Dataset Information

Proteomic and metabolomic profiling of acute and chronic stress events associated with military exercises.

ABSTRACT: By characterizing physiological changes that occur in warfighters during simulated combat, we can start to unravel the key biomolecular components that are linked to physical and cognitive performance. Viable field-based sensors for the warfighter must be rapid and noninvasive. In an effort to facilitate this, we applied a multiomics pipeline to characterize the stress response in the saliva of warfighters to correlate biomolecular changes with overall performance and health. In this study, two different stress models were observed - one of chronic stress and one of acute stress. In both models, significant perturbations in the immune, metabolic, and protein manufacturing/processing systems were observed. However, when differentiating between stress models, specific metabolites associated with the 'fight or flight' response and protein folding were seen to be discriminate of the acute stress model.

INSTRUMENT(S): Liquid Chromatography MS - alternating - reverse phase

SUBMITTER: Conor Jenkins

PROVIDER: MTBLS5463 | MetaboLights | 2023-12-05

REPOSITORIES: MetaboLights

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Proteomic and metabolomic profiling of acute and chronic stress events associated with military exercises.

McKetney Justin J Jenkins Conor C CC Minogue Catie C Mach Phillip M PM Hussey Erika K EK Glaros Trevor G TG Coon Joshua J Dhummakupt Elizabeth S ES

Molecular omics 20220511 4

By characterizing physiological changes that occur in warfighters during simulated combat, we can start to unravel the key biomolecular components that are linked to physical and cognitive performance. Viable field-based sensors for the warfighter must be rapid and noninvasive. In an effort to facilitate this, we applied a multiomics pipeline to characterize the stress response in the saliva of warfighters to correlate biomolecular changes with overall performance and health. In this study, two ...[more]

PMID: 34860218

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Project description:The most widely used method for detecting genome-wide protein-DNA interactions is chromatin immunoprecipitation on tiling microarrays, commonly known as ChIP-chip. Here, we conducted the first objective analysis of tiling array platforms, amplification procedures, and signal detection algorithms in a simulated ChIP-chip experiment. Mixtures of human genomic DNA and spike-ins comprised of nearly 100 human sequences at various concentrations were hybridized to four tiling array platforms by eight independent groups. Blind to the number of spike-ins, their locations, and the range of concentrations, each group made predictions of the spike-in locations. We found that microarray platform choice is not the primary determinant of overall performance. In fact, variation in performance between labs, protocols and algorithms within the same array platform was greater than the variation in performance between array platforms. However, each array platform had unique performance characteristics that varied with tiling resolution and the number of replicates, which have implications for cost versus detection power. Long oligonucleotide arrays were slightly more sensitive at detecting very low enrichment. On all platforms, simple sequence repeats and genome redundancy tended to result in false positives. LM-PCR and WGA, the most popular sample amplification techniques, reproduced relative enrichment levels with high fidelity. Performance among signal detection algorithms was heavily dependent on array platform. The spike-in DNA samples and the data presented here provide a stable benchmark against which future ChIP platforms, protocol improvements, and analysis methods can be evaluated. This SuperSeries is composed of the following subset Series: GSE9732: Spike-in Experiment for ChIP-chip Simulation GSE9842: Systematic evaluation of variability in simulated ChIP-chip experiments GSE9848: Systematic evaluation of variability in simulated ChIP-chip experiments Kevin_Encode GSE9849: Systematic evaluation of variability in simulated ChIP-chip experiments Myles_Encode GSE10004: ENCODE Spike-In, Yale Group GSE10076: ENCODE spikein, amplified DNA samples, NimbleGen arrays GSE10090: ENCODE spikein, nonamplified DNA samples, NimbleGen arrays GSE10112: Systematic evaluation of variability in simulated ChIP-chip experiments Keywords: SuperSeries For data usage terms and conditions, please refer to http://www.genome.gov/27528022 and http://www.genome.gov/Pages/Research/ENCODE/ENCODEDataReleasePolicyFinal2008.pdf Refer to individual Series

Dataset Information

Proteomic and metabolomic profiling of acute and chronic stress events associated with military exercises.

Publications

Proteomic and metabolomic profiling of acute and chronic stress events associated with military exercises.

Similar Datasets

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