Dataset Information

Quantitative Proteomics Reveals a Role for Epigenetic Reprogramming During Human Monocyte Differentiation

ABSTRACT: The data submitted is for the proteomics data published in the paper: Quantitative proteomics reveals a role for epigenetic reprogramming during human monocyte differentiation D Nicholas, H Tang, Q Zhang, J Rudra, F Xu, W Langridge, K Zhang Molecular & Cellular Proteomics 14 (1), 15-29.

INSTRUMENT(S): LTQ Orbitrap Velos

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Monocyte, Dendritic Cell, Blood, Macrophage

SUBMITTER: Kangling Zhang

LAB HEAD: Kangling Zhang

PROVIDER: PXD058308 | Pride | 2024-11-27

REPOSITORIES: Pride

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Quantitative proteomics reveals a role for epigenetic reprogramming during human monocyte differentiation.

Nicholas Dequina D Tang Hui H Zhang Qiongyi Q Rudra Jai J Xu Feng F Langridge William W Zhang Kangling K

Molecular & cellular proteomics : MCP 20141014 1

The differentiation of monocytes into macrophages and dendritic cells involves mechanisms for activation of the innate immune system in response to inflammatory stimuli, such as pathogen infection and environmental cues. Epigenetic reprogramming is thought to play an important role during monocyte differentiation. Complementary to cell surface markers, the characterization of monocytic cell lineages by mass spectrometry based protein/histone expression profiling opens a new avenue for studying i ...[more]

PMID: 25316709

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Project description:INTRO: The ongoing challenge of accurately diagnosing infection in the ICU motivates a search for novel molecular diagnostics. In the current study, we tested the hypothesis that the informational content of circulating leukocytes differs, thereby allowing one to rank leukocyte populations on their potential to contribute to RNA diagnostics for pneumonia. METHODS: Sixteen patients (10 male, 6 female) at risk for VAP were entered into our IRB-approved study that collects blood and clinical data every 48 hours for up to 21 days. Four of the sixteen patients developed VAP as diagnosed and treated by the attending ICU physician. Previously reported blood protocols were used to isolate buffy coat, enriched neutrophil, and enriched monocyte populations by using negative selection. Cellular purity was assessed by FACS for one of the 4 VAP patients. Genome-wide expression analysis was performed on RMA-normalized signal from Affymetrix U133 2.0 Plus GeneChips. EDGE software (FDR=0.10) was used to determine changes in mRNA abundance over time for each cell population. RESULTS: During the 5-day window in which each of the four patients (all males) developed VAP, significant changes in gene expression were observed (Table 2), but the information content (number of genes altered) varied across leukocyte populations. These differences were not due to signal variance (coefficient of variation, CV) or differences in the number of samples available for analysis. Moreover, only 0.6% of the monocyte gene list overlaps with the neutrophil list, arguing that neutrophil contamination of monocyte populations is insufficient to explain the 40-fold difference in gene number. CONCLUSIONS: Enriched monocyte populations from circulating blood provide far more genes for study of the host response to VAP than the other 2 cell populations studied. This information should be considered when designing blood gene expression profiling experiments in patients at risk for sepsis. Keywords: time course Four patients over several timepoints measured three different cell types for VAP signal

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