Xylella fastidiosa gene expression analysis by DNA microarrays

Xylella fastidiosa genome sequencing has generated valuable data by identifying genes acting either on metabolic pathways or in associated pathogenicity and virulence. Based on available information on these genes, new strategies for studying their expression patterns, such as microarray technology, were employed. A total of 2,600 primer pairs were synthesized and then used to generate fragments using the PCR technique. The arrays were hybridized against cDNAs labeled during reverse transcription reactions and which were obtained from bacteria grown under two different conditions (liquid XDM2 and liquid BCYE). All data were statistically analyzed to verify which genes were differentially expressed. In addition to exploring conditions for X. fastidiosa genome-wide transcriptome analysis, the present work observed the differential expression of several classes of genes (energy, protein, amino acid and nucleotide metabolism, transport, degradation of substances, toxins and hypothetical proteins, among others). The understanding of expressed genes in these two different media will be useful in comprehending the metabolic characteristics of X. fastidiosa, and in evaluating how important certain genes are for the functioning and survival of these bacteria in plants.

Immunological responses and cytokine gene expression analysis to Cooperia punctata infections in resistant and susceptible Nelore cattle

Cellular and humoral immune response, as well as cytokine gene expression, was assessed in Nelore cattle with different degrees of resistance to Cooperia punctata natural infection. One hundred cattle (male, weaned, 11-12 months old), kept together on pasture, were evaluated. Faecal and blood samples were collected for parasitological and immunological assays. Based on nematode faecal egg counts (FEC) and worm burden, the seven most resistant and the eight most susceptible animals were selected. Tissue samples of the small intestine were collected for histological quantification of inflammatory cells and analysis of cytokine gene expression (IL-2, IL-4, IL-8, IL-1 2p35, IL-13, TNF-alpha, IFN-gamma, MCP-1, MCP-2, and MUC- 1) using real-time RT-PCR. Mucus samples were also collected for IgA levels determination. Serum IgG1 mean levels against C. punctata antigens were higher in the resistant group, but significant differences between groups were only observed 14 days after the beginning of the experiment against infective larvae (1-3) and 14 and 84 days against adult antigens. The resistant group also presented higher IgA levels against C. punctata (L3 and adult) antigens with significant difference 14 days after the beginning of the trial (P < 0.05). In the small-intestine mucosa, levels of IgA anti-L3 and anti-adult C. punctata were higher in the resistant group, compared with the susceptible group (P < 0.05). Gene expression of both T(H)2 cytokines (IL-4 and IL-13) in the resistant group and T(H)1 cytokines (IL-2, IL-1 2p35, IFN-gamma and MCP-1) in the susceptible group was up-regulated. Such results suggested that immune response to C. punctata was probably mediated by TH2 cytokines in the resistant group and by T(H)1 cytokines in the susceptible group. (C) 2008 Elsevier B.V. All rights reserved.

Gene expression analysis of Paracoccidioides brasiliensis transition from conidium to yeast cell

Paracoccidioides brasiliensis infectious process relies on the initial expression of virulence faactors that are assumed to be controlled by molecular mechanisms through which the conidia and/or mycelial fragments convert to yeast cells. In order to analyze the profile of the thermally-induced dimorphic gene expression, 48 h C-L transition cultures which had been incubated at 36 degrees C were studied. By this time approximately 50% of the conidial population had already reverted to yeast form cells. At this transition time, an EST-Orestes library was constructed and characterized. As a result, 79 sequences were obtained, of which 39 (49.4%) had not been described previously in other libraries of this fungus and which could represent novel exclusive C-Y transition genes. Two of these sequences are, among others, cholestanol delta-isomerase, and electron transfer flavoprotein-ubiquinoneoxidoreductase (ETF-QO). The other 40 (50.6%) sequences were shared with Mycelia (M), Yeast (Y) or Mycelia to yest transition (M-Y) libraries. An important component of this group of sequences is a putative response regulator receiver SKN7, a protein of high importance in stress adaptation and a regulator of virulence in some bacteria and fungi. This is the first report identifying genes expressed during the C-Y transition process, the initial step required to understand the natural history of P brasiliensis conidia induced infection.

Differential gene expression analysis of iodide-treated rat thyroid follicular cell line PCCl3

The inhibitory effect of supraphysiological iodide concentrations on thyroid hormone synthesis (Wolff - Chaikoff effect) and on thyrocyte proliferation is largely known as iodine autoregulation. However, the molecular mechanisms by which iodide modulates thyroid function remain unclear. In this paper, we analyze the transcriptome profile of the rat follicular cell lineage PCCl3 under untreated and treated conditions with 10 (- 3) M sodium iodide (NaI). Serial analysis of gene expression (SAGE) revealed 84 transcripts differentially expressed in response to iodide (p <= 0.001). We also showed that iodide excess inhibits the expression of essential genes for thyroid differentiation: Tshr, Nis, Tg, and Tpo. Relative expression of 14 of 20 transcripts selected by SAGE was confirmed by real-time PCR. Considering the key role of iodide organification in thyroid physiology, we also observed that both the oxidized form of iodide and iodide per se are responsible for gene expression modulation in response to iodide excess. (c) 2008 Elsevier Inc. All rights reserved.

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.

Global Gene Expression Analysis during Sporulation of the Aquatic Fungus Blastocladiella emersonii

The Blastocladiella emersonii life cycle presents a number of drastic biochemical and morphological changes, mainly during two cell differentiation stages: germination and sporulation. To investigate the transcriptional changes taking place during the sporulation phase, which culminates with the production of the zoospores, motile cells responsible for the dispersal of the fungus, microarray experiments were performed. Among the 3,773 distinct genes investigated, a total of 1,207 were classified as differentially expressed, relative to time zero of sporulation, at at least one of the time points analyzed. These results indicate that accurate transcriptional control takes place during sporulation, as well as indicating the necessity for distinct molecular functions throughout this differentiation process. The main functional categories overrepresented among upregulated genes were those involving the microtubule, the cytoskeleton, signal transduction involving Ca(2+), and chromosome organization. On the other hand, protein biosynthesis, central carbon metabolism, and protein degradation were the most represented functional categories among downregulated genes. Gene expression changes were also analyzed in cells sporulating in the presence of subinhibitory concentrations of glucose or tryptophan. Data obtained revealed overexpression of microtubule and cytoskeleton transcripts in the presence of glucose, probably causing the shape and motility problems observed in the zoospores produced under this condition. In contrast, the presence of tryptophan during sporulation led to upregulation of genes involved in oxidative stress, proteolysis, and protein folding. These results indicate that distinct physiological pathways are involved in the inhibition of sporulation due to these two classes of nutrient sources.

Pre-processing for noise detection in gene expression classification data

Due to the imprecise nature of biological experiments, biological data is often characterized by the presence of redundant and noisy data. This may be due to errors that occurred during data collection, such as contaminations in laboratorial samples. It is the case of gene expression data, where the equipments and tools currently used frequently produce noisy biological data. Machine Learning algorithms have been successfully used in gene expression data analysis. Although many Machine Learning algorithms can deal with noise, detecting and removing noisy instances from the training data set can help the induction of the target hypothesis. This paper evaluates the use of distance-based pre-processing techniques for noise detection in gene expression data classification problems. This evaluation analyzes the effectiveness of the techniques investigated in removing noisy data, measured by the accuracy obtained by different Machine Learning classifiers over the pre-processed data.

Gene expression profile of the plant pathogen Fusarium graminearum under the antagonistic effect of Pantoea agglomerans

The pathogenic fungus Fusarium graminearum is an ongoing threat to agriculture, causing losses in grain yield and quality in diverse crops. Substantial progress has been made in the identification of genes involved in the suppression of phytopathogens by antagonistic microorganisms; however, limited information regarding responses of plant pathogens to these biocontrol agents is available. Gene expression analysis was used to identify differentially expressed transcripts of the fungal plant pathogen F. graminearum under antagonistic effect of the bacterium Pantoea agglomerans. A macroarray was constructed, using 1014 transcripts from an F. graminearum cDNA library. Probes consisted of the cDNA of F. graminearum grown in the presence and in the absence of P. agglomerans. Twenty-nine genes were either up (19) or down (10) regulated during interaction with the antagonist bacterium. Genes encoding proteins associated with fungal defense and/or virulence or with nutritional and oxidative stress responses were induced. The repressed genes coded for a zinc finger protein associated with cell division, proteins containing cellular signaling domains, respiratory chain proteins, and chaperone-type proteins. These data give molecular and biochemical evidence of response of F. graminearum to an antagonist and could help develop effective biocontrol procedures for pathogenic plant fungi.

Gene Expression Profiles in Radiation Workers Occupationally Exposed to Ionizing Radiation

Ionizing radiation OR) imposes risks to human health and the environment. IR at low doses and low (lose rates has the potency to initiate carcinogenesis. Genotoxic environmental agents such as IR trigger a cascade of signal transduction pathways for cellular protection. In this study, using cDNA microarray technique, we monitored the gene expression profiles in lymphocytes derived from radiation-ex posed individuals (radiation workers). Physical dosimetry records on these patients indicated that the absorbed dose ranged from 0.696 to 39.088 mSv. Gene expression analysis revealed statistically significant transcriptional changes in a total of 78 genes (21 up-regulated and 57 clown-regulated) involved in several biological processes such as ubiquitin cycle (UHRF2 and PIAS1), DNA repair (LIG3, XPA, ERCC5, RAD52, DCLRE1C), cell cycle regulation/proliferation (RHOA, CABLES2, TGFB2, IL16), and stress response (GSTP1, PPP2R5A, DUSP22). Some of the genes that showed altered expression profiles in this study call be used as biomarkers for monitoring the chronic low level exposure in humans. Additionally, alterations in gene expression patterns observed in chronically exposed radiation workers reinforces the need for defining the effective radiation dose that causes immediate genetic damage as well as the long-term effects on genomic instability, including cancer.

A score system for quality evaluation of RNA sequence tags: an improvement for gene expression profiling

Background: High-throughput molecular approaches for gene expression profiling, such as Serial Analysis of Gene Expression (SAGE), Massively Parallel Signature Sequencing (MPSS) or Sequencing-by-Synthesis (SBS) represent powerful techniques that provide global transcription profiles of different cell types through sequencing of short fragments of transcripts, denominated sequence tags. These techniques have improved our understanding about the relationships between these expression profiles and cellular phenotypes. Despite this, more reliable datasets are still necessary. In this work, we present a web-based tool named S3T: Score System for Sequence Tags, to index sequenced tags in accordance with their reliability. This is made through a series of evaluations based on a defined rule set. S3T allows the identification/selection of tags, considered more reliable for further gene expression analysis. Results: This methodology was applied to a public SAGE dataset. In order to compare data before and after filtering, a hierarchical clustering analysis was performed in samples from the same type of tissue, in distinct biological conditions, using these two datasets. Our results provide evidences suggesting that it is possible to find more congruous clusters after using S3T scoring system. Conclusion: These results substantiate the proposed application to generate more reliable data. This is a significant contribution for determination of global gene expression profiles. The library analysis with S3T is freely available at http://gdm.fmrp.usp.br/s3t/.S3T source code and datasets can also be downloaded from the aforementioned website.

Selection of suitable housekeeping genes for expression analysis in glioblastoma using quantitative RT-PCR

Background: Considering the broad variation in the expression of housekeeping genes among tissues and experimental situations, studies using quantitative RT-PCR require strict definition of adequate endogenous controls. For glioblastoma, the most common type of tumor in the central nervous system, there was no previous report regarding this issue. Results: Here we show that amongst seven frequently used housekeeping genes TBP and HPRT1 are adequate references for glioblastoma gene expression analysis. Evaluation of the expression levels of 12 target genes utilizing different endogenous controls revealed that the normalization method applied might introduce errors in the estimation of relative quantities. Genes presenting expression levels which do not significantly differ between tumor and normal tissues can be considered either increased or decreased if unsuitable reference genes are applied. Most importantly, genes showing significant differences in expression levels between tumor and normal tissues can be missed. We also demonstrated that the Holliday Junction Recognizing Protein, a novel DNA repair protein over expressed in lung cancer, is extremely over-expressed in glioblastoma, with a median change of about 134 fold. Conclusion: Altogether, our data show the relevance of previous validation of candidate control genes for each experimental model and indicate TBP plus HPRT1 as suitable references for studies on glioblastoma gene expression.

Sequential analysis of global gene expression profiles in immature and in vitro matured bovine oocytes: potential molecular markers of oocyte maturation

Background: Without intensive selection, the majority of bovine oocytes submitted to in vitro embryo production (IVP) fail to develop to the blastocyst stage. This is attributed partly to their maturation status and competences. Using the Affymetrix GeneChip Bovine Genome Array, global mRNA expression analysis of immature (GV) and in vitro matured (IVM) bovine oocytes was carried out to characterize the transcriptome of bovine oocytes and then use a variety of approaches to determine whether the observed transcriptional changes during IVM was real or an artifact of the techniques used during analysis. Results: 8489 transcripts were detected across the two oocyte groups, of which similar to 25.0% (2117 transcripts) were differentially expressed (p < 0.001); corresponding to 589 over-expressed and 1528 under-expressed transcripts in the IVM oocytes compared to their immature counterparts. Over expression of transcripts by IVM oocytes is particularly interesting, therefore, a variety of approaches were employed to determine whether the observed transcriptional changes during IVM were real or an artifact of the techniques used during analysis, including the analysis of transcript abundance in oocytes in vitro matured in the presence of a-amanitin. Subsets of the differentially expressed genes were also validated by quantitative real-time PCR (qPCR) and the gene expression data was classified according to gene ontology and pathway enrichment. Numerous cell cycle linked (CDC2, CDK5, CDK8, HSPA2, MAPK14, TXNL4B), molecular transport (STX5, STX17, SEC22A, SEC22B), and differentiation (NACA) related genes were found to be among the several over-expressed transcripts in GV oocytes compared to the matured counterparts, while ANXA1, PLAU, STC1and LUM were among the over-expressed genes after oocyte maturation. Conclusion: Using sequential experiments, we have shown and confirmed transcriptional changes during oocyte maturation. This dataset provides a unique reference resource for studies concerned with the molecular mechanisms controlling oocyte meiotic maturation in cattle, addresses the existing conflicting issue of transcription during meiotic maturation and contributes to the global goal of improving assisted reproductive technology.

Random X Inactivation and Extensive Mosaicism in Human Placenta Revealed by Analysis of Allele-Specific Gene Expression along the X Chromosome

Imprinted inactivation of the paternal X chromosome in marsupials is the primordial mechanism of dosage compensation for X-linked genes between females and males in Therians. In Eutherian mammals, X chromosome inactivation (XCI) evolved into a random process in cells from the embryo proper, where either the maternal or paternal X can be inactivated. However, species like mouse and bovine maintained imprinted XCI exclusively in extraembryonic tissues. The existence of imprinted XCI in humans remains controversial, with studies based on the analyses of only one or two X-linked genes in different extraembryonic tissues. Here we readdress this issue in human term placenta by performing a robust analysis of allele-specific expression of 22 X-linked genes, including XIST, using 27 SNPs in transcribed regions. We show that XCI is random in human placenta, and that this organ is arranged in relatively large patches of cells with either maternal or paternal inactive X. In addition, this analysis indicated heterogeneous maintenance of gene silencing along the inactive X, which combined with the extensive mosaicism found in placenta, can explain the lack of agreement among previous studies. Our results illustrate the differences of XCI mechanism between humans and mice, and highlight the importance of addressing the issue of imprinted XCI in other species in order to understand the evolution of dosage compensation in placental mammals.

Gene Expression Complex Networks: Synthesis, Identification, and Analysis

Thanks to recent advances in molecular biology, allied to an ever increasing amount of experimental data, the functional state of thousands of genes can now be extracted simultaneously by using methods such as cDNA microarrays and RNA-Seq. Particularly important related investigations are the modeling and identification of gene regulatory networks from expression data sets. Such a knowledge is fundamental for many applications, such as disease treatment, therapeutic intervention strategies and drugs design, as well as for planning high-throughput new experiments. Methods have been developed for gene networks modeling and identification from expression profiles. However, an important open problem regards how to validate such approaches and its results. This work presents an objective approach for validation of gene network modeling and identification which comprises the following three main aspects: (1) Artificial Gene Networks (AGNs) model generation through theoretical models of complex networks, which is used to simulate temporal expression data; (2) a computational method for gene network identification from the simulated data, which is founded on a feature selection approach where a target gene is fixed and the expression profile is observed for all other genes in order to identify a relevant subset of predictors; and (3) validation of the identified AGN-based network through comparison with the original network. The proposed framework allows several types of AGNs to be generated and used in order to simulate temporal expression data. The results of the network identification method can then be compared to the original network in order to estimate its properties and accuracy. Some of the most important theoretical models of complex networks have been assessed: the uniformly-random Erdos-Renyi (ER), the small-world Watts-Strogatz (WS), the scale-free Barabasi-Albert (BA), and geographical networks (GG). The experimental results indicate that the inference method was sensitive to average degree k variation, decreasing its network recovery rate with the increase of k. The signal size was important for the inference method to get better accuracy in the network identification rate, presenting very good results with small expression profiles. However, the adopted inference method was not sensible to recognize distinct structures of interaction among genes, presenting a similar behavior when applied to different network topologies. In summary, the proposed framework, though simple, was adequate for the validation of the inferred networks by identifying some properties of the evaluated method, which can be extended to other inference methods.

Crotalus durissus collilineatus venom gland transcriptome: Analysis of gene expression profile

Crotalus durissus rattlesnakes are responsible for the most lethal cases of snakebites in Brazil. Crotalus durissus collilineatus subspecies is related to a great number of accidents in Southeast and Central West regions, but few studies on its venom composition have been carried out to date. In an attempt to describe the transcriptional profile of the C. durissus collilineatus venom gland, we generated a cDNA library and the sequences obtained could be identified by similarity searches on existing databases. Out of 673 expressed sequence tags (ESTs) 489 produced readable sequences comprising 201 singletons and 47 clusters of two or more ESTs. One hundred and fifty reads (60.5%) produced significant hits to known sequences. The results showed a predominance of toxin-coding ESTs instead of transcripts coding for proteins involved in all cellular functions. The most frequent toxin was crotoxin, comprising 88% of toxin-coding sequences. Crotoxin B, a basic phospholipase A(2) (PLA(2)) subunit of crotoxin, was represented in more variable forms comparing to the non-enzymatic subunit (crotoxin A), and most sequences coding this molecule were identified as CB1 isoform from Crotalus durissus terrificus venom. Four percent of toxin-related sequences in this study were identified as growth factors, comprising five sequences for vascular endothelial growth factor (VEGF) and one for nerve growth factor (NGF) that showed 100% of identity with C. durissus terrificus NGF. We also identified two clusters for metalloprotease from PII class comprising 3% of the toxins, and two for serine proteases, including gyroxin (2.5%). The remaining 2.5% of toxin-coding ESTs represent singletons identified as homologue sequences to cardiotoxin, convulxin, angiotensin-converting enzyme inhibitor and C-type natriuretic peptide, Ohanin, crotamin and PLA(2) inhibitor. These results allowed the identification of the most common classes of toxins in C. durissus collilineatus snake venom, also showing some unknown classes for this subspecies and even for C. durissus species, such as cardiotoxins and VEGF. (C) 2009 Published by Elsevier Masson SAS.