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nELISA: A high-throughput, high-plex platform enables quantitative profiling of the secretome

Milad Dagher, Grant Ongo, Nathaniel Robichaud, Jinglin Kong, Woojong Rho, Ivan Teahulos, Arya Tavakoli, Samantha Bovaird, Shahem Merjaneh, Andrew Tan, Kiran Edwardson, Christelle Scheepers, Andy Ng, Andy Hajjar, Andy Lee, Philippe DeCorwin-Martin, Shafqat Rasool, JiaMin Huang, View ORCID ProfileYu Han, View ORCID ProfileSrinivas Niranj Chandrasekaran, View ORCID ProfileLisa Miller, View ORCID ProfileMaria Kost-Alimova, View ORCID ProfileAdam Skepner, View ORCID ProfileShantanu Singh, Jeffrey Munzar, View ORCID ProfileAnne E. Carpenter, View ORCID ProfileDavid Juncker
doi: https://doi.org/10.1101/2023.04.17.535914
Milad Dagher
1Nomic Bio, Montreal, QC, Canada
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
4Biomedical Engineering Department, McGill University, Montreal, QC, Canada
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  • For correspondence: milad@nomic.bio david.juncker@mcgill.ca
Grant Ongo
1Nomic Bio, Montreal, QC, Canada
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Nathaniel Robichaud
1Nomic Bio, Montreal, QC, Canada
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Jinglin Kong
1Nomic Bio, Montreal, QC, Canada
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
4Biomedical Engineering Department, McGill University, Montreal, QC, Canada
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Woojong Rho
1Nomic Bio, Montreal, QC, Canada
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
4Biomedical Engineering Department, McGill University, Montreal, QC, Canada
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Ivan Teahulos
1Nomic Bio, Montreal, QC, Canada
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
4Biomedical Engineering Department, McGill University, Montreal, QC, Canada
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Arya Tavakoli
1Nomic Bio, Montreal, QC, Canada
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Samantha Bovaird
1Nomic Bio, Montreal, QC, Canada
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Shahem Merjaneh
1Nomic Bio, Montreal, QC, Canada
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Andrew Tan
1Nomic Bio, Montreal, QC, Canada
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Kiran Edwardson
1Nomic Bio, Montreal, QC, Canada
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Christelle Scheepers
1Nomic Bio, Montreal, QC, Canada
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Andy Ng
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
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Andy Hajjar
1Nomic Bio, Montreal, QC, Canada
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Andy Lee
1Nomic Bio, Montreal, QC, Canada
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Philippe DeCorwin-Martin
1Nomic Bio, Montreal, QC, Canada
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Shafqat Rasool
1Nomic Bio, Montreal, QC, Canada
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JiaMin Huang
1Nomic Bio, Montreal, QC, Canada
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Yu Han
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Srinivas Niranj Chandrasekaran
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Lisa Miller
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Maria Kost-Alimova
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Adam Skepner
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Shantanu Singh
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Jeffrey Munzar
1Nomic Bio, Montreal, QC, Canada
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Anne E. Carpenter
2Broad Institute of MIT and Harvard, Cambridge, MA, USA
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David Juncker
3McGill University and Génome Québec Innovation Centre, Montreal, QC, Canada
4Biomedical Engineering Department, McGill University, Montreal, QC, Canada
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  • ORCID record for David Juncker
  • For correspondence: milad@nomic.bio david.juncker@mcgill.ca
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Abstract

We present the nELISA, a miniaturised, high-throughput, and high-fidelity protein profiling platform. DNA oligonucleotides are used to pre-colocalize antibody pairs on spectrally encoded microparticles and perform displacement-mediated detection while ensuring spatial separation between non-cognate antibody pairs. Read-out is performed cost-efficiently and at high-throughput using flow cytometry. We assembled an inflammatory panel of 191 targets that were multiplexed without cross-reactivity or impact to performance vs 1-plex signals, with sensitivities as low as 0.1pg/mL and measurements across the platform spanning 8 orders of magnitude. We then performed a large-scale PBMC secretome screen, with cytokines as both perturbagens and read-outs, measuring 7,392 samples and generating ∼1.5M protein datapoints in under a week, a significant advance in throughput compared to other highly multiplexed immunoassays. We uncovered 447 significant cytokine responses, including multiple putatively novel cytokine responses, that were conserved across donors and stimulation conditions. We also validated its use in phenotypic screening, and proposed applications for the nELISA in drug discovery.

Competing Interest Statement

The Authors declare the following competing interests: N.R., G.O., W.R., I.T., A.T., J.K., J.M., S.B., S.M., A.T., K.E., C.S., A.N., A.H., A.L., P.D.M., S.R., J.H. and M.D. are employees and have ownership interest in Nomic Bio, which markets the nELISA platform, D.J. has ownership interest in Nomic Bio. S.S. and A.E.C. serve as scientific advisors for companies that use image-based profiling and Cell Painting (A.E.C: Recursion, S.S.:Waypoint Bio, Dewpoint Therapeutics) and receive honoraria for occasional talks at pharmaceutical and biotechnology companies. All other authors declare no competing interests.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted April 18, 2023.
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nELISA: A high-throughput, high-plex platform enables quantitative profiling of the secretome
Milad Dagher, Grant Ongo, Nathaniel Robichaud, Jinglin Kong, Woojong Rho, Ivan Teahulos, Arya Tavakoli, Samantha Bovaird, Shahem Merjaneh, Andrew Tan, Kiran Edwardson, Christelle Scheepers, Andy Ng, Andy Hajjar, Andy Lee, Philippe DeCorwin-Martin, Shafqat Rasool, JiaMin Huang, Yu Han, Srinivas Niranj Chandrasekaran, Lisa Miller, Maria Kost-Alimova, Adam Skepner, Shantanu Singh, Jeffrey Munzar, Anne E. Carpenter, David Juncker
bioRxiv 2023.04.17.535914; doi: https://doi.org/10.1101/2023.04.17.535914
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nELISA: A high-throughput, high-plex platform enables quantitative profiling of the secretome
Milad Dagher, Grant Ongo, Nathaniel Robichaud, Jinglin Kong, Woojong Rho, Ivan Teahulos, Arya Tavakoli, Samantha Bovaird, Shahem Merjaneh, Andrew Tan, Kiran Edwardson, Christelle Scheepers, Andy Ng, Andy Hajjar, Andy Lee, Philippe DeCorwin-Martin, Shafqat Rasool, JiaMin Huang, Yu Han, Srinivas Niranj Chandrasekaran, Lisa Miller, Maria Kost-Alimova, Adam Skepner, Shantanu Singh, Jeffrey Munzar, Anne E. Carpenter, David Juncker
bioRxiv 2023.04.17.535914; doi: https://doi.org/10.1101/2023.04.17.535914

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