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.

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.

Reciprocal changes in gene expression profiles of cocultured breast epithelial cells and primary fibroblasts

The importance of epithelial-stroma interaction in normal breast development and tumor progression has been recognized. To identify genes that were regulated by these reciprocal interactions, we cocultured a nonmalignant (MCF10A) and a breast cancer derived (MDA-MB231) basal cell lines, with fibroblasts isolated from breast benign-disease adjacent tissues (NAF) or with carcinoma-associated fibroblasts (CAF), in a transwell system. Gene expression profiles of each coculture pair were compared with the correspondent monocultures, using a customized microarray. Contrariwise to large alterations in epithelial cells genomic profiles, fibroblasts were less affected. In MDA-MB231 highly represented genes downregulated by CAF derived factors coded for proteins important for the specificity of vectorial transport between ER and golgi, possibly affecting cell polarity whereas the response of MCF10A comprised an induction of genes coding for stress responsive proteins, representing a prosurvival effect. While NAF downregulated genes encoding proteins associated to glycolipid and fatty acid biosynthesis in MDA-MB231, potentially affecting membrane biogenesis, in MCF10A, genes critical for growth control and adhesion were altered. NAFs responded to coculture with MDA-MB231 by a decrease in the expression of genes induced by TGF beta 1 and associated to motility. However, there was little change in NAFs gene expression profile influenced by MCF10A. CAFs responded to the presence of both epithelial cells inducing genes implicated in cell proliferation. Our data indicate that interactions between breast fibroblasts and basal epithelial cells resulted in alterations in the genomic profiles of both cell types which may help to clarify some aspects of this heterotypic signaling. (C) 2009 UICC

Gene Expression Profiles Stratified according to Type 1 Diabetes Mellitus Susceptibility Regions

The MHC region (6p21) aggregates the major genes that contribute to susceptibility to type 1 diabetes (T1D). Three additional relevant susceptibility regions mapped on chromosomes 1p13 (PTPN22), 2q33 (CTLA-4), and 11p15 (insulin) have also been described by linkage studies. To evaluate the contribution of these susceptibility regions and the chromosomes that house these regions, we performed a large-scale differential gene expression on lymphomononuclear cells of recently diagnosed T1D patients, pinpointing relevant modulated genes clustered in these regions and their respective chromosomes. A total of 4608 cDNAs from the IMAGE library were spotted onto glass slides using robotic technology. Statistical analysis was carried out using the SAM program, and data regarding gene location and biological function were obtained at the SOURCE, NCBI, and FATIGO programs. Three induced genes were observed spanning around the MHC region (6p21-6p23), and seven modulated genes (5 repressed and 2 repressed) were seen spanning around the 6q21-24 region. Additional modulated genes were observed in and around the 1p13, 2q33, and 11p15 regions. Overall, modulated genes in these regions were primarily associated with cellular metabolism, transcription factors and signaling transduction. The differential gene expression characterization may identify new genes potentially involved with diabetes pathogenesis.

Mineralocorticoid Receptor Mutations Differentially Affect Individual Gene Expression Profiles in Pseudohypoaldosteronism Type 1

Context: Type 1 pseudohypoaldosteronism (PHA1), a primary form of mineralocorticoid resistance, isdueto inactivating mutations of the NR3C2 gene, coding for the mineralocorticoid receptor (MR). Objective: The objective of the study was to assess whether different NR3C2 mutations have distinct effects on the pattern of MR-dependent transcriptional regulation of aldosterone-regulated genes. Design and Methods: Four MR mutations affecting residues in the ligand binding domain, identified in families with PHA1, were tested. MR proteins generated by site-directed mutagenesis were analyzed for their binding to aldosterone and were transiently transfected into renal cells to explore the functional effects on the transcriptional activity of the receptors by cis-trans-cotrans-activation assays and by measuring the induction of endogenous gene transcription. Results: Binding assays showed very low or absent aldosterone binding for mutants MR(877Pro), MR(848Pro), and MR(947stop) and decreased affinity for aldosterone of MR(843Pro). Compared with wildtype MR, the mutations p.Leu843Pro and p.Leu877Pro displayed half-maximal aldosterone-dependent transactivation of reporter genes driven by mouse mammary tumor virus or glucocorticoid response element-2 dependent promoters, whereas MR(848Pro) and MR(947stop) nearly or completely lost transcriptional activity. Although MR(848Pro) and MR(947stop) were also incapable of inducing aldosterone-dependent gene expression ofendogenoussgk1, GILZ, NDRG2, and SCNN1A, MR(843Pro) retained complete transcriptional activity on sgk1 and GILZ gene expression, and MR(877Pro) negatively affected the expression of sgk1, NDRG2, and SCNN1A. Conclusions: Our data demonstrate that MR mutations differentially affect individual gene expression in a promoter-dependent manner. Investigation of differential gene expression profiles in PHA1 may allow a better understanding of the molecular substrate of phenotypic variability and to elucidate pathogenic mechanisms underlying the disease. (J Clin Endocrinol Metab 96: E519-E527, 2011)

Sub-telomere directed gene expression during initiation of invasive aspergillosis

Aspergillus fumigatus is a common mould whose spores are a component of the normal airborne flora. Immune dysfunction permits developmental growth of inhaled spores in the human lung causing aspergillosis, a significant threat to human health in the form of allergic, and life-threatening invasive infections. The success of A. fumigatus as a pathogen is unique among close phylogenetic relatives and is poorly characterised at the molecular level. Recent genome sequencing of several Aspergillus species provides an exceptional opportunity to analyse fungal virulence attributes within a genomic and evolutionary context. To identify genes preferentially expressed during adaptation to the mammalian host niche, we generated multiple gene expression profiles from minute samplings of A. fumigatus germlings during initiation of murine infection. They reveal a highly co-ordinated A. fumigatus gene expression programme, governing metabolic and physiological adaptation, which allows the organism to prosper within the mammalian niche. As functions of phylogenetic conservation and genetic locus, 28% and 30%, respectively, of the A. fumigatus subtelomeric and lineage-specific gene repertoires are induced relative to laboratory culture, and physically clustered genes including loci directing pseurotin, gliotoxin and siderophore biosyntheses are a prominent feature. Locationally biased A. fumigatus gene expression is not prompted by in vitro iron limitation, acid, alkaline, anaerobic or oxidative stress. However, subtelomeric gene expression is favoured following ex vivo neutrophil exposure and in comparative analyses of richly and poorly nourished laboratory cultured germlings. We found remarkable concordance between the A. fumigatus host-adaptation transcriptome and those resulting from in vitro iron depletion, alkaline shift, nitrogen starvation and loss of the methyltransferase LaeA. This first transcriptional snapshot of a fungal genome during initiation of mammalian infection provides the global perspective required to direct much-needed diagnostic and therapeutic strategies and reveals genome organisation and subtelomeric diversity as potential driving forces in the evolution of pathogenicity in the genus Aspergillus.

Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the sigma(54) regulon

Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a sigma(54)-dependent manner. A more complete picture of the sigma(54) regulon was achieved by combining the transcriptome data with an in silico search for potential sigma(54)-dependent promoters, using a position weight matrix approach. One of these sigma(54)-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a sigma(54)-dependent promoter. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the sigma(54) regulon.

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.

Identification of protein-coding and non-coding RNA expression profiles in CD34(+) and in stromal cells in refractory anemia with ringed sideroblasts

Background: Myelodysplastic syndromes (MDS) are a group of clonal hematological disorders characterized by ineffective hematopoiesis with morphological evidence of marrow cell dysplasia resulting in peripheral blood cytopenia. Microarray technology has permitted a refined high-throughput mapping of the transcriptional activity in the human genome. Non-coding RNAs (ncRNAs) transcribed from intronic regions of genes are involved in a number of processes related to post-transcriptional control of gene expression, and in the regulation of exon-skipping and intron retention. Characterization of ncRNAs in progenitor cells and stromal cells of MDS patients could be strategic for understanding gene expression regulation in this disease. Methods: In this study, gene expression profiles of CD34(+) cells of 4 patients with MDS of refractory anemia with ringed sideroblasts (RARS) subgroup and stromal cells of 3 patients with MDS-RARS were compared with healthy individuals using 44 k combined intron-exon oligoarrays, which included probes for exons of protein-coding genes, and for non-coding RNAs transcribed from intronic regions in either the sense or antisense strands. Real-time RT-PCR was performed to confirm the expression levels of selected transcripts. Results: In CD34(+) cells of MDS-RARS patients, 216 genes were significantly differentially expressed (q-value <= 0.01) in comparison to healthy individuals, of which 65 (30%) were non-coding transcripts. In stromal cells of MDS-RARS, 12 genes were significantly differentially expressed (q-value <= 0.05) in comparison to healthy individuals, of which 3 (25%) were non-coding transcripts. Conclusions: These results demonstrated, for the first time, the differential ncRNA expression profile between MDS-RARS and healthy individuals, in CD34(+) cells and stromal cells, suggesting that ncRNAs may play an important role during the development of myelodysplastic syndromes.

Gene expression profiling of papillary thyroid carcinoma identifies transcripts correlated with BRAF mutational status and lymph node metastasis

Purpose: To identify papillary thyroid carcinoma (PTC)-associated transcripts, we compared the gene expression profiles of three Serial Analysis of Gene Expression libraries generated from thyroid tumors and a normal thyroid tissue. Experimental Design: Selected transcripts were validated in a panel of 57 thyroid tumors using quantitative PCR (qPCR). An independent set of 71 paraffin-embedded sections was used for validation using immunohistochemical analysis. To determine if PTC-associated gene expression could predict lymph node involvement, a separate cohort of 130 primary PTC (54 metastatic and 76 nonmetastatic) was investigated. The BRAF(V600E) mutational status was compared with qPCR data to identify genes that might be regulated by abnormal BRAF/MEK/extracellular signal-regulated kinase signaling. Results: We identified and validated new PTC-associated transcripts. Three genes (CST6, CXCL14, and DHRS3) are strongly associated with PTC. Immunohistochemical analysis of CXCL14 confirmed the qPCR data and showed protein expression in PTC epithelial cells. We also observed that CST6, CXCL14, DHRS3, and SPP1 were associated with PTC lymph node metastasis, with CST6, CXCL14, and SPP1 being positively correlated with metastasis and DHRS3 being negatively correlated. Finally, we found a strong correlation between CST6 and CXCL14 expression and BRAF(V600E) mutational status, suggesting that these genes may be induced subsequently to BRAF activation and therefore may be downstream in the BRAF/MEK/extracellular signal-regulated kinase signaling pathway. Conclusion: CST6, CXCL14, DHRS3, and SPP1 may play a role in PTC pathogenesis and progression and are possible molecular targets for FTC therapy.

Deregulation of LOXL1 and HTRA1 Gene Expression in Endometriosis

Endometriosis is a gynecologic disease characterized by the presence of endometrial tissue outside the uterine cavity. Although 15% of the female population in reproductive age is affected by endometriosis, its pathogenesis remains unclear. According to the most accepted pathogenesis hypothesis, endometrial fragments from the menstrual phase are transported through the uterine tubes to the peritoneal cavity, where they undergo implantation and growth, invading adjacent tissues. However, the establishment of the disease requires that endometrial cells present molecular characteristics favoring the onset and progression of ectopic implantation. In this investigation, we analyzed the differential gene expression profiles of peritoneal and ovarian endometriotic lesions compared to the endometrial tissue of nonaffected women using rapid subtraction hybridization (RaSH). In our study, this method was applied to samples of endometriotic lesions from affected women and to biopsies of endometrium of healthy women without endometriosis, where we could identify 126 deregulated genes. To evaluate the expression of genes found by RaSH method, we measured LOXL1, HTRA1, and SPARC genes by real-time polymerase chain reaction. Significant different expression was obtained for HTRA1 and LOXL1, upregulated in the ectopic endometrium, suggesting that these genes are involved in the physiopathology of endometriosis and may favor the viability of endometrial cells at ectopic sites.

Gene Expression Profiling of Cultured Cells From Brainstem of Newborn Spontaneously Hypertensive and Wistar Kyoto Rats

The spontaneously hypertensive rat (SHR) is a good model to study several diseases such as the attention-deficit hyperactivity disorder, cardiopulmonary impairment, nephropathy, as well as hypertension, which is a multifactor disease that possibly involves alterations in gene expression in hypertensive relative to normotensive subjects. In this study, we used high-density oligoarrays to compare gene expression profiles in cultured neurons and glia from brainstem of newborn normotensive Wistar Kyoto (WKY) and SHR rats. We found 376 genes differentially expressed between SHR and WKY brainstem cells that preferentially map to 17 metabolic/signaling pathways. Some of the pathways and regulated genes identified herein are obviously related to cardiovascular regulation; in addition there are several genes differentially expressed in SHR not yet associated to hypertension, which may be attributed to other differences between SHR and WKY strains. This constitute a rich resource for the identification and characterization of novel genes associated to phenotypic differences observed in SHR relative to WKY, including hypertension. In conclusion, this study describes for the first time the gene profiling pattern of brainstem cells from SHR and WKY rats, which opens up new possibilities and strategies of investigation and possible therapeutics to hypertension, as well as for the understanding of the brain contribution to phenotypic differences between SHR and WKY rats.

Early Changes in Gene Expression Induced by Tobacco Smoke: Evidence for the Importance of Estrogen within Lung Tissue

Lung cancer is the leading cause of cancer deaths in the United States, surpassing breast cancer as the primary cause of cancer-related mortality in women. The goal of the present study was to identify early molecular changes in the lung induced by exposure to tobacco smoke and thus identify potential targets for chemoprevention. Female A/J mice were exposed to either tobacco smoke or HEPA-filtered air via a whole-body exposure chamber (6 h/d, 5 d/wk for 3, 8, and 20 weeks). Gene expression profiles of lung tissue from control and smoke-exposed animals were established using a 15K cDNA microarray. Cytochrome P450 1b1, a phase I enzyme involved in both the metabolism of xenobiotics and the 4-hydroxylation of 17 beta-estradiol (E(2)), was modulated to the greatest extent following smoke exposure. A panel of 10 genes were found to be differentially expressed in control and smoke-exposed lung tissues at 3, 8, and 20 weeks (P < 0.001). The interaction network of these differentially expressed genes revealed new pathways modulated by short-term smoke exposure, including estrogen metabolism. In addition, E(2) was detected within murine lung tissue by gas chromatography-coupled mass spectrometry and immunohistochemistry. Identification of the early molecular events that contribute to lung tumor formation is anticipated to lead to the development of promising targeted chemopreventive therapies. In conclusion, the presence of E2 within lung tissue when combined with the modulation of cytochrome P450 1b1 and other estrogen metabolism genes by tobacco smoke provides novel insight into a possible role for estrogens in lung cancer. Cancer Prev Res; 3(6); 707-17. (C) 2010 AACR.

Validation of reference genes for gene expression studies in the honey bee, Apis mellifera, by quantitative real-time RT-PCR

For obtaining accurate and reliable gene expression results it is essential that quantitative real-time RT-PCR (qRT-PCR) data are normalized with appropriate reference genes. The current exponential increase in postgenomic studies on the honey bee, Apis mellifera, makes the standardization of qRT-PCR results an important task for ongoing community efforts. For this aim we selected four candidate reference genes (actin, ribosomal protein 49, elongation factor 1-alpha, tbp-association factor) and used three software-based approaches (geNorm, BestKeeper and NormFinder) to evaluate the suitability of these genes as endogenous controls. Their expression was examined during honey bee development, in different tissues, and after juvenile hormone exposure. Furthermore, the importance of choosing an appropriate reference gene was investigated for two developmentally regulated target genes. The results led us to consider all four candidate genes as suitable genes for normalization in A. mellifera. However, each condition evaluated in this study revealed a specific set of genes as the most appropriated ones.

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.