Homo sapiens
Ontology highlight
ABSTRACT:
PROVIDER: PRJNA280230 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| SRR1951620.fastq.gz | Fastqsanger.gz | |||
| SRR1951630.fastq.gz | Fastqsanger.gz | |||
| SRR1951640.fastq.gz | Fastqsanger.gz | |||
| SRR1951650.fastq.gz | Fastqsanger.gz | |||
| SRR1951660.fastq.gz | Fastqsanger.gz |
Items per page: 5 1 - 5 of 133 |
Similar Datasets
Project description:Systemic inflammatory response syndrome and septic shock
| PRJNA94397 | ENA
Project description:A systems biology approach was used to comprehensively examine the impact of renal disease and hemodialysis (HD) on host response during critical illness. We examined the metabolome, proteome, and transcriptome of 150 patients with critical illness, stratified by renal function. Plasma metabolite values showed greater changes as renal function declined, with the greatest derangements in patients receiving chronic HD. Specifically, 6 uremic retention molecules, 17 other protein catabolites, 7 modified nucleosides, and 7 pentose phosphate sugars increased as renal function declined, consistent with decreased excretion or increased catabolism of amino acids and ribonucleotides. Similarly, the proteome showed increased levels of low-molecular weight proteins and acute phase reactants. The transcriptome revealed a broad-based decrease in mRNA levels among HD patients. Systems integration revealed an unrecognized association between plasma RNASE1 and several RNA catabolites and modified nucleosides. Further, allantoin, N1-methyl-4-pyridone-3-carboxamide, and n-acetylaspartate showed inverse correlations with the majority of significantly down-regulated genes. In conclusion, renal function broadly affected the plasma metabolome, proteome, and peripheral blood transcriptome during critical illness. These changes were not effectively mitigated by hemodialysis. These studies suggest several novel mechanisms whereby renal dysfunction contributes to critical illness. We sequenced peripheral blood RNA of 133 representative subjects with systemic inflammatory response syndrome that had Acute Kidney Injury (AKI) or Hemodialysis (HD). No injury (AKI0; n= 58); AKI Stage 1 (AKI1; n= 36); AKI stage 2 and 3 (AKI23; n= 17); HD (N=22).
2015-07-01 | E-GEOD-67401 | biostudies-arrayexpress
Project description:Comparison of temporal gene expression profiles to identify genes/pathways changing during ageing. Jena Centre for Systems Biology of Ageing - JenAge (www.jenage.de)
2018-01-08 | GSE103232 | GEO
Project description:Background: Comparison of temporal gene expression profiles Jena Centre for Systems Biology of Ageing - JenAge (www.jenage.de)
2018-01-08 | GSE75337 | GEO
Project description:Transcriptional profiling of Homo sapiens inflammatory skin diseases (whole skin biospies): Psoriasis (Pso), vs Atopic Dermatitis (AD) vs Lichen planus (Li), vs Contact Eczema (KE), vs Healthy control (KO) In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation. In recent years, different genes and proteins have been highlighted as potential biomarkers for psoriasis, one of the most common inflammatory skin diseases worldwide. However, most of these markers are not psoriasis-specific but also found in other inflammatory disorders. We performed an unsupervised cluster analysis of gene expression profiles in 150 psoriasis patients and other inflammatory skin diseases (atopic dermatitis, lichen planus, contact eczema, and healthy controls). We identified a cluster of IL-17/TNFα-associated genes specifically expressed in psoriasis, among which IL-36γ was the most outstanding marker. In subsequent immunohistological analyses IL-36γ was confirmed to be expressed in psoriasis lesions only. IL-36γ peripheral blood serum levels were found to be closely associated with disease activity, and they decreased after anti-TNFα-treatment. Furthermore, IL-36γ immunohistochemistry was found to be a helpful marker in the histological differential diagnosis between psoriasis and eczema in diagnostically challenging cases. These features highlight IL-36γ as a valuable biomarker in psoriasis patients, both for diagnostic purposes and measurement of disease activity during the clinical course. Furthermore, IL-36γ might also provide a future drug target, due to its potential amplifier role in TNFα- and IL-17 pathways in psoriatic skin inflammation.
2014-12-02 | GSE63741 | GEO
Project description:Expression profiling across the pediatric systemic inflammatory response syndrome, sepsis, and septic shock spectrum
| PRJNA110317 | ENA
Project description:Introduction: Diagnosis of severe influenza pneumonia remains challenging because of the lack of correlation between presence of influenza virus and patient’s clinical status. We conducted gene expression profiling in the whole blood of critically ill patients to identify a gene signature that would allow clinicians to distinguish influenza infection from other causes of severe respiratory failure (e.g. bacterial pneumonia, non-infective systemic inflammatory response syndrome). Methods: Whole blood samples were collected from critically ill individuals and assayed on Illumina HT-12 gene expression beadarrays. Differentially expressed genes were determined by linear mixed model analysis and over-represented biological pathways determined using GeneGo MetaCore. Results: The gene expression profile of H1N1 influenza A pneumonia was distinctly different from bacterial pneumonia and systemic inflammatory response syndrome. The influenza gene expression profile is characterized by up-regulation of genes from cell cycle regulation, apoptosis and DNA-damage response pathways. In contrast, no distinctive gene-expression signature was found in patients with bacterial pneumonia or systemic inflammatory response syndrome. The gene expression profile of influenza infection persisted through five days of follow-up. Furthermore, in patients with primary H1N1 influenza A infection who subsequently developed bacterial co-infection, the influenza gene-expression signature remained unaltered, despite the presence of a super-imposed bacterial infection. Conclusions: The whole blood expression profiling data indicates that the host response to influenza pneumonia is distinctly different from that caused by bacterial pathogens. This information may speed up identification of the cause of infection in patients presenting with severe respiratory failure, allowing appropriate patient care to be undertaken more rapidly. Daily PAXgene samples for up to 5 days for; influenza A pneumonia patients (n=8), bacterial pneumonia patients (n=16), mixed bacterial and influenza A pneumonia patients (n=3), systemic inflammatory response patients (SIRS, n=13). Days 1 and 5 PAXgene samples for healthy control individuals
2012-08-14 | E-GEOD-40012 | biostudies-arrayexpress
Project description:Analysis of ex vivo isolated lymphatic endothelial cells from the dermis of patients to define type 2 diabetes-induced changes. Results preveal aberrant dermal lymphangiogenesis and provide insight into its role in the pathogenesis of persistent skin inflammation in type 2 diabetes. The ex vivo dLEC transcriptome reveals a dramatic influence of the T2D environment on multiple molecular and cellular processes, mirroring the phenotypic changes seen in T2D affected skin. The positively and negatively correlated dLEC transcripts directly cohere to prolonged inflammatory periods and reduced infectious resistance of patients´ skin. Further, lymphatic vessels might be involved in tissue remodeling processes during T2D induced skin alterations associated with impaired wound healing and altered dermal architecture. Hence, dermal lymphatic vessels might be directly associated with T2D disease promotion.
2012-06-02 | GSE38396 | GEO
Project description:As part of our study in understanding the role of SP140 in inflammatory pathways in macrophages, we inhibited SP140 mRNA using siRNA. Peripheral blood mononuclear cells (PBMCs) were obtained from whole blood of healthy donors (from Sanquin Institute Amsterdam or from GSK Stevenage Blood Donation Unit) by Ficoll density gradient (Invitrogen). CD14+ monocytes were positively selected from PBMCs using CD14 Microbeads according to the manufacturer’s instructions (Miltenyi Biotec). CD14+ cells were differentiated with 20 ng/mL of macrophage colony-stimulating factor (M-CSF) (R&D systems) for 3 days followed by 3 days of polarization into classically activated (inflammatory) M1 macrophages (100 ng/mL IFN-γ; R&D systems). M1 macrophages were transfected with siGENOME human smartpool SP140 siRNA or non-targeting scrambled siRNA for 48h with DharmaFECT™ transfection reagents according to manufacturer’s protocol (Dharmacon). The cells were left unstimulated or stimulated with 100 ng/mL LPS (E. coli 0111:B4; Sigma) for 4h (for qPCR) or 24h (for Elisa). The cells were lysed (ISOLATE II RNA Lysis Buffer RLY-Bioline) for RNA extraction.150 ng total RNA was labelled using the cRNA labelling kit for Illumina BeadArrays (Ambion) and hybridized with Ref8v3 BeadArrays (Illumina). Arrays were scanned on a BeadArray 500GX scanner and data were normalized using quantile normalization with background subtraction (GenomeStudio software; Illumina). This submission only contains processed data
2022-07-22 | E-MTAB-12011 | biostudies-arrayexpress
Project description:Kynureninase is a member of a large family of catalytically diverse but structurally homologous pyridoxal 5'-phosphate (PLP) dependent enzymes known as the aspartate aminotransferase superfamily or alpha-family. The Homo sapiens and other eukaryotic constitutive kynureninases preferentially catalyze the hydrolytic cleavage of 3-hydroxy-l-kynurenine to produce 3-hydroxyanthranilate and l-alanine, while l-kynurenine is the substrate of many prokaryotic inducible kynureninases. The human enzyme was cloned with an N-terminal hexahistidine tag, expressed, and purified from a bacterial expression system using Ni metal ion affinity chromatography. Kinetic characterization of the recombinant enzyme reveals classic Michaelis-Menten behavior, with a Km of 28.3 +/- 1.9 microM and a specific activity of 1.75 micromol min-1 mg-1 for 3-hydroxy-dl-kynurenine. Crystals of recombinant kynureninase that diffracted to 2.0 A were obtained, and the atomic structure of the PLP-bound holoenzyme was determined by molecular replacement using the Pseudomonas fluorescens kynureninase structure (PDB entry 1qz9) as the phasing model. A structural superposition with the P. fluorescens kynureninase revealed that these two structures resemble the "open" and "closed" conformations of aspartate aminotransferase. The comparison illustrates the dynamic nature of these proteins' small domains and reveals a role for Arg-434 similar to its role in other AAT alpha-family members. Docking of 3-hydroxy-l-kynurenine into the human kynureninase active site suggests that Asn-333 and His-102 are involved in substrate binding and molecular discrimination between inducible and constitutive kynureninase substrates.
| S-EPMC2531291 | biostudies-literature