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Methods/New Tools, Novel Tools and Methods

Critical Analysis of Particle Detection Artifacts in Synaptosome Flow Cytometry

Benjamin D. Hobson and Peter A. Sims
eNeuro 22 May 2019, ENEURO.0009-19.2019; https://doi.org/10.1523/ENEURO.0009-19.2019
Benjamin D. Hobson
1Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, 10032
2Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, 10032
3Medical Scientist Training Program, Columbia University Irving Medical Center, New York, NY, 10032
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Peter A. Sims
1Department of Systems Biology, Columbia University Irving Medical Center, New York, NY, 10032
2Department of Biochemistry & Molecular Biophysics, Columbia University Irving Medical Center, New York, NY, 10032
4Sulzberger Columbia Genome Center, Columbia University Irving Medical Center, New York, NY, 10032
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Abstract

Flow cytometry and fluorescence-activated sorting are powerful techniques that hold great promise for studying heterogeneous populations of submicron particles such as synaptosomes, but many technical challenges arise in these experiments. To date, most flow cytometry studies of synaptosomes have relied on particle detection using forward scatter (FSC) measurements and size estimation with polystyrene (PS) bead standards. However, these practices have serious limitations, and special care must be taken to overcome the poor sensitivity of conventional flow cytometers in the analysis of submicron particles. Technical artifacts can confound these experiments, especially the detection of multiple particles as a single event. Here, we compared analysis of P2 crude synaptosomal preparations from murine forebrain on multiple flow cytometers using both FSC- and fluorescence-triggered detection. We implemented multicolor fluorescent dye-based assays to quantify coincident particle detection and aggregation, and we assessed the false colocalization of antigens in immunostaining analyses. Our results demonstrate that fluorescence-triggering and proper dilution can control for coincident particle detection, but not particle aggregation. We confirmed previous studies showing that FSC-based size estimation with PS beads underestimates biological particle size, and we identified pervasive aggregation in the FSC range analyzed in most synaptosome flow cytometry studies. We found that analyzing P2 samples in sucrose/tris/EDTA (SET) buffer reduces aggregation compared to phosphate-buffered saline (PBS), but does not completely eliminate the presence of aggregates, especially in immunostaining experiments. Our study highlights challenges and pitfalls in synaptosome flow cytometry and provides a methodological framework for future studies.

Significance Statement Synaptosomes are an invaluable model for synaptic biology, but these synaptic particles are traditionally analyzed in bulk preparations rather than at the level of single particles. Although flow cytometry is a powerful technique for high throughput particle analysis, submicron particles present unique challenges. Here, the authors investigate key elements of synaptosome flow cytometry experiments, especially those related to artifacts that confound the analysis of single synaptosomes. They identify aggregation as especially problematic and implement methods to minimize its impact on flow cytometry analysis.

  • flow cytometry
  • synaptosomes

Footnotes

  • The authors report no conflict of interest.

  • This work was supported by National Institute of General Medical Sciences Grant T32GM007367 (BH), National Institute on Drug Abuse Grant 1F30DA047775-01 (BH), and National Institute of Neurological Disorders and Stroke Grant R01NS103473 (PS). Research reported in this publication was performed in the CCTI Flow Cytometry Core, supported in part by the Office of the Director, National Institutes of Health under awards S10OD020056.  The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. These studies used the resources of the Cancer Center Flow Core Facility funded in part through Center Grant P30CA013696.

This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license, which permits unrestricted use, distribution and reproduction in any medium provided that the original work is properly attributed.

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Critical Analysis of Particle Detection Artifacts in Synaptosome Flow Cytometry
Benjamin D. Hobson, Peter A. Sims
eNeuro 22 May 2019, ENEURO.0009-19.2019; DOI: 10.1523/ENEURO.0009-19.2019

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Critical Analysis of Particle Detection Artifacts in Synaptosome Flow Cytometry
Benjamin D. Hobson, Peter A. Sims
eNeuro 22 May 2019, ENEURO.0009-19.2019; DOI: 10.1523/ENEURO.0009-19.2019
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  • flow cytometry
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