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Background: The prostate stroma is a key mediator of epithelial differentiation and development, and potentially plays a role in the initiation and progression of prostate cancer. The tumor-associated stroma is marked by increased expression of CD90/THY1. Isolation and characterization of these stromal cells could provide valuable insight into the biology of the tumor microenvironment.Methods: Prostate CD90+ stromal fibromuscular cells from tumor specimens were isolated by cell-sorting and analyzed by DNA microarray. Dataset analysis was used to compare gene expression between histologically normal and tumor-associated stromal cells. For comparison, stromal cells were also isolated and analyzed from the urinary bladder.Results: The tumor-associated stromal cells were found to have decreased expression of genes involved in smooth muscle differentiation, and those detected in prostate but not bladder. Other differential expression between the stromal cell types included that of the CXC-chemokine genes.Conclusion: CD90+ prostate tumor-associated stromal cells differed from their normal counterpart in expression of multiple genes, some of which are potentially involved in organ development. [ABSTRACT FROM AUTHOR]

UV-induced mutagenesis is, to greater extent, a phenomenon dependent on translesion synthesis (TLS) and regulated by the SOS response in bacteria. Caulobacter crescentus, like many bacterial species, employs the ImuABC (ImuAB DnaE2) pathway in TLS. To have a better understanding of the characteristics of UV-induced mutagenesis in this organism, we performed a whole genome analysis of mutations present in survivors after an acute UVC exposure (300 J/m 2 ). We found an average of 3.2 mutations/genome in irradiated samples, distributed in a mutational spectrum consisting exclusively of base substitutions, including tandem mutations. Although limited in conclusions by the small number of mutations identified, our study points to the feasibility of using whole-genome sequencing to study mutagenesis occurring in experiments involving a single acute exposure to genotoxic agents., Competing Interests: Declaration of Competing Interest The authors report no declarations of interest., (Copyright © 2022 Elsevier B.V. All rights reserved.)

Plasmodium vivax , the most widely distributed human malaria parasite, causes severe clinical syndromes despite low peripheral blood parasitemia. This conundrum is further complicated as cytoadherence in the microvasculature is still a matter of investigations. Previous reports in Plasmodium knowlesi , another parasite species shown to infect humans, demonstrated that variant genes involved in cytoadherence were dependent on the spleen for their expression. Hence, using a global transcriptional analysis of parasites obtained from spleen-intact and splenectomized monkeys, we identified 67 P. vivax genes whose expression was spleen dependent. To determine their role in cytoadherence, two Plasmodium falciparum transgenic lines expressing two variant proteins pertaining to VIR and Pv-FAM-D multigene families were used. Cytoadherence assays demonstrated specific binding to human spleen but not lung fibroblasts of the transgenic line expressing the VIR14 protein. To gain more insights, we expressed five P. vivax spleen-dependent genes as recombinant proteins, including members of three different multigene families (VIR, Pv-FAM-A, Pv-FAM-D), one membrane transporter (SECY), and one hypothetical protein (HYP1), and determined their immunogenicity and association with clinical protection in a prospective study of 383 children in Papua New Guinea. Results demonstrated that spleen-dependent antigens are immunogenic in natural infections and that antibodies to HYP1 are associated with clinical protection. These results suggest that the spleen plays a major role in expression of parasite proteins involved in cytoadherence and can reveal antigens associated with clinical protection, thus prompting a paradigm shift in P. vivax biology toward deeper studies of the spleen during infections., Competing Interests: The authors declare no competing interest., (Copyright © 2020 the Author(s). Published by PNAS.)

The lineage relationship between prostate adenocarcinoma and small cell carcinoma was studied by using the LuCaP family of xenografts established from primary neoplasm to metastasis. Expression of four stem cell transcription factor (TF) genes, LIN28A, NANOG, POU5F1, SOX2, were analyzed in the LuCaP lines. These genes, when force expressed in differentiated cells, can reprogram the recipients into stem-like induced pluripotent stem (iPS) cells. Most LuCaP lines expressed POU5F1, while LuCaP 145.1, representative of small cell carcinoma, expressed all four. Through transcriptome database query, many small cell carcinoma genes were also found in stem cells. To test the hypothesis that prostate cancer progression from "differentiated" adenocarcinoma to "undifferentiated" small cell carcinoma could involve re-expression of stem cell genes, the four TF genes were transduced via lentiviral vectors into five adenocarcinoma LuCaP lines-70CR, 73CR, 86.2, 92, 105CR-as done in iPS cell reprogramming. The resultant cells from these five transductions displayed a morphology of small size and dark appearing unlike the parentals. Transcriptome analysis of LuCaP 70CR* ("*" to denote transfected progeny) revealed a unique gene expression close to that of LuCaP 145.1. In a prostate principal components analysis space based on cell-type transcriptomes, the different LuCaP transcriptome datapoints were aligned to suggest a possible ordered sequence of expression changes from the differentiated luminal-like adenocarcinoma cell types to the less differentiated, more stem-like small cell carcinoma types, and LuCaP 70CR*. Prostate cancer progression can thus be molecularly characterized by loss of differentiation with re-expression of stem cell genes. J. Cell. Physiol. 231: 2040-2047, 2016. © 2016 Wiley Periodicals, Inc., (© 2016 Wiley Periodicals, Inc.)

Background: Voided urine samples have been shown to contain cells released from prostate tumors. Could good quality RNA from cells in urine be obtained from every donor for multimarker analysis? In addition, could urine donation be as simple as possible, a practical consideration for a lab test, without involving a prostate massage (as indicated for PCA3 testing), which precludes frequent collection; needing it done at a specific time of day (e.g., first or second urine); and requiring prompt processing of samples in clinics with limited molecular biology capability?, Methods: Collected urine samples were pelleted, and the RNA isolated was processed for cDNA synthesis and in vitro transcription to generate amplified sense aRNA. The resultant aRNA was rigorously analyzed for possible introduced changes. DMSO was used as a cell preservative for frozen storage of urine samples., Results: Good quality aRNA was obtained for over 100 samples collected at two different institutions. The process of RNA amplification removed co-isolated DNA in some samples, which did not affect RNA amplification. Amplification did not amplify genes that were absent and produce other expression alterations. The sense aRNA could be used to generate urinary transcriptomes specific to individual patients. No chaotropic agents for RNA preservation were added to the urine samples so that the supernatant could be used for analysis of secreted protein biomarkers. The time of donation was not important since patients were seen during the entire day. DMSO was an effective cell preservative for freezing urine., Conclusions: Urinary RNA can be readily isolated and amplified for prostate cancer biomarker analysis. Individual patients had unique set of transcripts derived from their tumor., (© 2015 Wiley Periodicals, Inc.)

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.

Statistical Inference of Function Through Evolutionary Relationships (SIFTER) is a powerful computational platform for probabilistic protein domain annotation. Nevertheless, SIFTER is not widely used, likely due to usability and scalability issues. Here we present SIFTER-T (SIFTER Throughput-optimized), a substantial improvement over SIFTER's original proof-of-principle implementation. SIFTER-T is optimized for better performance, allowing it to be used at the genome-wide scale. Compared to SIFTER 2.0, SIFTER-T achieved an 87-fold performance improvement using published test data sets for the known annotations recovering module and a 72.3% speed increase for the gene tree generation module in quad-core machines, as well as a major decrease in memory usage during the realignment phase. Memory optimization allowed an expanded set of proteins to be handled by SIFTER's probabilistic method. The improvement in performance and automation that we achieved allowed us to build a web server to bring the power of Bayesian phylogenomic inference to the genomics community. SIFTER-T and its online interface are freely available under GNU license at http://labpib.fmrp.usp.br/methods/SIFTER-t/ and https://github.com/dcasbioinfo/SIFTER-t.

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., (Copyright © 2015 Elsevier B.V. All rights reserved.)

The existence of sense overlapping transcripts that share regulatory and coding information in the same genomic sequence shows an additional level of prokaryotic gene expression complexity. Here we report the discovery of ncRNAs associated with IS1341-type transposase (tnpB) genes, at the 3'-end of such elements, with examples in archaea and bacteria. Focusing on the model haloarchaeon Halobacterium salinarum NRC-1, we show the existence of sense overlapping transcripts (sotRNAs) for all its IS1341-type transposases. Publicly available transcriptome compendium show condition-dependent differential regulation between sotRNAs and their cognate genes. These sotRNAs allowed us to find a UUCA tetraloop motif that is present in other archaea (ncRNA family HgcC) and in a H. salinarum intergenic ncRNA derived from a palindrome associated transposable elements (PATE). Overexpression of one sotRNA and the PATE-derived RNA harboring the tetraloop motif improved H. salinarum growth, indicating that these ncRNAs are functional.

Prostate cancer progression is characterized by tumor dedifferentiation. Cancer cells of less differentiated tumors have a gene expression/transcriptome more similar to that of stem cells. In dedifferentiation, cancer cells may follow a specific program of gene expression changes to a stem-like state. In order to treat cancer effectively, the stem-like cancer cells and cancer differentiation pathway need to be identified and studied. Due to the very low abundance of stem-like cancer cells, their isolation from fresh human tumors is technically challenging. Induced pluripotent stem cell technology can reprogram differentiated cells into stem-like, and this may be a tool to generate sufficient stem-like cancer cells.

A plethora of non-coding RNAs has been discovered using high-resolution transcriptomics tools, indicating that transcriptional and post-transcriptional regulation is much more complex than previously appreciated. Small RNAs associated with transcription start sites of annotated coding regions (TSSaRNAs) are pervasive in both eukaryotes and bacteria. Here, we provide evidence for existence of TSSaRNAs in several archaeal transcriptomes including: Halobacterium salinarum, Pyrococcus furiosus, Methanococcus maripaludis, and Sulfolobus solfataricus. We validated TSSaRNAs from the model archaeon Halobacterium salinarum NRC-1 by deep sequencing two independent small-RNA enriched (RNA-seq) and a primary-transcript enriched (dRNA-seq) strand-specific libraries. We identified 652 transcripts, of which 179 were shown to be primary transcripts (∼7% of the annotated genome). Distinct growth-associated expression patterns between TSSaRNAs and their cognate genes were observed, indicating a possible role in environmental responses that may result from RNA polymerase with varying pausing rhythms. This work shows that TSSaRNAs are ubiquitous across all domains of life.

Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

We present ProbMetab, an R package that promotes substantial improvement in automatic probabilistic liquid chromatography-mass spectrometry-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 reaction 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.

Background: The dermatophyte Trichophyton rubrum is an anthropophilic filamentous fungus that infects keratinized tissues and is the most common etiologic agent isolated in human dermatophytoses. The clinical treatment of these infections is challenging because only few antifungal drugs are commercially available. To understand the mode of action of cytotoxic drugs against fungi, we evaluated the time-dependent effects of acriflavine on T. rubrum transcriptome using high-throughput RNA-sequencing (RNA-seq) technology., Results: RNA-seq analysis generated approximately 200 million short reads that were mapped to the Broad Institute's Dermatophyte Comparative Database before differential gene expression analysis was performed. By employing a stringent cut-off threshold of -1.5 and 1.5 log₂-fold changes in gene expression, a subset of 490 unique genes were found to be modulated in T. rubrum in response to acriflavine exposure. Among the selected genes, 69 genes were modulated at all exposure time points. Functional categorization indicated the putative involvement of these genes in various cellular processes such as oxidation-reduction reaction, transmembrane transport, and metal ion binding. Interestingly, genes putatively involved in the pathogenicity of dermatophytoses were down-regulated suggesting that this drug interferes with the virulence of T. rubrum. Moreover, we identified 159 novel putative transcripts in intergenic regions and two transcripts in intron regions of T. rubrum genome., Conclusion: The results provide insights into the molecular events underlying the stress responses of T. rubrum to acriflavine, revealing that this drug interfered with important molecular events involved in the establishment and maintenance of fungal infection in the host. In addition, the identification of novel transcripts will further enable the improvement of gene annotation and open reading frame prediction of T. rubrum and other dermatophyte genomes.

Background: The study and analysis of gene expression measurements is the primary focus of functional genomics. Once expression data is available, biologists are faced with the task of extracting (new) knowledge associated to the underlying biological phenomenon. Most often, in order to perform this task, biologists execute a number of analysis activities on the available gene expression dataset rather than a single analysis activity. The integration of heterogeneous tools and data sources to create an integrated analysis environment represents a challenging and error-prone task. Semantic integration enables the assignment of unambiguous meanings to data shared among different applications in an integrated environment, allowing the exchange of data in a semantically consistent and meaningful way. This work aims at developing an ontology-based methodology for the semantic integration of gene expression analysis tools and data sources. The proposed methodology relies on software connectors to support not only the access to heterogeneous data sources but also the definition of transformation rules on exchanged data., Results: We have studied the different challenges involved in the integration of computer systems and the role software connectors play in this task. We have also studied a number of gene expression technologies, analysis tools and related ontologies in order to devise basic integration scenarios and propose a reference ontology for the gene expression domain. Then, we have defined a number of activities and associated guidelines to prescribe how the development of connectors should be carried out. Finally, we have applied the proposed methodology in the construction of three different integration scenarios involving the use of different tools for the analysis of different types of gene expression data., Conclusions: The proposed methodology facilitates the development of connectors capable of semantically integrating different gene expression analysis tools and data sources. The methodology can be used in the development of connectors supporting both simple and nontrivial processing requirements, thus assuring accurate data exchange and information interpretation from exchanged data.

Background: CD90(+) prostate cancer-associated (CP) stromal cells represent a diseased cell type found only in tumor tissue. They differ from their normal counterpart in gene expression and inductive signaling. Genetic reprogramming by induced pluripotent stem (iPS) cell technology can effectively change adult cells into stem-like cells through wholesale alteration of the gene expression program. This technology might be used to 'erase' the abnormal gene expression of diseased cells. The resultant iPS cells would no longer express the disease phenotype, and behave like stem cells., Methods: CP stromal cells, isolated from tumor tissue of a surgically resected prostate by anti-CD90-mediated sorting and cultured in vitro, were transfected with in vitro packaged lentiviral expression vectors containing stem cell transcription factor genes POU5F1, LIN28, NANOG, and SOX2., Results: Alkaline phosphatase-positive iPS cells were obtained in about 3 weeks post-transfection at a frequency of 10(-4) . Their colony morphology was indistinguishable from that of human embryonic stem (ES) cells. Transcriptome analysis showed a virtually complete match in gene expression between the iPS and ES cells., Conclusions: Genes of CP stromal cells could be fully inactivated by genetic reprogramming. As a consequence, the disease phenotype was 'cured'., (Copyright © 2012 Wiley Periodicals, Inc.)

Many cell types have no known functional attributes. In the bladder and prostate, basal epithelial and stromal cells appear similar in cytomorphology and share several cell surface markers. Their total gene expression (transcriptome) should provide a clear measure of the extent to which they are alike functionally. Since urologic stromal cells are known to mediate organ-specific tissue formation, these cells in cancers might exhibit aberrant gene expression affecting their function. For transcriptomes, cluster designation (CD) antigens have been identified for cell sorting. The sorted cell populations can be analyzed by DNA microarrays. Various bladder cell types have unique complements of CD molecules. CD9(+) urothelial, CD104(+) basal and CD13(+) stromal cells of the lamina propria were therefore analyzed, as were CD9(+) cancer and CD13(+) cancer-associated stromal cells. The transcriptome datasets were compared by principal components analysis for relatedness between cell types; those with similarity in gene expression indicated similar function. Although bladder and prostate basal cells shared CD markers such as CD104, CD44 and CD49f, they differed in overall gene expression. Basal cells also lacked stem cell gene expression. The bladder luminal and stromal transcriptomes were distinct from their prostate counterparts. In bladder cancer, not only the urothelial but also the stromal cells showed gene expression alteration. The cancer process in both might thus involve defective stromal signaling. These cell-type transcriptomes provide a means to monitor in vitro models in which various CD-isolated cell types can be combined to study bladder differentiation and bladder tumor development based on cell-cell interaction.

In silico analyses of Leishmania spp. genome data are a powerful resource to improve the understanding of these pathogens' biology. Trypanosomatids such as Leishmania spp. have their protein-coding genes grouped in long polycistronic units of functionally unrelated genes. The control of gene expression happens by a variety of posttranscriptional mechanisms. The high degree of synteny among Leishmania species is accompanied by highly conserved coding sequences (CDS) and poorly conserved intercoding untranslated sequences. To identify the elements involved in the control of gene expression, we conducted an in silico investigation to find conserved intercoding sequences (CICS) in the genomes of L. major, L. infantum, and L. braziliensis. We used a combination of computational tools, such as Linux-Shell, PERL and R languages, BLAST, MSPcrunch, SSAKE, and Pred-A-Term algorithms to construct a pipeline which was able to: (i) search for conservation in target-regions, (ii) eliminate CICS redundancy and mask repeat elements, (iii) predict the mRNA's extremities, (iv) analyze the distribution of orthologous genes within the generated LeishCICS-clusters, (v) assign GO terms to the LeishCICS-clusters, and (vi) provide statistical support for the gene-enrichment annotation. We associated the LeishCICS-cluster data, generated at the end of the pipeline, with the expression profile of L. donovani genes during promastigote-amastigote differentiation, as previously evaluated by others (GEO accession: GSE21936). A Pearson's correlation coefficient greater than 0.5 was observed for 730 LeishCICS-clusters containing from 2 to 17 genes. The designed computational pipeline is a useful tool and its application identified potential regulatory cis elements and putative regulons in Leishmania., (Copyright © 2012 Elsevier B.V. All rights reserved.)

Background: Ontologies have increasingly been used in the biomedical domain, which has prompted the emergence of different initiatives to facilitate their development and integration. The Open Biological and Biomedical Ontologies (OBO) Foundry consortium provides a repository of life-science ontologies, which are developed according to a set of shared principles. This consortium has developed an ontology called OBO Relation Ontology aiming at standardizing the different types of biological entity classes and associated relationships. Since ontologies are primarily intended to be used by humans, the use of graphical notations for ontology development facilitates the capture, comprehension and communication of knowledge between its users. However, OBO Foundry ontologies are captured and represented basically using text-based notations. The Unified Modeling Language (UML) provides a standard and widely-used graphical notation for modeling computer systems. UML provides a well-defined set of modeling elements, which can be extended using a built-in extension mechanism named Profile. Thus, this work aims at developing a UML profile for the OBO Relation Ontology to provide a domain-specific set of modeling elements that can be used to create standard UML-based ontologies in the biomedical domain.

HTself is a web-based bioinformatics tool designed to deal with the classification of differential gene expression in low replication microarray studies. It is based on a statistical test that uses self-self experiments to derive intensity-dependent cutoffs. We developed an extension of HTself, originally released in 2005, by calculating P values instead of using a fixed acceptance level α. As before, the statistic used to compute single-spot P values is obtained from the Gaussian kernel density estimator method applied to self-self data. Different spots corresponding to the same biological gene (replicas) give rise to a set of independent P values that can be combined by well-known statistical methods. The combined P value can be used to decide whether a gene can be considered differentially expressed or not. HTself2 is a new version of HTself that uses P values combination. It is implemented as a user-friendly desktop application to help laboratories without a bioinformatics infrastructure.

Background: Prostate tumor heterogeneity is a major factor in disease management. Heterogeneity could be due to multiple cancer cell types with distinct gene expression. Of clinical importance is the so-called cancer stem cell type. Cell type-specific transcriptomes are used to examine lineage relationship among cancer cell types and their expression similarity to normal cell types including stem/progenitor cells., Methods: Transcriptomes were determined by Affymetrix DNA array analysis for the following cell types. Putative prostate progenitor cell populations were characterized and isolated by expression of the membrane transporter ABCG2. Stem cells were represented by embryonic stem and embryonal carcinoma cells. The cancer cell types were Gleason pattern 3 (glandular histomorphology) and pattern 4 (aglandular) sorted from primary tumors, cultured prostate cancer cell lines originally established from metastatic lesions, xenografts LuCaP 35 (adenocarcinoma phenotype) and LuCaP 49 (neuroendocrine/small cell carcinoma) grown in mice. No detectable gene expression differences were detected among serial passages of the LuCaP xenografts., Results: Based on transcriptomes, the different cancer cell types could be clustered into a luminal-like grouping and a non-luminal-like (also not basal-like) grouping. The non-luminal-like types showed expression more similar to that of stem/progenitor cells than the luminal-like types. However, none showed expression of stem cell genes known to maintain stemness., Conclusions: Non-luminal-like types are all representatives of aggressive disease, and this could be attributed to the similarity in overall gene expression to stem and progenitor cell types.

Unlabelled: 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(+)CD90(lo) 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., Electronic Supplementary Material: The online version of this article (doi:10.1007/s12307-010-0061-4) contains supplementary material, which is available to authorized users.

Background: The post-genomic era has brought new challenges regarding the understanding of the organization and function of the human genome. Many of these challenges are centered on the meaning of differential gene regulation under distinct biological conditions and can be performed by analyzing the Multiple Differential Expression (MDE) of genes associated with normal and abnormal biological processes. Currently MDE analyses are limited to usual methods of differential expression initially designed for paired analysis., Results: We proposed a web platform named ProbFAST for MDE analysis which uses Bayesian inference to identify key genes that are intuitively prioritized by means of probabilities. A simulated study revealed that our method gives a better performance when compared to other approaches and when applied to public expression data, we demonstrated its flexibility to obtain relevant genes biologically associated with normal and abnormal biological processes., Conclusions: ProbFAST is a free accessible web-based application that enables MDE analysis on a global scale. It offers an efficient methodological approach for MDE analysis of a set of genes that are turned on and off related to functional information during the evolution of a tumor or tissue differentiation. ProbFAST server can be accessed at http://gdm.fmrp.usp.br/probfast.

In prostate tumors, both the epithelial and stromal mesenchyme compartments show gene expression changes from their respective normal counterpart. In fact, there are more such changes in the stroma than the epithelium. These include down-regulated expression of genes involved in smooth muscle cell differentiation and those differentially expressed between prostate and bladder, i.e., organ-restricted. In development, the stromal cell type mediates tissue formation from differentiation of stem or progenitor cells. Diseases like cancer may arise as a result of defective stromal signaling. Stromal signaling can be demonstrated by co-culture of stromal cells and embryonal carcinoma NCCIT cells used as a stem cell substitute. In co-culture, stromal cells induce NCCIT cells through diffusible molecules to lose stem cell gene expression, gain expression of prostate genes, alter cytomorphology, and lower proliferation. This NCCIT response is varied as co-cultured bladder stromal cells induce a different gene expression. At the same time, NCCIT factors also affect gene expression of co-cultured stromal cells. NCCIT induces normal prostate tissue (NP) stromal cells to become more like cancer-associated (CP) stromal cells in both mRNA and microRNA expression. In contrast, NCCIT shows minimal effect on CP stromal cells. CP stromal cells may represent a less differentiated state in the prostate stromal cell lineage.

Background: Prostate cancer cells in primary tumors have been typed CD10-/CD13-/CD24hi/CD26+/CD38lo/CD44-/CD104-. This CD phenotype suggests a lineage relationship between cancer cells and luminal cells. The Gleason grade of tumors is a descriptive of tumor glandular differentiation. Higher Gleason scores are associated with treatment failure., Methods: CD26+ cancer cells were isolated from Gleason 3+3 (G3) and Gleason 4+4 (G4) tumors by cell sorting, and their gene expression or transcriptome was determined by Affymetrix DNA array analysis. Dataset analysis was used to determine gene expression similarities and differences between G3 and G4 as well as to prostate cancer cell lines and histologically normal prostate luminal cells., Results: The G3 and G4 transcriptomes were compared to those of prostatic cell types of non-cancer, which included luminal, basal, stromal fibromuscular, and endothelial. A principal components analysis of the various transcriptome datasets indicated a closer relationship between luminal and G3 than luminal and G4. Dataset comparison also showed that the cancer transcriptomes differed substantially from those of prostate cancer cell lines., Conclusions: Genes differentially expressed in cancer are potential biomarkers for cancer detection, and those differentially expressed between G3 and G4 are potential biomarkers for disease stratification given that G4 cancer is associated with poor outcomes. Differentially expressed genes likely contribute to the prostate cancer phenotype and constitute the signatures of these particular cancer cell types.

Background: There is a growing body of evidence indicating that epigenetic influences originating from stromal cells in the immediate microenvironment may play a role in carcinogenesis. Determining the molecular mechanisms involved in stromal-stem cell interaction could provide critical insight into prostate development and disease progression, particularly with regard to their relationship to and influence on the putative cancer stem cell., Methods: Prostate and bladder stromal cells prepared from tissue specimens were co-cultured with the pluripotent embryonal carcinoma cell line NCCIT. Transcriptome analysis was used to characterize NCCIT cell response to prostate or bladder signaling., Results: A systems approach demonstrated that prostate stromal cells were capable of inducing gene expression changes in NCCIT through secreted factors. Induction led to a loss of embryonic stem cell markers, with concurrent up-regulation of many genes characteristic of stromal mesenchyme cells as well as some of epithelial and cancer stem cells. Bladder stromal signaling produced gene expression changes different from those of prostate signaling., Conclusions: This study indicates that paracrine stromal cell signaling can affect cancer stem cell response in an organ-specific manner and may provide insight for future development of treatment strategies such as differentiation therapy.

Background: Sucrose content is a highly desirable trait in sugarcane as the worldwide demand for cost-effective biofuels surges. Sugarcane cultivars differ in their capacity to accumulate sucrose and breeding programs routinely perform crosses to identify genotypes able to produce more sucrose. Sucrose content in the mature internodes reach around 20% of the culms dry weight. Genotypes in the populations reflect their genetic program and may display contrasting growth, development, and physiology, all of which affect carbohydrate metabolism. Few studies have profiled gene expression related to sugarcane's sugar content. The identification of signal transduction components and transcription factors that might regulate sugar accumulation is highly desirable if we are to improve this characteristic of sugarcane plants., Results: We have evaluated thirty genotypes that have different Brix (sugar) levels and identified genes differentially expressed in internodes using cDNA microarrays. These genes were compared to existing gene expression data for sugarcane plants subjected to diverse stress and hormone treatments. The comparisons revealed a strong overlap between the drought and sucrose-content datasets and a limited overlap with ABA signaling. Genes associated with sucrose content were extensively validated by qRT-PCR, which highlighted several protein kinases and transcription factors that are likely to be regulators of sucrose accumulation. The data also indicate that aquaporins, as well as lignin biosynthesis and cell wall metabolism genes, are strongly related to sucrose accumulation. Moreover, sucrose-associated genes were shown to be directly responsive to short term sucrose stimuli, confirming their role in sugar-related pathways., Conclusion: Gene expression analysis of sugarcane populations contrasting for sucrose content indicated a possible overlap with drought and cell wall metabolism processes and suggested signaling and transcriptional regulators to be used as molecular markers in breeding programs. Transgenic research is necessary to further clarify the role of the genes and define targets useful for sugarcane improvement programs based on transgenic plants.

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.

Plasmodium vivax is responsible for more than 100 million clinical cases yearly. Unlike P. falciparum, in which infected red blood cells cytoadhere via variant proteins, avoiding passage through the spleen, P.-vivax-infected reticulocytes seem not to cytoadhere. However, a variant subtelomeric multigene vir family has been identified in P. vivax. Thus, questions remain about how P. vivax circulates through the spleen and the role of Vir proteins. In this review, the importance of the vir multigene superfamily is reviewed in the light of the completion of the entire genome sequence of P. vivax and from data gathered from experimental infections in reticulocyte-prone non-lethal malaria parasites and natural P. vivax infections.

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 microM 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.

Background: As in many other areas of science, systems biology makes extensive use of statistical association and significance estimates in contingency tables, a type of categorical data analysis known in this field as enrichment (also over-representation or enhancement) analysis. In spite of efforts to create probabilistic annotations, especially in the Gene Ontology context, or to deal with uncertainty in high throughput-based datasets, current enrichment methods largely ignore this probabilistic information since they are mainly based on variants of the Fisher Exact Test., Results: We developed an open-source R-based software to deal with probabilistic categorical data analysis, ProbCD, that does not require a static contingency table. The contingency table for the enrichment problem is built using the expectation of a Bernoulli Scheme stochastic process given the categorization probabilities. An on-line interface was created to allow usage by non-programmers and is available at: http://xerad.systemsbiology.net/ProbCD/., Conclusion: We present an analysis framework and software tools to address the issue of uncertainty in categorical data analysis. In particular, concerning the enrichment analysis, ProbCD can accommodate: (i) the stochastic nature of the high-throughput experimental techniques and (ii) probabilistic gene annotation.

Purpose: To estimate between-scanner functional MRI (fMRI) reproducibility in a multisite study., Materials and Methods: A total of five identical 1.5T MR systems were used to repeatedly scan five subjects while performing a finger tapping task. A two-way (scanners, subjects) random effects analysis of variance (ANOVA) was used to estimate between-scanner and between-subject variability on two outcome variables: task-related mean blood oxygenation level dependent (BOLD) signal change and volume of activation within a motor region-of-interest (ROI)., Results: Between-scanner variability of fMRI data accounted for a small proportion of the total variation in the BOLD signal change (8.34%, P = 0.114) and volume of activation (5.46%, P = 0.203). Between-subject variation accounted for more than half of the total variation for both measurements (57.17% and 54.46%, respectively, P < 0.01)., Conclusion: These results support the feasibility of multisite studies using identical scanner systems., ((c) 2007 Wiley-Liss, Inc.)

Listeria monocytogenes is a food-borne, opportunistic, bacterial pathogen causing a wide spectrum of diseases, including meningitis, septicemia, abortion, and gastroenteritis, in humans and animals. Among the 13 L. monocytogenes serovars described, human listeriosis is mostly associated with strains of serovars 4b, 1/2b, and 1/2a. Within the species L. monocytogenes, three phylogenetic lineages are described. Serovar 1/2a belongs to phylogenetic lineage I, while serovars 4b and 1/2b group in phylogenetic lineage II. To explore the role of gene expression in the adaptation of L. monocytogenes strains of these two major lineages to different environments, as well as in virulence, we performed whole-genome expression profiling of six L. monocytogenes isolates of serovars 4b, 1/2b, and 1/2a of distinct origins, using a newly constructed Listeria multigenome DNA array. Comparison of the global gene expression profiles revealed differences among strains. The expression profiles of two strains having distinct 50% lethal doses, as assessed in the mouse model, were further analyzed. Gene ontology term enrichment analysis of the differentially expressed genes identified differences in protein-, nucleic acid-, carbon metabolism-, and virulence-related gene expression. Comparison of the expression profiles of the core genomes of all strains revealed differences between the two lineages with respect to cell wall synthesis, the stress-related sigma B regulon and virulence-related genes. These findings suggest different patterns of interaction with host cells and the environment, key factors for host colonization and survival in the environment.

Background: Transcript enumeration methods such as SAGE, MPSS, and sequencing-by-synthesis EST "digital northern", are important high-throughput techniques for digital gene expression measurement. As other counting or voting processes, these measurements constitute compositional data exhibiting properties particular to the simplex space where the summation of the components is constrained. These properties are not present on regular Euclidean spaces, on which hybridization-based microarray data is often modeled. Therefore, pattern recognition methods commonly used for microarray data analysis may be non-informative for the data generated by transcript enumeration techniques since they ignore certain fundamental properties of this space., Results: Here we present a software tool, Simcluster, designed to perform clustering analysis for data on the simplex space. We present Simcluster as a stand-alone command-line C package and as a user-friendly on-line tool. Both versions are available at: http://xerad.systemsbiology.net/simcluster., Conclusion: Simcluster is designed in accordance with a well-established mathematical framework for compositional data analysis, which provides principled procedures for dealing with the simplex space, and is thus applicable in a number of contexts, including enumeration-based gene expression data.

Background: Uncovering the molecular mechanism underlying expansion of hematopoietic stem and progenitor cells is critical to extend current therapeutic applications and to understand how its deregulation relates to leukemia. The characterization of genes commonly relevant to stem/progenitor cell expansion and tumor development should facilitate the identification of novel therapeutic targets in cancer., Methods: CD34+/CD133+ progenitor cells were purified from human umbilical cord blood and expanded in vitro. Correlated molecular changes were analyzed by gene expression profiling using microarrays covering up to 55,000 transcripts. Genes regulated during progenitor cell expansion were identified and functionally classified. Aberrant expression of such genes in cancer was indicated by in silico SAGE. Differential expression of selected genes was assessed by real-time PCR in hematopoietic cells from chronic myeloid leukemia patients and healthy individuals., Results: Several genes and signaling pathways not previously associated with ex vivo expansion of CD133+/CD34+ cells were identified, most of which associated with cancer. Regulation of MEK/ERK and Hedgehog signaling genes in addition to numerous proto-oncogenes was detected during conditions of enhanced progenitor cell expansion. Quantitative real-time PCR analysis confirmed down-regulation of several newly described cancer-associated genes in CD133+/CD34+ cells, including DOCK4 and SPARCL1 tumor suppressors, and parallel results were verified when comparing their expression in cells from chronic myeloid leukemia patients, Conclusion: Our findings reveal potential molecular targets for oncogenic transformation in CD133+/CD34+ cells and strengthen the link between deregulation of stem/progenitor cell expansion and the malignant process.

Background: Sugarcane is an increasingly economically and environmentally important C4 grass, used for the production of sugar and bioethanol, a low-carbon emission fuel. Sugarcane originated from crosses of Saccharum species and is noted for its unique capacity to accumulate high amounts of sucrose in its stems. Environmental stresses limit enormously sugarcane productivity worldwide. To investigate transcriptome changes in response to environmental inputs that alter yield we used cDNA microarrays to profile expression of 1,545 genes in plants submitted to drought, phosphate starvation, herbivory and N2-fixing endophytic bacteria. We also investigated the response to phytohormones (abscisic acid and methyl jasmonate). The arrayed elements correspond mostly to genes involved in signal transduction, hormone biosynthesis, transcription factors, novel genes and genes corresponding to unknown proteins., Results: Adopting an outliers searching method 179 genes with strikingly different expression levels were identified as differentially expressed in at least one of the treatments analysed. Self Organizing Maps were used to cluster the expression profiles of 695 genes that showed a highly correlated expression pattern among replicates. The expression data for 22 genes was evaluated for 36 experimental data points by quantitative RT-PCR indicating a validation rate of 80.5% using three biological experimental replicates. The SUCAST Database was created that provides public access to the data described in this work, linked to tissue expression profiling and the SUCAST gene category and sequence analysis. The SUCAST database also includes a categorization of the sugarcane kinome based on a phylogenetic grouping that included 182 undefined kinases., Conclusion: An extensive study on the sugarcane transcriptome was performed. Sugarcane genes responsive to phytohormones and to challenges sugarcane commonly deals with in the field were identified. Additionally, the protein kinases were annotated based on a phylogenetic approach. The experimental design and statistical analysis applied proved robust to unravel genes associated with a diverse array of conditions attributing novel functions to previously unknown or undefined genes. The data consolidated in the SUCAST database resource can guide further studies and be useful for the development of improved sugarcane varieties.

The majority of individuals in the chronic phase of Chagas disease are asymptomatic (indeterminate form). Every year 2-3% of these individuals develop severe clinical manifestations (cardiac and digestive forms). In this study a Trypanosoma cruzi DNA microarray was used to compare the transcript profiles of six human isolates: three from asymptomatic and three from cardiac patients. Seven signals were expressed differentially between the two classes of isolates, including tryparedoxin, surface protease GP63, cyclophilin, some hypothetical proteins and the pre-edited maxicircle gene NADH dehydrogenase subunit 7 (ND7). The approximately 30-fold greater signal in cardiac strains for ND7 was the most pronounced of the group, and differential levels of pre-edited ND7 transcript confirmed the microarray analysis. The ND7 gene from asymptomatic isolates showed a deletion of 455bp from nt 222 to nt 677 relative to ND7 of the CL Brener reference strain. The ND7 gene structure correlated with disease manifestation for 20 isolates from clinically characterised, chronic phase patients. The ND7 lesion produces a truncated product that could impair the function of mitochondrial complex I. Possible links between the integrity of the electron transport chain and symptom presentation are discussed. We propose that ND7 and other genes of the pathway constitute valuable targets for PCR assays in the differential diagnosis of the infective T. cruzi strain. While this hypothesis requires validation by the examination of additional recent parasite isolates from patients with defined pathologies, the identification of specific molecular markers represents a promising advance in the association between parasite genetics and disease pathology.

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 sigma(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.

SpotWhatR is a user-friendly microarray data analysis tool that runs under a widely and freely available R statistical language (http://www.r-project.org) for Windows and Linux operational systems. The aim of SpotWhatR is to help the researcher to analyze microarray data by providing basic tools for data visualization, normalization, determination of differentially expressed genes, summarization by Gene Ontology terms, and clustering analysis. SpotWhatR allows researchers who are not familiar with computational programming to choose the most suitable analysis for their microarray dataset. Along with well-known procedures used in microarray data analysis, we have introduced a stand-alone implementation of the HTself method, especially designed to find differentially expressed genes in low-replication contexts. This approach is more compatible with our local reality than the usual statistical methods. We provide several examples derived from the Blastocladiella emersonii and Xylella fastidiosa Microarray Projects. SpotWhatR is freely available at http://blasto.iq.usp.br/~tkoide/SpotWhatR, in English and Portuguese versions. In addition, the user can choose between "single experiment" and "batch processing" versions.

One of the goals of gene expression experiments is the identification of differentially expressed genes among populations that could be used as markers. For this purpose, we implemented a model-free Bayesian approach in a user-friendly and freely available web-based tool called BayBoots. In spite of a common misunderstanding that Bayesian and model-free approaches are incompatible, we merged them in the BayBoots implementation using the Kernel density estimator and Rubin 's Bayesian Bootstrap. We used the Bayes error rate (BER) instead of the usual P values as an alternative statistical index to rank a class marker's discriminative potential, since it can be visualized by a simple graphical representation and has an intuitive interpretation. Subsequently, Bayesian Bootstrap was used to assess BER 's credibility. We tested BayBoots on microarray data to look for markers for Trypanosoma cruzi strains isolated from cardiac and asymptomatic patients. We found that the three most frequently used methods in microarray analysis: t-test, non-parametric Wilcoxon test and correlation methods, yielded several markers that were discarded by a time-consuming visual check. On the other hand, the BayBoots graphical output and ranking was able to automatically identify markers for which classification performance was consistent. BayBoots is available at: http://www.vision.ime.usp.br/~rvencio/BayBoots.

Background: Spotted cDNA microarrays generally employ co-hybridization of fluorescently-labeled RNA targets to produce gene expression ratios for subsequent analysis. Direct comparison of two RNA samples in the same microarray provides the highest level of accuracy; however, due to the number of combinatorial pair-wise comparisons, the direct method is impractical for studies including large number of individual samples (e.g., tumor classification studies). For such studies, indirect comparisons using a common reference standard have been the preferred method. Here we evaluated the precision and accuracy of reconstructed ratios from three indirect methods relative to ratios obtained from direct hybridizations, herein considered as the gold-standard., Results: We performed hybridizations using a fixed amount of Cy3-labeled reference oligonucleotide (RefOligo) against distinct Cy5-labeled targets from prostate, breast and kidney tumor samples. Reconstructed ratios between all tissue pairs were derived from ratios between each tissue sample and RefOligo. Reconstructed ratios were compared to (i) ratios obtained in parallel from direct pair-wise hybridizations of tissue samples, and to (ii) reconstructed ratios derived from hybridization of each tissue against a reference RNA pool (RefPool). To evaluate the effect of the external references, reconstructed ratios were also calculated directly from intensity values of single-channel (One-Color) measurements derived from tissue sample data collected in the RefOligo experiments. We show that the average coefficient of variation of ratios between intra- and inter-slide replicates derived from RefOligo, RefPool and One-Color were similar and 2 to 4-fold higher than ratios obtained in direct hybridizations. Correlation coefficients calculated for all three tissue comparisons were also similar. In addition, the performance of all indirect methods in terms of their robustness to identify genes deemed as differentially expressed based on direct hybridizations, as well as false-positive and false-negative rates, were found to be comparable., Conclusion: RefOligo produces ratios as precise and accurate as ratios reconstructed from a RNA pool, thus representing a reliable alternative in reference-based hybridization experiments. In addition, One-Color measurements alone can reconstruct expression ratios without loss in precision or accuracy. We conclude that both methods are adequate options in large-scale projects where the amount of a common reference RNA pool is usually restrictive.

Background: The search for enriched (aka over-represented or enhanced) ontology terms in a list of genes obtained from microarray experiments is becoming a standard procedure for a system-level analysis. This procedure tries to summarize the information focussing on classification designs such as Gene Ontology, KEGG pathways, and so on, instead of focussing on individual genes. Although it is well known in statistics that association and significance are distinct concepts, only the former approach has been used to deal with the ontology term enrichment problem., Results: BayGO implements a Bayesian approach to search for enriched terms from microarray data. The R source-code is freely available at http://blasto.iq.usp.br/~tkoide/BayGO in three versions: Linux, which can be easily incorporated into pre-existent pipelines; Windows, to be controlled interactively; and as a web-tool. The software was validated using a bacterial heat shock response dataset, since this stress triggers known system-level responses., Conclusion: The Bayesian model accounts for the fact that, eventually, not all the genes from a given category are observable in microarray data due to low intensity signal, quality filters, genes that were not spotted and so on. Moreover, BayGO allows one to measure the statistical association between generic ontology terms and differential expression, instead of working only with the common significance analysis.

Purpose: This study was designed to identify genes that could predict response to doxorubicin-based primary chemotherapy in breast cancer patients., Experimental Design: Biopsy samples were obtained before primary treatment with doxorubicin and cyclophosphamide. RNA was extracted and amplified and gene expression was analyzed using cDNA microarrays., Results: Response to chemotherapy was evaluated in 51 patients, and based on Response Evaluation Criteria in Solid Tumors guidelines, 42 patients, who presented at least a partial response (> or =30% reduction in tumor dimension), were classified as responsive. Gene profile of samples, divided into training set (n = 38) and independent validation set (n = 13), were at first analyzed against a cDNA microarray platform containing 692 genes. Unsupervised clustering could not separate responders from nonresponders. A classifier was identified comprising EMILIN1, FAM14B, and PBEF, which however could not correctly classify samples included in the validation set. Our next step was to analyze gene profile in a more comprehensive cDNA microarray platform, containing 4,608 open reading frame expressed sequence tags. Seven samples of the initial training set (all responder patients) could not be analyzed. Unsupervised clustering could correctly group all the resistant samples as well as at least 85% of the sensitive samples. Additionally, a classifier, including PRSS11, MTSS1, and CLPTM1, could correctly distinguish 95.4% of the 44 samples analyzed, with only two misclassifications, one sensitive sample and one resistant tumor. The robustness of this classifier is 2.5 greater than the first one., Conclusion: A trio of genes might potentially distinguish doxorubicin-responsive from nonresponsive tumors, but further validation by a larger number of samples is still needed.

Xylella fastidiosa is the etiologic agent of diseases in a wide range of economically important crops including citrus variegated chlorosis, a major threat to the Brazilian citrus industry. The genomes of several strains of this phytopathogen have been completely sequenced enabling large-scale functional studies. In this work we used whole-genome DNA microarrays to investigate the transcription profile of X. fastidiosa grown in defined media with different glucose concentrations. Our analysis revealed that while transcripts related to fastidian gum production were unaffected, colicin-V-like and fimbria precursors were induced in high glucose medium. Based on these results, we suggest a model for colicin-defense mechanism in X. fastidiosa.

A collection of 237,954 sugarcane ESTs was examined in search of signal transduction genes. Over 3500 components involved in several aspects of signal transduction, transcription, development, cell cycle, stress responses and pathogen interaction were compiled into the Sugarcane Signal Transduction (SUCAST) Catalogue. Sequence comparisons and protein domain analysis revealed 477 receptors, 510 protein kinases, 107 protein phosphatases, 75 small GTPases, 17 G-proteins, 114 calcium and inositol metabolism proteins, and over 600 transcription factors. The elements were distributed into 29 main categories subdivided into 409 sub-categories. Genes with no matches in the public databases and of unknown function were also catalogued. A cDNA microarray was constructed to profile individual variation of plants cultivated in the field and transcript abundance in six plant organs (flowers, roots, leaves, lateral buds, and 1st and 4th internodes). From 1280 distinct elements analyzed, 217 (17%) presented differential expression in two biological samples of at least one of the tissues tested. A total of 153 genes (12%) presented highly similar expression levels in all tissues. A virtual profile matrix was constructed and the expression profiles were validated by real-time PCR. The expression data presented can aid in assigning function for the sugarcane genes and be useful for promoter characterization of this and other economically important grasses.

Blastocladiella emersonii is an aquatic fungus of the chytridiomycete class which diverged early from the fungal lineage and is notable for the morphogenetic processes which occur during its life cycle. Its particular taxonomic position makes this fungus an interesting system to be considered when investigating phylogenetic relationships and studying the biology of lower fungi. To contribute to the understanding of the complexity of the B. emersonii genome, we present here a survey of expressed sequence tags (ESTs) from various stages of the fungal development. Nearly 20,000 cDNA clones from 10 different libraries were partially sequenced from their 5' end, yielding 16,984 high-quality ESTs. These ESTs were assembled into 4,873 putative transcripts, of which 48% presented no matches with existing sequences in public databases. As a result of Gene Ontology (GO) project annotation, 1,680 ESTs (35%) were classified into biological processes of the GO structure, with transcription and RNA processing, protein biosynthesis, and transport as prevalent processes. We also report full-length sequences, useful for construction of molecular phylogenies, and several ESTs that showed high similarity with known proteins, some of which were not previously described in fungi. Furthermore, we analyzed the expression profile (digital Northern analysis) of each transcript throughout the life cycle of the fungus using Bayesian statistics. The in silico approach was validated by Northern blot analysis with good agreement between the two methodologies.

Different statistical methods have been used to classify a gene as differentially expressed in microarray experiments. They usually require a number of experimental observations to be adequately applied. However, many microarray experiments are constrained to low replication designs for different reasons, from financial restrictions to scarcely available RNA samples. Although performed in a high-throughput framework, there are few experimental replicas for each gene to allow the use of traditional or state-of-art statistical methods. In this work, we present a web-based bioinformatics tool that deals with real-life problems concerning low replication experiments. It uses an empirically derived criterion to classify a gene as differentially expressed by combining two widely accepted ideas in microarray analysis: self-self experiments to derive intensity-dependent cutoffs and non-parametric estimation techniques. To help laboratories without a bioinformatics infrastructure, we implemented the tool in a user-friendly website (http://blasto.iq.usp.br/~rvencio/HTself).

Trypanosoma cruzi presents high genetic diversity and parasite isolates show remarkable differences in biological parameters. In this study, we evaluated whether DNA microarrays containing CL Brener cDNAs can be used for comparative genomics and for the analysis of gene expression in T. cruzi. We constructed a prototype microarray with 710 expression sequence tags of CL Brener and 20 sequences of T. cruzi strains. These probes represent 665 unique genes. Results from four hybridisations with genomic DNA of Silvio (T. cruzi I) and CL Brener (hybrid genotype) identified 9.3% of the probes (68/730) differentially represented in the two genomes. Data from eight hybridisations with cDNA obtained from three independent parasite harvests of Silvio and CL Brener disclosed 84 sequences of 730 (11.5%) that showed statistical significant (P < or = 0.01) changes in expression (1.6-6.5-fold). Some of the array-identified sequences were confirmed by Southern and Northern blot analysis. Only 20% of the probes with increased expression in Silvio or CL Brener presented higher hybridisation with genomic DNA of either strain. Approximately 2.5% (18/730) and 9.0% (65/730) of the probes were differentially expressed (P < or = 0.01), respectively, in epimastigotes and metacyclic trypomastigotes of two T. cruzi II strains isolated from chronic chagasic patients. Microarrays identified several sequences for which differences in gene copy number and/or in the levels of RNA transcripts were previously demonstrated by different approaches. The data indicate that DNA microarrays are a useful tool for comparative studies between strains and provide further evidence for a high level of post-transcriptional regulation of RNA abundance in T. cruzi.