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Multidimensional assessment of alveolar T cells in critically ill patients.

ABSTRACT: Pneumonia represents the leading infectious cause of death in the United States. Foxp3+ regulatory T cells promote recovery from severe pneumonia in mice, but T cell responses in patients with pneumonia remain incompletely characterized because of the limited ability to serially sample the distal airspaces and perform multidimensional molecular assessments on the small numbers of recovered cells. As T cell function is governed by their transcriptional and epigenetic landscape, we developed a method to safely perform high-resolution transcriptional and DNA methylation profiling of T cell subsets from the alveoli of critically ill patients. Our method involves nonbronchoscopic bronchoalveolar lavage combined with multiparameter fluorescence-activated cell sorting, unsupervised low-input RNA-sequencing, and a modified reduced-representation bisulfite sequencing protocol. Here, we demonstrate the safety and feasibility of our method and use it to validate functional genomic elements that were predicted by mouse models. Because of its potential for widespread application, our techniques allow unprecedented insights into the biology of human pneumonia.

SUBMITTER: Walter JM

PROVIDER: S-EPMC6171809 | biostudies-other | 2018 Sep

REPOSITORIES: biostudies-other

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Multidimensional assessment of alveolar T cells in critically ill patients.

Walter James M JM Helmin Kathryn A KA Abdala-Valencia Hiam H Wunderink Richard G RG Singer Benjamin D BD

JCI insight 20180906 17

Pneumonia represents the leading infectious cause of death in the United States. Foxp3+ regulatory T cells promote recovery from severe pneumonia in mice, but T cell responses in patients with pneumonia remain incompletely characterized because of the limited ability to serially sample the distal airspaces and perform multidimensional molecular assessments on the small numbers of recovered cells. As T cell function is governed by their transcriptional and epigenetic landscape, we developed a met ...[more]

PMID: 30185658

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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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Multidimensional assessment of alveolar T cells in critically ill patients.

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Multidimensional assessment of alveolar T cells in critically ill patients.

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