• Our aim is to advance our understanding of biological systems,

    ranging from single species to multi-species systems and ecosystems,

    based on data from large-scale bioanalytical methods.

  • We develop, improve and apply

    computational methods

    for the interpretation of molecular information in biology.

  • We establish and analyse

    quantitative mathematical models.

CUBE News

  • Holovir released, HoloVir: a workflow for metaviromics in invertebrate holobionts

    14.07.16
    News

    HoloVir is a robust and flexible data analysis pipeline that provides an optimized and validated workflow for taxonomic and functional characterization of viral metagenomes derived from invertebrate holobionts. It has been ...

  • Public release of CONSPRED genome annotation pipeline

    14.07.16
    News

    CONSPRED is a prokaryotic genome annotation framework that performs various intrinsic gene predictions, homology searches, predictions of non-coding genes, and complex features and integrates all evidence into a consensus annotation.

    CONSPRED 1.28 has now been publicly released along with an applications ...

  • Dr. rer. nat. Raheleh Sheibani

    13.07.16
    Personal

    Raheleh has successfully defended her PhD thesis "ECF sigma factors: how endophytes sense the plants" this morning. The thesis was reviewed by Prof. Eva Stukenbrock, Kiel, and by Dr. Stefanie Wienkoop, University of Vienna. Congratulations, Raheleh!

  • Job opening: Group Leader Position

    27.06.16
    Personal

    The Division of Computational Systems Biology at the University of Vienna is offering a

    Group Leader Position in Bioinformatics

    CUBE - the division of Computational Systems Biology - is part of the Department of Microbiology and Ecosystem Science of the ...

Latest publications

ConsPred - a rule-based (re-)annotation framework for prokaryotic genomes.

The rapidly growing number of available prokaryotic genome sequences requires fully automated and high-quality software solutions for their initial and re-annotation. Here we present ConsPred, a prokaryotic genome annotation framework that performs intrinsic gene predictions, homology searches, predictions of non-coding genes as well as CRISPR repeats and integrates all evidence into a consensus annotation. ConsPred achieves comprehensive, high-quality annotations based on rules and priorities, similar to decision-making in manual curation and avoids conflicting predictions. Parameters controlling the annotation process are configurable by the user. ConsPred has been used in the institutions of the authors for longer than 5 years and can easily be extended and adapted to specific needs.
The ConsPred algorithm for producing a consensus from the varying scores of multiple gene prediction programs approaches manual curation in accuracy. Its rule-based approach for choosing final predictions avoids overriding previous manual curations.Implementation and availability: ConsPred is implemented in Java, Perl, and Shell and is freely available under the Creative Commons license as a stand-alone in-house pipeline or as an Amazon Machine Image for cloud computing, see https://sourceforge.net/projects/conspred/.

Weinmaier T, Platzer A, Frank J, Hellinger HJ, Tischler P, Rattei T
2016 - Bioinformatics, in press

HoloVir: A Workflow for Investigating the Diversity and Function of Viruses in Invertebrate Holobionts.

Abundant bioinformatics resources are available for the study of complex microbial metagenomes, however their utility in viral metagenomics is limited. HoloVir is a robust and flexible data analysis pipeline that provides an optimized and validated workflow for taxonomic and functional characterization of viral metagenomes derived from invertebrate holobionts. Simulated viral metagenomes comprising varying levels of viral diversity and abundance were used to determine the optimal assembly and gene prediction strategy, and multiple sequence assembly methods and gene prediction tools were tested in order to optimize our analysis workflow. HoloVir performs pairwise comparisons of single read and predicted gene datasets against the viral RefSeq database to assign taxonomy and additional comparison to phage-specific and cellular markers is undertaken to support the taxonomic assignments and identify potential cellular contamination. Broad functional classification of the predicted genes is provided by assignment of COG microbial functional category classifications using EggNOG and higher resolution functional analysis is achieved by searching for enrichment of specific Swiss-Prot keywords within the viral metagenome. Application of HoloVir to viral metagenomes from the coral Pocillopora damicornis and the sponge Rhopaloeides odorabile demonstrated that HoloVir provides a valuable tool to characterize holobiont viral communities across species, environments, or experiments.

Laffy PW, Wood-Charlson EM, Turaev D, Weynberg KD, Botté ES, van Oppen MJ, Webster NS, Rattei T
2016 - Front Microbiol, 822

Deep metagenome and metatranscriptome analyses of microbial communities affiliated with an industrial biogas fermenter, a cow rumen, and elephant feces reveal major differences in carbohydrate hydrolysis strategies.

The diverse microbial communities in agricultural biogas fermenters are assumed to be well adapted for the anaerobic transformation of plant biomass to methane. Compared to natural systems, biogas reactors are limited in their hydrolytic potential. The reasons for this are not understood.
In this paper, we show that a typical industrial biogas reactor fed with maize silage, cow manure, and chicken manure has relatively lower hydrolysis rates compared to feces samples from herbivores. We provide evidence that on average, 2.5 genes encoding cellulolytic GHs/Mbp were identified in the biogas fermenter compared to 3.8 in the elephant feces and 3.2 in the cow rumen data sets. The ratio of genes coding for cellulolytic GH enzymes affiliated with the Firmicutes versus the Bacteroidetes was 2.8:1 in the biogas fermenter compared to 1:1 in the elephant feces and 1.4:1 in the cow rumen sample. Furthermore, RNA-Seq data indicated that highly transcribed cellulases in the biogas fermenter were four times more often affiliated with the Firmicutes compared to the Bacteroidetes, while an equal distribution of these enzymes was observed in the elephant feces sample.
Our data indicate that a relatively lower abundance of bacteria affiliated with the phylum of Bacteroidetes and, to some extent, Fibrobacteres is associated with a decreased richness of predicted lignocellulolytic enzymes in biogas fermenters. This difference can be attributed to a partial lack of genes coding for cellulolytic GH enzymes derived from bacteria which are affiliated with the Fibrobacteres and, especially, the Bacteroidetes. The partial deficiency of these genes implies a potentially important limitation in the biogas fermenter with regard to the initial hydrolysis of biomass. Based on these findings, we speculate that increasing the members of Bacteroidetes and Fibrobacteres in biogas fermenters will most likely result in an increased hydrolytic performance.

Güllert S, Fischer MA, Turaev D, Noebauer B, Ilmberger N, Wemheuer B, Alawi M, Rattei T, Daniel R, Schmitz RA, Grundhoff A, Streit WR
2016 - Biotechnol Biofuels, 121