Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant
Bremges A, Maus I, Belmann P, Eikmeyer FG, Winkler A, Albersmeier A, Pühler A, Schlüter A, Sczyrba A (2015)
GigaScience 4(1): 33.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Einrichtung
Centrum für Biotechnologie > Graduate Center > Graduate Cluster Industrial Biotechnology
Centrum für Biotechnologie > Arbeitsgruppe A. Pühler
Technische Fakultät > Computational Metagenomics
Centrum für Biotechnologie > Arbeitsgruppe A. Sczyrba
Technische Fakultät > Int. Graduiertenkolleg DiDy (GRK 1906)
Centrum für Biotechnologie > Arbeitsgruppe A. Pühler
Technische Fakultät > Computational Metagenomics
Centrum für Biotechnologie > Arbeitsgruppe A. Sczyrba
Technische Fakultät > Int. Graduiertenkolleg DiDy (GRK 1906)
Abstract / Bemerkung
Background
The production of biogas takes place under anaerobic conditions and involves microbial decomposition of organic matter. Most of the participating microbes are still unknown and non-cultivable. Accordingly, shotgun metagenome sequencing currently is the method of choice to obtain insights into community composition and the genetic repertoire.
Findings
Here, we report on the deeply sequenced metagenome and metatranscriptome of a complex biogas-producing microbial community from an agricultural production-scale biogas plant. We assembled the metagenome and, as an example application, show that we reconstructed most genes involved in the methane metabolism, a key pathway involving methanogenesis performed by methanogenic Archaea. This result indicates that there is sufficient sequencing coverage for most downstream analyses.
Conclusions
Sequenced at least one order of magnitude deeper than previous studies, our metagenome data will enable new insights into community composition and the genetic potential of important community members. Moreover, mapping of transcripts to reconstructed genome sequences will enable the identification of active metabolic pathways in target organisms.
Stichworte
Biogas;
Metatranscriptomics;
Sequencing;
Metagenomics;
Anaerobic digestion;
Wet fermentation;
Methanogenesis;
Assembly
Erscheinungsjahr
2015
Zeitschriftentitel
GigaScience
Band
4
Ausgabe
1
Art.-Nr.
33
ISSN
2047-217x
eISSN
2047-217X
Finanzierungs-Informationen
Open-Access-Publikationskosten wurden durch die Deutsche Forschungsgemeinschaft und die Universität Bielefeld gefördert.
Page URI
https://pub.uni-bielefeld.de/record/2764906
Zitieren
Bremges A, Maus I, Belmann P, et al. Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. GigaScience. 2015;4(1): 33.
Bremges, A., Maus, I., Belmann, P., Eikmeyer, F. G., Winkler, A., Albersmeier, A., Pühler, A., et al. (2015). Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. GigaScience, 4(1), 33. https://doi.org/10.1186/s13742-015-0073-6
Bremges, Andreas, Maus, Irena, Belmann, Peter, Eikmeyer, Felix Gregor, Winkler, Anika, Albersmeier, Andreas, Pühler, Alfred, Schlüter, Andreas, and Sczyrba, Alexander. 2015. “Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant”. GigaScience 4 (1): 33.
Bremges, A., Maus, I., Belmann, P., Eikmeyer, F. G., Winkler, A., Albersmeier, A., Pühler, A., Schlüter, A., and Sczyrba, A. (2015). Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. GigaScience 4:33.
Bremges, A., et al., 2015. Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. GigaScience, 4(1): 33.
A. Bremges, et al., “Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant”, GigaScience, vol. 4, 2015, : 33.
Bremges, A., Maus, I., Belmann, P., Eikmeyer, F.G., Winkler, A., Albersmeier, A., Pühler, A., Schlüter, A., Sczyrba, A.: Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant. GigaScience. 4, : 33 (2015).
Bremges, Andreas, Maus, Irena, Belmann, Peter, Eikmeyer, Felix Gregor, Winkler, Anika, Albersmeier, Andreas, Pühler, Alfred, Schlüter, Andreas, and Sczyrba, Alexander. “Deeply sequenced metagenome and metatranscriptome of a biogas-producing microbial community from an agricultural production-scale biogas plant”. GigaScience 4.1 (2015): 33.
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Dieses Objekt ist durch das Urheberrecht und/oder verwandte Schutzrechte geschützt. [...]
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2019-09-06T09:18:32Z
MD5 Prüfsumme
07f10816b0a904387b82cefb0167363c
Daten bereitgestellt von European Bioinformatics Institute (EBI)
16 Zitationen in Europe PMC
Daten bereitgestellt von Europe PubMed Central.
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Grohmann A, Fehrmann S, Vainshtein Y, Haag NL, Wiese F, Stevens P, Naegele HJ, Oechsner H, Hartsch T, Sohn K, Grumaz C., Bioresour Technol 247(), 2018
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Targeted in situ metatranscriptomics for selected taxa from mesophilic and thermophilic biogas plants.
Stolze Y, Bremges A, Maus I, Pühler A, Sczyrba A, Schlüter A., Microb Biotechnol 11(4), 2018
PMID: 29205917
Stolze Y, Bremges A, Maus I, Pühler A, Sczyrba A, Schlüter A., Microb Biotechnol 11(4), 2018
PMID: 29205917
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PMID: 29659545
Metagenome, metatranscriptome, and metaproteome approaches unraveled compositions and functional relationships of microbial communities residing in biogas plants.
Hassa J, Maus I, Off S, Pühler A, Scherer P, Klocke M, Schlüter A., Appl Microbiol Biotechnol 102(12), 2018
PMID: 29713790
Hassa J, Maus I, Off S, Pühler A, Scherer P, Klocke M, Schlüter A., Appl Microbiol Biotechnol 102(12), 2018
PMID: 29713790
Comparative analysis of deep sequenced methanogenic communities: identification of microorganisms responsible for methane production.
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PMID: 30572955
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A novel archaeal species belonging to Methanoculleus genus identified via de-novo assembly and metagenomic binning process in biogas reactors.
Kougias PG, Campanaro S, Treu L, Zhu X, Angelidaki I., Anaerobe 46(), 2017
PMID: 28219787
Kougias PG, Campanaro S, Treu L, Zhu X, Angelidaki I., Anaerobe 46(), 2017
PMID: 28219787
Genomics and prevalence of bacterial and archaeal isolates from biogas-producing microbiomes.
Maus I, Bremges A, Stolze Y, Hahnke S, Cibis KG, Koeck DE, Kim YS, Kreubel J, Hassa J, Wibberg D, Weimann A, Off S, Stantscheff R, Zverlov VV, Schwarz WH, König H, Liebl W, Scherer P, McHardy AC, Sczyrba A, Klocke M, Pühler A, Schlüter A., Biotechnol Biofuels 10(), 2017
PMID: 29158776
Maus I, Bremges A, Stolze Y, Hahnke S, Cibis KG, Koeck DE, Kim YS, Kreubel J, Hassa J, Wibberg D, Weimann A, Off S, Stantscheff R, Zverlov VV, Schwarz WH, König H, Liebl W, Scherer P, McHardy AC, Sczyrba A, Klocke M, Pühler A, Schlüter A., Biotechnol Biofuels 10(), 2017
PMID: 29158776
Metagenomic analysis and functional characterization of the biogas microbiome using high throughput shotgun sequencing and a novel binning strategy.
Campanaro S, Treu L, Kougias PG, De Francisci D, Valle G, Angelidaki I., Biotechnol Biofuels 9(), 2016
PMID: 26839589
Campanaro S, Treu L, Kougias PG, De Francisci D, Valle G, Angelidaki I., Biotechnol Biofuels 9(), 2016
PMID: 26839589
Deeper insight into the structure of the anaerobic digestion microbial community; the biogas microbiome database is expanded with 157 new genomes.
Treu L, Kougias PG, Campanaro S, Bassani I, Angelidaki I., Bioresour Technol 216(), 2016
PMID: 27243603
Treu L, Kougias PG, Campanaro S, Bassani I, Angelidaki I., Bioresour Technol 216(), 2016
PMID: 27243603
An integrated metagenome and -proteome analysis of the microbial community residing in a biogas production plant.
Ortseifen V, Stolze Y, Maus I, Sczyrba A, Bremges A, Albaum SP, Jaenicke S, Fracowiak J, Pühler A, Schlüter A., J Biotechnol 231(), 2016
PMID: 27312700
Ortseifen V, Stolze Y, Maus I, Sczyrba A, Bremges A, Albaum SP, Jaenicke S, Fracowiak J, Pühler A, Schlüter A., J Biotechnol 231(), 2016
PMID: 27312700
Tools and techniques for computational reproducibility.
Piccolo SR, Frampton MB., Gigascience 5(1), 2016
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Piccolo SR, Frampton MB., Gigascience 5(1), 2016
PMID: 27401684
Proteotyping of biogas plant microbiomes separates biogas plants according to process temperature and reactor type.
Heyer R, Benndorf D, Kohrs F, De Vrieze J, Boon N, Hoffmann M, Rapp E, Schlüter A, Sczyrba A, Reichl U., Biotechnol Biofuels 9(), 2016
PMID: 27462366
Heyer R, Benndorf D, Kohrs F, De Vrieze J, Boon N, Hoffmann M, Rapp E, Schlüter A, Sczyrba A, Reichl U., Biotechnol Biofuels 9(), 2016
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Identification and genome reconstruction of abundant distinct taxa in microbiomes from one thermophilic and three mesophilic production-scale biogas plants.
Stolze Y, Bremges A, Rumming M, Henke C, Maus I, Pühler A, Sczyrba A, Schlüter A., Biotechnol Biofuels 9(), 2016
PMID: 27462367
Stolze Y, Bremges A, Rumming M, Henke C, Maus I, Pühler A, Sczyrba A, Schlüter A., Biotechnol Biofuels 9(), 2016
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