Technical phosphoproteomic and bioinformatic tools useful in cancer research

Reversible protein phosphorylation is one of the most important forms of cellular regulation. Thus, phosphoproteomic analysis of protein phosphorylation in cells is a powerful tool to evaluate cell functional status. The importance of protein kinase-regulated signal transduction pathways in human cancer has led to the development of drugs that inhibit protein kinases at the apex or intermediary levels of these pathways. Phosphoproteomic analysis of these signalling pathways will provide important insights for operation and connectivity of these pathways to facilitate identification of the best targets for cancer therapies. Enrichment of phosphorylated proteins or peptides from tissue or bodily fluid samples is required. The application of technologies such as phosphoenrichments, mass spectrometry (MS) coupled to bioinformatics tools is crucial for the identification and quantification of protein phosphorylation sites for advancing in such relevant clinical research. A combination of different phosphopeptide enrichments, quantitative techniques and bioinformatic tools is necessary to achieve good phospho-regulation data and good structural analysis of protein studies. The current and most useful proteomics and bioinformatics techniques will be explained with research examples. Our aim in this article is to be helpful for cancer research via detailing proteomics and bioinformatic tools

(Tissue) P Systems with Vesicles of Multisets

We consider tissue P systems working on vesicles of multisets with the very simple operations of insertion, deletion, and substitution of single objects. With the whole multiset being enclosed in a vesicle, sending it to a target cell can be indicated in those simple rules working on the multiset. As derivation modes we consider the sequential mode, where exactly one rule is applied in a derivation step, and the set maximal mode, where in each derivation step a non-extendable set of rules is applied. With the set maximal mode, computational completeness can already be obtained with tissue P systems having a tree structure, whereas tissue P systems even with an arbitrary communication structure are not computationally complete when working in the sequential mode. Adding polarizations (-1, 0, 1 are sufficient) allows for obtaining computational completeness even for tissue P systems working in the sequential mode.Comment: In Proceedings AFL 2017, arXiv:1708.0622

Developmental ORIgins of Healthy and Unhealthy AgeiNg : The Role of Maternal Obesity - Introduction to DORIAN

Peer reviewe

Genome sequence of OXA-48 carbapenemase-producing Klebsiella pneumoniae KpO3210

Klebsiella pneumoniae KpO3210 is a OXA-48 carbapenemase-producing isolate obtained from a blood culture in the context of an outbreak in Hospital Universitario La Paz (Madrid, Spain) in 2010. It belongs to the major clone detected during the outbreak and is resistant to all beta-lactams and to several other antibiotics. © 2012, American Society for Microbiology.Ministerio de Economía y Competitividad; IdiPAZPeer Reviewe

Determination and validation of principal gene products

Motivation: Alternative splicing has the potential to generate a wide range of protein isoforms. For many computational applications and for experimental research it is important to be able to concentrate on the isoform that retains the core biological function. For many genes this is far from clear. Results: We have combined five methods into a pipeline that allows us to detect the principal variant for a gene. Most of the methods were based on conservation between species, at the level of both gene and protein. The five methods used were the conservation of exonic structure, the detection of non-neutral evolution, the conservation of functional residues, the existence of a known protein structure and the abundance of vertebrate orthologues. The pipeline was able to determine a principal isoform for 83 % of a set of well-annotated genes with multiple variants.

Genome-wide mapping of transcriptional enhancer candidates using DNA and chromatin features in maize

Background While most cells in multicellular organisms carry the same genetic information, in each cell type only a subset of genes is being transcribed. Such differentiation in gene expression depends, for a large part, on the activation and repression of regulatory sequences, including transcriptional enhancers. Transcriptional enhancers can be located tens of kilobases from their target genes, but display characteristic chromatin and DNA features, allowing their identification by genome-wide profiling. Here we show that integration of chromatin characteristics can be applied to predict distal enhancer candidates in Zea mays, thereby providing a basis for a better understanding of gene regulation in this important crop plant. Result To predict transcriptional enhancers in the crop plant maize (Zea mays L. ssp. mays), we integrated available genome-wide DNA methylation data with newly generated maps for chromatin accessibility and histone 3 lysine 9 acetylation (H3K9ac) enrichment in young seedling and husk tissue. Approximately 1500 intergenic regions, displaying low DNA methylation, high chromatin accessibility and H3K9ac enrichment, were classified as enhancer candidates. Based on their chromatin profiles, candidate sequences can be classified into four subcategories. Tissue-specificity of enhancer candidates is defined based on the tissues in which they are identified and putative target genes are assigned based on tissue-specific expression patterns of flanking genes. Conclusions Our method identifies three previously identified distal enhancers in maize, validating the new set of enhancer candidates and enlarging the toolbox for the functional characterization of gene regulation in the highly repetitive maize genome