Dataset Information

Mortality Risk-Stratified Septic Serum Depresses Contractility and Mitochondrial Function in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

ABSTRACT: We sought to investigate human induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) exposed to mortality risk-stratified septic serum as a model of cardiomyocyte pathobiology in septic shock. We stratified previously banked serum from children with septic shock by Pediatric Sepsis Biomarker Risk Model (PERSEVERE) II mortality probability as low, intermediate, or high risk. We treated iPSC-CM spheroids with 10% v/v diluted risk-stratified septic serum and defined contractile and mitochondrial functional and transcriptomic responses. High-risk septic serum reversibly depressed iPSC-CM contractility as measured by percent shortening and spontaneous beat frequency, while low-risk septic serum had no impact. Further, high-risk septic serum depressed measures of mitochondrial function and drove distinct patterns of gene expression. These findings validate mortality risk-stratified septic serum exposure of iPSC-CMs as a human-relevant translational platform to interrogate mechanisms of myocardial dysfunction in septic shock.

ORGANISM(S): Homo sapiens

PROVIDER: GSE314561 | GEO | 2026/09/01

REPOSITORIES: GEO

ACCESS DATA

Dataset's files

Source:

			Action	DRS
		Other

Items per page:

1 - 1 of 1

Similar Datasets

Project description:Background: We had shown that cardiomyocytes (CMs) were more efficiently differentiated from human induced pluripotent stem cells (hiPSCs) when the hiPSCs were reprogrammed from cardiac fibroblasts rather than dermal fibroblasts or blood mononuclear cells. Here, we continued to investigate the relationship between somatic-cell lineage and hiPSC-CM production by comparing the yield and functional properties of CMs differentiated from iPSCs reprogrammed from human atrial or ventricular cardiac fibroblasts (AiPSC or ViPSC, respectively). Methods: Atrial and ventricular heart tissues were obtained from the same patient, reprogrammed into AiPSCs or ViPSCs, and then differentiated into CMs (AiPSC-CMs or ViPSC-CMs, respectively) via established protocols. Results: The time-course of expression for pluripotency genes (OCT4, NANOG, and SOX2), the early mesodermal marker Brachyury, the cardiac mesodermal markers MESP1 and Gata4, and the cardiovascular progenitor-cell transcription factor NKX2.5 were broadly similar in AiPSC-CMs and ViPSC-CMs during the differentiation protocol. Flow-cytometry analyses of cardiac troponin T expression also indicated that purity of the two differentiated hiPSC-CM populations (AiPSC-CMs: 88.23±4.69%, ViPSC-CMs: 90.25±4.99%) was equivalent. While the field-potential durations were significantly longer in ViPSC-CMs than in AiPSC-CMs, measurements of action potential duration, beat period, spike amplitude, conduction velocity, and peak calcium-transient amplitude did not differ significantly between the two hiPSC-CM populations. Yet, our cardiac-origin iPSC-CM showed higher ADP and conduction velocity than previously reported iPSC-CM derived from non-cardiac tissues. Transcriptomic data comparing iPSC and iPSC-CMs showed similar gene expression profiles between AiPSC-CMs and ViPSC-CMs with significant differences when compared to iPSC-CM derived from other tissues. This analysis also pointed to several genes involved in electrophysiology processes to be responsible for the physiological differences observed between cardiac and non-cardiac-derived cardiomyocytes. ¬ Conclusions: AiPSC and ViPSC were differentiated into CMs with equal efficiency. Detected differences in electrophysiological properties, calcium handling activity, and transcription profiles between cardiac and non-cardiac derived cardiomyocytes demonstrated that 1) tissue of origin matters to generate a better-featured iPSC-CMs, 2) the sublocation within the cardiac tissue has marginal effects on the differentiation process.

Project description:Goal of the experiment: To identify correlated genes, pathways and groups of patients with systemic inflammatory response syndrome and septic shock that is indicative of biologically important processes active in these patients. Background: We measured gene expression levels and profiles of children with systemic inflammatory response syndrome (SIRS) and septic shock as a means for discovering patient sub-groups and gene signatures that are active in disease-affected individuals and potentially in patients with poor outcomes. Methods: Microarray and bioinformatics analyses of 123 microarray chips representing whole blood derived RNA from controls, children with SIRS, and children with septic shock. Results: A discovery-based filtering approach was undertaken to identify genes whose expression levels were altered in patients with SIRS or septic shock. Clustering of these genes identified 3 Major and several minor sub-groups of patients with SIRS or septic shock. The three groups differed with respect to incidence of septic shock and trended toward differences in mortality. Statistical analyses demonstrated that 6,435 gene probes were differentially regulated between the three patient sub-groups (false discovery rate < 0.001%). Of these gene probes, 623 gene probes within 7 major gene ontologies accounted for the majority of group differentiation. Network analyses of these 623 gene probes demonstrated 5 major gene networks that were differentially expressed between the 3 groups. Statistical comparison of septic shock survivors and non-survivors identified one major gene network that was under expressed in a high fraction of the non-survivors and identified potential biomarkers for poor outcome. Conclusions: This is the first genome-level demonstration of pediatric patient sub-groups with SIRS and septic shock. The sub-groups differ clinically and differentially express 5 major gene networks. We have identified gene signatures and potential biomarkers associated with poor outcome in children with septic shock. These data represent a major advancement in our genome-level understanding of pediatric SIRS and septic shock. Experiment Overall Design: Children < 10 years of age admitted to the pediatric intensive care unit and meeting the criteria for either SIRS or septic shock were eligible for the study. SIRS and septic shock were defined based on pediatric-specific criteria. We did not use separate categories of "sepsis" or "severe sepsis". Patients meeting criteria for "sepsis" or "severe sepsis" were placed in the categories of SIRS and septic shock, respectively, for study purposes. Control patients were recruited from the outpatient or inpatient departments of the participating institutions using the following exclusion criteria: a recent febrile illness (within 2 weeks), recent use of anti-inflammatory medications (within 2 weeks), or any history of chronic or acute disease associated with inflammation. Experiment Overall Design: After obtaining informed consent, blood samples were obtained on Day 1 of the study, and when possible on Day 3 of the study. Blood samples were divided for RNA extraction and isolation of serum. Severity of illness was calculated based on the PRISM III score. Organ failure was defined based on pediatric-specific criteria. Annotated clinical and laboratory data were collected daily while in the intensive care unit. Study patients were placed in the study categories of SIRS or Septic Shock on Day 1 of the study. On Day 3 of the study, patients were classified as SIRS, Septic Shock, or SIRS resolved (no longer meeting criteria for SIRS). All study patients were followed for 28 days to determine mortality or survival. Clinical, laboratory, and biological data were entered and stored using a web-based data base developed locally.

Project description:The cardiomyocytes (CMs) differentiation of 12 validated iPSC lines were induced using the Gibco PSC Cardiomyocyte Differentiation Kit and following manufacturer method with minor modifications (Thermo Fisher Scientific, Waltham, MA, USA). The differentiation kit consists of a set of serum-free and xeno-free media that enable efficient differentiation of human iPSCs into spontaneously contracting functional cardiomyocytes in 14 days. On day 14 of the differentiation, spontaneously contracting CMs were characterized by immunocytochemistry (ICC) analysis of cardiac mesoderm marker NKX2-5, and mature cardiomyocyte marker TNNT2 and genome-wide mRNA sequencing of the 12 iPSC lines and generated 12 CM lines were performed. The CMs differentiated from all the 12 iPSC lines expressed NKX2-5 and TNNT2 cardiomyocyte markers. Based on the criteria normalized read count (NRC) ≥ 20 in all 12 CM samples, a total of 12280 genes were found expressed. The average correlation coefficient at 95% CI between 12 CM samples, calculated based on all expressed genes, was 0.92 ± 0.02, suggesting a uniform differentiation of generated CMs across 12 samples. The expression of the well-known CMs genes/markers MYH6, MYL4, MYL3, MYL7, NPPA, NPPB, MYH7, NKX2-5, TBX5, TNNT2, ACTN2, TNNC1 and MB, was significantly up-regulated across all 12 CM samples (FDR corrected p-value ≤ 0.05 and fold change absolute (FC-abs) ≥ 2.0); whereas the expression of pluripotency markers and the ectodermal markers was significantly down regulated. The endodermal markers SOX17 and CLDN6 were below the expression threshold of NRC ≥ 20. A differential gene expression analysis of iPSC’s and CM’s expressed transcription identified 4,191 genes that were significantly differentially expressed (DE) between iPSCs and differentiated CMs. The 2,116 DE genes that were significantly up regulated in differentiated CMs showed significantly high enrichment in cardiovascular system development and functions (571 mRNAs; FDR adjusted p-value range: 1.75x10-66 – 1.61x10-14) and predicted activation of the functions associated with development of human heart and cardiovascular system.

Dataset Information

Mortality Risk-Stratified Septic Serum Depresses Contractility and Mitochondrial Function in Human Induced Pluripotent Stem Cell-Derived Cardiomyocytes

Dataset's files

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets