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Magdalena Kröber,
Thomas Bekel,
Naryttza N Diaz,
Alexander Goesmann,
Sebastian Jaenicke,
Lutz Krause,
Dimitri Miller, Kai J Runte,
Prisca Viehöver,
Alfred Pühler,
Andreas Schlüter
[show abstract]
[hide abstract]
ABSTRACT: The phylogenetic structure of the microbial community residing in a fermentation sample from a production-scale biogas plant fed with maize silage, green rye and liquid manure was analysed by an integrated approach using clone library sequences and metagenome sequence data obtained by 454-pyrosequencing. Sequencing of 109 clones from a bacterial and an archaeal 16S-rDNA amplicon library revealed that the obtained nucleotide sequences are similar but not identical to 16S-rDNA database sequences derived from different anaerobic environments including digestors and bioreactors. Most of the bacterial 16S-rDNA sequences could be assigned to the phylum Firmicutes with the most abundant class Clostridia and to the class Bacteroidetes, whereas most archaeal 16S-rDNA sequences cluster close to the methanogen Methanoculleus bourgensis. Further sequences of the archaeal library most probably represent so far non-characterised species within the genus Methanoculleus. A similar result derived from phylogenetic analysis of mcrA clone sequences. The mcrA gene product encodes the alpha-subunit of methyl-coenzyme-M reductase involved in the final step of methanogenesis. BLASTn analysis applying stringent settings resulted in assignment of 16S-rDNA metagenome sequence reads to 62 16S-rDNA amplicon sequences thus enabling frequency of abundance estimations for 16S-rDNA clone library sequences. Ribosomal Database Project (RDP) Classifier processing of metagenome 16S-rDNA reads revealed abundance of the phyla Firmicutes, Bacteroidetes and Euryarchaeota and the orders Clostridiales, Bacteroidales and Methanomicrobiales. Moreover, a large fraction of 16S-rDNA metagenome reads could not be assigned to lower taxonomic ranks, demonstrating that numerous microorganisms in the analysed fermentation sample of the biogas plant are still unclassified or unknown.
Journal of biotechnology 07/2009; 142(1):38-49. · 2.88 Impact Factor
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Michael Dondrup,
Stefan P. Albaum,
Thasso Griebel,
Kolja Henckel,
Sebastian Jünemann,
Tim Kahlke,
Christiane K. Kleindt,
Helge Küster,
Burkhard Linke,
Dominik Mertens,
Virginie Mittard-Runte,
Heiko Neuweger, Kai J. Runte,
Andreas Tauch,
Felix Tille,
Alfred Pühler,
Alexander Goesmann
BMC Bioinformatics. 01/2009; 10.
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Andreas Schlüter,
Thomas Bekel,
Naryttza N Diaz,
Michael Dondrup,
Rudolf Eichenlaub,
Karl-Heinz Gartemann,
Irene Krahn,
Lutz Krause,
Holger Krömeke,
Olaf Kruse,
Jan H Mussgnug,
Heiko Neuweger,
Karsten Niehaus,
Alfred Pühler, Kai J Runte,
Rafael Szczepanowski,
Andreas Tauch,
Alexandra Tilker,
Prisca Viehöver,
Alexander Goesmann
[show abstract]
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ABSTRACT: Composition and gene content of a biogas-producing microbial community from a production-scale biogas plant fed with renewable primary products was analysed by means of a metagenomic approach applying the ultrafast 454-pyrosequencing technology. Sequencing of isolated total community DNA on a Genome Sequencer FLX System resulted in 616,072 reads with an average read length of 230 bases accounting for 141,664,289 bases sequence information. Assignment of obtained single reads to COG (Clusters of Orthologous Groups of proteins) categories revealed a genetic profile characteristic for an anaerobic microbial consortium conducting fermentative metabolic pathways. Assembly of single reads resulted in the formation of 8752 contigs larger than 500 bases in size. Contigs longer than 10kb mainly encode house-keeping proteins, e.g. DNA polymerase, recombinase, DNA ligase, sigma factor RpoD and genes involved in sugar and amino acid metabolism. A significant portion of contigs was allocated to the genome sequence of the archaeal methanogen Methanoculleus marisnigri JR1. Mapping of single reads to the M. marisnigri JR1 genome revealed that approximately 64% of the reference genome including methanogenesis gene regions are deeply covered. These results suggest that species related to those of the genus Methanoculleus play a dominant role in methanogenesis in the analysed fermentation sample. Moreover, assignment of numerous contig sequences to clostridial genomes including gene regions for cellulolytic functions indicates that clostridia are important for hydrolysis of cellulosic plant biomass in the biogas fermenter under study. Metagenome sequence data from a biogas-producing microbial community residing in a fermenter of a biogas plant provide the basis for a rational approach to improve the biotechnological process of biogas production.
Journal of Biotechnology 06/2008; 136(1-2):77-90. · 3.05 Impact Factor
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Michael Dondrup,
Stefan P Albaum,
Thasso Griebel,
Kolja Henckel,
Sebastian Jünemann,
Tim Kahlke,
Christiane K Kleindt,
Helge Küster,
Burkhard Linke,
Dominik Mertens,
Virginie Mittard-Runte,
Heiko Neuweger, Kai J Runte,
Andreas Tauch,
Felix Tille,
Alfred Pühler,
Alexander Goesmann
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Michael Dondrup,
Stefan P Albaum,
Thasso Griebel,
Kolja Henckel,
Sebastian Jünemann,
Tim Kahlke,
Christiane Katja Kleindt,
Helge Küster,
Burkhard Linke,
Dominik Mertens,
Virginie Mittard-Runte,
Heiko Neuweger, Kai J Runte,
Andreas Tauch,
Felix Tille,
Alfred Pühler,
Alexander Goesmann
[show abstract]
[hide abstract]
ABSTRACT: Background: Understanding transcriptional regulation by genome-wide microarray studies can contribute to unravel complex relationships between genes. Attempts to standardize the annotation of microarray data include the Minimum Information About a Microarray Experiment (MIAME) recommendations, the MAGE-ML format for data interchange, and the use of controlled vocabularies or ontologies. The existing software systems for microarray data analysis implement the mentioned standards only partially and are often hard to use and extend. Integration of genomic annotation data and other sources of external knowledge using open standards is therefore a key requirement for future integrated analysis systems. Results: The EMMA 2 software has been designed to resolve shortcomings with respect to full MAGE-ML and ontology support and makes use of modern data integration techniques. We present a software system that features comprehensive data analysis functions for spotted arrays, and for the most common synthesized oligo arrays such as Agilent, Affymetrix and NimbleGen. The system is based on the full MAGE object model. Analysis functionality is based on R and Bioconductor packages and can make use of a compute cluster for distributed services. Conclusion: Our model-driven approach for automatically implementing a full MAGE object model provides high flexibility and compatibility. Data integration via SOAP-based web-services is advantageous in a distributed client-server environment as the collaborative analysis of microarray data is gaining more and more relevance in international research consortia. The adequacy of the EMMA 2 software design and implementation has been proven by its application in many distributed functional genomics projects. Its scalability makes the current architecture suited for extensions towards future transcriptomics methods based on high-throughput sequencing approaches which have much higher computational requirements than microarrays.
BMC Bioinformatics, 10:50.
