ICB (insoluble chromogenic biomass) labeled polysaccharide substrates. Seventy-one depolymerase-encoding genes were identified from 55 active fosmid clones by using Illumina and Sanger sequencing and dbCAN CAZyme (carbohydrate-active enzyme) annotation. An around 56 kb assembled DNA fragment putatively originating from Xylanivirga thermophila strain or a close relative was analyzed in detail. It contained 48 ORFs (open reading frames), of which 31 were assigned to sugar metabolism. Interestingly, a large number of genes for enzymes putatively involved in degradation and utilization of arabinose-containing carbohydrates were found. Seven putative arabinosyl hydrolases from this DNA fragment belonging to glycoside hydrolase (GH) families GH51 and GH43 were biochemically characterized, revealing two with endo-arabinanase activity and four with exo-α-L-arabinofuranosidase activity but with complementary cleavage properties. These enzymes were found to act synergistically and can completely hydrolyze SBA (sugar beet arabinan) and DA (debranched arabinan).ConclusionsWe screened 32,776 fosmid clones from several metagenomic libraries with chromogenic lignocellulosic substrates for functional enzymes to advance the understanding about the saccharification of recalcitrant lignocellulose. Seven putative X. thermophila arabinosyl hydrolases were characterized for pectic substrate degradation. The arabinosyl hydrolases displayed maximum activity and significant long-term stability around 50 °C. The enzyme cocktails composed in this study fully degraded the arabinan substrates and thus could serve for arabinose production in food and biofuel industries.

Project description:Background:Biogas production is an attractive technology for a sustainable generation of renewable energy. Although the microbial community is fundamental for such production, the process control is still limited to technological and chemical parameters. Currently, most of the efforts on microbial management system (MiMaS) are focused on process-specific marker species and community dynamics, but a practical implementation is in its infancy. The high number of unknown and uncharacterized microorganisms in general is one of the reasons hindering further advancements. Results:A Biogas Metagenomics Hybrid Assembly (BioMETHA) database, derived from microbiomes of biogas plants, was generated using a dedicated assembly strategy for different metagenomic datasets. Long reads from nanopore sequencing (MinION) were combined with short, more accurate second-generation sequencing reads (Illumina). The hybrid assembly resulted in 231 genomic bins each representing a taxonomic unit with an average completeness of 47%. Functional annotation identified 13,190 non-redundant genes covering roughly 207 k coding sequences. Mapping rates of metagenomics DNA derived from diverse biogas plants and laboratory reactors increased up to 73%. In addition, an EC (enzyme commission) reference sequence collection (ERSC) was generated whose genes are crucial for biogas-related processes, consisting of 235 unique EC numbers organized in 52 metabolic modules. Mapping rates of metatranscriptomic data to this ERSC revealed coverages of up to 93%. Process parameters and imbalances of laboratory reactors could be reconstructed by evaluating abundance of biogas-specific metabolic modules using metatranscriptomic data derived from various fermenter systems. Conclusion:This newly established metagenomic hybrid assembly in combination with an EC reference sequence collection might help to shed light on the microbial dark matter of biogas plants by contributing to the development of a reference for biogas plant microbiome-specific gene sequences. Considering a biogas microbiome as a complex meta-organism expressing a meta-transcriptome, the approach established here could lay the foundation for a function-based microbial management system.

Project description:BackgroundBiofuel production from conversion of biomass is indispensable in the portfolio of renewable energies. Complex microbial communities are involved in the anaerobic digestion process of plant material, agricultural residual products and food wastes. Analysis of the genetic potential and microbiology of communities degrading biomass to biofuels is considered to be the key to develop process optimisation strategies. Hence, due to the still incomplete taxonomic and functional characterisation of corresponding communities, new and unknown species are of special interest.ResultsThree mesophilic and one thermophilic production-scale biogas plants (BGPs) were taxonomically profiled using high-throughput 16S rRNA gene amplicon sequencing. All BGPs shared a core microbiome with the thermophilic BGP featuring the lowest diversity. However, the phyla Cloacimonetes and Spirochaetes were unique to BGPs 2 and 3, Fusobacteria were only found in BGP3 and members of the phylum Thermotogae were present only in the thermophilic BGP4. Taxonomic analyses revealed that these distinctive taxa mostly represent so far unknown species. The only exception is the dominant Thermotogae OTU featuring 16S rRNA gene sequence identity to Defluviitoga tunisiensis L3, a sequenced and characterised strain. To further investigate the genetic potential of the biogas communities, corresponding metagenomes were sequenced in a deepness of 347.5 Gbp in total. A combined assembly comprised 80.3 % of all reads and resulted in the prediction of 1.59 million genes on assembled contigs. Genome binning yielded genome bins comprising the prevalent distinctive phyla Cloacimonetes, Spirochaetes, Fusobacteria and Thermotogae. Comparative genome analyses between the most dominant Thermotogae bin and the very closely related Defluviitoga tunisiensis L3 genome originating from the same BGP revealed high genetic similarity. This finding confirmed applicability and reliability of the binning approach. The four highly covered genome bins of the other three distinct phyla showed low or very low genetic similarities to their closest phylogenetic relatives, and therefore indicated their novelty.ConclusionsIn this study, the 16S rRNA gene sequencing approach and a combined metagenome assembly and binning approach were used for the first time on different production-scale biogas plants and revealed insights into the genetic potential and functional role of so far unknown species.

Project description:Plant-parasitic nematodes cause considerable damage to crop plants. The rhizosphere microbiome can affect invasion and reproductive success of plant-parasitic nematodes, thus affecting plant damage. In this study, we investigated how the transplanted rhizosphere microbiome from different crops affect plant-parasitic nematodes on soybean or tomato, and whether the plant's own microbiome from the rhizosphere protects it better than the microbiome from fallow soil. Soybean plants growing in sterilized substrate were inoculated with the microbiome extracted from the rhizosphere of soybean, maize, or tomato. Controls were inoculated with extracts from bulk soil, or not inoculated. After the microbiome was established, the root lesion nematode Pratylenchus penetrans was added. Root invasion of P. penetrans was significantly reduced on soybean plants inoculated with the microbiome from maize or soybean compared to tomato or bulk soil, or the uninoculated control. In the analogous experiment with tomato plants inoculated with either P. penetrans or the root knot nematode Meloidogyne incognita, the rhizosphere microbiomes of maize and tomato reduced root invasion by P. penetrans and M. incognita compared to microbiomes from soybean or bulk soil. Reproduction of M. incognita on tomato followed the same trend, and it was best suppressed by the tomato rhizosphere microbiome. In split-root experiments with soybean and tomato plants, a systemic effect of the inoculated rhizosphere microbiomes on root invasion of P. penetrans was shown. Furthermore, some transplanted microbiomes slightly enhanced plant growth compared to uninoculated plants. The microbiomes from maize rhizosphere and bulk soil increased the fresh weights of roots and shoots of soybean plants, and microbiomes from soybean rhizosphere and bulk soil increased the fresh weights of roots and shoots of tomato plants. Nematode invasion did not affect plant growth in these short-term experiments. In conclusion, this study highlights the importance of the rhizosphere microbiome in protecting crops against plant-parasitic nematodes. An effect of pre-crops on the rhizosphere microbiome might be harnessed to enhance the resistance of crops towards plant-parasitic nematodes. However, nematode-suppressive effects of a particular microbiome may not necessarily coincide with improvement of plant growth in the absence of plant-parasitic nematodes.

Project description:Background:To elucidate biogas microbial communities and processes, the application of high-throughput DNA analysis approaches is becoming increasingly important. Unfortunately, generated data can only partialy be interpreted rudimentary since databases lack reference sequences. Results:Novel cellulolytic, hydrolytic, and acidogenic/acetogenic Bacteria as well as methanogenic Archaea originating from different anaerobic digestion communities were analyzed on the genomic level to assess their role in biomass decomposition and biogas production. Some of the analyzed bacterial strains were recently described as new species and even genera, namely Herbinix hemicellulosilytica T3/55T, Herbinix luporum SD1DT, Clostridium bornimense M2/40T, Proteiniphilum saccharofermentans M3/6T, Fermentimonas caenicola ING2-E5BT, and Petrimonas mucosa ING2-E5AT. High-throughput genome sequencing of 22 anaerobic digestion isolates enabled functional genome interpretation, metabolic reconstruction, and prediction of microbial traits regarding their abilities to utilize complex bio-polymers and to perform specific fermentation pathways. To determine the prevalence of the isolates included in this study in different biogas systems, corresponding metagenome fragment mappings were done. Methanoculleus bourgensis was found to be abundant in three mesophilic biogas plants studied and slightly less abundant in a thermophilic biogas plant, whereas Defluviitoga tunisiensis was only prominent in the thermophilic system. Moreover, several of the analyzed species were clearly detectable in the mesophilic biogas plants, but appeared to be only moderately abundant. Among the species for which genome sequence information was publicly available prior to this study, only the species Amphibacillus xylanus, Clostridium clariflavum, and Lactobacillus acidophilus are of importance for the biogas microbiomes analyzed, but did not reach the level of abundance as determined for M. bourgensis and D. tunisiensis. Conclusions:Isolation of key anaerobic digestion microorganisms and their functional interpretation was achieved by application of elaborated cultivation techniques and subsequent genome analyses. New isolates and their genome information extend the repository covering anaerobic digestion community members.

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Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.

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Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.

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