1
|
Rancati S, Nicora G, Prosperi M, Bellazzi R, Salemi M, Marini S. Forecasting dominance of SARS-CoV-2 lineages by anomaly detection using deep AutoEncoders. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.10.24.563721. [PMID: 37961168 PMCID: PMC10634784 DOI: 10.1101/2023.10.24.563721] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
The coronavirus disease of 2019 (COVID-19) pandemic is characterized by sequential emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants, lineages, and sublineages, outcompeting previously circulating ones because of, among other factors, increased transmissibility and immune escape. We propose DeepAutoCoV, an unsupervised deep learning anomaly detection system to predict future dominant lineages (FDLs). We define FDLs as viral (sub)lineages that will constitute more than 10% of all the viral sequences added to the GISAID database on a given week. DeepAutoCoV is trained and validated by assembling global and country-specific data sets from over 16 million Spike protein sequences sampled over a period of about 4 years. DeepAutoCoV successfully flags FDLs at very low frequencies (0.01% - 3%), with median lead times of 4-17 weeks, and predicts FDLs ∼5 and ∼25 times better than a baseline approach For example, the B.1.617.2 vaccine reference strain was flagged as FDL when its frequency was only 0.01%, more than a year before it was considered for an updated COVID-19 vaccine. Furthermore, DeepAutoCoV outputs interpretable results by pinpointing specific mutations potentially linked to increased fitness, and may provide significant insights for the optimization of public health pre-emptive intervention strategies.
Collapse
|
2
|
Markin A, Wagle S, Grover S, Vincent Baker AL, Eulenstein O, Anderson TK. PARNAS: Objectively Selecting the Most Representative Taxa on a Phylogeny. Syst Biol 2023; 72:1052-1063. [PMID: 37208300 PMCID: PMC10627562 DOI: 10.1093/sysbio/syad028] [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: 09/13/2022] [Revised: 04/26/2023] [Accepted: 05/03/2023] [Indexed: 05/21/2023] Open
Abstract
The use of next-generation sequencing technology has enabled phylogenetic studies with hundreds of thousands of taxa. Such large-scale phylogenies have become a critical component in genomic epidemiology in pathogens such as SARS-CoV-2 and influenza A virus. However, detailed phenotypic characterization of pathogens or generating a computationally tractable dataset for detailed phylogenetic analyses requires objective subsampling of taxa. To address this need, we propose parnas, an objective and flexible algorithm to sample and select taxa that best represent observed diversity by solving a generalized k-medoids problem on a phylogenetic tree. parnas solves this problem efficiently and exactly by novel optimizations and adapting algorithms from operations research. For more nuanced selections, taxa can be weighted with metadata or genetic sequence parameters, and the pool of potential representatives can be user-constrained. Motivated by influenza A virus genomic surveillance and vaccine design, parnas can be applied to identify representative taxa that optimally cover the diversity in a phylogeny within a specified distance radius. We demonstrated that parnas is more efficient and flexible than existing approaches. To demonstrate its utility, we applied parnas to 1) quantify SARS-CoV-2 genetic diversity over time, 2) select representative influenza A virus in swine genes derived from over 5 years of genomic surveillance data, and 3) identify gaps in H3N2 human influenza A virus vaccine coverage. We suggest that our method, through the objective selection of representatives in a phylogeny, provides criteria for quantifying genetic diversity that has application in the the rational design of multivalent vaccines and genomic epidemiology. PARNAS is available at https://github.com/flu-crew/parnas.
Collapse
Affiliation(s)
- Alexey Markin
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| | - Sanket Wagle
- Department of Computer Science, Iowa State University, Ames, IA, 50011, USA
| | - Siddhant Grover
- Department of Computer Science, Iowa State University, Ames, IA, 50011, USA
| | - Amy L Vincent Baker
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| | - Oliver Eulenstein
- Department of Computer Science, Iowa State University, Ames, IA, 50011, USA
| | - Tavis K Anderson
- Virus and Prion Research Unit, National Animal Disease Center, USDA-ARS, Ames, IA, 50010, USA
| |
Collapse
|
3
|
Junqueira DM, Tochetto C, Anderson TK, Gava D, Haach V, Cantão ME, Baker ALV, Schaefer R. Human-to-swine introductions and onward transmission of 2009 H1N1 pandemic influenza viruses in Brazil. Front Microbiol 2023; 14:1243567. [PMID: 37614592 PMCID: PMC10442540 DOI: 10.3389/fmicb.2023.1243567] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 07/27/2023] [Indexed: 08/25/2023] Open
Abstract
Introduction Once established in the human population, the 2009 H1N1 pandemic virus (H1N1pdm09) was repeatedly introduced into swine populations globally with subsequent onward transmission among pigs. Methods To identify and characterize human-to-swine H1N1pdm09 introductions in Brazil, we conducted a large-scale phylogenetic analysis of 4,141 H1pdm09 hemagglutinin (HA) and 3,227 N1pdm09 neuraminidase (NA) gene sequences isolated globally from humans and swine between 2009 and 2022. Results Phylodynamic analysis revealed that during the period between 2009 and 2011, there was a rapid transmission of the H1N1pdm09 virus from humans to swine in Brazil. Multiple introductions of the virus were observed, but most of them resulted in self-limited infections in swine, with limited onward transmission. Only a few sustained transmission clusters were identified during this period. After 2012, there was a reduction in the number of human-to-swine H1N1pdm09 transmissions in Brazil. Discussion The virus underwent continuous antigenic drift, and a balance was established between swine-to-swine transmission and extinction, with minimal sustained onward transmission from humans to swine. These results emphasize the dynamic interplay between human-to-swine transmission, antigenic drift, and the establishment of swine-to-swine transmission in shaping the evolution and persistence of H1N1pdm09 in swine populations.
Collapse
Affiliation(s)
- Dennis Maletich Junqueira
- Laboratório de Bioinformática e Evolução de Vírus, Departamento de Bioquímica e Biologia Molecular, Centro de Ciências Naturais e Exatas (CCNE), Universidade Federal de Santa Maria (UFSM), Santa Maria, Brazil
| | | | - Tavis K. Anderson
- Virus and Prion Research Unit, United States Department of Agriculture, National Animal Disease Center, Agricultural Research Service, Ames, IA, United States
| | | | - Vanessa Haach
- Laboratório de Virologia, Departamento de Microbiologia, Imunologia e Parasitologia, Instituto de Ciências Básicas da Saúde, Universidade Federal do Rio Grande do Sul (UFRGS), Porto Alegre, Brazil
| | | | - Amy L. Vincent Baker
- Virus and Prion Research Unit, United States Department of Agriculture, National Animal Disease Center, Agricultural Research Service, Ames, IA, United States
| | | |
Collapse
|
4
|
Prosperi M, Rife B, Marini S, Salemi M. Transmission cluster characteristics of global, regional, and lineage-specific SARS-CoV-2 phylogenies. IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE WORKSHOPS. IEEE INTERNATIONAL CONFERENCE ON BIOINFORMATICS AND BIOMEDICINE 2022; 2022:2940-2944. [PMID: 36780250 PMCID: PMC9912475 DOI: 10.1109/bibm55620.2022.9995364] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
The SARS-CoV-2 pandemic has been presenting in periodic waves and multiple variants, of which some dominated over time with increased transmissibility. SARS-CoV-2 is still adapting in the human population, thus it is crucial to understand its evolutionary patterns and dynamics ahead of time. In this work, we analyzed transmission clusters and topology of SARS-CoV-2 phylogenies at the global, regional (North America) and clade-specific (Delta and Omicron) epidemic scales. We used the Nextstrain's nCov open global all-time phylogeny (September 2022, 2,698 strains, 2,243 for North America, 499 for Delta21A, and 543 for Omicron20M), with Nextstrain's clade annotation and Pango lineages. Transmission clusters were identified using Phylopart, DYNAMITE, and several tree imbalance measures were calculated, including staircase-ness, Sackin and Colless index. We found that the phylogenetic clustering profiles of the global epidemic have highest diversification at a distance threshold of 3% (divergence of 10, where the tree sampled median is 49). Phylopart and DYNAMITE clusters moderately-to-highly agree with the Pango nomenclature and the Nextstrain's clade. At the regional and clade-specific scale, transmission clustering profiles tend to flatten and similar clusters are found at distance thresholds between 0.05% and 25%. All the considered phylogenies exhibit high tree imbalance with respect to what expected in random phylogenies, suggesting short infection times and antigenic drift, perhaps due to progressive transition from innate to adaptive immunity in the population.
Collapse
Affiliation(s)
- Mattia Prosperi
- Department of Epidemiology, College of Public Health and
Health Professions, University of Florida Gainesville, Fl,
USA
| | - Brittany Rife
- Department of Pathology, Immunology and Laboratory
Medicine, College of Medicine, University of Florida
Gainesville, Fl, USA
| | - Simone Marini
- Department of Epidemiology, College of Public Health and
Health Professions, University of Florida Gainesville, Fl,
USA
| | - Marco Salemi
- Department of Pathology, Immunology and Laboratory
Medicine, College of Medicine, University of Florida
Gainesville, Fl, USA
| |
Collapse
|
5
|
Cella E, Ali S, Schmedes SE, Rife Magalis B, Marini S, Salemi M, Blanton J, Azarian T. Early Emergence Phase of SARS-CoV-2 Delta Variant in Florida, US. Viruses 2022; 14:766. [PMID: 35458495 PMCID: PMC9028683 DOI: 10.3390/v14040766] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 03/24/2022] [Accepted: 04/04/2022] [Indexed: 12/04/2022] Open
Abstract
SARS-CoV-2, the causative agent of COVID-19, emerged in late 2019. The highly contagious B.1.617.2 (Delta) variant of concern (VOC) was first identified in October 2020 in India and subsequently disseminated worldwide, later becoming the dominant lineage in the US. Understanding the local transmission dynamics of early SARS-CoV-2 introductions may inform actionable mitigation efforts during subsequent pandemic waves. Yet, despite considerable genomic analysis of SARS-CoV-2 in the US, several gaps remain. Here, we explore the early emergence of the Delta variant in Florida, US using phylogenetic analysis of representative Florida and globally sampled genomes. We find multiple independent introductions into Florida primarily from North America and Europe, with a minority originating from Asia. These introductions led to three distinct clades that demonstrated varying relative rates of transmission and possessed five distinct substitutions that were 3-21 times more prevalent in the Florida sample as compared to the global sample. Our results underscore the benefits of routine viral genomic surveillance to monitor epidemic spread and support the need for more comprehensive genomic epidemiology studies of emerging variants. In addition, we provide a model of epidemic spread of newly emerging VOCs that can inform future public health responses.
Collapse
Affiliation(s)
- Eleonora Cella
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
| | - Sobur Ali
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
| | - Sarah E. Schmedes
- Bureau of Public Health Laboratories, Florida Department of Health, Jacksonville, FL 32202, USA; (S.E.S.); (J.B.)
| | - Brittany Rife Magalis
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA; (B.R.M.); (M.S.)
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32608, USA
| | - Simone Marini
- Department of Epidemiology, University of Florida, Gainesville, FL 32608, USA;
| | - Marco Salemi
- Emerging Pathogens Institute, University of Florida, Gainesville, FL 32608, USA; (B.R.M.); (M.S.)
- Department of Pathology, Immunology, and Laboratory Medicine, University of Florida, Gainesville, FL 32608, USA
| | - Jason Blanton
- Bureau of Public Health Laboratories, Florida Department of Health, Jacksonville, FL 32202, USA; (S.E.S.); (J.B.)
| | - Taj Azarian
- Burnett School of Biomedical Sciences, University of Central Florida, Orlando, FL 32827, USA; (E.C.); (S.A.)
| |
Collapse
|