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, 87 (22), 11317-24

Identifying States Along the Hematopoietic Stem Cell Differentiation Hierarchy With Single Cell Specificity via Raman Spectroscopy

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Identifying States Along the Hematopoietic Stem Cell Differentiation Hierarchy With Single Cell Specificity via Raman Spectroscopy

Yelena Ilin et al. Anal Chem.

Abstract

A major challenge for expanding specific types of hematopoietic cells ex vivo for the treatment of blood cell pathologies is identifying the combinations of cellular and matrix cues that direct hematopoietic stem cells (HSC) to self-renew or differentiate into cell populations ex vivo. Microscale screening platforms enable minimizing the number of rare HSCs required to screen the effects of numerous cues on HSC fate decisions. These platforms create a strong demand for label-free methods that accurately identify the fate decisions of individual hematopoietic cells at specific locations on the platform. We demonstrate the capacity to identify discrete cells along the HSC differentiation hierarchy via multivariate analysis of Raman spectra. Notably, cell state identification is accurate for individual cells and independent of the biophysical properties of the functionalized polyacrylamide gels upon which these cells are cultured. We report partial least-squares discriminant analysis (PLS-DA) models of single cell Raman spectra enable identifying four dissimilar hematopoietic cell populations across the HSC lineage specification. Successful discrimination was obtained for a population enriched for long-term repopulating HSCs (LT-HSCs) versus their more differentiated progeny, including closely related short-term repopulating HSCs (ST-HSCs) and fully differentiated lymphoid (B cells) and myeloid (granulocytes) cells. The lineage-specific differentiation states of cells from these four subpopulations were accurately identified independent of the stiffness of the underlying biomaterial substrate, indicating subtle spectral variations that discriminated these populations were not masked by features from the culture substrate. This approach enables identifying the lineage-specific differentiation stages of hematopoietic cells on biomaterial substrates of differing composition and may facilitate correlating hematopoietic cell fate decisions with the extrinsic cues that elicited them.

Figures

Figure 1
Figure 1
Diagram of hematopoiesis. Populations in analyzed in this study are circled, and cell-specific surface markers are noted. Adapted with permission from ref . Copyright 2003 National Academy of Sciences, U.S.A.
Figure 2
Figure 2
Average Raman spectra of hematopoietic cells and the corresponding mean-centered spectra. (a) Average spectra acquired from single LT-HSCs (red), ST-HSCs (green), granulocytes (blue), and B cells (cyan) using a 785 nm laser over the region 600–1750 cm−1 were baseline-subtracted, normalized to the area under the peak at 1437 – 1465 cm−1, and offset for clarity. Grey lines indicate standard deviation from the average spectra. The spectra were mean-centered (b) to emphasize major sources of spectral variance between the different cell types. Refer to SI for peak assignments.
Figure 3
Figure 3
Identification plots for the PLS-DA models generated using Raman spectra of calibration hematopoietic cells that were seeded on the same stiff polyacrylamide gels as the cells in the test set. Cells located above the classification threshold (red dashed line) were identified as (a) LT-HSCs, (b) ST-HSCs, (c) granulocytes, and (d) B cells.
Figure 4
Figure 4
Average latent variable (LV) scores for the hematopoietic cell populations in the PLS-DA model presented in Figure 3. Average scores on LV1 (12.3% variance) (a), LV2 (9.8% variance) (b), LV3 (11.5% variance) (c), and LV4 (19.6% variance) (d) for the calibration LT-HSCs (red), ST-HSCs (green), granulocytes (blue), and B cells (cyan). The corresponding latent variable loadings for LV1 (e), LV2 (f), LV3 (g), and LV4 (h) contain combinations of cell-associated Raman peaks. Refer to SI for peak assignments.
Figure 5
Figure 5
Score plots for the PCA model generated using Raman spectra of hematopoietic cells seeded on stiff polyacrylamide gels. Score plots for (a) PC1 (81.6% of variance) and PC2 (5.25% of variance), (b) PC1 and PC3 (3.67% of variance), and (c) PC2 and PC3 account for the majority of the spectral variance in the dataset. The ellipse in each PC model represents the border for the entire model at the 95% confidence limit.
Figure 6
Figure 6
Identification plots for the PLS-DA models generated using Raman spectra of calibration hematopoietic cells seeded on stiff and soft polyacrylamide gels were used to classify a test set of hematopoietic cells seeded on stiff and soft polyacrylamide gels. Cells located above the classification threshold (red dashed line) were identified as (a) LT-HSCs, (b) ST-HSCs, (c) granulocytes, and (d) B cells.

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