Single-cell protein-mRNA correlation analysis enabled by multiplexed dual-analyte co-detection

• Published in: Scientific reports Vol. 7; no. 1; pp. 2776 - 8
• Main Authors: Gong, Haibiao, Wang, Xiaohui, Liu, Benjamin, Boutet, Stephane, Holcomb, Ilona, Dakshinamoorthy, Gajalakshmi, Ooi, Aik, Sanada, Chad, Sun, Gang, Ramakrishnan, Ramesh
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 05.06.2017; Nature Publishing Group; Nature Portfolio
• Subjects: 38; 38/39; 38/62; 38/77; 45; 631/1647/2017; 631/1647/2067; 82; 82/80; 96/1; Biomarkers; Cell Line; Correlation analysis; Deoxyribonucleic acid; DNA; Gene expression; Gene Expression Profiling - methods; Humanities and Social Sciences; Humans; multidisciplinary; Proteins; Proteins - metabolism; Proteomics - methods; Real-Time Polymerase Chain Reaction; Reverse transcription; RNA, Messenger - genetics; RNA, Messenger - metabolism; Science; Science (multidisciplinary); Single-Cell Analysis - methods; Single-cell protein
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-017-03057-5

We have investigated the correlation between proteins and mRNAs in single cells employing an integrated workflow for dual-analyte co-detection. This is achieved by combining the oligo extension reaction (OER), which converts protein levels to DNA levels, with reverse transcription for mRNA detection. Unsupervised gene expression profiling analysis, including principal component analysis and hierarchical clustering, revealed different aspects of the protein-mRNA relationship. Violin plot analysis showed that some genes exhibited similar distribution patterns for proteins and mRNAs. We also demonstrate that cells can be separated into subpopulations based on their protein-mRNA expression profiles, and that different subpopulations have distinct correlation coefficient values. Our results demonstrated that integrated investigations of mRNA and protein levels in single cells allows comprehensive analysis not attainable at bulk levels.