Gene ARMADA: an integrated multi-analysis platform for microarray data implemented in MATLAB

<p>Abstract</p> <p>Background</p> <p>The microarray data analysis realm is ever growing through the development of various tools, open source and commercial. However there is absence of predefined rational algorithmic analysis workflows or batch standardized processing to incorporate all steps, from raw data import up to the derivation of significantly differentially expressed gene lists. This absence obfuscates the analytical procedure and obstructs the massive comparative processing of genomic microarray datasets. Moreover, the solutions provided, heavily depend on the programming skills of the user, whereas in the case of GUI embedded solutions, they do not provide direct support of various raw image analysis formats or a versatile and simultaneously flexible combination of signal processing methods.</p> <p>Results</p> <p>We describe here Gene ARMADA (Automated Robust MicroArray Data Analysis), a MATLAB implemented platform with a Graphical User Interface. This suite integrates all steps of microarray data analysis including automated data import, noise correction and filtering, normalization, statistical selection of differentially expressed genes, clustering, classification and annotation. In its current version, Gene ARMADA fully supports 2 coloured cDNA and Affymetrix oligonucleotide arrays, plus custom arrays for which experimental details are given in tabular form (Excel spreadsheet, comma separated values, tab-delimited text formats). It also supports the analysis of already processed results through its versatile import editor. Besides being fully automated, Gene ARMADA incorporates numerous functionalities of the Statistics and Bioinformatics Toolboxes of MATLAB. In addition, it provides numerous visualization and exploration tools plus customizable export data formats for seamless integration by other analysis tools or MATLAB, for further processing. Gene ARMADA requires MATLAB 7.4 (R2007a) or higher and is also distributed as a stand-alone application with MATLAB Component Runtime.</p> <p>Conclusion</p> <p>Gene ARMADA provides a highly adaptable, integrative, yet flexible tool which can be used for automated quality control, analysis, annotation and visualization of microarray data, constituting a starting point for further data interpretation and integration with numerous other tools.</p

A Two-Color Haploid Genetic Screen Identifies Novel Host Factors Involved in HIV-1 Latency

To identify novel host factors as putative targets to reverse HIV-1 latency, we performed an insertional mutagenesis genetic screen in a latent HIV-1 infected pseudohaploid KBM7 cell line (Hap-Lat). Following mutagenesis, insertions were mapped to the genome, and bioinformatic analysis resulted in the identification of 69 candidate host genes involved in maintaining HIV-1 latency. A select set of candidate genes was functionally validated using short hairpin RNA (shRNA)-mediated depletion in latent HIV-1 infected J-Lat A2 and 11.1 T cell lines. We confirmed ADK, CHD9, CMSS1, EVI2B, EXOSC8, FAM19A, GRIK5, IRF2BP2, NF1, and USP15 as novel host factors involved in the maintenance of HIV-1 latency. Chromatin immunoprecipitation assays indicated that CHD9, a chromodomain helicase DNA-binding protein, maintains HIV-1 latency via direct association with the HIV-1 5′ long terminal repeat (LTR), and its depletion results in increased histone acetylation at the HIV-1 promoter, concomitant with HIV-1 latency reversal. FDA-approved inhibitors 5-iodotubercidin, trametinib, and topiramate, targeting ADK, NF1, and GRIK5, respectively, were characterized for their latency reversal potential. While 5-iodotubercidin exhibited significant cytotoxicity in both J-Lat and primary CD4(+) T cells, trametinib reversed latency in J-Lat cells but not in latent HIV-1 infected primary CD4(+) T cells. Importantly, topiramate reversed latency in cell line models, in latently infected primary CD4(+) T cells, and crucially in CD4(+) T cells from three people living with HIV-1 (PLWH) under suppressive antiretroviral therapy, without inducing T cell activation or significant toxicity. Thus, using an adaptation of a haploid forward genetic screen, we identified novel and druggable host factors contributing to HIV-1 latency

The transcription factor BCL-6 controls early development of innate-like T cells

Innate T cells, including invariant natural killer T (iNKT) and mucosal-associated innate T (MAIT) cells, are a heterogeneous T lymphocyte population with effector properties preprogrammed during their thymic differentiation. How this program is initiated is currently unclear. Here, we show that the transcription factor BCL-6 was transiently expressed in iNKT cells upon exit from positive selection and was required for their proper development beyond stage 0. Notably, development of MAIT cells was also impaired in the absence of Bcl6. BCL-6-deficient iNKT cells had reduced expression of genes that were associated with the innate T cell lineage, including Zbtb16, which encodes PLZF, and PLZF-targeted genes. BCL-6 contributed to a chromatin accessibility landscape that was permissive for the expression of development-related genes and inhibitory for genes associated with naive T cell programs. Our results revealed new functions for BCL-6 and illuminated how this transcription factor controls early iNKT cell development

Catchet-MS identifies IKZF1-targeting thalidomide analogues as novel HIV-1 latency reversal agents

A major pharmacological strategy toward HIV cure aims to reverse latency in infected cells as a first step leading to their elimination. While the unbiased identification of molecular targets physically associated with the latent HIV-1 provirus would be highly valuable to unravel the molecular determinants of HIV-1 transcriptional repression and latency reversal, due to technical limitations, this has been challenging. Here we use a dCas9 targeted chromatin and histone enrichment strategy coupled to mass spectrometry (Catchet-MS) to probe the differential protein composition of the latent and activated HIV-1 5′LTR. Catchet-MS identified known and novel latent 5′LTR-associated host factors. Among these, IKZF1 is a novel HIV-1 transcriptional repressor, required for Polycomb Repressive Complex 2 recruitment to the LTR. We find the clinically advanced thalidomide analogue iberdomide, and the FDA approved analogues lenalidomide and pomalidomide, to be novel LRAs. We demonstrate that, by targeting IKZF1 for degradation, these compounds reverse HIV-1 latency in CD4+ T-cells isolated from virally suppressed people living with HIV-1 and that they are able to synergize with other known LRAs

Whole-transcriptome analysis of UUO mouse model of renal fibrosis reveals new molecular players in kidney diseases

International audienceAbstract Transcriptome analysis by RNA-seq technology allows novel insights into gene expression and regulatory networks in health and disease. To better understand the molecular basis of renal fibrosis, we performed RNA-seq analysis in the Unilateral Ureteric Obstruction (UUO) mouse model. We analysed sham operated, 2- and 8-day post-ligation renal tissues. Thousands of genes with statistical significant changes in their expression were identified and classified into cellular processes and molecular pathways. Many novel protein-coding genes were identified, including critical transcription factors with important regulatory roles in other tissues and diseases. Emphasis was placed on long non-coding RNAs (lncRNAs), a class of molecular regulators of multiple and diverse cellular functions. Selected lncRNA genes were further studied and their transcriptional activity was confirmed. For three of them, their transcripts were also examined in other mouse models of nephropathies and their up- or down-regulation was found similar to the UUO model. In vitro experiments confirmed that one selected lncRNA is independent of TGFβ or IL1b stimulation but can influence the expression of fibrosis-related proteins and the cellular phenotype. These data provide new information about the involvement of protein-coding and lncRNA genes in nephropathies, which can become novel diagnostic and therapeutic targets in the near future