Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq
- University of California, San Francisco, United States
- National Institute of Allergy and Infectious Diseases, United States
- Karolinska Institute, Sweden
- Rockefeller University, United States
- Stanford University, United States
- University of California, San Diego, United States
- Seattle Children's Research Institute, United States
Abstract
Phage Immunoprecipitation-Sequencing (PhIP-Seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-Seq for autoantigen discovery, including our previous work (Vazquez et al. 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki Disease (KD), Multisystem Inflammatory Syndrome in Children (MIS-C), and finally, mild and severe forms of COVID19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as PDYN in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in 2 patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-Seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID19, including the endosomal protein EEA1. Together, scaled PhIP-Seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.
Data availability
Full PhIP-Seq data for all cohorts presented is available for download at Dryad at https://doi.org/10.5061/dryad.qfttdz0k4. All available deidentified clinical data for this study is available in Supplemental Table 1.
-
Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-SeqDryad Digital Repository, doi:10.5061/dryad.qfttdz0k4.
Article and author information
Author details
Funding
National Institute of Allergy and Infectious Diseases (5P01AI118688)
- Mark S Anderson
UCSF-CTSI TL1 (TR001871)
- Zoe Quandt
Division of Intramural Research, National Institute of Allergy and Infectious Diseases (1 ZIA AI001222)
- Luigi D Notarangelo
National Institute of Child Health and Development (1R61HD105590)
- Adriana Tremoulet
- Jane C Burns
Multiple sources**
- Jean-Laurent Casanova
FRM (EA20170638020)
- Paul Bastard
MD-PhD program of the Imagine Institute
- Paul Bastard
National Institute of Allergy and Infectious Diseases (1ZIAAI001175)
- Michail S Lionakis
National Institute of Diabetes and Digestive and Kidney Diseases (1F30DK123915)
- Sara E Vazquez
Chan Zuckerberg Biohub
- Joseph L DeRisi
Parker Institute for Cancer Immunotherapy
- Mark S Anderson
Juvenile Diabetes Research Foundation United States of America
- Mark S Anderson
Helmsley Charitable Trust
- Mark S Anderson
National Institute of General Medical Sciences (5T32GM007618)
- Mark S Anderson
American Diabetes Association (1-19-PDF-131)
- Zoe Quandt
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.**multiple sources includes: The Laboratory of Human Genetics of Infectious Diseases is supported by the Howard Hughes Medical Institute, the Rockefeller University, the St. Giles Foundation, the National Institutes of Health (NIH) (R01AI088364 and R01AI163029), the National Center for Advancing Translational Sciences (NCATS), NIH Clinical and Translational Science Award (CTSA) program (UL1TR001866), the Fisher Center for Alzheimer's Research Foundation, the Meyer Foundation, the JPB Foundation, the French National Research Agency (ANR) under the Investments for the Future" program (ANR-10-IAHU-01)
Ethics
Human subjects: Detailed information on consent, where applicable, is available in the methods section of the manuscript.
Copyright
This is an open-access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 public domain dedication.
Metrics
-
- 2,397
- views
-
- 353
- downloads
-
- 33
- citations
Views, downloads and citations are aggregated across all versions of this paper published by eLife.
Download links
A two-part list of links to download the article, or parts of the article, in various formats.
Downloads (link to download the article as PDF)
Open citations (links to open the citations from this article in various online reference manager services)
Cite this article (links to download the citations from this article in formats compatible with various reference manager tools)
Autoantibody discovery across monogenic, acquired, and COVID19-associated autoimmunity with scalable PhIP-Seq
eLife 11:e78550.
https://doi.org/10.7554/eLife.78550
Further reading
-
- Immunology and Inflammation
Macrophages control intracellular pathogens like Salmonella by using two caspase enzymes at different times during infection.
-
- Immunology and Inflammation
- Microbiology and Infectious Disease
The members of the Mycobacterium tuberculosis complex (MTBC) causing human tuberculosis comprise 10 phylogenetic lineages that differ in their geographical distribution. The human consequences of this phylogenetic diversity remain poorly understood. Here, we assessed the phenotypic properties at the host-pathogen interface of 14 clinical strains representing five major MTBC lineages. Using a human in vitro granuloma model combined with bacterial load assessment, microscopy, flow cytometry, and multiplexed-bead arrays, we observed considerable intra-lineage diversity. Yet, modern lineages were overall associated with increased growth rate and more pronounced granulomatous responses. MTBC lineages exhibited distinct propensities to accumulate triglyceride lipid droplets—a phenotype associated with dormancy—that was particularly pronounced in lineage 2 and reduced in lineage 3 strains. The most favorable granuloma responses were associated with strong CD4 and CD8 T cell activation as well as inflammatory responses mediated by CXCL9, granzyme B, and TNF. Both of which showed consistent negative correlation with bacterial proliferation across genetically distant MTBC strains of different lineages. Taken together, our data indicate that different virulence strategies and protective immune traits associate with MTBC genetic diversity at lineage and strain level.
