ArticleAnalytical chemistry2022
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.
Article in Analytical chemistry, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed, 7 citations in OpenAlex.
- Raman spectroscopy combined with multiple technologies for label-free identification of immune cells: An overview.Journal of pharmaceutical analysis · 2026Review
- Noninvasive andThe Analyst · 2025Article
- High-content stimulated Raman pathology imaging and transcriptomics reveal leukemia subtype-specific lipid metabolic heterogeneity.Frontiers in immunology · 2025Article
- Raman Spectroscopy as a Research and Diagnostic Tool in Clinical Hematology and Hematooncology.International journal of molecular sciences · 2024Review
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Authors and funding
5 authors at 1 institution in 1 country.
Funding
Abstract
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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Registered trials
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