A novel microfluidic flow-cytometry for counting numbers of single-cell β-actins  

作　　者：Lixing Liu Beiyuan Fan Hongyu Yang Deyong Chen Shuang Zhang Junbo Wang Jian Chen 

机构地区：[1]State Key Laboratory of Transducer Technology,Aerospace Information Research Institute,Chinese Academy of Sciences,Beijing 100190,China [2]School of Electronic,Electrical and Communication Engineering,University of Chinese Academy of Sciences,Beijing 100049,China [3]School of Future Technology,University of Chinese Academy of Sciences,Beijing 100049,China [4]Research Center for Eco-Environmental Sciences,Chinese Academy of Sciences,Beijing 100085,China

出　　处：《Nanotechnology and Precision Engineering》2020年第3期156-161,共6页纳米技术与精密工程（英文）

摘　　要：As a house keeping protein with stable expressions, β-actin is used as a loading control in normalization of western blotting. However, the actual numbers of β-actins at the single-cell level remain elusive. Based on a homedeveloped flow cytometry, single-cell numbers of β-actin from 8 cell types(subtypes) and 2 tumour patient samples were quantified as 9.62 ± 4.29 × 105(A549, Ncell= 14,242), 6.46 ± 3.34 × 105(Hep G2, Ncell= 35,932),1.58 ± 0.90 × 106(MCF 10 A, N6 cell= 16,650), 1.08 ± 0.48 × 10(HeLa, Ncell= 26,151), 7.60 ± 4.34 × 105(PC3, Ncell= 11,922), 1.10 ± 0.72 × 106(SACC-83, Ncell= 13,616), 8.58 ± 4.54 × 105(CAL 27, Ncell= 7271),9.00 ± 4.69 × 105(CAL 27-LN2, Ncell= 6222), 8.26 ± 4.48 × 105(Oral Tumour Patient I, Ncell= 359), and8.19 ± 5.12 × 105(Oral Tumour Patient II, Ncell= 175), and were analyzed by statistical approaches including one-way analysis of variance, neural network based pattern recognition and Bayesian estimation, with varied expressions of β-actins among different cell types located. The dataset reported in this study may serve as a reference in future studies of quantitative protein analysis.

关 键 词：Single-cellβ-actin quantification Cell line and subset Tumour sample Large dataset Statistical analysis 

分 类 号：Q26[生物学—细胞生物学]