Blood handling and leukocyte isolation methods impact the global transcriptome of immune cells
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Author(s) • • • • •
Goods, Brittany A
Vahey, Jacqueline M.
Steinschneider, Arthur S
Askenase, Michael H
Sansing, Lauren
Love, Christopher J.
Date Issued
October 2018
Journal
BMC Immunology
Publisher
BioMed Central
Citation
Goods, Brittany A. et al. "Blood handling and leukocyte isolation methods impact the global transcriptome of immune cells." BMC Immunology 2018, 19 (October 2018): 30 © 2018 The Author(s)
Version
Final published version
Abstract
Background
Transcriptional profiling with ultra-low input methods can yield valuable insights into disease, particularly when applied to the study of immune cells using RNA-sequencing. The advent of these methods has allowed for their use in profiling cells collected in clinical trials and other studies that involve the coordination of human-derived material. To date, few studies have sought to quantify what effects that collection and handling of this material can have on resulting data.
Results
We characterized the global effects of blood handling, methods for leukocyte isolation, and preservation media on low numbers of immune cells isolated from blood. We found overall that storage/shipping temperature of blood prior to leukocyte isolation and sorting led to global changes in both CD8+ T cells and monocytes, including alterations in immune-related gene sets. We found that the use of a leukocyte filtration system minimized these alterations and we applied this method to generate high-quality transcriptional data from sorted immune cells isolated from the blood of intracerebral hemorrhage patients and matched healthy controls.
Conclusions
Our data underscore the necessity of processing samples with comparably defined protocols prior to transcriptional profiling and demonstrate that a filtration method can be applied to quickly isolate immune cells of interest while minimizing transcriptional bias. Keywords: Immune profiling; Peripheral blood mononuclear cells; Transcriptome; RNA-seq
MIT Department
Massachusetts Institute of Technology. Department of Biological Engineering
Massachusetts Institute of Technology. Department of Chemical Engineering
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Koch Institute for Integrative Cancer Research at MIT
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Creative Commons Attribution
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DOI of Published Version
https://doi.org/10.1186/s12865-018-0268-6