ProbMetab: an R package for Bayesian probabilistic annotation of LC-MS based metabolomics

We present ProbMetab, an R package which promotes substantial improvement in automatic probabilistic LC-MS based metabolome annotation. The inference engine core is based on a Bayesian model implemented to: (i) allow diverse source of experimental data and metadata to be systematically incorporated into the model with alternative ways to calculate the likelihood function and; (ii) allow sensitive selection of biologically meaningful biochemical reactions databases as Dirichlet-categorical prior distribution. Additionally, to ensure result interpretation by system biologists, we display the annotation in a network where observed mass peaks are connected if their candidate metabolites are substrate/product of known biochemical reactions. This graph can be overlaid with other graph-based analysis, such as partial correlation networks, in a visualization scheme exported to Cytoscape, with web and stand alone versions. ProbMetab was implemented in a modular fashion to fit together with established upstream (xcms, CAMERA, AStream, mzMatch.R, etc) and downstream R package tools (GeneNet, RCytoscape, DiffCorr, etc). ProbMetab, along with extensive documentation and case studies, is freely available under GNU license at: http://labpib.fmrp.usp.br/methods/probmetab/.Comment: Manuscript to be submitted very soon. 7 pages, 3 color figures. There is a companion material, the two case studies, which are going to be posted here together with the main text in next updated versio

Differential Inductive Signaling of CD90+ Prostate Cancer-Associated Fibroblasts Compared to Normal Tissue Stromal Mesenchyme Cells

Prostate carcinomas are surrounded by a layer of stromal fibroblastic cells that are characterized by increased expression of CD90. These CD90+ cancer-associated stromal fibroblastic cells differ in gene expression from their normal counterpart, CD49a+CD90lo stromal smooth muscle cells; and were postulated to represent a less differentiated cell type with altered inductive properties. CD90+ stromal cells were isolated from tumor tissue specimens and co-cultured with the pluripotent embryonal carcinoma cell line NCCIT in order to elucidate the impact of tumor-associated stroma on stem cells, and the ‘cancer stem cell.’ Transcriptome analysis identified a notable decreased induction of smooth muscle and prostate stromal genes such as PENK, BMP2 and ChGn compared to previously determined NCCIT response to normal prostate stromal cell induction. CD90+ stromal cell secreted factors induced an increased expression of CD90 and differential induction of genes involved in extracellular matrix remodeling and the RECK pathway in NCCIT. These results suggest that, compared to normal tissue stromal cells, signaling from cancer-associated stromal cells has a markedly different effect on stem cells as represented by NCCIT. Given that stromal cells are important in directing organ-specific differentiation, stromal cells in tumors appear to be defective in this function, which may contribute to abnormal differentiation found in diseases such as cancer

Integração entre Biologia e Física: construindo redes de regulação gênica usando equações diferenciais

Este artigo apresenta dois elementos básicos no modelamento de redes de regulação gênica:um sistema de switch ON-OFF (chave ligado-desligado) e um sistema de oscilações periódicas.Apesar de aparentemente simples, essas duas formas básicas de controle e resposta dascélulas a sinais externos ("circuito genético") devem ser entendidas em termos de equaçõesquímicas de equilíbrio, que por sua vez podem ser descritas em termos de EquaçõesDiferenciais. Os dois modelos apresentados são vistos, num contexto multidisciplinar, comomotivação para introdução à Biofísica de sistemas não-lineares para alunos das Ciências ditasExatas ou motivação para o aprendizado de matemática avançada por alunos vindos dasCiências Biológicas

Low Salt Influences Archaellum-Based Motility, Glycerol Metabolism, and Gas Vesicles Biogenesis in <i>Halobacterium salinarum</i>

Halobacterium salinarum NRC-1 is an extremophile that grows optimally at 4.3 M NaCl concentration. In spite of being an established model microorganism for the archaea domain, direct comparisons between its proteome and transcriptome during osmotic stress are still not available. Through RNA-seq-based transcriptomics, we compared a low salt (2.6 M NaCl) stress condition with 4.3 M of NaCl and found 283 differentially expressed loci. The more commonly found classes of genes were: ABC-type transporters and transcription factors. Similarities, and most importantly, differences between our findings and previously published datasets in similar experimental conditions are discussed. We validated three important biological processes differentially expressed: gas vesicles production (due to down-regulation of gvpA1b, gvpC1b, gvpN1b, and gvpO1b); archaellum formation (due to down-regulation of arlI, arlB1, arlB2, and arlB3); and glycerol metabolism (due to up-regulation of glpA1, glpB, and glpC). Direct comparison between transcriptomics and proteomics showed 58% agreement between mRNA and protein level changes, pointing to post-transcriptional regulation candidates. From those genes, we highlight rpl15e, encoding for the 50S ribosomal protein L15e, for which we hypothesize an ionic strength-dependent conformational change that guides post-transcriptional processing of its mRNA and, thus, possible salt-dependent regulation of the translation machinery

Global Gene Expression Analysis of the Heat Shock Response in the Phytopathogen Xylella fastidiosa

Xylella fastidiosa is a phytopathogenic bacterium that is responsible for diseases in many economically important crops. Although different strains have been studied, little is known about X. fastidiosa stress responses. One of the better characterized stress responses in bacteria is the heat shock response, which induces the expression of specific genes to prevent protein misfolding and aggregation and to promote degradation of the irreversibly denatured polypeptides. To investigate X. fastidiosa genes involved in the heat shock response, we performed a whole-genome microarray analysis in a time course experiment. Globally, 261 genes were induced (9.7%) and 222 genes were repressed (8.3%). The expression profiles of the differentially expressed genes were grouped, and their expression patterns were validated by quantitative reverse transcription-PCR experiments. We determined the transcription start sites of six heat shock-inducible genes and analyzed their promoter regions, which allowed us to propose a putative consensus for σ(32) promoters in Xylella and to suggest additional genes as putative members of this regulon. Besides the induction of classical heat shock protein genes, we observed the up-regulation of virulence-associated genes such as vapD and of genes for hemagglutinins, hemolysin, and xylan-degrading enzymes, which may indicate the importance of heat stress to bacterial pathogenesis. In addition, we observed the repression of genes related to fimbriae, aerobic respiration, and protein biosynthesis and the induction of genes related to the extracytoplasmic stress response and some phage-related genes, revealing the complex network of genes that work together in response to heat shock

Global Gene Expression Analysis during Germination in the Chytridiomycete Blastocladiella emersonii▿ †

Blastocladiella emersonii is an aquatic fungus of the Chytridiomycete class. During germination, the zoospore, a motile nongrowing cell, goes through a cascade of morphological changes that culminates with its differentiation into the germling cell, capable of coenocytic vegetative growth. Transcriptome analyses of B. emersonii cells were carried out during germination induced under various environmental conditions. Microarray data analyzing 3,563 distinct B. emersonii genes revealed that 26% of them are differentially expressed during germination in nutrient medium at at least one of the time points investigated. Over 500 genes are upregulated during the time course of germination under those conditions, most being related to cell growth, including genes involved in protein biosynthesis, DNA transcription, energetic metabolism, carbohydrate and oligopeptide transport, and cell cycle control. On the other hand, several transcripts stored in the zoospores are downregulated during germination in nutrient medium, such as genes involved in signal transduction, amino acid transport, and chromosome organization. In addition, germination induced in the presence of nutrients was compared with that triggered either by adenine or potassium ions in inorganic salt solution. Several genes involved in cell growth, induced during germination in nutrient medium, do not show increased expression when B. emersonii zoospores germinate in inorganic solution, suggesting that nutrients exert a positive effect on gene transcription. The transcriptome data also revealed that most genes involved in cell signaling show the same expression pattern irrespective of the initial germination stimulus

A Metabolomic Protocol For Plant Systematics By Matrix-assisted Laser-desorption/ionization Time-of Flight Mass Spectrometry.

Matrix-assisted laser desorption/ionization time-of flight mass spectrometry (MALDI-TOF MS) has been widely used for the identification and classification of microorganisms based on their proteomic fingerprints. However, the use of MALDI-TOF MS in plant research has been very limited. In the present study, a first protocol is proposed for metabolic fingerprinting by MALDI-TOF MS using three different MALDI matrices with subsequent multivariate data analysis by in-house algorithms implemented in the R environment for the taxonomic classification of plants from different genera, families and orders. By merging the data acquired with different matrices, different ionization modes and using careful algorithms and parameter selection, we demonstrate that a close taxonomic classification can be achieved based on plant metabolic fingerprints, with 92% similarity to the taxonomic classifications found in literature. The present work therefore highlights the great potential of applying MALDI-TOF MS for the taxonomic classification of plants and, furthermore, provides a preliminary foundation for future research.85946-5

The Iron Stimulon of Xylella fastidiosa Includes Genes for Type IV Pilus and Colicin V-Like Bacteriocins▿ †

Xylella fastidiosa is the etiologic agent of a wide range of plant diseases, including citrus variegated chlorosis (CVC), a major threat to citrus industry. The genomes of several strains of this phytopathogen were completely sequenced, enabling large-scale functional studies. DNA microarrays representing 2,608 (91.6%) coding sequences (CDS) of X. fastidiosa CVC strain 9a5c were used to investigate transcript levels during growth with different iron availabilities. When treated with the iron chelator 2,2′-dipyridyl, 193 CDS were considered up-regulated and 216 were considered down-regulated. Upon incubation with 100 μM ferric pyrophosphate, 218 and 256 CDS were considered up- and down-regulated, respectively. Differential expression for a subset of 44 CDS was further evaluated by reverse transcription-quantitative PCR. Several CDS involved with regulatory functions, pathogenicity, and cell structure were modulated under both conditions assayed, suggesting that major changes in cell architecture and metabolism occur when X. fastidiosa cells are exposed to extreme variations in iron concentration. Interestingly, the modulated CDS include those related to colicin V-like bacteriocin synthesis and secretion and to functions of pili/fimbriae. We also investigated the contribution of the ferric uptake regulator Fur to the iron stimulon of X. fastidiosa. The promoter regions of the strain 9a5c genome were screened for putative Fur boxes, and candidates were analyzed by electrophoretic mobility shift assays. Taken together, our data support the hypothesis that Fur is not solely responsible for the modulation of the iron stimulon of X. fastidiosa, and they present novel evidence for iron regulation of pathogenicity determinants

A Methodology for the Development of RESTful Semantic Web Services for Gene Expression Analysis.

Gene expression studies are generally performed through multi-step analysis processes, which require the integrated use of a number of analysis tools. In order to facilitate tool/data integration, an increasing number of analysis tools have been developed as or adapted to semantic web services. In recent years, some approaches have been defined for the development and semantic annotation of web services created from legacy software tools, but these approaches still present many limitations. In addition, to the best of our knowledge, no suitable approach has been defined for the functional genomics domain. Therefore, this paper aims at defining an integrated methodology for the implementation of RESTful semantic web services created from gene expression analysis tools and the semantic annotation of such services. We have applied our methodology to the development of a number of services to support the analysis of different types of gene expression data, including microarray and RNASeq. All developed services are publicly available in the Gene Expression Analysis Services (GEAS) Repository at http://dcm.ffclrp.usp.br/lssb/geas. Additionally, we have used a number of the developed services to create different integrated analysis scenarios to reproduce parts of two gene expression studies documented in the literature. The first study involves the analysis of one-color microarray data obtained from multiple sclerosis patients and healthy donors. The second study comprises the analysis of RNA-Seq data obtained from melanoma cells to investigate the role of the remodeller BRG1 in the proliferation and morphology of these cells. Our methodology provides concrete guidelines and technical details in order to facilitate the systematic development of semantic web services. Moreover, it encourages the development and reuse of these services for the creation of semantically integrated solutions for gene expression analysis