Thermal acclimation of methanotrophs from the genus Methylobacter.

Methanotrophs oxidize most of the methane (CH4) produced in natural and anthropogenic ecosystems. Often living close to soil surfaces, these microorganisms must frequently adjust to temperature change. While many environmental studies have addressed temperature effects on CH4 oxidation and methanotrophic communities, there is little knowledge about the physiological adjustments that underlie these effects. We have studied thermal acclimation in Methylobacter, a widespread, abundant, and environmentally important methanotrophic genus. Comparisons of growth and CH4 oxidation kinetics at different temperatures in three members of the genus demonstrate that temperature has a strong influence on how much CH4 is consumed to support growth at different CH4 concentrations. However, the temperature effect varies considerably between species, suggesting that how a methanotrophic community is composed influences the temperature effect on CH4 uptake. To understand thermal acclimation mechanisms widely we carried out a transcriptomics experiment with Methylobacter tundripaludum SV96T. We observed, at different temperatures, how varying abundances of transcripts for glycogen and protein biosynthesis relate to cellular glycogen and ribosome concentrations. Our data also demonstrated transcriptional adjustment of CH4 oxidation, oxidative phosphorylation, membrane fatty acid saturation, cell wall composition, and exopolysaccharides between temperatures. In addition, we observed differences in M. tundripaludum SV96T cell sizes at different temperatures. We conclude that thermal acclimation in Methylobacter results from transcriptional adjustment of central metabolism, protein biosynthesis, cell walls and storage. Acclimation leads to large shifts in CH4 consumption and growth efficiency, but with major differences between species. Thus, our study demonstrates that physiological adjustments to temperature change can substantially influence environmental CH4 uptake rates and that consideration of methanotroph physiology might be vital for accurate predictions of warming effects on CH4 emissions.

Conserved Secondary Structures in Viral mRNAs.

RNA secondary structure in untranslated and protein coding regions has been shown to play an important role in regulatory processes and the viral replication cycle. While structures in non-coding regions have been investigated extensively, a thorough overview of the structural repertoire of protein coding mRNAs, especially for viruses, is lacking. Secondary structure prediction of large molecules, such as long mRNAs remains a challenging task, as the contingent of structures a sequence can theoretically fold into grows exponentially with sequence length. We applied a structure prediction pipeline to Viral Orthologous Groups that first identifies the local boundaries of potentially structured regions and subsequently predicts their functional importance. Using this procedure, the orthologous groups were split into structurally homogenous subgroups, which we call subVOGs. This is the first compilation of potentially functional conserved RNA structures in viral coding regions, covering the complete RefSeq viral database. We were able to recover structural elements from previous studies and discovered a variety of novel structured regions. The subVOGs are available through our web resource RNASIV (RNA structure in viruses; http://rnasiv.bio.wzw.tum.de).

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

MOTIVATION: 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. SUMMARY: 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. AVAILABILITY AND IMPLEMENTATION: 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/. CONTACT: thomas.rattei@univie.ac.atSupplementary information: Supplementary data are available at Bioinformatics online.