Disease-Relevant Single Cell Photonic Signatures Identify S100β Stem Cells and their Myogenic Progeny in Vascular Lesions.
Disease-Relevant Single Cell Photonic Signatures Identify S100β Stem Cells and their Myogenic Progeny in Vascular Lesions.
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DOI：
10.1007/s12015-021-10125-x
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发表时间：
2021-10
影响因子：
4.8
通讯作者：
Cahill PA
中科院分区：
文献类型：
--
作者：
Molony C;King D;Di Luca M;Kitching M;Olayinka A;Hakimjavadi R;Julius LAN;Fitzpatrick E;Gusti Y;Burtenshaw D;Healy K;Finlay EK;Kernan D;Llobera A;Liu W;Morrow D;Redmond EM;Ducrée J;Cahill PA
亚临床动脉粥样硬化的一个标志是血管平滑肌细胞（SMC）样细胞的积累导致内膜增厚和病变形成。虽然内侧SMCs有助于血管病变，但驻留血管干细胞（vSCs）的参与尚不清楚。我们在体外评估单细胞光子学作为细胞表型的鉴别器，然后使用监督机器学习评估血管病变内vSC的存在，并使用谱系追踪分析进一步验证。利用一种新型的实验室-光盘（负载）平台，研究了正常和损伤血管的无标记单细胞离体光子发射，并与新鲜分离的主动脉SMCs、培养的Movas SMCs、巨噬细胞、b细胞、S100β+ mVSc、骨髓间充质干细胞（MSC）及其各自的肌源性子代进行了比较，波长为λ465 - λ670±20 nm。我们发现，这些图谱具有足够的覆盖范围、特异性和质量，可以清楚地区分不同血管床（颈动脉与主动脉）的内侧SMCs，在体外流动限制下区分正常颈动脉内侧SMCs与病变SMCs样细胞，并通过多变量分析确定转化生长因子β1 （TGF- β1）、Notch配体Jagged1和Sonic Hedgehog处理后一系列多能干细胞的SMC分化。由于光子发射增强胶原III和弹性蛋白的表达。监督式机器学习支持S100β+ vSCs的遗传谱系追踪分析，并在血管病变中发现了S100β+ vsc衍生的肌源性后代。我们认为与疾病相关的光子特征可能对血管疾病具有预测价值。在线版本包含补充资料，网址为10.1007/s12015-021-10125-x。
A hallmark of subclinical atherosclerosis is the accumulation of vascular smooth muscle cell (SMC)-like cells leading to intimal thickening and lesion formation. While medial SMCs contribute to vascular lesions, the involvement of resident vascular stem cells (vSCs) remains unclear. We evaluated single cell photonics as a discriminator of cell phenotype in vitro before the presence of vSC within vascular lesions was assessed ex vivo using supervised machine learning and further validated using lineage tracing analysis. Using a novel lab-on-a-Disk(Load) platform, label-free single cell photonic emissions from normal and injured vessels ex vivo were interrogated and compared to freshly isolated aortic SMCs, cultured Movas SMCs, macrophages, B-cells, S100β+ mVSc, bone marrow derived mesenchymal stem cells (MSC) and their respective myogenic progeny across five broadband light wavelengths (λ465 - λ670 ± 20 nm). We found that profiles were of sufficient coverage, specificity, and quality to clearly distinguish medial SMCs from different vascular beds (carotid vs aorta), discriminate normal carotid medial SMCs from lesional SMC-like cells ex vivo following flow restriction, and identify SMC differentiation of a series of multipotent stem cells following treatment with transforming growth factor beta 1 (TGF- β1), the Notch ligand Jagged1, and Sonic Hedgehog using multivariate analysis, in part, due to photonic emissions from enhanced collagen III and elastin expression. Supervised machine learning supported genetic lineage tracing analysis of S100β+ vSCs and identified the presence of S100β+vSC-derived myogenic progeny within vascular lesions. We conclude disease-relevant photonic signatures may have predictive value for vascular disease. The online version contains supplementary material available at 10.1007/s12015-021-10125-x.
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影响因子：
48
作者：
Buggenthin F;Buettner F;Hoppe PS;Endele M;Kroiss M;Strasser M;Schwarzfischer M;Loeffler D;Kokkaliaris KD;Hilsenbeck O;Schroeder T;Theis FJ;Marr C
通讯作者：
Marr C
内皮 TGF-β 信号传导驱动血管炎症和动脉粥样硬化
影响因子：
20.8
作者：
Chen, Pei-Yu;Qin, Lingfeng;Simons, Michael
通讯作者：
Simons, Michael
DOI：
10.1016/j.bbrc.2014.10.092
发表时间：
2014-11-07
影响因子：
3.1
作者：
Gao, Fu;Chambon, Pierre;Li, Wei
通讯作者：
Li, Wei
影响因子：
3.4
作者：
Gunaratne, Rajitha;Monteath, Isaac;Fick, Daniel
通讯作者：
Fick, Daniel
影响因子：
4.6
作者：
Esner, M;Meilhac, SM;Buckingham, ME
通讯作者：
Buckingham, ME