Phylogenomic Surveillance of Drug Resistant Mycobacterium tuberculosis in Jalisco Mexico
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PROVIDER: PRJEB75503 | ENA |
REPOSITORIES: ENA
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Project description:Omicron is currently the dominant SARS-CoV-2 variant and several sublineages have emerged. Questions remain about the impact of previous SARS-CoV-2 exposure on cross-variant immune responses elicited by the SARS-CoV-2 Omicron sublineage BA.2 compared to BA.1. Here we show that without previous history of COVID-19, BA.2 infection induces a reduced immune response against all variants of concern (VOC) compared to BA.1 infection. The absence of ACE2 binding in sera of previously naïve BA.1 and BA.2 patients indicates a lack of meaningful neutralization. In contrast, anti-spike antibody levels and neutralizing activity greatly increased in the BA.1 and BA.2 patients with a previous history of COVID-19. Transcriptome analyses of peripheral immune cells showed significant differences in immune response and specific antibody generation between BA.1 and BA.2 patients as well as significant differences in the expression of specific immune genes. In summary, prior infection status significantly impacts the innate and adaptive immune response against VOC following BA.2 infection.
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Project description:Triple negative breast cancer (TNBC) represents a challenging tumor type due to their poor prognosis and limited treatment options. It is well recognize that clinical and molecular heterogeneity of TNBC is driven in part by mRNA and lncRNAs. To stratify TNBCs, we profiled mRNAs and lncRNA in 158 adjuvant TNBC tumors using an Affymetrix microarray platform. Lehmann clustering analysis allowed us to identify TNBC subtypes featuring unique lncRNA expression patterns, disease free and overall survival rates and particular gene ontology enrichments (performed with GSEA algorithm).
2018-08-31 | GSE86946 | GEO
Project description:Lymphangioleiomyomatosis (LAM) is characterized by cystic lung destruction caused by smooth, muscle-like LAM cells which have mutations in the tumor suppressor genes Tuberous Sclerosis Complex (TSC) 1 or 2, and the capacity to metastasize. Since chemokines and their receptors function in chemotaxis of metastatic cells, we hypothesized that LAM cells may be recruited by chemokine(s) in the lung. Quantification of 25 chemokines in bronchoalveolar lavage fluid from LAM patients and healthy volunteers revealed that concentrations of MCP-1/CCL2, GROa/CXCL1 and ENA-78/CXCL5 were significantly higher in samples from LAM patients than healthy volunteers. In this transcript analysis, expression of chemokine and chemokine receptor mRNA in LAM cells differed from those in melanoma and smooth muscle cells. Subsequent immunohistochemistry of lung sections from 30 LAM patients confirmed protein expression of chemokines and these receptors varied among LAM patient and differed from that seen in breast cancer and melanoma cells. . In vitro, MCP-1/CCL2 induced selective migration of cells showing loss of heterozygosity of TSC2 from a heterogeneous populations of cells grown from explanted LAM lungs. In addition, the frequencies of single-nucleotide polymorphisms in the MCP-1 gene promoter region differed significantly in LAM patients and healthy volunteers (p=0.018), and one polymorphism was associated significantly more frequently with the decline of lung function. These observations are consistent with the notion that chemokines such as MCP-1 may serve to specify site of LAM cell metastasis. Keywords: Human patient sample comparison with cell lines The study is of case/control design with biological replication. Biopsies of nodules from 14 LAM patients (cases) are compared with cultured cell lines (controls) with similar properties.
2008-12-30 | E-GEOD-12027 | biostudies-arrayexpress
Project description:Lymphangioleiomyomatosis (LAM) is a debilitating, progressive lung disease with few therapeutic options, largely due to a paucity of mechanistic knowledge of disease pathogenesis. Lymphatic endothelial cells (LECs) are known to envelope and invade clusters of LAM-cells, comprising of smooth muscle α-actin and/or HMB-45 positive "smooth muscle-like cells” however the role of LECs in LAM pathogenesis is still unknown. To address this critical knowledge gap, we investigated wether LECs interact with LAM-cells to augment their metastatic behaviour of LAM-cells. We performed in situ spatialomics and identified a core of transcriptomically related cells within the LAM nodules. Pathway analysis highlights wound and pulmonary healing, VEGF signaling, extracellular matrix/actin cytoskeletal regulating and the HOTAIR regulatory pathway enriched in the LAM Core cells. We developed an organoid co-culture model combining primary LAM-cells with LECs and applied this to evaluate invasion, migration, and the impact of Sorafenib, a multi-kinase inhibitor. LAM-LEC organoids had significantly higher extracellular matrix invasion, decreased solidity and a greater perimeter, reflecting increased invasion compared to non-LAM control smooth muscle cells. Sorafenib significantly inhibited this invasion in both LAM spheroids and LAM-LEC organoids compared to their respective controls. We identified TGFβ1ι1, a molecular adapter coordinating protein-protein interactions at the focal adhesion complex and known to regulate VEGF, TGFβ and Wnt signalling, as a Sorafenib-regulated kinase in LAM-cells. In conclusion we have developed a novel 3D co-culture LAM model and have demonstrated the effectiveness of Sorafenib to inhibit LAM-cell invasion, identifying new avenues for therapeutic intervention.
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Project description:3 x 3 comparison of the inbred strains SM/J and NZB/BinJ. Experiment Overall Design: Simple comparison of native untreated gene expression profiles of female 8wk old SM mice (x3) by female 8wk old NZB mice (x3)
2008-06-13 | E-GEOD-4765 | biostudies-arrayexpress
Project description:We report a whole-genome expression profiling of PMA-treated THP-1 human macrophages as a host system, infected by W-Beijing strains of different sublineages or the H37Rv reference strain. Surprisingly, we found that host transcriptional responses were irrespective of inter-sublineage variations. Based on this finding, we further showed that such common host transcriptional responses were probably under the control of a regulatory network involving STATs, IRF-1, IRF-7 and Oct-1 transcriptional factors. We also suggested that these putative regulators might act in a cooperative manner to induce the expression of host-responsive genes, particularly those involved in cytokine-cytokine receptor interactions. THP-1 cells were infected by 11 different sublineages plus one reference strain H37Rv (two replications) at three time points (i.e., 4h, 18h and 48h). For each infection as well as a non-infection control, RNA was extracted using Trizol (Life Technologies)TRIZOL® reagent (Invitrogen), and subsequently amplified and labeled with biotin according to the standard Affymetrix® protocol. Specifically, RNA was DNase-treated and purified with RNeasy columns (Qiagen). The purified RNA was quantified using the ND-1000 Spectrophotometer (NanoDrop Technologies) and Agilent 2100 Bioanalyzer (Agilent Technologies). The biotinylated cRNA was then fragmented and subjected to hybridization on Human Genome U133 Plus 2.0 Array (Affymetrix, USA). The scanned images were converted to cell intensity files (CEL) using GeneChip® Operating Software (GCOS) (Affymetrix). These CEL raw expression data were normalized using Robust Multi-array Averaging (RMA) with quantile normalization in R (Bioconductor). Detection call-based filter was applied to remove all the probe-sets whose expression values were consistently below an empirically-determined value of minimum sensitivity, which were evaluated according to the 95th percentile of all the ‘Absent’ call-flagged signals of the entire dataset. Following the normalization and filtering, a gene expression matrix (termed as TB expression matrix) was constructed. The TB expression matrix was then subjected to component plane presentation integrated self-organizing map (CPP-SOM) for visual comparisons, or subjected to Cluster3.0/TreeView-1.0.8 softwares with Euclidean distance algorithm for sample classification of 13 time-course transcriptome profiles. Also, Linear Models for Microarray Data (LIMMA) bioconductor library[18] was applied to identify those differentially expressed genes between any two successive time points. The criteria for identifying the top significant genes for the designed contrast was based on P-values (< 0.01) corrected using Benjamini and Hochberg false discovery rate (FDR) procedure. Sets of genes of interest such as differentially expressed genes between 4h and 18h infections were uploaded onto Database for Annotation, Visualization and Integrated Discovery (DAVID) v6.7 for identifying enriched gene ontology and KEGG pathways (FDR<0.01). For TFBS enrichment analysis, we applied PRIMA (PRomoter Integration in Microarray Analysis) program to identify TFs whose binding sites are significantly over-represented in a given gene set (i.e., differentially expressed genes) compared to background. Bonferroni-corrected P-values (< 0.01) were utilized to determine the significance of the binding site enrichments of TFs. Such computationally predicted TFs were considered as candidate regulators responsible for the putative co-regulations of differentially expressed genes.
2011-12-01 | E-GEOD-29628 | biostudies-arrayexpress
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2019-01-19 | GSE125346 | GEO