Cystic fibrosis (CF), the most common lethal genetic disease among Caucasians, is caused by mutations in cystic fibrosis transmembrane conductance regulator (CFTR). CFTR’s main role is to transport chloride ions across epithelial cell membranes. It also regulates many cell functions. However, the exact role of CFTR in cellular processes is not yet fully understood. It is recognized that a key factor in CFTR-related regulation is its phosphorylation state. The important kinases regulating CFTR are cAMP-dependent protein kinase A (PKA) and 5′-AMP-activated protein kinase (AMPK). PKA and AMPK have opposite effects on CFTR activity despite their highly similar structures and recognition motifs. Utilizing homology modeling, in silico mutagenesis and literature mining, we supplement available information regarding the atomic-resolution structures of PKA, AMPK and CFTR, and the complexes CFTR–PKA and CFTR–AMPK. The atomic-resolution structural predictions reveal an unexpected availability of CFTR Ser813 for phosphorylation by both PKA and AMPK. These results indicate the key role of the structural flexibility of the serine-rich R-domain in CFTR regulation by phosphorylation.Electronic supplementary materialThe online version of this article (doi:10.1007/s00894-011-1029-0) contains supplementary material, which is available to authorized users.

Biodiversity analysis of metagenomic and metatranscriptomic data acquired from nextgeneration sequencing (NGS) requires following multiple analytic steps, often independent from each other with exception of passing output files of previous step as input for the following. If parameterization of steps following one after another is independent from one another, they may be pipelined. There are three most popular pipelines used for NGS analyses: QIIME, mothur and MetAMOS. In this work we describe our extensions to the latter. One is supplementing MetAMOS' default modes with taxonomic and metabolic biodiversity using metagenomics and metatranscriptomics data and the other provides a web-based interface to run predefined analyses that is easy to integrate with laboratory information management systems.PeerJ PrePrints | https://doi.org/10.7287/peerj.preprints.1706v1 | CC-BY 4.0 Open Access | rec:

Biodiversity analysis of metagenomic and metatranscriptomic data acquired from next-generation sequencing (NGS) requires following multiple analytic steps, often independent from each other with exception of passing output files of previous step as input for the following. If parameterization of steps following one after another is independent from one another, they may be pipelined. There are three most popular pipelines used for NGS analyses: QIIME, mothur and MetAMOS. In this work we describe our extensions to the latter. One is supplementing MetAMOS’ default modes with taxonomic and metabolic biodiversity using metagenomics and metatranscriptomics data and the other provides a web-based interface to run predefined analyses that is easy to integrate with laboratory information management systems.