Dual transcript and protein quantification in a massive single cell array

Seung-min Park; Jae Young Lee; Soongweon Hong; Sang Hun Lee; Ivan K. Dimov; Hojae Lee; Susie Suh; Qiong Pan; Keyu Li; Anna M. Wu; Shannon M. Mumenthaler; Parag Mallick; Luke P. Lee

doi:10.1039/C6LC00762G

Dual transcript and protein quantification in a massive single cell array†‡

Seung-min Park,^abcj Jae Young Lee,^ab Soongweon Hong,^ab Sang Hun Lee,^ab Ivan K. Dimov,^a Hojae Lee,^a Susie Suh,^d Qiong Pan,^ab Keyu Li,^e Anna M. Wu,^e Shannon M. Mumenthaler,^f Parag Mallick*^cg and Luke P. Lee*^abhi

Author affiliations

* Corresponding authors

^a Department of Bioengineering, University of California, Berkeley, California, USA
E-mail: lplee@berkeley.edu

^b Berkeley Sensor & Actuator Center, University of California, Berkeley, California, USA

^c Department of Radiology, Stanford University School of Medicine, Stanford, California, USA
E-mail: paragm@stanford.edu

^d Department of Pharmacology, School of Medicine, Case Western Reserve University School of Medicine, Cleveland, Ohio, USA

^e Crump Institute for Molecular Imaging, Department of Molecular and Medical Pharmacology, David Geffen School of Medicine at UCLA, Los Angeles, California, USA

^f Lawrence J. Ellison Institute for Transformative Medicine, University of Southern California, Los Angeles, California, USA

^g Canary Center at Stanford for Cancer Early Detection, Stanford University School of Medicine, Palo Alto, California, USA

^h Department of Electrical Engineering & Computer Sciences, University of California, Berkeley, California, USA

ⁱ Biophysics Graduate Program, University of California, Berkeley, California, USA

^j Molecular Imaging Program at Stanford, Stanford University School of Medicine, Stanford, California, USA

Abstract

Recently, single-cell molecular analysis has been leveraged to achieve unprecedented levels of biological investigation. However, a lack of simple, high-throughput single-cell methods has hindered in-depth population-wide studies with single-cell resolution. We report a microwell-based cytometric method for simultaneous measurements of gene and protein expression dynamics in thousands of single cells. We quantified the regulatory effects of transcriptional and translational inhibitors on cMET mRNA and cMET protein in cell populations. We studied the dynamic responses of individual cells to drug treatments, by measuring cMET overexpression levels in individual non-small cell lung cancer (NSCLC) cells with induced drug resistance. Across NSCLC cell lines with a given protein expression, distinct patterns of transcript–protein correlation emerged. We believe this platform is applicable for interrogating the dynamics of gene expression, protein expression, and translational kinetics at the single-cell level – a paradigm shift in life science and medicine toward discovering vital cell regulatory mechanisms.

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Dual transcript and protein quantification in a massive single cell array†‡

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Dual transcript and protein quantification in a massive single cell array

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