The H3K4me3 pattern of mouse renal cortex tissues treated with dexmedetomidine against lipopolysaccharide-induced sepsis
Ontology highlight
ABSTRACT:
INSTRUMENT(S): HiSeq X Ten
ORGANISM(S): Mus musculus
SUBMITTER: Chunting Wang
PROVIDER: E-MTAB-8133 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Sepsis-associated acute kidney injury (SA-AKI) is a key contributor to the life threatening sequalae attributed to sepsis. Mechanistically, SA-AKI is a consequence of unabated myeloid cell activation and oxidative stress that induces tubular injury. Iron mediates inflammatory pathways directly and through regulating the expression of myeloid-derived ferritin, an iron storage protein comprised of ferritin light (FtL) and ferritin heavy chain (FtH) subunits. Previous work revealed myeloid FtH deletion leads to a compensatory increase in intracellular and circulating FtL and is associated with amelioration of SA-AKI. We designed this study to test the hypothesis that loss of myeloid FtL and subsequently, circulating FtL will exacerbate the sepsis-induced inflammatory response and worsen SA-AKI. We generated a novel myeloid-specific FtL knockout mouse (FtLLysM-/-) and induced sepsis via cecal ligation and puncture or lipopolysaccharide endotoxemia. As expected, serum ferritin levels were significantly lower in the knockout mice, suggesting that myeloid cells dominantly contribute to circulating ferritin. Interestingly, while sepsis induction led to a marked production of pro- and anti-inflammatory cytokines, there was no statistical difference between the genotypes. There was a similar loss of kidney function, as evident by a rise in serum creatinine and cystatin C, and renal injury identified by expression of kidney injury molecule-1 and neutrophil gelatinase associated lipocalin. Finally, RNA sequencing revealed upregulation of pathways for cell cycle arrest and autophagy post-sepsis, but no significant differences were observed between genotypes, including in key genes associated with ferroptosis, an iron-mediated form of cell death. The loss of FtL did not impact sepsis-mediated activation of NFkB or HIF-1a signaling, key inflammatory pathways associated with dysregulated host response. Taken together, while FtL overexpression was shown to be protective against sepsis, loss of FtL did not influence sepsis pathogenesis.
2024-05-13 | GSE255281 | GEO
Project description:# Background Acute kidney injury (AKI) in sepsis patients increases patient mortality. Endothelial cells are important players in the pathophysiology of sepsis-associated AKI (SA-AKI), yet knowledge regarding their spatiotemporal involvement in coagulation disbalance and leukocyte recruitment is lacking. This study investigated the identity and kinetics of responses of different microvascular compartments in kidney cortex in response to SA-AKI. # Methods Laser microdissected arterioles, glomeruli, peritubular capillaries, and postcapillary venules from kidneys of mice subjected to cecal ligation and puncture (CLP) were analyzed using RNA sequencing. Differential expression and pathway enrichment analyses identified genes involved in coagulation and inflammation. A selection of these genes was evaluated by RT-qPCR in microvascular compartments of renal biopsies from patients with SA-AKI. The role of two identified genes in lipopolysaccharide-induced endothelial coagulation and inflammatory activation were determined in vitro in HUVEC using siRNA-based gene silencing. # Results CLP-sepsis in mice induced altered expression of approximately 400 genes in the renal microvasculature, with microvascular compartments exhibiting unique spatiotemporal responses. In mice, changes in gene expression related to coagulation and inflammation were most extensive in glomeruli at early and intermediate time points, with high induction of Plat, Serpine1, Thbd, Icam1, Stat3, and Ifitm3. In human SA-AKI, PROCR and STAT3 were induced in postcapillary venules, while SERPINE1 expression was diminished. IFITM3 was increased in arterioles and glomeruli. In vitro studies revealed that STAT3 and IFITM3 partly control endothelial coagulation and inflammatory activation. # Conclusion Renal microvascular compartments in mice and humans exhibited heterogeneous changes in coagulation- and inflammation-related gene expression in response to SA-AKI. Additional research should aim at understanding the functional consequences of the here described heterogeneous microvascular responses to establish the usefulness of identified genes as therapeutic targets in SA-AKI.
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Project description:Sepsis-induced acute kidney injury (S-AKI) is the most common complication in hospitalized and critically ill patients, highlighted by a rapid decline of kidney function occurring a few hours or days after sepsis onset. Systemic inflammation elicited by microbial infections is believed to lead to kidney damage under immunocompromised conditions. However, while AKI has been recognized as a disease with long-term sequelae, partly due to the associated higher risk of chronic kidney disease (CKD), the understanding of kidney pathophysiology at the molecular level and the global view of dynamic regulations in situ after S-AKI, including the transition to CKD, remains limited. Existing studies of S-AKI mainly focus on deriving sepsis biomarkers from body fluids. In the present study, we constructed a mid-severity septic murine model using cecal ligation and puncture (CLP), and examined the temporal changes to the kidney proteome and phosphoproteome at day 2 and day 7 after CLP surgery, corresponding to S-AKI and the transition to CKD, respectively, by employing an ultrafast and economical filter-based sample processing method combined with the label-free quantitation approach. Collectively, we identified 2,119 proteins and 2,950 phosphosites through multi-proteomics analyses. Among them, we identified an array of highly promising candidate marker proteins indicative of disease onset and progression accompanied by immunoblot validations, and further denoted the pathways that are specifically responsive to S-AKI and its transition to CKD, which include regulation of cell metabolism regulation, oxidative stress, and energy consumption in the diseased kidneys. Our data can serve as an enriched resource for the identification of mechanisms and biomarkers for sepsis-induced kidney diseases.
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Project description:Sepsis induced acute kidney injury (AKI) is associated with a rapid decline of kidney function, leading to unacceptably high morbidity and mortality rate as well as progression to chronic kidney disease (CKD). We have recently developed a septic AKI mouse model. By quantitatively assessing the kidney proteome and phosphoproteome changes upon bacterial infection, we accurately quantified over 2,200 kidney proteins with high confidence, which provided us the first global overview of the extensively remodeled kidney proteome and revealed widespread metabolic and oxidation-reduction processes undergone in septic kidney. This data will give us unprecedented insight into how renal cells response to microbe invasion, and will likely serve as a reference dataset of systems biology.
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Project description:Using the highly sensitive miRNA array, we screened 40 miRNAs were differentially expressed among the three groups and we explored the functions of these miRNAs in the serum by Gene Ontology and Kyoto Encyclopedia of Genes annotation. The enrichment results indicated that these miRNAs mainly participated in the oxidative stress and mitochondrial dysfunction pathways. Furthermore, the quantitative real-time polymerase chain reaction showed the different expression of miRNA might potentially be used to discriminate septic AKI from sepsis-non AKI and they were correlated with the regulation of mitochondrial oxidative stress and dysfunction, including PGC-1α, SIRT1, mTOR, OXSR1 and NOX5.
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Project description:Both sepsis and acute respiratory distress syndrome (ARDS) rely on imprecise clinical definitions leading to heterogeneity, which has contributed to negative trials. Because circulating protein/DNA complexes have been implicated in sepsis and ARDS, we aimed to develop a proteomic signature of DNA-bound proteins to discriminate between children with sepsis with and without ARDS. We performed a prospective case-control study in 12 children with sepsis with ARDS matched to 12 children with sepsis without ARDS on age, severity of illness score, and source of infection. We performed co-immunoprecipitation and downstream proteomics in plasma collected ≤ 24 h of intensive care unit admission. Expression profiles were generated, and a random forest classifier was used on differentially expressed proteins to develop a signature which discriminated ARDS. The classifier was tested in six independent blinded samples. Neutrophil and nucleosome proteins were over-represented in ARDS, including two S100A proteins, superoxide dismutase (SOD), and three histones. Random forest produced a 10-protein signature that accurately discriminated between children with sepsis with and without ARDS. This classifier perfectly assigned six independent blinded samples as having ARDS or not. We validated higher expression of the most informative discriminating protein, galectin-3-binding protein, in children with ARDS. Our methodology has applicability to isolation of DNA-bound proteins from plasma. Our results support the premise of a molecular definition of ARDS, and give preliminary insight into why some children with sepsis, but not others, develop ARDS.
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Project description:Epigenetic abnormalities are frequently involved in the initiation and progression of cancers including acute myeloid leukemia (AML). A subtype of AML, Acute promyelocytic leukemia (APL), is mainly driven by a specific oncogenic fusion event of PML-RARα. PML-RARα was reported as a transcription repressor through the interaction with NCoR/HDAC complexes leading to the mis-suppression of its target genes and differentiation blockage. While previous studies were mainly focused on the connection of histone acetylation, it is still largely unknown whether alternative epigenetics mechanisms are involved in APL progression. KDM5A is a demethylase of histone H3 lysine 4 di- and tri- methylations (H3K4me2/3) and a transcription corepressor. Here, we found that the loss of KDM5A led to APL NB4 cell differentiation and retarded growth. Mechanistically, through epigenomics and transcriptomics analyses, we detected KDM5A binding in 1,889 genes, with the majority of the binding events at promoter regions. KDM5A suppressed the expression of 621 genes, including 42 PML-RARα target genes primarily by controlling the H3K4me2 in the promoters and 5’ end intragenic regions. In addition, a recently reported pan-KDM5 inhibitor, CPI-455 on its own could phenocopy the differentiation effects as KDM5A loss in NB4 cells. CPI-455 treatment or KDM5A knockout could greatly sensitize NB4 cells to ATRA induced differentiation. Our findings indicated that KDM5A contributed to the differentiation blockage in the APL cell line NB4, and inhibition of KDM5A could greatly potentiate NB4 differentiation.
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Project description:Objective: It is unclear whether the host response of gram-positive sepsis differs from gram-negative sepsis at a transcriptome level. Using microarray technology, we compared the gene-expression profiles of gram-positive sepsis and gram-negative sepsis in critically ill patients. Design: A prospective cross-sectional study. Setting: A 20-bed general intensive care unit of a tertiary referral hospital. Patients: Seventy-two patients admitted to the intensive care unit. Interventions: Intravenous blood was collected for leukocyte separation and RNA extraction. Microarray experiements were then performed examing the expression level of 19,232 genes in each sample. Measurements and Main Results: There was no difference in the expression profile between gram-positive and gram-negative sepsis. The finding remained unchanged even when genes with lower expression level were included or after statistical stringency was lowered. There were, however, ninety-four genes differentially expressed between sepsis and control patients. These genes included those involved in immune regulation, inflammation and mitochondrial function. Hierarchical cluster analysis confirmed that the difference in gene expression profile existed between sepsis and control patients, but not between gram-positive and gram-negative patients. Conclusion: Gram-positive and gram-negative sepsis share a common host response at a transcriptome level. These findings support the hypothesis that the septic response is non-specific and is designed to provide a more general response that can be elicited by a wide range of different micro-organisms. The study included seventy-two critically ill patients admitted to the intensive care unit (ICU) of Nepean Hospital, Sydney, Australia. Of these, fifty-five patients were diagnosed to have sepsis, as confirmed by microbiological culture. The remaining seventeen patients did not have sepsis and were therefore used as controls. The study was approved by the hospital ethics committee and informed consent was obtained from all patients or their relatives. Patient Samples. Whole blood was taken from each patient on admission to ICU. Neutrophils were separated from whole blood using density-gradient separation with Ficoll-PaqueP P(Amersham). Subsequent neutrophil RNA extraction was performed using guanidinium thiocyanate (Ambion). Microarray Experiment. The neutrophil RNA was converted to cDNA, fluorescently labeled and hybridized to its complimentary sequences on the microarray (Invitrogen). The fluorescent signals on each micrroarray were captured using the GenePix 4000B laser scanner (Axon Instruments). Expression level of each gene was represented by the intensity of its fluorescent signal. Data Extraction. All signal intensity values were processed using background-subtraction method. Prior to analysis, all values were log-transformed and normalized by fitting a print-tip group Lowess curve. Normalization minimizes bias due to dye chemistry, signal intensity or location of a gene on the array. It ensures the detection of genes that are truly differentially expressed, instead of those caused by experimental artifacts or variation in the hybridization process. After normalization, genes that had more than 50% of data missing were removed. We then selected genes that had at least 80% of the data showing two-fold changes from the geneâs median values. After filtering, 1617 genes were available for further analysis.
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