1
|
Grant-McAuley W, Morgenlander WR, Ruczinski I, Kammers K, Laeyendecker O, Hudelson SE, Thakar M, Piwowar-Manning E, Clarke W, Breaud A, Ayles H, Bock P, Moore A, Kosloff B, Shanaube K, Meehan SA, van Deventer A, Fidler S, Hayes R, Larman HB, Eshleman SH. Identification of antibody targets associated with lower HIV viral load and viremic control. PLoS One 2024; 19:e0305976. [PMID: 39288118 PMCID: PMC11407625 DOI: 10.1371/journal.pone.0305976] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2024] [Accepted: 06/09/2024] [Indexed: 09/19/2024] Open
Abstract
BACKGROUND High HIV viral loads (VL) are associated with increased morbidity, mortality, and on-going transmission. HIV controllers maintain low VLs in the absence of antiretroviral therapy (ART). We previously used a massively multiplexed antibody profiling assay (VirScan) to compare antibody profiles in HIV controllers and persons living with HIV (PWH) who were virally suppressed on ART. In this report, we used VirScan to evaluate whether antibody reactivity to specific HIV targets and broad reactivity across the HIV genome was associated with VL and controller status 1-2 years after infection. METHODS Samples were obtained from participants who acquired HIV infection in a community-randomized trial in Africa that evaluated an integrated strategy for HIV prevention (HPTN 071 PopART). Controller status was determined using VL and antiretroviral (ARV) drug data obtained at the seroconversion visit and 1 year later. Viremic controllers had VLs <2,000 copies/mL at both visits; non-controllers had VLs >2,000 copies/mL at both visits. Both groups had no ARV drugs detected at either visit. VirScan testing was performed at the second HIV-positive visit (1-2 years after HIV infection). RESULTS The study cohort included 13 viremic controllers and 64 non-controllers. We identified ten clusters of homologous peptides that had high levels of antibody reactivity (three in gag, three in env, two in integrase, one in protease, and one in vpu). Reactivity to 43 peptides (eight unique epitopes) in six of these clusters was associated with lower VL; reactivity to six of the eight epitopes was associated with HIV controller status. Higher aggregate antibody reactivity across the eight epitopes (more epitopes targeted, higher mean reactivity across all epitopes) and across the HIV genome was also associated with lower VL and controller status. CONCLUSIONS We identified HIV antibody targets associated with lower VL and HIV controller status 1-2 years after infection. Robust aggregate responses to these targets and broad antibody reactivity across the HIV genome were also associated with lower VL and controller status. These findings provide novel insights into the relationship between humoral immunity and viral containment that could help inform the design of antibody-based approaches for reducing HIV VL.
Collapse
Affiliation(s)
- Wendy Grant-McAuley
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - William R. Morgenlander
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, United States of America
| | - Kai Kammers
- Quantitative Sciences Division, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Sarah E. Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Manjusha Thakar
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Estelle Piwowar-Manning
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - William Clarke
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Autumn Breaud
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Helen Ayles
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Peter Bock
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Ayana Moore
- FHI 360, Durham, North Carolina, United States of America
| | - Barry Kosloff
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Kwame Shanaube
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
| | - Sue-Ann Meehan
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Anneen van Deventer
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Stellenbosch, Western Cape, South Africa
| | - Sarah Fidler
- Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Richard Hayes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - H. Benjamin Larman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | - Susan H. Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America
| | | |
Collapse
|
2
|
Huang Z, Gunarathne SMS, Liu W, Zhou Y, Jiang Y, Li S, Huang J. PhIP-Seq: methods, applications and challenges. FRONTIERS IN BIOINFORMATICS 2024; 4:1424202. [PMID: 39295784 PMCID: PMC11408297 DOI: 10.3389/fbinf.2024.1424202] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2024] [Accepted: 08/22/2024] [Indexed: 09/21/2024] Open
Abstract
Phage-immunoprecipitation sequencing (PhIP-Seq) technology is an innovative, high-throughput antibody detection method. It enables comprehensive analysis of individual antibody profiles. This technology shows great potential, particularly in exploring disease mechanisms and immune responses. Currently, PhIP-Seq has been successfully applied in various fields, such as the exploration of biomarkers for autoimmune diseases, vaccine development, and allergen detection. A variety of bioinformatics tools have facilitated the development of this process. However, PhIP-Seq technology still faces many challenges and has room for improvement. Here, we review the methods, applications, and challenges of PhIP-Seq and discuss its future directions in immunological research and clinical applications. With continuous progress and optimization, PhIP-Seq is expected to play an even more important role in future biomedical research, providing new ideas and methods for disease prevention, diagnosis, and treatment.
Collapse
Affiliation(s)
- Ziru Huang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | | | - Wenwen Liu
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuwei Zhou
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Yuqing Jiang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Shiqi Li
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
| | - Jian Huang
- School of Life Science and Technology, University of Electronic Science and Technology of China, Chengdu, China
- School of Healthcare Technology, Chengdu Neusoft University, Chengdu, China
| |
Collapse
|
3
|
Sundell GN, Tao SC. Phage Immunoprecipitation and Sequencing-a Versatile Technique for Mapping the Antibody Reactome. Mol Cell Proteomics 2024; 23:100831. [PMID: 39168282 PMCID: PMC11417174 DOI: 10.1016/j.mcpro.2024.100831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/10/2024] [Revised: 08/13/2024] [Accepted: 08/16/2024] [Indexed: 08/23/2024] Open
Abstract
Characterizing the antibody reactome for circulating antibodies provide insight into pathogen exposure, allergies, and autoimmune diseases. This is important for biomarker discovery, clinical diagnosis, and prognosis of disease progression, as well as population-level insights into the immune system. The emerging technology phage display immunoprecipitation and sequencing (PhIP-seq) is a high-throughput method for identifying antigens/epitopes of the antibody reactome. In PhIP-seq, libraries with sequences of defined lengths and overlapping segments are bioinformatically designed using naturally occurring proteins and cloned into phage genomes to be displayed on the surface. These libraries are used in immunoprecipitation experiments of circulating antibodies. This can be done with parallel samples from multiple sources, and the DNA inserts from the bound phages are barcoded and subjected to next-generation sequencing for hit determination. PhIP-seq is a powerful technique for characterizing the antibody reactome that has undergone rapid advances in recent years. In this review, we comprehensively describe the history of PhIP-seq and discuss recent advances in library design and applications.
Collapse
Affiliation(s)
- Gustav N Sundell
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China
| | - Sheng-Ce Tao
- Shanghai Center for Systems Biomedicine, Key Laboratory of Systems Biomedicine (Ministry of Education), Shanghai Jiao Tong University, Shanghai, China.
| |
Collapse
|
4
|
Guenthoer J, Garrett ME, Lilly M, Depierreux DM, Ruiz F, Chi M, Stoddard CI, Chohan V, Yaffe ZA, Sung K, Ralph D, Chu HY, Matsen FA, Overbaugh J. The S2 subunit of spike encodes diverse targets for functional antibody responses to SARS-CoV-2. PLoS Pathog 2024; 20:e1012383. [PMID: 39093891 PMCID: PMC11324185 DOI: 10.1371/journal.ppat.1012383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/27/2024] [Revised: 08/14/2024] [Accepted: 07/01/2024] [Indexed: 08/04/2024] Open
Abstract
The SARS-CoV-2 virus responsible for the COVID-19 global pandemic has exhibited a striking capacity for viral evolution that drives continued evasion from vaccine and infection-induced immune responses. Mutations in the receptor binding domain of the S1 subunit of the spike glycoprotein have led to considerable escape from antibody responses, reducing the efficacy of vaccines and monoclonal antibody (mAb) therapies. Therefore, there is a need to interrogate more constrained regions of spike, such as the S2 subdomain. Here, we present a collection of S2 mAbs from two SARS-CoV-2 convalescent individuals that target multiple regions in S2, including regions outside of those commonly reported. One of the S2 mAbs, C20.119, which bound to a highly conserved epitope in the fusion peptide, was able to broadly neutralize across SARS-CoV-2 variants, SARS-CoV-1, and closely related zoonotic sarbecoviruses. The majority of the mAbs were non-neutralizing; however, many of them could mediate antibody-dependent cellular cytotoxicity (ADCC) at levels similar to the S1-targeting mAb S309 that was previously authorized for treatment of SARS-CoV-2 infections. Several of the mAbs with ADCC function also bound to spike trimers from other human coronaviruses (HCoVs), such as MERS-CoV and HCoV-HKU1. Our findings suggest S2 mAbs can target diverse epitopes in S2, including functional mAbs with HCoV and sarbecovirus breadth that likely target functionally constrained regions of spike. These mAbs could be developed for potential future pandemics, while also providing insight into ideal epitopes for eliciting a broad HCoV response.
Collapse
Affiliation(s)
- Jamie Guenthoer
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Meghan E. Garrett
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Michelle Lilly
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Delphine M. Depierreux
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Felicitas Ruiz
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Margaret Chi
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Caitlin I. Stoddard
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Vrasha Chohan
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Zak A. Yaffe
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Kevin Sung
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Duncan Ralph
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| | - Helen Y. Chu
- Division of Allergy and Infectious Diseases, University of Washington, Seattle, Washington, United States of America
| | - Frederick A. Matsen
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Howard Hughes Medical Institute, Seattle, Washington, United States of America
| | - Julie Overbaugh
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, Washington, United States of America
| |
Collapse
|
5
|
Liebhoff AM, Venkataraman T, Morgenlander WR, Na M, Kula T, Waugh K, Morrison C, Rewers M, Longman R, Round J, Elledge S, Ruczinski I, Langmead B, Larman HB. Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn. Nat Commun 2024; 15:1577. [PMID: 38383452 PMCID: PMC10881494 DOI: 10.1038/s41467-024-45601-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 01/26/2024] [Indexed: 02/23/2024] Open
Abstract
We investigate a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To cover large antigenic spaces, we develop Dolphyn, a method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn compresses the size of a peptide library by 78% compared to traditional tiling, increasing the antibody-reactive peptides from 10% to 31%. We find that the immune system develops antibodies to human gut bacteria-infecting viruses, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.
Collapse
Affiliation(s)
- Anna-Maria Liebhoff
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Institute of Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Thiagarajan Venkataraman
- Institute of Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - William R Morgenlander
- Institute of Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Miso Na
- Institute of Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Tomasz Kula
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA, USA
| | - Kathleen Waugh
- Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO, USA
| | - Charles Morrison
- Behavioral, Clinical and Epidemiologic Sciences, FHI 360, Durham, NC, USA
| | - Marian Rewers
- Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, CO, USA
| | - Randy Longman
- Jill Roberts Institute for Research in IBD, Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - June Round
- Department of Pathology, Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Stephen Elledge
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Ben Langmead
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - H Benjamin Larman
- Institute of Cell Engineering, Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA.
| |
Collapse
|
6
|
Galloway JG, Sung K, Minot SS, Garrett ME, Stoddard CI, Willcox AC, Yaffe ZA, Yucha R, Overbaugh J, Matsen FA. phippery: a software suite for PhIP-Seq data analysis. Bioinformatics 2023; 39:btad583. [PMID: 37740324 PMCID: PMC10547927 DOI: 10.1093/bioinformatics/btad583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2022] [Revised: 08/14/2023] [Accepted: 09/20/2023] [Indexed: 09/24/2023] Open
Abstract
SUMMARY We present the phippery software suite for analyzing data from phage display methods that use immunoprecipitation and deep sequencing to capture antibody binding to peptides, often referred to as PhIP-Seq. It has three main components that can be used separately or in conjunction: (i) a Nextflow pipeline, phip-flow, to process raw sequencing data into a compact, multidimensional dataset format and allows for end-to-end automation of reproducible workflows. (ii) a Python API, phippery, which provides interfaces for tasks such as count normalization, enrichment calculation, multidimensional scaling, and more, and (iii) a Streamlit application, phip-viz, as an interactive interface for visualizing the data as a heatmap in a flexible manner. AVAILABILITY AND IMPLEMENTATION All software packages are publicly available under the MIT License. The phip-flow pipeline: https://github.com/matsengrp/phip-flow. The phippery library: https://github.com/matsengrp/phippery. The phip-viz Streamlit application: https://github.com/matsengrp/phip-viz.
Collapse
Affiliation(s)
- Jared G Galloway
- Computational Biology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Kevin Sung
- Computational Biology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Samuel S Minot
- Data Core, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Meghan E Garrett
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
| | - Caitlin I Stoddard
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Alexandra C Willcox
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
- Medical Scientist Training Program, University of Washington, Seattle, WA 98195, USA
| | - Zak A Yaffe
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Molecular and Cellular Biology Program, University of Washington, Seattle, WA 98195, USA
- Medical Scientist Training Program, University of Washington, Seattle, WA 98195, USA
| | - Ryan Yucha
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Department of Microbiology, University of Washington School of Medicine, Seattle, WA 98195, USA
| | - Julie Overbaugh
- Computational Biology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Human Biology Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
| | - Frederick A Matsen
- Computational Biology, Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA 98109, USA
- Howard Hughes Medical Institute, Seattle, WA, 98109, USA
| |
Collapse
|
7
|
Grant-McAuley W, Morgenlander W, Hudelson SE, Thakar M, Piwowar-Manning E, Clarke W, Breaud A, Blankson J, Wilson E, Ayles H, Bock P, Moore A, Kosloff B, Shanaube K, Meehan SA, van Deventer A, Fidler S, Hayes R, Ruczinski I, Kammers K, Laeyendecker O, Larman HB, Eshleman SH. Comprehensive profiling of pre-infection antibodies identifies HIV targets associated with viremic control and viral load. Front Immunol 2023; 14:1178520. [PMID: 37744365 PMCID: PMC10512082 DOI: 10.3389/fimmu.2023.1178520] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 08/15/2023] [Indexed: 09/26/2023] Open
Abstract
Background High HIV viral load (VL) is associated with increased transmission risk and faster disease progression. HIV controllers achieve viral suppression without antiretroviral (ARV) treatment. We evaluated viremic control in a community-randomized trial with >48,000 participants. Methods A massively multiplexed antibody profiling system, VirScan, was used to quantify pre- and post-infection antibody reactivity to HIV peptides in 664 samples from 429 participants (13 controllers, 135 viremic non-controllers, 64 other non-controllers, 217 uninfected persons). Controllers had VLs <2,000 copies/mL with no ARV drugs detected at the first HIV-positive visit and one year later. Viremic non-controllers had VLs 2,000 copies/mL with no ARV drugs detected at the first HIV-positive visit. Other non-controllers had either ARV drugs detected at the first HIV-positive visit (n=47) or VLs <2,000 copies/mL with no ARV drugs detected at only one HIV-positive visit (n=17). Results We identified pre-infection HIV antibody reactivities that correlated with post-infection VL. Pre-infection reactivity to an epitope in the HR2 domain of gp41 was associated with controller status and lower VL. Pre-infection reactivity to an epitope in the C2 domain of gp120 was associated with non-controller status and higher VL. Different patterns of antibody reactivity were observed over time for these two epitopes. Conclusion These studies suggest that pre-infection HIV antibodies are associated with controller status and modulation of HIV VL. These findings may inform research on antibody-based interventions for HIV treatment.
Collapse
Affiliation(s)
- Wendy Grant-McAuley
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - William Morgenlander
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Sarah E. Hudelson
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Manjusha Thakar
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Estelle Piwowar-Manning
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - William Clarke
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Autumn Breaud
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Joel Blankson
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Ethan Wilson
- Statistical Center for HIV/AIDS Research and Prevention, Fred Hutchinson Cancer Research Center, Seattle, WA, United States
| | - Helen Ayles
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Peter Bock
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Western Cape, South Africa
| | | | - Barry Kosloff
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
- Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Kwame Shanaube
- Zambart, University of Zambia School of Public Health, Lusaka, Zambia
| | - Sue-Ann Meehan
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Western Cape, South Africa
| | - Anneen van Deventer
- Desmond Tutu TB Center, Department of Paediatrics and Child Health, Stellenbosch University, Western Cape, South Africa
| | - Sarah Fidler
- Department of Infectious Disease, Imperial College London, London, United Kingdom
| | - Richard Hayes
- Department of Infectious Disease Epidemiology, London School of Hygiene and Tropical Medicine, London, United Kingdom
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, United States
| | - Kai Kammers
- Quantitative Sciences Division, Department of Oncology, Sidney Kimmel Comprehensive Cancer Center, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Oliver Laeyendecker
- Department of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, MD, United States
| | - H. Benjamin Larman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
- Institute for Cell Engineering, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Susan H. Eshleman
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| |
Collapse
|
8
|
Liebhoff AM, Venkataraman T, Morgenlander WR, Na M, Kula T, Waugh K, Morrison C, Rewers M, Longman R, Round J, Elledge S, Ruczinski I, Langmead B, Larman HB. Efficient encoding of large antigenic spaces by epitope prioritization with Dolphyn. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.30.551179. [PMID: 37577562 PMCID: PMC10418057 DOI: 10.1101/2023.07.30.551179] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
We investigated a relatively underexplored component of the gut-immune axis by profiling the antibody response to gut phages using Phage Immunoprecipitation Sequencing (PhIP-Seq). To enhance this approach, we developed Dolphyn, a novel method that uses machine learning to select peptides from protein sets and compresses the proteome through epitope-stitching. Dolphyn improves the fraction of gut phage library peptides bound by antibodies from 10% to 31% in healthy individuals, while also reducing the number of synthesized peptides by 78%. In our study on gut phages, we discovered that the immune system develops antibodies to bacteria-infecting viruses in the human gut, particularly E.coli-infecting Myoviridae. Cost-effective PhIP-Seq libraries designed with Dolphyn enable the assessment of a wider range of proteins in a single experiment, thus facilitating the study of the gut-immune axis.
Collapse
Affiliation(s)
- Anna-Maria Liebhoff
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
- Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | | | - William R Morgenlander
- Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Miso Na
- Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| | - Tomasz Kula
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA, USA
| | - Kathleen Waugh
- Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, Colorado, USA
| | - Charles Morrison
- Behavioral, Clinical and Epidemiologic Sciences, FHI 360, Durham, NC, USA
| | - Marian Rewers
- Barbara Davis Center for Diabetes, University of Colorado Denver, Aurora, Colorado, USA
| | - Randy Longman
- Jill Roberts Institute for Research in IBD, Division of Gastroenterology and Hepatology, Department of Medicine, Weill Cornell Medicine, New York, NY, USA
| | - June Round
- Department of Pathology, Division of Microbiology and Immunology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Stephen Elledge
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Division of Genetics, Department of Medicine, Howard Hughes Medical Institute, Brigham and Women's Hospital, Boston, MA, USA
| | - Ingo Ruczinski
- Department of Biostatistics, Johns Hopkins University, Baltimore, MD, USA
| | - Ben Langmead
- Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA
| | - H Benjamin Larman
- Division of Immunology, Department of Pathology, Johns Hopkins University, Baltimore, MD, USA
| |
Collapse
|