Short communication: Acute but transient increase in serum insulin reduces messenger RNA expression of hepatic enzymes associated with progesterone catabolism in dairy cows

The objective of this experiment was to evaluate the effects of glucose infusion on serum concentrations of glucose, insulin, and progesterone (P4), as well as mRNA expression of hepatic CYP2C19 and CYP3A4 in nonlactating, ovariectomized cows in adequate nutritional status. Eight Gir × Holstein cows were maintained on a low-quality Brachiaria brizantha pasture with reduced forage availability, but they individually received, on average, 3. kg/cow daily (as fed) of a corn-based concentrate from d -28 to 0 of the experiment. All cows had an intravaginal P4-releasing device inserted on d -14, which remained in cows until the end of the experiment (d 1). On d 0, cows were randomly assigned to receive, in a crossover design containing 2 periods of 24. h each (d 0 and 1), (1) an intravenous glucose infusion (GLUC; 0.5. g of glucose/kg of BW, over a 3-h period) or (2) an intravenous saline infusion (SAL; 0.9%, over a 3-h period). Cows were fasted for 12. h before infusions, and they remained fasted during infusion and sample collections. Blood samples were collected at 0, 3, and 6. h relative to the beginning of infusions. Liver biopsies were performed concurrently with blood collections at 0 and 3. h. After the last blood collection of period 1, cows received concentrate and returned to pasture. Cows gained BW (16.5 ± 3.6. kg) and BCS (0.08 ± 0.06) from d -28 to 0. Cows receiving GLUC had greater serum glucose and insulin concentrations at 3. h compared with SAL cohorts. No treatment effects were detected for serum P4 concentrations, although mRNA expression of CYP2C19 and CYP3A4 after the infusion period was reduced for cows in the GLUC treatment compared with their cohorts in the SAL treatment. In conclusion, hepatic CYP3A4 and CYP2C19 mRNA expression can be promptly modulated by glucose infusion followed by acute increases in circulating insulin, which provides novel insight into the physiological mechanisms associating nutrition and reproductive function in dairy cows. © 2013 American Dairy Science Association.

Reference Gene Selection for Gene Expression Analysis of Oocytes Collected from Dairy Cattle and Buffaloes during Winter and Summer

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comprehensive genome methylation and whole genome expression analysis in penile carcinoma: Uncovering new molecular markers

Background: Penile carcinoma (PeCa) is frequently associated with high morbidity rates. Unlikely of the vast majority of tumors, there is no molecular markers described that are able to assist in diagnosis and prognosis or with potential to be therapeutic targets in PeCa. Patients and methods: DNA methylation status (244K Human DNA Methylation Microarray platform, Agilent Technologies) and large-scale expression analysis (4x44K Whole Human Genome Microarray, Agilent Technologies) were performed in 35 and 37 PeCa, respectively. Quantitative bisulfite pyrosequencing (qBP) and RT-qPCR were used to validate the findings in 93 samples. HPV status was assessed using the Linear Array HPV Genotyping kit (Roche Molecular Diagnostics, CA, USA). Results: Methylome analysis revealed 171 hypermethylated and 449 hypomethylated CpGs sites and the transcriptome profiling showed 2986 down- and 2817 over-expressed genes. HPV positivity was found in 32.7% of the cases, mainly the HPV16. The integrative analysis in 32 PeCa revealed a panel of 96 genes with inverse correlation between methylation and gene expression levels. The CpG hypermetlylation and gene downexpression, was confirmed for TWIST1, RSOP2, SOX3, SOX17, CD133, OTX2, HOXA3 and MEIS. In addition, BIRC5, DNMT1 and DNMT3B presented low levels of methylation and overexpression. The comparison of the results with clinical findings revealed that LIN28A, NKX2.2, NKX2.3, LHX5, BDNF, FOXA1 and CDX2 were associated with poor prognosis features. Conclusion: Putative prognostic markers were detected revealing that DNA methylation modulates the expression of several genes in PeCa. These data may prove instrumental for biomarker discovery in clinics and molecular epidemiology of PeCa.

Gene expression analysis of laryngeal squamous cell carcinoma

Laryngeal squamous cell carcinoma (LSCC) is one of the most common malignancies of the head and neck tumors Zhang et al., 2013 [1]). Previous studies have associated its occurrence with social activities, such as tobacco and alcohol consumption (Hashibe et al., 2007a [2]; Hashibe et al., 2007b [3]; Shangina et al., 2006 [4]). Here, we performed a genome-wide gene expression profiling in thirty-one patients positively diagnosed for LSCC, in order to investigate new targets involved in tumorigenesis.

Xylella fastidiosa: An in vivo system to study possible survival strategies within citrus xylem vessels based on global gene expression analysis

Xylella fastidiosa inhabits the plant xylem, a nutrient-poor environment, so that mechanisms to sense and respond to adverse environmental conditions are extremely important for bacterial survival in the plant host. Although the complete genome sequences of different Xylella strains have been determined, little is known about stress responses and gene regulation in these organisms. In this work, a DNA microarray was constructed containing 2,600 ORFs identified in the genome sequencing project of Xylella fastidiosa 9a5c strain, and used to check global gene expression differences in the bacteria when it is infecting a symptomatic and a tolerant citrus tree. Different patterns of expression were found in each variety, suggesting that bacteria are responding differentially according to each plant xylem environment. The global gene expression profile was determined and several genes related to bacterial survival in stressed conditions were found to be differentially expressed between varieties, suggesting the involvement of different strategies for adaptation to the environment. The expression pattern of some genes related to the heat shock response, toxin and detoxification processes, adaptation to atypical conditions, repair systems as well as some regulatory genes are discussed in this paper. DNA microarray proved to be a powerful technique for global transcriptome analyses. This is one of the first studies of Xylella fastidiosa gene expression in vivo which helped to increase insight into stress responses and possible bacterial survival mechanisms in the nutrient-poor environment of xylem vessels.

Resistance to octreotide LAR in acromegalic patients with high SSTR2 expression: analysis of AIP expression

We present here the clinical and molecular data of two patients with acromegaly treated with octreotide LAR after non-curative surgery, and who presented different responses to therapy. Somatostatin receptor type 2 and 5 (SSTR2 and SSTR5), and aryl hydrocarbon receptor-interacting protein (AIP) expression levels were analyzed by qPCR. In both cases, high SSTR2 and low SSTR5 expression levels were detected; however, only one of the patients achieved disease control after octreotide LAR therapy. When we analyzed AIP expression levels of both cases, the patient whose disease was controlled after therapy exhibited AIP expression levels that were two times higher than the patient whose disease was still active. These two cases illustrate that, although the currently available somatostatin analogs bind preferentially to SSTR2, some patients are not responsive to therapy despite high expression of this receptor. This difference could be explained by differences in post-receptor signaling pathways, including the recently described involvement of AIP. Arq Bras Endocrinol Metab. 2012;56(8):501-6

Decreased RNA expression of interleukin 17A in skin of leprosy

Interleukin-17A (IL-17A) is a proinflamatory cytokine that plays an important role in fighting pathogens at mucosal interfaces, by summoning neutrophils and upregulating cytoplasmatic antimicrobial peptides. So far, the presence of IL-17A in leprosy has not been demonstrated. The expression of IL-17A and related cytokines (IL-6 and IL-23p19) was addressed through RNA extraction and cDNA quantitative amplification in macerated biopsies of active lesions of 48 leprosy patients and 20 fragments of normal skin of individuals. Blood levels of IL-17A, IL-23p19 and IL-6 were determined by ELISA. We found an abrogated mRNA IL-17A response in all biopsies of leprosy patients, as compared with controls. Circulating IL-17A and IL-23p19 were undetectable in both patients and controls, but IL-6 was higher in lepromatous patients. Although at low levels, IL-17A mRNA in lepromatous patients had an inverse linear correlation with bacillary burden. Low expression of IL-17A in patients may be a constitutive genetic feature of leprosy patients or a circumstantial event induced by the local presence of the pathogen, as an escape mechanism.

CLONING AND EXPRESSION ANALYSIS OF ALLOGRAFT INFLAMMATORY FACTOR TYPE 1 IN COELOMOCYTES OF ANTARCTIC SEA URCHIN (STERECHINUS NEUMAYERI)

We have cloned and characterized for the first time an allograft inflammatory factor 1 (Sn-AIF-1) from the Antarctic sea urchin. We report the cloning of Sn-AIF-1 cDNA and the characterization of its expression in coelomocytes after a bacterial challenge. The cDNA Sn-AIF-1 has a size of 608 bp and encodes a polypeptide of 151 aa. The deduced amino acid sequence has a putative size of 17.430 Da, an isoelectric point of 4.92, and shows 2 elongation factor handlike motifs that normally bind calcium ions. BLAST analysis revealed close matches with other known AIF-1. The deduced amino acid sequence of Sn-AIF-1 showed high homology with AIF-1 in vertebrates such as fish, mice, and humans; and in the case of invertebrates, the major degree of identity (55%) was with a predicted sequence of the purple sea urchin AIF-1, and 52% corresponded to a sponge. Expression of Sn-AIF-1 mRNA was analyzed by qPCR. Sn-AIF-1 mRNA expression was measured from coelomocytes after a bacterial challenge using RT-PCR and revealed that the gene was upregulated after 24 h. Sn-AIF-1 could participate in the inflammatory response, particularly in the activation of coelomocytes and their survival.

Expression analysis of stem cell-related genes reveal OCT4 as a predictor of poor clinical outcome in medulloblastoma

Aberrant expression of stem cell-related genes in tumors may confer more primitive and aggressive traits affecting clinical outcome. Here, we investigated expression and prognostic value of the neural stem cell marker CD133, as well as of the pluripotency genes LIN28 and OCT4 in 37 samples of pediatric medulloblastoma, the most common and challenging type of embryonal tumor. While most medulloblastoma samples expressed CD133 and LIN28, OCT4 expression was found to be more sporadic, with detectable levels occurring in 48% of tumors. Expression levels of OCT4, but not CD133 or LIN28, were significantly correlated with shorter survival (P <= 0.0001). Median survival time of patients with tumors hyperexpressing OCT4 and tumors displaying low/undetectable OCT4 expression were 6 and 153 months, respectively. More importantly, when patients were clinically stratified according to their risk of tumor recurrence, positive OCT4 expression in primary tumor specimens could discriminate patients classified as average risk but which further deceased within 5 years of diagnosis (median survival time of 28 months), a poor clinical outcome typical of high risk patients. Our findings reveal a previously unknown prognostic value for OCT4 expression status in medulloblastoma, which might be used as a further indicator of poor survival and aid postoperative treatment selection, with a particular potential benefit for clinically average risk patients.

Expression Analysis of Wound Healing Genes in Human Periapical Granulomas of Progressive and Stable Nature

Introduction: Wound healing process involves the activation of extracellular matrix components, remodeling enzymes, cellular adhesion molecules, growth factors, cytokines and chemokines genes. However, the molecular patterns underlying the healing process periapical environment remain unclear. Here we hypothesized that endodontic infection might result in an imbalance in the expression of wound healing genes involved in the pathogenesis of periapical lesions. Furthermore, we suggest that differential expression of wound healing markers in active and latent granulomas could account for different clinical outcomes for such lesions. Methods: Study samples consisted of 93 periapical granulomas collected after endodontic surgeries and 24 healthy periodontal ligament tissues collected from premolars extracted for orthodontic purposes as control samples. Of these, 10 periapical granulomas and 5 healthy periapical tissues were used for expression analysis of 84 wound healing genes by using a pathway-specific real-time polymerase chain reaction array. The remaining 83 granulomas and all 24 control specimens were used to validate the obtained array data by real-time polymerase chain reaction. Observed variations in expression of wound healing genes were analyzed according to the classification of periapical granulomas as active/progressive versus inactive/stable (as determined by receptor activator for nuclear factor kappa B ligand/osteoprotegerin expression ratio). Results: We observed a marked increase of 5-fold or greater in SERPINE1, TIMP1, COL1A1, COL5A1, VTN, CTGF, FGF7, TGFB1, TNF, CXCL11, ITGA4, and ITGA5 genes in the periapical granulomas when compared with control samples. SERPINE1, TIMP1, COL1A1, TGFB1, and ITGA4 mRNA expression was significantly higher in inactive compared with active periapical granulomas (P < .001), whereas TNF and CXCL11 mRNA expression was higher in active lesions (P < .001). Conclusions: The identification of novel gene targets that curb the progression status of periapical lesions might contribute to a more accurate diagnosis and lead to treatment modalities more conducive to endodontic success. (J Endod 2012;38:185-190)

Identification and expression analysis of microRNAs and targets in the biofuel crop sugarcane

Abstract Background MicroRNAs (miRNAs) are small regulatory RNAs, some of which are conserved in diverse plant genomes. Therefore, computational identification and further experimental validation of miRNAs from non-model organisms is both feasible and instrumental for addressing miRNA-based gene regulation and evolution. Sugarcane (Saccharum spp.) is an important biofuel crop with publicly available expressed sequence tag and genomic survey sequence databases, but little is known about miRNAs and their targets in this highly polyploid species. Results In this study, we have computationally identified 19 distinct sugarcane miRNA precursors, of which several are highly similar with their sorghum homologs at both nucleotide and secondary structure levels. The accumulation pattern of mature miRNAs varies in organs/tissues from the commercial sugarcane hybrid as well as in its corresponding founder species S. officinarum and S. spontaneum. Using sugarcane MIR827 as a query, we found a novel MIR827 precursor in the sorghum genome. Based on our computational tool, a total of 46 potential targets were identified for the 19 sugarcane miRNAs. Several targets for highly conserved miRNAs are transcription factors that play important roles in plant development. Conversely, target genes of lineage-specific miRNAs seem to play roles in diverse physiological processes, such as SsCBP1. SsCBP1 was experimentally confirmed to be a target for the monocot-specific miR528. Our findings support the notion that the regulation of SsCBP1 by miR528 is shared at least within graminaceous monocots, and this miRNA-based post-transcriptional regulation evolved exclusively within the monocots lineage after the divergence from eudicots. Conclusions Using publicly available nucleotide databases, 19 sugarcane miRNA precursors and one new sorghum miRNA precursor were identified and classified into 14 families. Comparative analyses between sugarcane and sorghum suggest that these two species retain homologous miRNAs and targets in their genomes. Such conservation may help to clarify specific aspects of miRNA regulation and evolution in the polyploid sugarcane. Finally, our dataset provides a framework for future studies on sugarcane RNAi-dependent regulatory mechanisms.

Multivariate gene expression analysis reveals functional connectivity changes between normal/tumoral prostates

Abstract Background Prostate cancer is a leading cause of death in the male population, therefore, a comprehensive study about the genes and the molecular networks involved in the tumoral prostate process becomes necessary. In order to understand the biological process behind potential biomarkers, we have analyzed a set of 57 cDNA microarrays containing ~25,000 genes. Results Principal Component Analysis (PCA) combined with the Maximum-entropy Linear Discriminant Analysis (MLDA) were applied in order to identify genes with the most discriminative information between normal and tumoral prostatic tissues. Data analysis was carried out using three different approaches, namely: (i) differences in gene expression levels between normal and tumoral conditions from an univariate point of view; (ii) in a multivariate fashion using MLDA; and (iii) with a dependence network approach. Our results show that malignant transformation in the prostatic tissue is more related to functional connectivity changes in their dependence networks than to differential gene expression. The MYLK, KLK2, KLK3, HAN11, LTF, CSRP1 and TGM4 genes presented significant changes in their functional connectivity between normal and tumoral conditions and were also classified as the top seven most informative genes for the prostate cancer genesis process by our discriminant analysis. Moreover, among the identified genes we found classically known biomarkers and genes which are closely related to tumoral prostate, such as KLK3 and KLK2 and several other potential ones. Conclusion We have demonstrated that changes in functional connectivity may be implicit in the biological process which renders some genes more informative to discriminate between normal and tumoral conditions. Using the proposed method, namely, MLDA, in order to analyze the multivariate characteristic of genes, it was possible to capture the changes in dependence networks which are related to cell transformation.

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

Abstract 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.

Semantic integration of gene expression analysis tools and data sources using software connectors

Abstract 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 heteregeneous 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.