4.8 Article

Identification of the Differentiation Stages of Living Cells from the Six Most Immature Murine Hematopoietic Cell Populations by Multivariate Analysis of Single-Cell Raman Spectra

Journal

ANALYTICAL CHEMISTRY
Volume 94, Issue 35, Pages 11999-12007

Publisher

AMER CHEMICAL SOC
DOI: 10.1021/acs.analchem.2c00714

Keywords

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Funding

  1. National Institutes of Health [R21 HL132642, F31 DK117514, T32 EB019944, R01 DK099528]

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This study demonstrates that a combination of Raman microspectroscopy and partial least squares discriminant analysis (PLS-DA) can be used to location-specifically identify individual living cells from the six most immature hematopoietic cell populations. By utilizing spectral features associated with cell biochemistries, the differentiation stages of cells can be accurately identified.
Efforts to expand hematopoietic stem and progenitor cells (HSPCs) in vitro are motivated by their use in the treatment of leukemias and other blood and immune system diseases. The combinations of extrinsic cues within the hematopoietic stem cell (HSC) niche that lead to HSC fate decisions remain unknown. New noninvasive and location-specific techniques are needed to enable identification of the differentiation stages of individual hematopoietic cells on biomaterial microarray screening platforms that minimize the usage of rare HSCs. Here, we show that a combination of Raman microspectroscopy and partial least squares discriminant analysis (PLS-DA) enables the location-specific identification of individual living cells from the six most immature hematopoietic cell populations, HSC, multipotent progenitor (MPP)-1, MPP-2, MPP-3, common myeloid progenitor, and common lymphoid progenitor. Better than 90% accuracy was achieved. We show that the accuracy of this differentiation stage identification was based on spectral features associated with cell biochemistries. This work establishes that PLS-DA can capture the subtle spectral variations between as many as six closely related cell populations in the presence of potentially significant within-population spectral variation. This noninvasive approach can be used to screen HSC fate decisions elicited by extrinsic cues within biomaterial microarray screening platforms.

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