Abstract
Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.
Original language | English |
---|---|
Pages (from-to) | 604-617 |
Number of pages | 14 |
Journal | Nature Methods |
Volume | 18 |
Issue number | 6 |
DOIs | |
Publication status | Published - Jun 2021 |
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In: Nature Methods, Vol. 18, No. 6, 06.2021, p. 604-617.
Research output: Contribution to journal › Review article › peer-review
TY - JOUR
T1 - The emerging landscape of single-molecule protein sequencing technologies
AU - Alfaro, Javier Antonio
AU - Bohländer, Peggy
AU - Dai, Mingjie
AU - Filius, Mike
AU - Howard, Cecil J.
AU - van Kooten, Xander F.
AU - Ohayon, Shilo
AU - Pomorski, Adam
AU - Schmid, Sonja
AU - Aksimentiev, Aleksei
AU - Anslyn, Eric V.
AU - Bedran, Georges
AU - Cao, Chan
AU - Chinappi, Mauro
AU - Coyaud, Etienne
AU - Dekker, Cees
AU - Dittmar, Gunnar
AU - Drachman, Nicholas
AU - Eelkema, Rienk
AU - Goodlett, David
AU - Hentz, Sébastien
AU - Kalathiya, Umesh
AU - Kelleher, Neil L.
AU - Kelly, Ryan T.
AU - Kelman, Zvi
AU - Kim, Sung Hyun
AU - Kuster, Bernhard
AU - Rodriguez-Larrea, David
AU - Lindsay, Stuart
AU - Maglia, Giovanni
AU - Marcotte, Edward M.
AU - Marino, John P.
AU - Masselon, Christophe
AU - Mayer, Michael
AU - Samaras, Patroklos
AU - Sarthak, Kumar
AU - Sepiashvili, Lusia
AU - Stein, Derek
AU - Wanunu, Meni
AU - Wilhelm, Mathias
AU - Yin, Peng
AU - Meller, Amit
AU - Joo, Chirlmin
N1 - Funding Information: We thank all the presenting delegates of the 2019 Single-Molecule Protein Sequencing conference (Jerusalem). We thank the PL-Grid and CI-TASK Infrastructure, Poland, for providing their hardware and software resources. S.S. acknowledges Postdoc Mobility fellowship no. P400PB 180889 from the Swiss National Science Foundation. E.M.M. and E.V.A. acknowledge funding from the NIH (R35 GM122480 and R01 DK110520 to E.M.M.), Welch Foundation (F1515 to E.M.M. and F-0046 to E.V.A.), Army Research Office grant W911NF-12-1-0390 and Erisyon. E.M.M. and E.V.A. are co-founders and shareholders of Erisyon. R.T.K. acknowledges funding from NIGMS (R01 GM138931). P.Y. acknowledges funding from an NIH Director’s New Innovator Award (1DP2OD007292), an NIH Transformative Research Award (1R01EB018659), an NIH Pioneer Award (1DP1GM133052), and the Molecular Robotics Initiative fund at the Wyss Institute for Biologically Inspired Engineering. M.D. acknowledges funding from a Systems Biology Department Fellowship from Harvard Medical School and a Technology Development Fellowship from Wyss Institute for Biologically Inspired Engineering. C.C. acknowledges the Peter and Traudl Engelhorn Foundation. C.D. acknowledges the ERC Advanced Grant Looping DNA (no. 883684) and the NWO programs NanoFront and Basyc. E.M.M., E.V.A. and C.J.H. are co-inventors on patents relevant to this work. S.O. acknowledges the support of the Azrieli fellowship foundation. N.L.K. acknowledges funding from the Paul G. Allen Frontiers Program (11715), the NIH HuBMAP program (UH3 CA246635) and NIGMS (P41 GM108569). J.P.M. and Z.K. acknowledge internal funding from NIST and are co-inventors on patents relevant to this work. M. Wanunu acknowledges funding from the NIH (HG009186). K.S. and A.A. acknowledge funding from the NSF (PHY-1430124). C.J., C.D. and R.E. acknowledge funding from NWO-I (SMPS). C.J. acknowledges funding from HFSP (RGP0026/2019). A.P. acknowledges Bekker fellowship no. PPN/BEK/2018/1/00296 from the Polish National Agency for Academic Exchange. C.M. and S.H. acknowledge funding from the European Research Council (ERC ‘Enlightened’, GA 616251) and the CEA Transverse Program ‘Instrumentation and Detection’ (PTC-ID VIRIONEMS). Support from the Proteomics French Infrastructure (PROFI) is also gratefully acknowledged. G.D. acknowledges funding from FNR (C17/BM/11642138). M.M. acknowledges funding from the Adolphe Merkle Foundation, the Michael J. Fox Foundation for Parkinson’s Research (grant 17924) and the Swiss National Science Foundation (grant no. 200021-169304). A.M. acknowledges funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 833399-ERC NanoProt-ID and ISF award 3485/19. M.C. acknowledges computational resources from CINECA (NATWE project) and the Swiss National Super-Computing Centre (CSCS), under projects sm11 and s865. E.C. acknowledges funding from I-Site Lille, Région Hauts-de-France, and the European Union’s Horizon 2020 Marie Skłodowska-Curie no. 843052. The study was supported by the project ‘International Centre for Cancer Vaccine Science’ that is carried out within the International Agendas Programme of the Foundation for Polish Science co-financed by the European Union under the European Regional Development Fund. D.G. thanks Genome Canada and Genome British Columbia for financial support for Genomics Technology Platforms (GTP) funding for operations and technology development (264PRO). We thank V. Globyte for critical reading. Publisher Copyright: © 2021, Springer Nature America, Inc.
PY - 2021/6
Y1 - 2021/6
N2 - Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.
AB - Single-cell profiling methods have had a profound impact on the understanding of cellular heterogeneity. While genomes and transcriptomes can be explored at the single-cell level, single-cell profiling of proteomes is not yet established. Here we describe new single-molecule protein sequencing and identification technologies alongside innovations in mass spectrometry that will eventually enable broad sequence coverage in single-cell profiling. These technologies will in turn facilitate biological discovery and open new avenues for ultrasensitive disease diagnostics.
UR - http://www.scopus.com/inward/record.url?scp=85107573284&partnerID=8YFLogxK
U2 - 10.1038/s41592-021-01143-1
DO - 10.1038/s41592-021-01143-1
M3 - Review article
C2 - 34099939
AN - SCOPUS:85107573284
SN - 1548-7091
VL - 18
SP - 604
EP - 617
JO - Nature Methods
JF - Nature Methods
IS - 6
ER -