Multiplexed, targeted profiling of single-cell proteomes and transcriptomes in a single reaction

We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidig...

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Bibliographic Details
Main Authors: Li, Shuqiang (Author), Darmanis, Spyros (Author), Lundberg, Martin (Author), Fredriksson, Simon (Author), Landegren, Ulf (Author), Gallant, Caroline J. (Author), Livak, Kenneth J. (Author), Genshaft, Alex S. (Contributor), Prakadan, Sanjay (Contributor), Ziegler, Carly (Contributor), Hong, Joyce (Contributor), Regev, Aviv (Contributor), Shalek, Alexander K (Contributor)
Other Authors: Massachusetts Institute of Technology. Institute for Medical Engineering & Science (Contributor), Harvard University- (Contributor), Massachusetts Institute of Technology. Department of Biology (Contributor), Massachusetts Institute of Technology. Department of Chemistry (Contributor), Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science (Contributor), Ragon Institute of MGH, MIT and Harvard (Contributor), Koch Institute for Integrative Cancer Research at MIT (Contributor)
Format: Article
Language:English
Published: BioMed Central, 2016-12-12T21:14:31Z.
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Summary:We present a scalable, integrated strategy for coupled protein and RNA detection from single cells. Our approach leverages the DNA polymerase activity of reverse transcriptase to simultaneously perform proximity extension assays and complementary DNA synthesis in the same reaction. Using the Fluidigm C1™ system, we profile the transcriptomic and proteomic response of a human breast adenocarcinoma cell line to a chemical perturbation, benchmarking against in situ hybridizations and immunofluorescence staining, as well as recombinant proteins, ERCC Spike-Ins, and population lysate dilutions. Through supervised and unsupervised analyses, we demonstrate synergies enabled by simultaneous measurement of single-cell protein and RNA abundances. Collectively, our generalizable approach highlights the potential for molecular metadata to inform highly-multiplexed single-cell analyses.
Searle Scholars Program
Arnold and Mabel Beckman Foundation. Beckman Young Investigator
National Institutes of Health (U.S.) (Center for Excellence in Genomic Sciences. Grant P50HG006193)
Klarman Cell Observatory
National Institutes of Health (U.S.) (Grant U24AI11862-01)
Howard Hughes Medical Institute
National Institute of General Medical Sciences (U.S.) (Award T32GM007753)
National Institutes of Health (U.S.) (New Innovator Award DP2OD020839)