Dataset Information

Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

ABSTRACT: Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on the GS FLX platform. Taxonomic profiling based on 16S rRNA-specific sequences and an Environmental Gene Tag (EGT) analysis employing CARMA demonstrated that both approaches benefit from the longer read lengths obtained on the Titanium platform. Results confirmed Clostridia as the most prevalent taxonomic class, whereas species of the order Methanomicrobiales are dominant among methanogenic Archaea. However, the analyses also identified additional taxa that were missed by the previous study, including members of the genera Streptococcus, Acetivibrio, Garciella, Tissierella, and Gelria, which might also play a role in the fermentation process leading to the formation of methane. Taking advantage of the CARMA feature to correlate taxonomic information of sequences with their assigned functions, it appeared that Firmicutes, followed by Bacteroidetes and Proteobacteria, dominate within the functional context of polysaccharide degradation whereas Methanomicrobiales represent the most abundant taxonomic group responsible for methane production. Clostridia is the most important class involved in the reductive CoA pathway (Wood-Ljungdahl pathway) that is characteristic for acetogenesis. Based on binning of 16S rRNA-specific sequences allocated to the dominant genus Methanoculleus, it could be shown that this genus is represented by several different species. Phylogenetic analysis of these sequences placed them in close proximity to the hydrogenotrophic methanogen Methanoculleus bourgensis. While rarefaction analyses still indicate incomplete coverage, examination of the GS FLX Titanium dataset resulted in the identification of additional genera and functional elements, providing a far more complete coverage of the community involved in anaerobic fermentative pathways leading to methane formation.

SUBMITTER: Jaenicke S

PROVIDER: S-EPMC3027613 | biostudies-literature | 2011

REPOSITORIES: biostudies-literature

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Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

Jaenicke Sebastian S Ander Christina C Bekel Thomas T Bisdorf Regina R Dröge Marcus M Gartemann Karl-Heinz KH Jünemann Sebastian S Kaiser Olaf O Krause Lutz L Tille Felix F Zakrzewski Martha M Pühler Alfred A Schlüter Andreas A Goesmann Alexander A

PloS one 20110126 1

Biogas production from renewable resources is attracting increased attention as an alternative energy source due to the limited availability of traditional fossil fuels. Many countries are promoting the use of alternative energy sources for sustainable energy production. In this study, a metagenome from a production-scale biogas fermenter was analysed employing Roche's GS FLX Titanium technology and compared to a previous dataset obtained from the same community DNA sample that was sequenced on ...[more]

PMID: 21297863

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Project description:BackgroundA solid-state anaerobic digestion method is used to produce biogas from various solid wastes in China but the efficiency of methane production requires constant improvement. The diversity and abundance of relevant microorganisms play important roles in methanogenesis of biomass. The next-generation high-throughput pyrosequencing platform (Roche/454 GS FLX Titanium) provides a powerful tool for the discovery of novel microbes within the biogas-generating microbial communities.ResultsTo improve the power of our metagenomic analysis, we first evaluated five different protocols for extracting total DNA from biogas-producing mesophilic solid-state fermentation materials and then chose two high-quality protocols for a full-scale analysis. The characterization of both sequencing reads and assembled contigs revealed that the most prevalent microbes of the fermentation materials are derived from Clostridiales (Firmicutes), which contribute to degrading both protein and cellulose. Other important bacterial species for decomposing fat and carbohydrate are Bacilli, Gammaproteobacteria, and Bacteroidetes (belonging to Firmicutes, Proteobacteria, and Bacteroidetes, respectively). The dominant bacterial species are from six genera: Clostridium, Aminobacterium, Psychrobacter, Anaerococcus, Syntrophomonas, and Bacteroides. Among them, abundant Psychrobacter species, which produce low temperature-adaptive lipases, and Anaerococcus species, which have weak fermentation capabilities, were identified for the first time in biogas fermentation. Archaea, represented by genera Methanosarcina, Methanosaeta and Methanoculleus of Euryarchaeota, constitute only a small fraction of the entire microbial community. The most abundant archaeal species include Methanosarcina barkeri fusaro, Methanoculleus marisnigri JR1, and Methanosaeta theromphila, and all are involved in both acetotrophic and hydrogenotrophic methanogenesis.ConclusionsThe identification of new bacterial genera and species involved in biogas production provides insights into novel designs of solid-state fermentation under mesophilic or low-temperature conditions.

Project description:BackgroundLong reads have gained popularity in the analysis of metagenomics data. Therefore, we comprehensively assessed metagenomics classification tools on the species taxonomic level. We analysed kmer-based tools, mapping-based tools and two general-purpose long reads mappers. We evaluated more than 20 pipelines which use either nucleotide or protein databases and selected 13 for an extensive benchmark. We prepared seven synthetic datasets to test various scenarios, including the presence of a host, unknown species and related species. Moreover, we used available sequencing data from three well-defined mock communities, including a dataset with abundance varying from 0.0001 to 20% and six real gut microbiomes.ResultsGeneral-purpose mappers Minimap2 and Ram achieved similar or better accuracy on most testing metrics than best-performing classification tools. They were up to ten times slower than the fastest kmer-based tools requiring up to four times less RAM. All tested tools were prone to report organisms not present in datasets, except CLARK-S, and they underperformed in the case of the high presence of the host's genetic material. Tools which use a protein database performed worse than those based on a nucleotide database. Longer read lengths made classification easier, but due to the difference in read length distributions among species, the usage of only the longest reads reduced the accuracy. The comparison of real gut microbiome datasets shows a similar abundance profiles for the same type of tools but discordance in the number of reported organisms and abundances between types. Most assessments showed the influence of database completeness on the reports.ConclusionThe findings indicate that kmer-based tools are well-suited for rapid analysis of long reads data. However, when heightened accuracy is essential, mappers demonstrate slightly superior performance, albeit at a considerably slower pace. Nevertheless, a combination of diverse categories of tools and databases will likely be necessary to analyse complex samples. Discrepancies observed among tools when applied to real gut datasets, as well as a reduced performance in cases where unknown species or a significant proportion of the host genome is present in the sample, highlight the need for continuous improvement of existing tools. Additionally, regular updates and curation of databases are important to ensure their effectiveness.

Project description:BackgroundRNA viruses infecting a host usually exist as a set of closely related sequences, referred to as quasispecies. The genomic diversity of viral quasispecies is a subject of great interest, particularly for chronic infections, since it can lead to resistance to existing therapies. High-throughput sequencing is a promising approach to characterizing viral diversity, but unfortunately standard assembly software was originally designed for single genome assembly and cannot be used to simultaneously assemble and estimate the abundance of multiple closely related quasispecies sequences.ResultsIn this paper, we introduce a new Viral Spectrum Assembler (ViSpA) method for quasispecies spectrum reconstruction and compare it with the state-of-the-art ShoRAH tool on both simulated and real 454 pyrosequencing shotgun reads from HCV and HIV quasispecies. Experimental results show that ViSpA outperforms ShoRAH on simulated error-free reads, correctly assembling 10 out of 10 quasispecies and 29 sequences out of 40 quasispecies. While ShoRAH has a significant advantage over ViSpA on reads simulated with sequencing errors due to its advanced error correction algorithm, ViSpA is better at assembling the simulated reads after they have been corrected by ShoRAH. ViSpA also outperforms ShoRAH on real 454 reads. Indeed, 7 most frequent sequences reconstructed by ViSpA from a real HCV dataset are viable (do not contain internal stop codons), and the most frequent sequence was within 1% of the actual open reading frame obtained by cloning and Sanger sequencing. In contrast, only one of the sequences reconstructed by ShoRAH is viable. On a real HIV dataset, ShoRAH correctly inferred only 2 quasispecies sequences with at most 4 mismatches whereas ViSpA correctly reconstructed 5 quasispecies with at most 2 mismatches, and 2 out of 5 sequences were inferred without any mismatches. ViSpA source code is available at http://alla.cs.gsu.edu/~software/VISPA/vispa.html.ConclusionsViSpA enables accurate viral quasispecies spectrum reconstruction from 454 pyrosequencing reads. We are currently exploring extensions applicable to the analysis of high-throughput sequencing data from bacterial metagenomic samples and ecological samples of eukaryote populations.

Project description:BackgroundThe Antarctic krill Euphausia superba is a keystone species in the Antarctic food chain. Not only is it a significant grazer of phytoplankton, but it is also a major food item for charismatic megafauna such as whales and seals and an important Southern Ocean fisheries crop. Ecological data suggest that this species is being affected by climate change and this will have considerable consequences for the balance of the Southern Ocean ecosystem. Hence, understanding how this organism functions is a priority area and will provide fundamental data for life history studies, energy budget calculations and food web models.Methodology/principal findingsThe assembly of the 454 transcriptome of E. superba resulted in 22,177 contigs with an average size of 492bp (ranging between 137 and 8515bp). In depth analysis of the data revealed an extensive catalogue of the cellular chaperone systems and the major antioxidant proteins. Full length sequences were characterised for the chaperones HSP70, HSP90 and the super-oxide dismutase antioxidants, with the discovery of potentially novel duplications of these genes. The sequence data contained 41,470 microsatellites and 17,776 Single Nucleotide Polymorphisms (SNPs/INDELS), providing a resource for population and also gene function studies.ConclusionsThis paper details the first 454 generated data for a pelagic Antarctic species or any pelagic crustacean globally. The classical "stress proteins", such as HSP70, HSP90, ferritin and GST were all highly expressed. These genes were shown to be over expressed in the transcriptomes of Antarctic notothenioid fish and hypothesized as adaptations to living in the cold, with the associated problems of decreased protein folding efficiency and increased vulnerability to damage by reactive oxygen species. Hence, these data will provide a major resource for future physiological work on krill, but in particular a suite of "stress" genes for studies understanding marine ectotherms' capacities to cope with environmental change.

Dataset Information

Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

Publications

Comparative and joint analysis of two metagenomic datasets from a biogas fermenter obtained by 454-pyrosequencing.

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