Unbiased discovery of autoantibodies associated with severe COVID-19 via genome-scale self-assembled DNA-barcoded protein libraries

Joel J. Credle, Jonathan Gunn, Puwanat Sangkhapreecha, Daniel R. Monaco, Xuwen Alice Zheng, Hung Ji Tsai, Azaan Wilbon, William R. Morgenlander, Andre Rastegar, Yi Dong, Sahana Jayaraman, Lorenzo Tosi, Biju Parekkadan, Alan N. Baer, Mario Roederer, Evan M. Bloch, Aaron A.R. Tobian, Israel Zyskind, Jonathan I. Silverberg, Avi Z. RosenbergAndrea L. Cox, Tom Lloyd, Andrew L. Mammen, H. Benjamin Larman

Research output: Contribution to journalArticlepeer-review


Pathogenic autoreactive antibodies that may be associated with life-threatening coronavirus disease 2019 (COVID-19) remain to be identified. Here, we show that self-assembled genome-scale libraries of full-length proteins covalently coupled to unique DNA barcodes for analysis by sequencing can be used for the unbiased identification of autoreactive antibodies in plasma samples. By screening 11,076 DNA-barcoded proteins expressed from a sequence-verified human ORFeome library, the method, which we named MIPSA (for Molecular Indexing of Proteins by Self-Assembly), allowed us to detect circulating neutralizing type-I and type-III interferon (IFN) autoantibodies in five plasma samples from 55 patients with life-threatening COVID-19. In addition to identifying neutralizing type-I IFN-α and IFN-ω autoantibodies and other previously known autoreactive antibodies in patient plasma, MIPSA enabled the detection of as yet unidentified neutralizing type-III anti-IFN-λ3 autoantibodies that were not seen in healthy plasma samples or in convalescent plasma from ten non-hospitalized individuals with COVID-19. The low cost and simple workflow of MIPSA will facilitate unbiased high-throughput analyses of protein–antibody, protein–protein and protein–small-molecule interactions.

Original languageEnglish (US)
Pages (from-to)992-1003
Number of pages12
JournalNature biomedical engineering
Issue number8
StatePublished - Aug 2022

ASJC Scopus subject areas

  • Bioengineering
  • Biotechnology
  • Biomedical Engineering
  • Medicine (miscellaneous)
  • Computer Science Applications


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