Department of Chemical and Biomolecular Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.
Department of Materials Science and Engineering, University of Illinois Urbana-Champaign, Urbana, Illinois 61801, United States.
Anal Chem. 2022 Sep 6;94(35):11999-12007. doi: 10.1021/acs.analchem.2c00714. Epub 2022 Aug 24.
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.
人们努力在体外扩增造血干细胞和祖细胞(HSPCs),其目的是将其用于治疗白血病和其他血液及免疫系统疾病。导致造血干细胞(HSC)命运决定的 HSC 龛位中外在线索的组合仍不清楚。需要新的非侵入性和位置特异性技术,以便在最小化稀有 HSC 使用量的生物材料微阵列筛选平台上识别单个造血细胞的分化阶段。在这里,我们表明,拉曼微光谱和偏最小二乘判别分析(PLS-DA)的组合能够从六个最不成熟的造血细胞群体(HSC、多能祖细胞(MPP)-1、MPP-2、MPP-3、共同髓系祖细胞和共同淋巴祖细胞)中对单个活细胞进行位置特异性识别。准确率达到 90%以上。我们表明,这种分化阶段识别的准确性基于与细胞生物化学相关的光谱特征。这项工作确立了 PLS-DA 可以在存在潜在的显著群体内光谱变化的情况下,捕捉多达六个密切相关的细胞群体之间的细微光谱变化。这种非侵入性方法可用于筛选生物材料微阵列筛选平台中由外在线索引起的 HSC 命运决定。