ResearchPad - microarrays https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[<i>In silico</i> analyses identify lncRNAs: WDFY3-AS2, BDNF-AS and AFAP1-AS1 as potential prognostic factors for patients with triple-negative breast tumors]]> https://www.researchpad.co/article/elastic_article_13870 Long non-coding RNAs (lncRNAs) are characterized as having 200 nucleotides or more and not coding any protein, and several been identified as differentially expressed in several human malignancies, including breast cancer.MethodsHere, we evaluated lncRNAs differentially expressed in triple-negative breast cancer (TNBC) from a cDNA microarray data set obtained in a previous study from our group. Using in silico analyses in combination with a review of the current literature, we identify three lncRNAs as potential prognostic factors for TNBC patients.ResultsWe found that the expression of WDFY3-AS2, BDNF-AS, and AFAP1-AS1 was associated with poor survival in patients with TNBCs. WDFY3-AS2 and BDNF-AS are lncRNAs known to play an important role in tumor suppression of different types of cancer, while AFAP1-AS1 exerts oncogenic activity.ConclusionOur findings provided evidence that WDFY3-AS2, BDNF-AS, and AFAP1-AS1 may be potential prognostic factors in TNBC development. ]]> <![CDATA[Investigating gene-microRNA networks in atrial fibrillation patients with mitral valve regurgitation]]> https://www.researchpad.co/article/elastic_article_7684 Atrial fibrillation (AF) is predicted to affect around 17.9 million individuals in Europe by 2060. The disease is associated with severe electrical and structural remodelling of the heart, and increased the risk of stroke and heart failure. In order to improve treatment and find new drug targets, the field needs to better comprehend the exact molecular mechanisms in these remodelling processes.ObjectivesThis study aims to identify gene and miRNA networks involved in the remodelling of AF hearts in AF patients with mitral valve regurgitation (MVR).MethodsTotal RNA was extracted from right atrial biopsies from patients undergoing surgery for mitral valve replacement or repair with AF and without history of AF to test for differentially expressed genes and miRNAs using RNA-sequencing and miRNA microarray. In silico predictions were used to construct a mRNA-miRNA network including differentially expressed mRNAs and miRNAs. Gene and chromosome enrichment analysis were used to identify molecular pathways and high-density AF loci.ResultsWe found 644 genes and 43 miRNAs differentially expressed in AF patients compared to controls. From these lists, we identified 905 pairs of putative miRNA-mRNA interactions, including 37 miRNAs and 295 genes. Of particular note, AF-associated miR-130b-3p, miR-338-5p and miR-208a-3p were differentially expressed in our AF tissue samples. These miRNAs are predicted regulators of several differentially expressed genes associated with cardiac conduction and fibrosis. We identified two high-density AF loci in chromosomes 14q11.2 and 6p21.3.ConclusionsAF in MVR patients is associated with down-regulation of ion channel genes and up-regulation of extracellular matrix genes. Other AF related genes are dysregulated and several are predicted to be targeted by miRNAs. Our novel miRNA-mRNA regulatory network provides new insights into the mechanisms of AF. ]]> <![CDATA[Micro-RNA signatures in monozygotic twins discordant for congenital heart defects]]> https://www.researchpad.co/article/N5a7c737e-22cf-4de0-b5e8-861cb3f8f58f

Background

MicroRNAs (miRNAs) are small RNAs regulating gene expression post-transcriptionally. Recent studies demonstrated that miRNAs are involved in the development of congenital heart defects (CHD). In this study, we aimed at identifying the specific patterns of miRNAs in blood of monozygotic twin pairs discordant for CHD and to assess whether miRNAs might be involved in the development or reflect the consequences of CHD.

Methods

miRNA microarray analysis and Real-Time Quantitative PCR (RT-qPCR) were employed to determine the miRNA abundance level from 12 monozygotic twins discordant for CHD and their non-CHD co-twins (n = 12). Enrichment analyses of altered miRNAs were performed using bioinformatics tools.

Results

Compared with non-CHD co-twins, profiling analysis indicated 34 miRNAs with a significant difference in abundance level (p<0.05, fold change ≥ 1.3), of which 11 miRNAs were up-regulated and 23 miRNAs were down-regulated. Seven miRNAs were validated with RT-qPCR including miR-511-3p, miR-1306-5p, miR-421, miR-4707-3p, miR-4732-3p, miR-5189-3p, and miR-890, and the results were consistent with microarray analysis. Five miRNAs namely miR-511-3p, miR-1306-5p, miR-4732-3p, miR-5189-3p, and miR-890 were found to be significantly up-regulated in twins < 10 years old. Bioinformatics analysis showed that the 7 validated miRNAs were involved in phosphatidylinositol signaling, gap junction signaling, and adrenergic signaling in cardiomyocytes.

Conclusions

Our data show deregulated miRNA abundance levels in the peripheral blood of monozygotic twins discordant for CHD, and identify new candidates for further analysis, which may contribute to understanding the development of CHD in the future. Bioinformatics analysis indicated that the target genes of these miRNAs are likely involved in signaling and communication of cardiomyocytes.

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<![CDATA[Rosellinia necatrix infection induces differential gene expression between tolerant and susceptible avocado rootstocks]]> https://www.researchpad.co/article/5c6f14bbd5eed0c48467a754

Rosellinia necatrix is the causal agent of avocado white root rot (WRR). Control of this soil-borne disease is difficult, and the use of tolerant rootstocks may present an effective method to lessen its impact. To date, no studies on the molecular mechanisms regulating the avocado plant response towards this pathogen have been undertaken. To shed light on the mechanisms underpinning disease susceptibility and tolerance, molecular analysis of the gene’s response in two avocado rootstocks with a contrasting disease reaction was assessed. Gene expression profiles against R. necatrix were carried out in the susceptible ‘Dusa’ and the tolerant selection BG83 avocado genotypes by micro-array analysis. In ‘Dusa’, the early response was mainly related to redox processes and cell-wall degradation activities, all becoming enhanced after disease progression affected photosynthetic capacity, whereas tolerance to R. necatrix in BG83 relied on the induction of protease inhibitors and their negative regulators, as well as genes related to tolerance to salt and osmotic stress such as aspartic peptidase domain-containing proteins and gdsl esterase lipase proteins. In addition, three protease inhibitors were identified, glu protease, trypsin and endopeptidase inhibitors, which were highly overexpressed in the tolerant genotype when compared to susceptible ‘Dusa’, after infection with R. necatrix, reaching fold change values of 52, 19 and 38, respectively. The contrasting results between ‘Dusa’ and BG83 provide new insights into the different mechanisms involved in avocado tolerance to Phytophthora cinnamomi and R. necatrix, which are consistent with their biotrophic and necrotrophic lifestyles, respectively. The differential induction of genes involved in salt and osmotic stress in BG83 could indicate that R. necatrix penetration into the roots is associated with osmotic effects, suggesting that BG83’s tolerance to R. necatrix is related to the ability to withstand osmotic imbalance. In addition, the high expression of protease inhibitors in tolerant BG83 compared to susceptible ‘Dusa’ after infection with the pathogen suggests the important role that these proteins may play in the defence of avocado rootstocks against R. necatrix.

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<![CDATA[Leukemia multiclass assessment and classification from Microarray and RNA-seq technologies integration at gene expression level]]> https://www.researchpad.co/article/5c6c7591d5eed0c4843cfeb1

In more recent years, a significant increase in the number of available biological experiments has taken place due to the widespread use of massive sequencing data. Furthermore, the continuous developments in the machine learning and in the high performance computing areas, are allowing a faster and more efficient analysis and processing of this type of data. However, biological information about a certain disease is normally widespread due to the use of different sequencing technologies and different manufacturers, in different experiments along the years around the world. Thus, nowadays it is of paramount importance to attain a correct integration of biologically-related data in order to achieve genuine benefits from them. For this purpose, this work presents an integration of multiple Microarray and RNA-seq platforms, which has led to the design of a multiclass study by collecting samples from the main four types of leukemia, quantified at gene expression. Subsequently, in order to find a set of differentially expressed genes with the highest discernment capability among different types of leukemia, an innovative parameter referred to as coverage is presented here. This parameter allows assessing the number of different pathologies that a certain gen is able to discern. It has been evaluated together with other widely known parameters under assessment of an ANOVA statistical test which corroborated its filtering power when the identified genes are subjected to a machine learning process at multiclass level. The optimal tuning of gene extraction evaluated parameters by means of this statistical test led to the selection of 42 highly relevant expressed genes. By the use of minimum-Redundancy Maximum-Relevance (mRMR) feature selection algorithm, these genes were reordered and assessed under the operation of four different classification techniques. Outstanding results were achieved by taking exclusively the first ten genes of the ranking into consideration. Finally, specific literature was consulted on this last subset of genes, revealing the occurrence of practically all of them with biological processes related to leukemia. At sight of these results, this study underlines the relevance of considering a new parameter which facilitates the identification of highly valid expressed genes for simultaneously discerning multiple types of leukemia.

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<![CDATA[A genetic variant associated with multiple sclerosis inversely affects the expression of CD58 and microRNA-548ac from the same gene]]> https://www.researchpad.co/article/5c65dcb0d5eed0c484dec049

Genome-wide association studies have identified more than 200 genetic variants to be associated with an increased risk of developing multiple sclerosis (MS). Still, little is known about the causal molecular mechanisms that underlie the genetic contribution to disease susceptibility. In this study, we investigated the role of the single-nucleotide polymorphism (SNP) rs1414273, which is located within the microRNA-548ac stem-loop sequence in the first intron of the CD58 gene. We conducted an expression quantitative trait locus (eQTL) analysis based on public RNA-sequencing and microarray data of blood-derived cells of more than 1000 subjects. Additionally, CD58 transcripts and mature hsa-miR-548ac molecules were measured using real-time PCR in peripheral blood samples of 32 MS patients. Cell culture experiments were performed to evaluate the efficiency of Drosha-mediated stem-loop processing dependent on genotype and to determine the target genes of this underexplored microRNA. Across different global populations and data sets, carriers of the MS risk allele showed reduced CD58 mRNA levels but increased hsa-miR-548ac levels. We provide evidence that the SNP rs1414273 might alter Drosha cleavage activity, thereby provoking partial uncoupling of CD58 gene expression and microRNA-548ac production from the shared primary transcript in immune cells. Moreover, the microRNA was found to regulate genes, which participate in inflammatory processes and in controlling the balance of protein folding and degradation. We thus uncovered new regulatory implications of the MS-associated haplotype of the CD58 gene locus, and we remind that paradoxical findings can be encountered in the analysis of eQTLs upon data aggregation. Our study illustrates that a better understanding of RNA processing events might help to establish the functional nature of genetic variants, which predispose to inflammatory and neurological diseases.

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<![CDATA[Characterization of a novel microRNA, miR-188, elevated in serum of muscular dystrophy dog model]]> https://www.researchpad.co/article/5c5b525dd5eed0c4842bc6ee

MicroRNAs (miRNAs) are non-coding small RNAs that regulate gene expression at the post-transcriptional level. Several miRNAs are exclusively expressed in skeletal muscle and participate in the regulation of muscle differentiation by interacting with myogenic factors. These miRNAs can be found at high levels in the serum of patients and animal models for Duchenne muscular dystrophy, which is expected to be useful as biomarkers for their clinical conditions. By miRNA microarray analysis, we identified miR-188 as a novel miRNA that is elevated in the serum of the muscular dystrophy dog model, CXMDJ. miR-188 was not muscle-specific miRNA, but its expression was up-regulated in skeletal muscles associated with muscle regeneration induced by cardiotoxin-injection in normal dogs and mice. Manipulation of miR-188 expression using antisense oligo and mimic oligo RNAs alters the mRNA expression of the myogenic regulatory factors, MRF4 and MEF2C. Our results suggest that miR-188 is a new player that participates in the gene regulation process of muscle differentiation and that it may serve as a serum biomarker reflecting skeletal muscle regeneration.

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<![CDATA[Surface molecules of extracellular vesicles secreted by the helminth pathogen Fasciola hepatica direct their internalisation by host cells]]> https://www.researchpad.co/article/5c4b7f2dd5eed0c484840b72

Helminth parasites secrete extracellular vesicles (EVs) that can be internalised by host immune cells resulting in modulation of host immunity. While the molecular cargo of EVs have been characterised in many parasites, little is known about the surface-exposed molecules that participate in ligand-receptor interactions with the host cell surface to initiate vesicle docking and subsequent internalisation. Using a membrane-impermeable biotin reagent to capture proteins displayed on the outer membrane surface of two EV sub-populations (termed 15k and 120k EVs) released by adult F. hepatica, we describe 380 surface proteins including an array of virulence factors, membrane transport proteins and molecules involved in EV biogenesis/trafficking. Proteomics and immunohistochemical analysis show that the 120k EVs have an endosomal origin and may be released from the parasite via the protonephridial (excretory) system whilst the larger 15k EVs are released from the gastrodermal epithelial cells that line the fluke gut. A parallel lectin microarray strategy was used to profile the topology of major surface oligosaccharides of intact fluorogenically-labelled EVs as they would be displayed to the host. Lectin profiles corresponding to glycoconjugates exposed on the surface of the 15 K and 120K EV sub-populations are practically identical but are distinct from those of the parasite surface tegument, although all are predominated by high mannose sugars. We found that while the F. hepatica EVs were resistant to exo- and endo-glycosidases, the glyco-amidase PNGase F drastically remodelled the surface oligosaccharides and blocked the uptake of EVs by host macrophages. In contrast, pre-treatment with antibodies obtained from infected hosts, or purified antibodies raised against the extracellular domains of specific EV surface proteins (DM9-containing protein, CD63 receptor and myoferlin), significantly enhanced their cellular internalisation. This work highlights the diversity of EV biogenesis and trafficking pathways used by F. hepatica and sheds light on the molecular interaction between parasite EVs and host cells.

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<![CDATA[Unique and overlapping GLI1 and GLI2 transcriptional targets in neoplastic chondrocytes]]> https://www.researchpad.co/article/5c59ff07d5eed0c48413599d

Excessive Hedgehog (Hh) signaling in chondrocytes is sufficient to cause formation of enchondroma-like lesions which can progress to chondrosarcoma. To elucidate potential underlying mechanisms, we identified GLI1 and GLI2 target genes in human chondrosarcoma. Using chromatin immunoprecipitation (ChIP) sequencing and microarray data, in silico analyses were conducted to identify and characterize unique and overlapping GLI1 and GLI2 binding regions in neoplastic chondrocytes. After overlaying microarray data from human chondrosarcoma, 204 upregulated and 106 downregulated genes were identified as Hh-responsive Gli binding targets. After overlaying published Gli ChIP-on-chip data from mouse, 48 genes were identified as potential direct downstream targets of Hedgehog signaling with shared GLI binding regions in evolutionarily conserved DNA elements. Among these was BMP2, pointing to potential cross-talk between TGF beta signaling and Hh signaling. Our identification of potential target genes that are unique and common to GLI1 and GLI2 in neoplastic chondrocytes contributes to elucidating potential pathways through which Hh signaling impacts cartilage tumor biology.

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<![CDATA[Automatic microarray image segmentation with clustering-based algorithms]]> https://www.researchpad.co/article/5c50c44bd5eed0c4845e8467

Image segmentation, as a key step of microarray image processing, is crucial for obtaining the spot expressions simultaneously. However, state-of-art clustering-based segmentation algorithms are sensitive to noises. To solve this problem and improve the segmentation accuracy, in this article, several improvements are introduced into the fast and simple clustering methods (K-means and Fuzzy C means). Firstly, a contrast enhancement algorithm is implemented in image preprocessing to improve the gridding precision. Secondly, the data-driven means are proposed for cluster center initialization, instead of usual random setting. The third improvement is that the multi features, including intensity features, spatial features, and shape features, are implemented in feature selection to replace the sole pixel intensity feature used in the traditional clustering-based methods to avoid taking noises as spot pixels. Moreover, the principal component analysis is adopted for various feature extraction. Finally, an adaptive adjustment algorithm is proposed based on data mining and learning for further dealing with the missing spots or low contrast spots. Experiments on real and simulation data sets indicate that the proposed improvements made our proposed method obtains higher segmented precision than the traditional K-means and Fuzzy C means clustering methods.

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<![CDATA[ESBL colonization and acquisition in a hospital population: The molecular epidemiology and transmission of resistance genes]]> https://www.researchpad.co/article/5c466564d5eed0c484518ef0

A prospective cohort study (German Clinical Trial Registry, No. 00005273) was performed to determine pre-admission colonization rates, hospital acquisition risk factors, subsequent infection rates and colonization persistence including the respective molecular epidemiology and transmission rates of extended-spectrum β-lactamase (ESBL)-producing Enterobacteriaceae (EPE). A total of 342 EPEs were isolated from rectal swabs of 1,334 patients on admission, at discharge and 6 months after hospitalization. Inclusion criteria were patients’ age > 18 years, expected length of stays > 48 hours, external referral. The EPEs were characterized by routine microbiological methods, a DNA microarray and ERIC-PCR. EPE colonization was found in 12.7 % of admitted patients, with the highest rate (23.8 %) in patients from nursing homes. During hospitalization, 8.1 % of the patients were de novo EPE colonized, and invasive procedures, antibiotic and antacid therapies were independent risk factors. Only 1/169 patients colonized on admission developed a hospital-acquired EPE infection. Escherichia coli was the predominant EPE (88.9 %), and 92.1% of the ESBL phenotypes could be related to CTX-M variants with CTX-M-1/15 group being most frequent (88.9%). A corresponding β-lactamase could not be identified in five isolates. Hospital-acquired EPE infections in patients colonized before or during hospitalization were rare. The diversity of the EPE strains was much higher than that of the underlying plasmids. In seven patients, transmission of the respective plasmid across different species could be observed indicating that the current strain-based surveillance approaches may underestimate the risk of inter-species transmission of resistance genes.

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<![CDATA[Literature optimized integration of gene expression for organ-specific evaluation of toxicogenomics datasets]]> https://www.researchpad.co/article/5c466586d5eed0c4845199b5

The study of drug toxicity in human organs is complicated by their complex inter-relations and by the obvious difficulty to testing drug effects on biologically relevant material. Animal models and human cell cultures offer alternatives for systematic and large-scale profiling of drug effects on gene expression level, as typically found in the so-called toxicogenomics datasets. However, the complexity of these data, which includes variable drug doses, time points, and experimental setups, makes it difficult to choose and integrate the data, and to evaluate the appropriateness of one or another model system to study drug toxicity (of particular drugs) of particular human organs. Here, we define a protocol to integrate drug-wise rankings of gene expression changes in toxicogenomics data, which we apply to the TG-GATEs dataset, to prioritize genes for association to drug toxicity in liver or kidney. Contrast of the results with sets of known human genes associated to drug toxicity in the literature allows to compare different rank aggregation approaches for the task at hand. Collectively, ranks from multiple models point to genes not previously associated to toxicity, notably, the PCNA clamp associated factor (PCLAF), and genes regulated by the master regulator of the antioxidant response NFE2L2, such as NQO1 and SRXN1. In addition, comparing gene ranks from different models allowed us to evaluate striking differences in terms of toxicity-associated genes between human and rat hepatocytes or between rat liver and rat hepatocytes. We interpret these results to point to the different molecular functions associated to organ toxicity that are best described by each model. We conclude that the expected production of toxicogenomics panels with larger numbers of drugs and models, in combination with the ongoing increase of the experimental literature in organ toxicity, will lead to increasingly better associations of genes for organism toxicity.

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<![CDATA[Transcriptomic characterization of signaling pathways associated with osteoblastic differentiation of MC-3T3E1 cells]]> https://www.researchpad.co/article/5c390bc6d5eed0c48491e481

Bone remodeling involves the coordinated actions of osteoclasts, which resorb the calcified bony matrix, and osteoblasts, which refill erosion pits created by osteoclasts to restore skeletal integrity and adapt to changes in mechanical load. Osteoblasts are derived from pluripotent mesenchymal stem cell precursors, which undergo differentiation under the influence of a host of local and environmental cues. To characterize the autocrine/paracrine signaling networks associated with osteoblast maturation and function, we performed gene network analysis using complementary “agnostic” DNA microarray and “targeted” NanoString nCounter datasets derived from murine MC3T3-E1 cells induced to undergo synchronized osteoblastic differentiation in vitro. Pairwise datasets representing changes in gene expression associated with growth arrest (day 2 to 5 in culture), differentiation (day 5 to 10 in culture), and osteoblast maturation (day 10 to 28 in culture) were analyzed using Ingenuity Systems Pathways Analysis to generate predictions about signaling pathway activity based on the temporal sequence of changes in target gene expression. Our data indicate that some pathways involved in osteoblast differentiation, e.g. Wnt/β-catenin signaling, are most active early in the process, while others, e.g. TGFβ/BMP, cytokine/JAK-STAT and TNFα/RANKL signaling, increase in activity as differentiation progresses. Collectively, these pathways contribute to the sequential expression of genes involved in the synthesis and mineralization of extracellular matrix. These results provide insight into the temporal coordination and complex interplay between signaling networks controlling gene expression during osteoblast differentiation. A more complete understanding of these processes may aid the discovery of novel methods to promote osteoblast development for the treatment of conditions characterized by low bone mineral density.

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<![CDATA[Pan- and core- gene association networks: Integrative approaches to understanding biological regulation]]> https://www.researchpad.co/article/5c3fa593d5eed0c484ca5fac

The rapid increase in transcriptome data provides an opportunity to access the complex regulatory mechanisms in cellular systems through gene association network (GAN). Nonetheless, GANs derived from single datasets generally allow us to envisage only one side of the regulatory network, even under the particular condition of study. The circumstance is well demonstrated by inconsistent GANs of individual datasets proposed for similar experimental conditions, which always leads to ambiguous interpretation. Here, pan- and core-gene association networks (pan- and core-GANs), analogous to the pan- and core-genome concepts, are proposed to increase the power of inference through the integration of multiple, diverse datasets. The core-GAN represents the consensus associations of genes that were inferred from all individual networks. On the other hand, the pan-GAN represents the extensive gene-gene associations that occurred in each individual network. The pan- and core-GANs prospects were demonstrated based on three time series microarray datasets in leaves of Arabidopsis thaliana grown under diurnal conditions. We showed the overall performance of pan- and core-GANs was more robust to the number of data points in gene expression data compared to the GANs inferred from individual datasets. In addition, the incorporation of multiple data broadened our understanding of the biological regulatory system. While the pan-GAN enabled us to observe the landscape of gene association system, core-GAN highlighted the basic gene-associations in essence of the regulation regulating starch metabolism in leaves of Arabidopsis.

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<![CDATA[Downregulation of ERG and FLI1 expression in endothelial cells triggers endothelial-to-mesenchymal transition]]> https://www.researchpad.co/article/5c0ae435d5eed0c48458928b

Endothelial cell (EC) plasticity in pathological settings has recently been recognized as a driver of disease progression. Endothelial-to-mesenchymal transition (EndMT), in which ECs acquire mesenchymal properties, has been described for a wide range of pathologies, including cancer. However, the mechanism regulating EndMT in the tumor microenvironment and the contribution of EndMT in tumor progression are not fully understood. Here, we found that combined knockdown of two ETS family transcription factors, ERG and FLI1, induces EndMT coupled with dynamic epigenetic changes in ECs. Genome-wide analyses revealed that ERG and FLI1 are critical transcriptional activators for EC-specific genes, among which microRNA-126 partially contributes to blocking the induction of EndMT. Moreover, we demonstrated that ERG and FLI1 expression is downregulated in ECs within tumors by soluble factors enriched in the tumor microenvironment. These data provide new insight into the mechanism of EndMT, functions of ERG and FLI1 in ECs, and EC behavior in pathological conditions.

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<![CDATA[Antibody responses to Zika virus proteins in pregnant and non-pregnant macaques]]> https://www.researchpad.co/article/5c06f04ad5eed0c484c6d62b

The specificity of the antibody response against Zika virus (ZIKV) is not well-characterized. This is due, in part, to the antigenic similarity between ZIKV and closely related dengue virus (DENV) serotypes. Since these and other similar viruses co-circulate, are spread by the same mosquito species, and can cause similar acute clinical syndromes, it is difficult to disentangle ZIKV-specific antibody responses from responses to closely-related arboviruses in humans. Here we use high-density peptide microarrays to profile anti-ZIKV antibody reactivity in pregnant and non-pregnant macaque monkeys with known exposure histories and compare these results to reactivity following DENV infection. We also compare cross-reactive binding of ZIKV-immune sera to the full proteomes of 28 arboviruses. We independently confirm a purported ZIKV-specific IgG antibody response targeting ZIKV nonstructural protein 2B (NS2B) that was recently reported in ZIKV-infected people and we show that antibody reactivity in pregnant animals can be detected as late as 127 days post-infection (dpi). However, we also show that these responses wane over time, sometimes rapidly, and in one case the response was elicited following DENV infection in a previously ZIKV-exposed animal. These results suggest epidemiologic studies assessing seroprevalence of ZIKV immunity using linear epitope-based strategies will remain challenging to interpret due to susceptibility to false positive results. However, the method used here demonstrates the potential for rapid profiling of proteome-wide antibody responses to a myriad of neglected diseases simultaneously and may be especially useful for distinguishing antibody reactivity among closely related pathogens.

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<![CDATA[GradientScanSurv—An exhaustive association test method for gene expression data with censored survival outcome]]> https://www.researchpad.co/article/5c117b67d5eed0c4846990f6

Accurate assessment of the association between continuous variables such as gene expression and survival is a critical aspect of precision medicine. In this report, we provide a review of some of the available survival analysis and validation tools by referencing published studies that have utilized these tools. We have identified pitfalls associated with the assumptions inherent in those applications that have the potential to impact scientific research through their potential bias. In order to overcome these pitfalls, we have developed a novel method that enables the logrank test method to handle continuous variables that comprehensively evaluates survival association with derived aggregate statistics. This is accomplished by exhaustively considering all the cutpoints across the full expression gradient. Direct side-by-side comparisons, global ROC analysis, and evaluation of the ability to capture relevant biological themes based on current understanding of RAS biology all demonstrated that the new method shows better consistency between multiple datasets of the same disease, better reproducibility and robustness, and better detection power to uncover biological relevance within the selected datasets over the available survival analysis methods on univariate gene expression and penalized linear model-based methods.

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<![CDATA[Pro-osteoporotic miR-320a impairs osteoblast function and induces oxidative stress]]> https://www.researchpad.co/article/5c0841e5d5eed0c484fcb16a

MicroRNAs (miRNAs) are important regulators of many cellular processes, including the differentiation and activity of osteoblasts, and therefore, of bone turnover. MiR-320a is overexpressed in osteoporotic bone tissue but its role in osteoblast function is unknown. In the present study, functional assays were performed with the aim to elucidate the mechanism of miR-320a action in osteoblastic cells. MiR-320a was either overexpressed or inhibited in human primary osteoblasts (hOB) and gene expression changes were evaluated through microarray analysis. In addition, the effect of miR-320a on cell proliferation, viability, and oxidative stress in hOB was evaluated. Finally, matrix mineralization and alkaline phosphatase activity were assessed in order to evaluate osteoblast functionality. Microarray results showed miR-320a regulation of a number of key osteoblast genes and of genes involved in oxidative stress. Regulation of osteoblast differentiation and ossification appeared as the best significant biological processes (PANTHER P value = 3.74E-05; and P value = 3.06E-04, respectively). The other enriched pathway was that of the cellular response to cadmium and zinc ions, mostly by the overexpression of metallothioneins. In hOBs, overexpression of miR-320a increased cell proliferation and oxidative stress levels whereas mineralization capacity was reduced. In conclusion, overexpression of miR-320a increased stress oxidation levels and was associated with reduced osteoblast differentiation and functionality, which could trigger an osteoporotic phenotype.

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<![CDATA[A common molecular signature of patients with sickle cell disease revealed by microarray meta-analysis and a genome-wide association study]]> https://www.researchpad.co/article/5b4a28a4463d7e4513b89812

A chronic inflammatory state to a large extent explains sickle cell disease (SCD) pathophysiology. Nonetheless, the principal dysregulated factors affecting this major pathway and their mechanisms of action still have to be fully identified and elucidated. Integrating gene expression and genome-wide association study (GWAS) data analysis represents a novel approach to refining the identification of key mediators and functions in complex diseases. Here, we performed gene expression meta-analysis of five independent publicly available microarray datasets related to homozygous SS patients with SCD to identify a consensus SCD transcriptomic profile. The meta-analysis conducted using the MetaDE R package based on combining p values (maxP approach) identified 335 differentially expressed genes (DEGs; 224 upregulated and 111 downregulated). Functional gene set enrichment revealed the importance of several metabolic pathways, of innate immune responses, erythrocyte development, and hemostasis pathways. Advanced analyses of GWAS data generated within the framework of this study by means of the atSNP R package and SIFT tool identified 60 regulatory single-nucleotide polymorphisms (rSNPs) occurring in the promoter of 20 DEGs and a deleterious SNP, affecting CAMKK2 protein function. This novel database of candidate genes, transcription factors, and rSNPs associated with SCD provides new markers that may help to identify new therapeutic targets.

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<![CDATA[Candidate gene biodosimetry markers of exposure to external ionizing radiation in human blood: A systematic review]]> https://www.researchpad.co/article/5b28b8a6463d7e14181b1860

Purpose

To compile a list of genes that have been reported to be affected by external ionizing radiation (IR) and to assess their performance as candidate biomarkers for individual human radiation dosimetry.

Methods

Eligible studies were identified through extensive searches of the online databases from 1978 to 2017. Original English-language publications of microarray studies assessing radiation-induced changes in gene expression levels in human blood after external IR were included. Genes identified in at least half of the selected studies were retained for bio-statistical analysis in order to evaluate their diagnostic ability.

Results

24 studies met the criteria and were included in this study. Radiation-induced expression of 10,170 unique genes was identified and the 31 genes that have been identified in at least 50% of studies (12/24 studies) were selected for diagnostic power analysis. Twenty-seven genes showed a significant Spearman’s correlation with radiation dose. Individually, TNFSF4, FDXR, MYC, ZMAT3 and GADD45A provided the best discrimination of radiation dose < 2 Gy and dose ≥ 2 Gy according to according to their maximized Youden’s index (0.67, 0.55, 0.55, 0.55 and 0.53 respectively). Moreover, 12 combinations of three genes display an area under the Receiver Operating Curve (ROC) curve (AUC) = 1 reinforcing the concept of biomarker combinations instead of looking for an ideal and unique biomarker.

Conclusion

Gene expression is a promising approach for radiation dosimetry assessment. A list of robust candidate biomarkers has been identified from analysis of the studies published to date, confirming for example the potential of well-known genes such as FDXR and TNFSF4 or highlighting other promising gene such as ZMAT3. However, heterogeneity in protocols and analysis methods will require additional studies to confirm these results.

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