Investigating gene expression profiles of whole blood and peripheral blood mononuclear cells using multiple collection and processing methods

• DOI: 10.1371/journal.pone.0225137
• Publication Date: 2019-12-06T18:28:15Z
• Authors: Aarti Gautam; Duncan Donohue; Allison Hoke; Stacy Ann Miller; Seshamalini Srini...; Bintu Sowe; Leanne Detwiler; Jesse Lynch; Michael Levangie; Rasha Hammamieh; Marti Jett
• Keywords: Trizol; Blood cell

Gene expression profiling using blood samples is a valuable tool for biomarker discovery in clinical studies. Different whole RNA collection and processing methods are highly variable might confound comparisons of results across The main aim the current study to compare how storage, extraction methodologies, components themselves may influence gene profiling. Whole peripheral mononuclear cell (PBMC) were collected triplicate from five healthy donors. was RNAgard® PAXgene® Blood Tubes, as well tubes with anticoagulants such dipotassium ethylenediaminetetraacetic acid (K2EDTA) Acid Citrate Dextrose Solution A (ACD-A). PBMCs separated sodium citrate Cell Preparation Tubes (CPT™), FICOLL™, magnetic separation, LeukoLOCK™ methods. After collection, LeukoLOCK™, K2EDTA ACD-A shipped overnight cold conditions rest immediately frozen or without pre-processing. isolated total 10 different experimental employing several widely utilized isolation quality assessed by Integrity Number (RIN), which showed that all PBMC procedures had highest RIN values when stabilized TRIzol® Reagent before extraction. Initial data analysis human stored at 4°C performed equally checked integrity number compared blood. Comparisons within donor/method replicates signal-to-noise patterns not captured value alone. Pathway top 1000 false rate (FDR) corrected differentially expressed genes (DEGs) vs. shipping greatly impacted However, FDR DEGs preserved after (LeukoLOCK™ RNAlater®) revealed no significantly affected pathways. Our provide novel insight into isolation, various handling, methodologies can apparent samples. Careful consideration necessary avoid bias resulting downstream processing. Better characterization effects method idiosyncrasies will facilitate further research understanding effect variability sample types.