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Rios-Guzman E, Simons LM, Dean TJ, Agnes F, Pawlowski A, Alisoltanidehkordi A, Nam HH, Ison MG, Ozer EA, Lorenzo-Redondo R, Hultquist JF. Deviations in RSV epidemiological patterns and population structures in the United States following the COVID-19 pandemic. Nat Commun 2024; 15:3374. [PMID: 38643200 PMCID: PMC11032338 DOI: 10.1038/s41467-024-47757-9] [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: 12/12/2023] [Accepted: 04/11/2024] [Indexed: 04/22/2024] Open
Abstract
Respiratory Syncytial Virus (RSV) is a leading cause of acute respiratory tract infection, with the greatest impact on infants, immunocompromised individuals, and older adults. RSV prevalence decreased substantially in the United States (US) following the implementation of COVID-19-related non-pharmaceutical interventions but later rebounded with abnormal seasonality. The biological and epidemiological factors underlying this altered behavior remain poorly defined. In this retrospective cohort study from 2009 to 2023 in Chicago, Illinois, US, we examined RSV epidemiology, clinical severity, and genetic diversity. We found that changes in RSV diagnostic platforms drove increased detections in outpatient settings post-2020 and that hospitalized adults infected with RSV-A were at higher risk of intensive care admission than those with RSV-B. While population structures of RSV-A remained unchanged, RSV-B exhibited a genetic shift into geographically distinct clusters. Mutations in the antigenic regions of the fusion protein suggest convergent evolution with potential implications for vaccine and therapeutic development.
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Affiliation(s)
- Estefany Rios-Guzman
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Lacy M Simons
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Taylor J Dean
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Francesca Agnes
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Anna Pawlowski
- Northwestern Medicine Enterprise Data Warehouse, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
| | - Arghavan Alisoltanidehkordi
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Hannah H Nam
- Department of Infectious Diseases, University of California - Irvine, Orange, CA, 92868, USA
| | - Michael G Ison
- Division of Microbiology and Infectious Diseases (DMID), National Institute of Health, Rockville, MD, 20852, USA
| | - Egon A Ozer
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Ramon Lorenzo-Redondo
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA
| | - Judd F Hultquist
- Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Chicago, IL, 60611, USA.
- Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL, 60611, USA.
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Ji D, Aboukhalil R, Moshiri N. ViralWasm: a client-side user-friendly web application suite for viral genomics. Bioinformatics 2024; 40:btae018. [PMID: 38200583 PMCID: PMC10809900 DOI: 10.1093/bioinformatics/btae018] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Accepted: 01/09/2024] [Indexed: 01/12/2024] Open
Abstract
MOTIVATION The genomic surveillance of viral pathogens such as SARS-CoV-2 and HIV-1 has been critical to modern epidemiology and public health, but the use of sequence analysis pipelines requires computational expertise, and web-based platforms require sending potentially sensitive raw sequence data to remote servers. RESULTS We introduce ViralWasm, a user-friendly graphical web application suite for viral genomics. All ViralWasm tools utilize WebAssembly to execute the original command line tools client-side directly in the web browser without any user setup, with a cost of just 2-3x slowdown with respect to their command line counterparts. AVAILABILITY AND IMPLEMENTATION The ViralWasm tool suite can be accessed at: https://niema-lab.github.io/ViralWasm.
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Affiliation(s)
- Daniel Ji
- Department of Computer Science & Engineering, UC San Diego, La Jolla, CA 92093, United States
| | | | - Niema Moshiri
- Department of Computer Science & Engineering, UC San Diego, La Jolla, CA 92093, United States
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3
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Hultquist J, Rios-Guzman E, Simons L, Dean T, Agnes F, Pawlowski A, Alisoltanidehkordi A, Nam H, Ison M, Ozer E, Lorenzo-Redondo R. Altered RSV Epidemiology and Genetic Diversity Following the COVID-19 Pandemic. RESEARCH SQUARE 2023:rs.3.rs-3712859. [PMID: 38168164 PMCID: PMC10760306 DOI: 10.21203/rs.3.rs-3712859/v1] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/05/2024]
Abstract
Respiratory Syncytial Virus (RSV) is a leading cause of acute respiratory tract infection, with greatest impact on infants, immunocompromised individuals, and older adults. RSV prevalence decreased substantially following the implementation of non-pharmaceutical interventions to mitigate the COVID-19 pandemic but later rebounded with initially abnormal seasonality. The biological and epidemiological factors underlying this altered behavior remain poorly defined. In this retrospective cohort study, we examined RSV epidemiology, clinical severity, and genetic diversity in the years surrounding the COVID-19 pandemic. We found that changes in RSV diagnostic platforms drove increased detections in outpatient settings after 2020 and that hospitalized adults with RSV-A were at higher risk of needing intensive care than those with RSV-B. While the population structure of RSV-A remained unchanged, the population structure of RSV-B shifted in geographically distinct clusters. Mutations in the antigenic regions of the fusion protein suggest convergent evolution with potential implications for vaccine and therapeutic development.
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4
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Grant HE, Roy S, Williams R, Tutill H, Ferns B, Cane PA, Carswell JW, Ssemwanga D, Kaleebu P, Breuer J, Leigh Brown AJ. A large population sample of African HIV genomes from the 1980s reveals a reduction in subtype D over time associated with propensity for CXCR4 tropism. Retrovirology 2022; 19:28. [PMID: 36514107 PMCID: PMC9746199 DOI: 10.1186/s12977-022-00612-5] [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: 08/03/2022] [Accepted: 11/12/2022] [Indexed: 12/15/2022] Open
Abstract
We present 109 near full-length HIV genomes amplified from blood serum samples obtained during early 1986 from across Uganda, which to our knowledge is the earliest and largest population sample from the initial phase of the HIV epidemic in Africa. Consensus sequences were made from paired-end Illumina reads with a target-capture approach to amplify HIV material following poor success with standard approaches. In comparisons with a smaller 'intermediate' genome dataset from 1998 to 1999 and a 'modern' genome dataset from 2007 to 2016, the proportion of subtype D was significantly higher initially, dropping from 67% (73/109), to 57% (26/46) to 17% (82/465) respectively (p < 0.0001). Subtype D has previously been shown to have a faster rate of disease progression than other subtypes in East African population studies, and to have a higher propensity to use the CXCR4 co-receptor ("X4 tropism"); associated with a decrease in time to AIDS. Here we find significant differences in predicted tropism between A1 and D subtypes in all three sample periods considered, which is particularly striking the 1986 sample: 66% (53/80) of subtype D env sequences were predicted to be X4 tropic compared with none of the 24 subtype A1. We also analysed the frequency of subtype in the envelope region of inter-subtype recombinants, and found that subtype A1 is over-represented in env, suggesting recombination and selection have acted to remove subtype D env from circulation. The reduction of subtype D frequency over three decades therefore appears to be a result of selective pressure against X4 tropism and its higher virulence. Lastly, we find a subtype D specific codon deletion at position 24 of the V3 loop, which may explain the higher propensity for subtype D to utilise X4 tropism.
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Affiliation(s)
- Heather E Grant
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK.
| | - Sunando Roy
- Division of Infection and Immunity, University College London, London, UK
| | - Rachel Williams
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Helena Tutill
- Division of Infection and Immunity, University College London, London, UK
| | - Bridget Ferns
- Department of Virology, University College London Hospitals NHS Foundation Trust, London, UK
| | | | | | - Deogratius Ssemwanga
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe, Uganda
| | - Pontiano Kaleebu
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe, Uganda
| | - Judith Breuer
- Division of Infection and Immunity, University College London, London, UK
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Bendall ML, Gibson KM, Steiner MC, Rentia U, Pérez-Losada M, Crandall KA. HAPHPIPE: Haplotype Reconstruction and Phylodynamics for Deep Sequencing of Intrahost Viral Populations. Mol Biol Evol 2021; 38:1677-1690. [PMID: 33367849 PMCID: PMC8042772 DOI: 10.1093/molbev/msaa315] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Deep sequencing of viral populations using next-generation sequencing (NGS) offers opportunities to understand and investigate evolution, transmission dynamics, and population genetics. Currently, the standard practice for processing NGS data to study viral populations is to summarize all the observed sequences from a sample as a single consensus sequence, thus discarding valuable information about the intrahost viral molecular epidemiology. Furthermore, existing analytical pipelines may only analyze genomic regions involved in drug resistance, thus are not suited for full viral genome analysis. Here, we present HAPHPIPE, a HAplotype and PHylodynamics PIPEline for genome-wide assembly of viral consensus sequences and haplotypes. The HAPHPIPE protocol includes modules for quality trimming, error correction, de novo assembly, alignment, and haplotype reconstruction. The resulting consensus sequences, haplotypes, and alignments can be further analyzed using a variety of phylogenetic and population genetic software. HAPHPIPE is designed to provide users with a single pipeline to rapidly analyze sequences from viral populations generated from NGS platforms and provide quality output properly formatted for downstream evolutionary analyses.
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Affiliation(s)
- Matthew L Bendall
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Keylie M Gibson
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Margaret C Steiner
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Uzma Rentia
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Marcos Pérez-Losada
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.,Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.,CIBIO-InBIO, Centro de Investigação em Biodiversidade e Recursos Genéticos, Universidade do Porto, Vairão, Portugal
| | - Keith A Crandall
- Computational Biology Institute, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA.,Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
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