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Jones LR. Intra-host variability of SARS-CoV-2: Patterns, causes and impact on COVID-19. Virology 2024; 603:110366. [PMID: 39724740 DOI: 10.1016/j.virol.2024.110366] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2024] [Revised: 12/06/2024] [Accepted: 12/17/2024] [Indexed: 12/28/2024]
Abstract
Intra-host viral variability is related to pathogenicity, persistence, drug resistance, and the emergence of new clades. This work reviews the large amount of data on SARS-CoV-2 intra-host variability accumulated to date, addressing known and potential implications in COVID-19 and the emergence of VOCs and lineage-defining mutations. Topics covered include the distribution of intra-host polymorphisms across the genome, the corresponding mutational signatures, their patterns of emergence and extinction throughout infection, and the processes governing their abundance, frequency, and type (synonymous, nonsynonymous, indels, nonsense). Besides, evidence is reviewed that the virus can replicate and mutate in isolation at different anatomical compartments, which may imply that what we have learned from respiratory samples could be part of a broader picture.
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Affiliation(s)
- Leandro R Jones
- Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Avenida Rivadavia 1917, C1083ACA Ciudad Autónoma de Buenos Aires, Argentina; Laboratorio de Virología y Genética Molecular (LVGM), Facultad de Ciencias Naturales y Ciencias de la Salud, Universidad Nacional de la Patagonia San Juan Bosco, Belgrano 160, Trelew, CP, 9100, Argentina.
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2
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Li C, Culhane MR, Schroeder DC, Cheeran MCJ, Galina Pantoja L, Jansen ML, Torremorell M. Quantifying the impact of vaccination on transmission and diversity of influenza A variants in pigs. J Virol 2024; 98:e0124524. [PMID: 39530665 DOI: 10.1128/jvi.01245-24] [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: 07/22/2024] [Accepted: 10/09/2024] [Indexed: 11/16/2024] Open
Abstract
Global evolutionary dynamics of influenza A virus (IAV) are fundamentally driven by the extent of virus diversity generated, transmitted, and shaped in individual hosts. How vaccination affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs is unknown. To evaluate the effect of vaccination on the transmission of genetically distinct IAV variants and their diversity after transmission in pigs, we examined the whole genome of IAV recovered from the nasal cavities of pigs vaccinated with different influenza immunization regimens after being infected simultaneously by H1N1 and H3N2 IAVs using a seeder pig model. We found that the seeder pigs harbored more diversified virus populations than the contact pigs. Among contact pigs, H3N2 and H1N1 viruses recovered from pigs vaccinated with a single dose of an unmatched modified live vaccine generally accumulated more extensive genetic mutations than non-vaccinated pigs. Furthermore, the non-sterilizing immunity elicited by the single-dose-modified live vaccine may have exerted positive selection on H1 antigenic regions as we detected significantly higher nonsynonymous but lower synonymous evolutionary rates in H1 antigenic regions than non-antigenic regions. In addition, we observed that the vaccinated pigs shared significantly less proportion of H3N2 variants with seeder pigs than unvaccinated pigs. These results indicated that vaccination might reduce the impact of transmitted influenza variants on the overall diversity of IAV populations harbored in recipient pigs and that within-host genetic selection of IAV is more likely to occur in pigs vaccinated with improperly matched vaccines.IMPORTANCEUnderstanding how vaccination shapes the diversity of influenza variants that transmit and propagate among pigs is essential for designing effective IAV surveillance and control programs. Current knowledge about the transmission of IAV variants has primarily been explored in humans during natural infection. However, how immunity elicited by improperly matched vaccines affects the degree of IAV genetic diversity that can be transmitted and expanded in pigs at the whole-genome level is unknown. We analyzed IAV sequences from samples collected daily from experimentally infected pigs vaccinated with various protocols in a field-represented IAV co-infection model. We found that vaccine-induced non-sterilizing immunity might promote genetic variation on the IAV genome and drive positive selection at antigenic sites during infection. In addition, a smaller proportion of H3N2 viral variants were shared between seeder pigs and vaccinated pigs, suggesting the influence of vaccination on shaping the virus genomic diversity in recipient pigs during the transmission events.
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Affiliation(s)
- Chong Li
- College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
| | - Marie R Culhane
- College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
| | - Declan C Schroeder
- College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
| | - Maxim C-J Cheeran
- College of Veterinary Medicine, University of Minnesota, St. Paul, Minnesota, USA
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3
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Sigal A, Neher RA, Lessells RJ. The consequences of SARS-CoV-2 within-host persistence. Nat Rev Microbiol 2024:10.1038/s41579-024-01125-y. [PMID: 39587352 DOI: 10.1038/s41579-024-01125-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/28/2024] [Indexed: 11/27/2024]
Abstract
SARS-CoV-2 causes an acute respiratory tract infection that resolves in most people in less than a month. Yet some people with severely weakened immune systems fail to clear the virus, leading to persistent infections with high viral titres in the respiratory tract. In a subset of cases, persistent SARS-CoV-2 replication results in an accelerated accumulation of adaptive mutations that confer escape from neutralizing antibodies and enhance cellular infection. This may lead to the evolution of extensively mutated SARS-CoV-2 variants and introduce an element of chance into the timing of variant evolution, as variant formation may depend on evolution in a single person. Whether long COVID is also caused by persistence of replicating SARS-CoV-2 is controversial. One line of evidence is detection of SARS-CoV-2 RNA and proteins in different body compartments long after SARS-CoV-2 infection has cleared from the upper respiratory tract. However, thus far, no replication competent virus has been cultured from individuals with long COVID who are immunocompetent. In this Review, we consider mechanisms of viral persistence, intra-host evolution in persistent infections, the connection of persistent infections with SARS-CoV-2 variants and the possible role of SARS-CoV-2 persistence in long COVID. Understanding persistent infections may therefore resolve much of what is still unclear in COVID-19 pathophysiology, with possible implications for other emerging viruses.
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Affiliation(s)
- Alex Sigal
- The Lautenberg Center for Immunology and Cancer Research, Faculty of Medicine, Hebrew University of Jerusalem, Jerusalem, Israel.
- Africa Health Research Institute, Durban, South Africa.
- School of Laboratory Medicine and Medical Sciences, University of KwaZulu-Natal, Durban, South Africa.
| | - Richard A Neher
- Biozentrum, University of Basel, Basel, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Richard J Lessells
- KwaZulu-Natal Research Innovation & Sequencing Platform, School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
- Centre for the AIDS Programme of Research in South Africa, Durban, South Africa
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4
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Banga J, Brock-Fisher T, Petros BA, Dai EY, Leonelli AT, Dobbins ST, Messer KS, Nathanson AB, Capone A, Littlehale N, Appiah-Danquah V, Dim S, Moreno GK, Crowther M, DeRuff KC, MacInnis BL, Springer M, Sabeti PC, Stephenson KE. Severe Acute Respiratory Syndrome Coronavirus 2 Household Transmission During the Omicron Era in Massachusetts: A Prospective, Case-Ascertained Study Using Genomic Epidemiology. Open Forum Infect Dis 2024; 11:ofae591. [PMID: 39529936 PMCID: PMC11551451 DOI: 10.1093/ofid/ofae591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2024] [Accepted: 10/03/2024] [Indexed: 11/16/2024] Open
Abstract
Background Households are a major setting for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections, but there remains a lack of knowledge regarding the dynamics of viral transmission, particularly in the setting of preexisting SARS-CoV-2 immunity and evolving variants. Methods We conducted a prospective, case-ascertained household transmission study in the greater Boston area in March-July 2022. Anterior nasal swabs, along with clinical and demographic data, were collected for 14 days. Nasal swabs were tested for SARS-CoV-2 by polymerase chain reaction (PCR). Whole genome sequencing was performed on high-titer samples. Results We enrolled 33 households in a primary analysis set, with a median participant age of 25 years (range, 2-66 years), 98% of whom had received at least 2 doses of a coronavirus disease 2019 (COVID-19) vaccine. Fifty-eight percent of households had a secondary case during follow-up and the secondary attack rate (SAR) for contacts was 39%. We further examined a strict analysis set of 21 households that had only 1 PCR-positive case at baseline, finding an SAR of 22.5%. Genomic epidemiology further determined that there were multiple sources of infection for household contacts, including the index case and outside introductions. When limiting estimates to only highly probable transmissions given epidemiologic and genomic data, the SAR was 18.4%. Conclusions Household contacts of a person newly diagnosed with COVID-19 are at high risk for SARS-CoV-2 infection in the following 2 weeks. This is, however, not only due to infection from the household index case, but also because the presence of an infected household member implies increased SARS-CoV-2 community transmission.
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Affiliation(s)
- Jaspreet Banga
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Taylor Brock-Fisher
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts, USA
| | - Brittany A Petros
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
- Harvard/Massachusetts Institute of Technology MD-PhD Program, Boston, Massachusetts, USA
| | - Eric Y Dai
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Ariana T Leonelli
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Sabrina T Dobbins
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Katelyn S Messer
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Audrey B Nathanson
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Amelia Capone
- Beth Israel Lahey Health Primary Care, Chelsea, Massachusetts, USA
| | - Nancy Littlehale
- Beth Israel Lahey Health Primary Care, Chelsea, Massachusetts, USA
| | - Viola Appiah-Danquah
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Siang Dim
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Gage K Moreno
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Maura Crowther
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
| | - Katherine C DeRuff
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Bronwyn L MacInnis
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, Massachusetts, USA
- Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, Massachusetts, USA
| | - Pardis C Sabeti
- The Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, Massachusetts, USA
- Department of Immunology and Infectious Diseases, Harvard T. H. Chan School of Public Health, Boston, Massachusetts, USA
- Howard Hughes Medical Institute, Chevy Chase, Maryland, USA
| | - Kathryn E Stephenson
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, Massachusetts, USA
- Harvard Medical School, Boston, Massachusetts, USA
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard, Cambridge, Massachusetts, USA
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Zhao N, He M, Wang H, Zhu L, Wang N, Yong W, Fan H, Ding S, Ma T, Zhang Z, Dong X, Wang Z, Dong X, Min X, Zhang H, Ding J. Genomic epidemiology reveals the variation and transmission properties of SARS-CoV-2 in a single-source community outbreak. Virus Evol 2024; 10:veae085. [PMID: 39493536 PMCID: PMC11529616 DOI: 10.1093/ve/veae085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2024] [Revised: 09/04/2024] [Accepted: 10/10/2024] [Indexed: 11/05/2024] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the coronavirus disease 2019 (COVID-19) pandemic, which is still a global public health concern. During March 2022, a rapid and confined single-source outbreak of SARS-CoV-2 was identified in a community in Nanjing municipal city. Overall, 95 individuals had laboratory-confirmed SARS-CoV-2 infection. The whole genomes of 61 viral samples were obtained, which were all members of the BA.2.2 lineage and clearly demonstrated the presence of one large clade, and all the infections could be traced back to the original index case. The most distant sequence from the index case presented a difference of 4 SNPs, and 118 intrahost single-nucleotide variants (iSNVs) at 74 genomic sites were identified. Some minor iSNVs can be transmitted and subsequently rapidly fixed in the viral population. The minor iSNVs transmission resulted in at least two nucleotide substitutions among all seven SNPs identified in the outbreak, generating genetically diverse populations. We estimated the overall transmission bottleneck size to be 3 using 11 convincing donor-recipient transmission pairs. Our study provides new insights into genomic epidemiology and viral transmission, revealing how iSNVs become fixed in local clusters, followed by viral transmission across the community, which contributes to population diversity.
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Affiliation(s)
- Ning Zhao
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Min He
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
- School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, China
| | - HengXue Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - LiGuo Zhu
- Department of Acute Infectious Disease Control and Prevention, Jiangsu Provincial Center for Disease Control and Prevention, 172 Jiangsu Road, Nanjing, Jiangsu 210009, China
| | - Nan Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Wei Yong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - HuaFeng Fan
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - SongNing Ding
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Tao Ma
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Zhong Zhang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoXiao Dong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - ZiYu Wang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoQing Dong
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - XiaoYu Min
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - HongBo Zhang
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
| | - Jie Ding
- Microbiology Laboratory, Nanjing Medical University Affiliated Nanjing Municipal Center for Disease Control and Prevention, 2 Zizhulin Road, Nanjing, Jiangsu 210003, China
- School of Public Health, Nanjing Medical University, 101 Longmian Avenue, Nanjing, Jiangsu 211166, China
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Rodríguez-Horta E, Strahan J, Dinner AR, Barton JP. Chronic infections can generate SARS-CoV-2-like bursts of viral evolution without epistasis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.06.616878. [PMID: 39416020 PMCID: PMC11482859 DOI: 10.1101/2024.10.06.616878] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
Multiple SARS-CoV-2 variants have arisen during the first years of the pandemic, often bearing many new mutations. Several explanations have been offered for the surprisingly sudden emergence of multiple mutations that enhance viral fitness, including cryptic transmission, spillover from animal reservoirs, epistasis between mutations, and chronic infections. Here, we simulated pathogen evolution combining within-host replication and between-host transmission. We found that, under certain conditions, chronic infections can lead to SARS-CoV-2-like bursts of mutations even without epistasis. Chronic infections can also increase the global evolutionary rate of a pathogen even in the absence of clear mutational bursts. Overall, our study supports chronic infections as a plausible origin for highly mutated SARS-CoV-2 variants. More generally, we also describe how chronic infections can influence pathogen evolution under different scenarios.
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Affiliation(s)
- Edwin Rodríguez-Horta
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, USA
- Group of Complex Systems and Statistical Physics, Department of Theoretical Physics, Physics Faculty, University of Havana, Cuba
| | - John Strahan
- Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA
| | - Aaron R. Dinner
- Department of Chemistry and James Franck Institute, University of Chicago, Chicago, Illinois 60637, USA
| | - John P. Barton
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, USA
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Bendall EE, Zhu Y, Fitzsimmons WJ, Rolfes M, Mellis A, Halasa N, Martin ET, Grijalva CG, Talbot HK, Lauring AS. Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons. Virus Evol 2024; 10:veae084. [PMID: 39444487 PMCID: PMC11498174 DOI: 10.1093/ve/veae084] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2024] [Revised: 09/24/2024] [Accepted: 09/30/2024] [Indexed: 10/25/2024] Open
Abstract
While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNVs) were identified at a 0.5% frequency threshold. Within-host populations exhibited low diversity, with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4 × 10-6 vs. 9.42 × 10-7 and 3.45 × 10-6, P < .001). Forty-five iSNVs had evidence of parallel evolution but were not over-represented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNVs across segments. A Wright-Fisher approximate Bayesian computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to genetic drift and purifying selection, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.
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Affiliation(s)
- Emily E Bendall
- Department of Microbiology & Immunology, University of Michigan, Ann Arbor, MI 48109, United States
| | - Yuwei Zhu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - William J Fitzsimmons
- Division of Infectious Diseases, University of Michigan, Ann Arbor, MI 48109, United States
| | - Melissa Rolfes
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30333, United States
| | - Alexandra Mellis
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA 30333, United States
| | - Natasha Halasa
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - Emily T Martin
- Department of Epidemiology, University of Michigan, Ann Arbor, MI 48109, United States
| | - Carlos G Grijalva
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - H Keipp Talbot
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN 37203, United States
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN 37203, United States
| | - Adam S Lauring
- Department of Microbiology & Immunology, University of Michigan, Ann Arbor, MI 48109, United States
- Division of Infectious Diseases, University of Michigan, Ann Arbor, MI 48109, United States
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8
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Schoefbaenker M, Günther T, Lorentzen EU, Romberg ML, Hennies MT, Neddermeyer R, Müller MM, Mellmann A, Bojarzyn CR, Lenz G, Stelljes M, Hrincius ER, Vollenberg R, Ludwig S, Tepasse PR, Kühn JE. Characterisation of the antibody-mediated selective pressure driving intra-host evolution of SARS-CoV-2 in prolonged infection. PLoS Pathog 2024; 20:e1012624. [PMID: 39405332 PMCID: PMC11508484 DOI: 10.1371/journal.ppat.1012624] [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: 02/05/2024] [Revised: 10/25/2024] [Accepted: 09/28/2024] [Indexed: 10/26/2024] Open
Abstract
Neutralising antibodies against the SARS-CoV-2 spike (S) protein are major determinants of protective immunity, though insufficient antibody responses may cause the emergence of escape mutants. We studied the humoral immune response causing intra-host evolution in a B-cell depleted, haemato-oncologic patient experiencing clinically severe, prolonged SARS-CoV-2 infection with a virus of lineage B.1.177.81. Following bamlanivimab treatment at an early stage of infection, the patient developed a bamlanivimab-resistant mutation, S:S494P. After five weeks of apparent genetic stability, the emergence of additional substitutions and deletions within the N-terminal domain (NTD) and the receptor binding domain (RBD) of S was observed. Notably, the composition and frequency of escape mutations changed in a short period with an unprecedented dynamic. The triple mutant S:Delta141-4 E484K S494P became dominant until virus elimination. Routine serology revealed no evidence of an antibody response in the patient. A detailed analysis of the variant-specific immune response by pseudotyped virus neutralisation test, surrogate virus neutralisation test, and immunoglobulin-capture enzyme immunoassay showed that the onset of an IgM-dominated antibody response coincided with the appearance of escape mutations. The formation of neutralising antibodies against S:Delta141-4 E484K S494P correlated with virus elimination. One year later, the patient experienced clinically mild re-infection with Omicron BA.1.18, which was treated with sotrovimab and resulted in an increase in Omicron-reactive antibodies. In conclusion, the onset of an IgM-dominated endogenous immune response in an immunocompromised patient coincided with the appearance of additional mutations in the NTD and RBD of S in a bamlanivimab-resistant virus. Although virus elimination was ultimately achieved, this humoral immune response escaped detection by routine diagnosis and created a situation temporarily favouring the rapid emergence of various antibody escape mutants with known epidemiological relevance.
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Affiliation(s)
| | - Theresa Günther
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
| | - Eva Ulla Lorentzen
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
| | | | - Marc Tim Hennies
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
| | - Rieke Neddermeyer
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
| | | | - Alexander Mellmann
- Institute of Hygiene, University Hospital Muenster, University of Muenster, Muenster, Germany
| | | | - Georg Lenz
- Department of Medicine A, Haematology, Oncology and Pneumology, University Hospital Muenster, Muenster, Germany
| | - Matthias Stelljes
- Department of Medicine A, Haematology, Oncology and Pneumology, University Hospital Muenster, Muenster, Germany
| | | | - Richard Vollenberg
- Department of Medicine B for Gastroenterology, Hepatology, Endocrinology and Clinical Infectiology, University Hospital Muenster, Muenster, Germany
| | - Stephan Ludwig
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
| | - Phil-Robin Tepasse
- Department of Medicine B for Gastroenterology, Hepatology, Endocrinology and Clinical Infectiology, University Hospital Muenster, Muenster, Germany
| | - Joachim Ewald Kühn
- Institute of Virology Muenster, University of Muenster, Muenster, Germany
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9
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Wouters C, Sachithanandham J, Akin E, Pieterse L, Fall A, Truong TT, Bard JD, Yee R, Sullivan DJ, Mostafa HH, Pekosz A. SARS-CoV-2 Variants from Long-Term, Persistently Infected Immunocompromised Patients Have Altered Syncytia Formation, Temperature-Dependent Replication, and Serum Neutralizing Antibody Escape. Viruses 2024; 16:1436. [PMID: 39339912 PMCID: PMC11437501 DOI: 10.3390/v16091436] [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: 05/19/2024] [Revised: 09/01/2024] [Accepted: 09/02/2024] [Indexed: 09/30/2024] Open
Abstract
SARS-CoV-2 infection of immunocompromised individuals often leads to prolonged detection of viral RNA and infectious virus in nasal specimens, presumably due to the lack of induction of an appropriate adaptive immune response. Mutations identified in virus sequences obtained from persistently infected patients bear signatures of immune evasion and have some overlap with sequences present in variants of concern. We characterized virus isolates obtained greater than 100 days after the initial COVID-19 diagnosis from two COVID-19 patients undergoing immunosuppressive cancer therapy, wand compared them to an isolate from the start of the infection. Isolates from an individual who never mounted an antibody response specific to SARS-CoV-2 despite the administration of convalescent plasma showed slight reductions in plaque size and some showed temperature-dependent replication attenuation on human nasal epithelial cell culture compared to the virus that initiated infection. An isolate from another patient-who did mount a SARS-CoV-2 IgM response-showed temperature-dependent changes in plaque size as well as increased syncytia formation and escape from serum-neutralizing antibodies. Our results indicate that not all virus isolates from immunocompromised COVID-19 patients display clear signs of phenotypic change, but increased attention should be paid to monitoring virus evolution in this patient population.
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Affiliation(s)
- Camille Wouters
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Jaiprasath Sachithanandham
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Elgin Akin
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Lisa Pieterse
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Amary Fall
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Thao T Truong
- Department of Laboratory Medicine and Pathology, University of Washington, Seattle, WA 98195, USA
- Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA
| | - Jennifer Dien Bard
- Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA
- Keck School of Medicine, University of Southern California, Los Angeles, CA 90033, USA
| | - Rebecca Yee
- Department of Pathology and Laboratory Medicine, Children's Hospital Los Angeles, Los Angeles, CA 90027, USA
- Department of Pathology, The George Washington University School of Medicine and Health Sciences, Washington, DC 20052, USA
| | - David J Sullivan
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Heba H Mostafa
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
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10
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Bendall EE, Zhu Y, Fitzsimmons WJ, Rolfes M, Mellis A, Halasa N, Martin ET, Grijalva CG, Talbot HK, Lauring AS. Influenza A virus within-host evolution and positive selection in a densely sampled household cohort over three seasons. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.08.15.608152. [PMID: 39229225 PMCID: PMC11370358 DOI: 10.1101/2024.08.15.608152] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Indexed: 09/05/2024]
Abstract
While influenza A virus (IAV) antigenic drift has been documented globally, in experimental animal infections, and in immunocompromised hosts, positive selection has generally not been detected in acute infections. This is likely due to challenges in distinguishing selected rare mutations from sequencing error, a reliance on cross-sectional sampling, and/or the lack of formal tests of selection for individual sites. Here, we sequenced IAV populations from 346 serial, daily nasal swabs from 143 individuals collected over three influenza seasons in a household cohort. Viruses were sequenced in duplicate, and intrahost single nucleotide variants (iSNV) were identified at a 0.5% frequency threshold. Within-host populations were subject to purifying selection with >75% mutations present at <2% frequency. Children (0-5 years) had marginally higher within-host evolutionary rates than adolescents (6-18 years) and adults (>18 years, 4.4×10-6 vs. 9.42×10-7 and 3.45×10-6, p <0.001). Forty-five iSNV had evidence of parallel evolution, but were not overrepresented in HA and NA. Several increased from minority to consensus level, with strong linkage among iSNV across segments. A Wright Fisher Approximate Bayesian Computational model identified positive selection at 23/256 loci (9%) in A(H3N2) specimens and 19/176 loci (11%) in A(H1N1)pdm09 specimens, and these were infrequently found in circulation. Overall, we found that within-host IAV populations were subject to purifying selection and genetic drift, with only subtle differences across seasons, subtypes, and age strata. Positive selection was rare and inconsistently detected.
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Affiliation(s)
- Emily E. Bendall
- Department of Microbiology & Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Yuwei Zhu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
| | | | - Melissa Rolfes
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Alexandra Mellis
- Influenza Division, Centers for Disease Control and Prevention, Atlanta, GA USA
| | - Natasha Halasa
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Emily T. Martin
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Carlos G. Grijalva
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA
| | - H. Keipp Talbot
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, TN, USA
- Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Adam S. Lauring
- Department of Microbiology & Immunology, University of Michigan, Ann Arbor, MI, USA
- Division of Infectious Diseases, University of Michigan, Ann Arbor, MI, USA
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11
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Bonetti Franceschi V, Volz E. Phylogenetic signatures reveal multilevel selection and fitness costs in SARS-CoV-2. Wellcome Open Res 2024; 9:85. [PMID: 39132669 PMCID: PMC11316176 DOI: 10.12688/wellcomeopenres.20704.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 07/16/2024] [Indexed: 08/13/2024] Open
Abstract
Background Large-scale sequencing of SARS-CoV-2 has enabled the study of viral evolution during the COVID-19 pandemic. Some viral mutations may be advantageous to viral replication within hosts but detrimental to transmission, thus carrying a transient fitness advantage. By affecting the number of descendants, persistence times and growth rates of associated clades, these mutations generate localised imbalance in phylogenies. Quantifying these features in closely-related clades with and without recurring mutations can elucidate the tradeoffs between within-host replication and between-host transmission. Methods We implemented a novel phylogenetic clustering algorithm ( mlscluster, https://github.com/mrc-ide/mlscluster) to systematically explore time-scaled phylogenies for mutations under transient/multilevel selection. We applied this method to a SARS-CoV-2 time-calibrated phylogeny with >1.2 million sequences from England, and characterised these recurrent mutations that may influence transmission fitness across PANGO-lineages and genomic regions using Poisson regressions and summary statistics. Results We found no major differences across two epidemic stages (before and after Omicron), PANGO-lineages, and genomic regions. However, spike, nucleocapsid, and ORF3a were proportionally more enriched for transmission fitness polymorphisms (TFP)-homoplasies than other proteins. We provide a catalog of SARS-CoV-2 sites under multilevel selection, which can guide experimental investigations within and beyond the spike protein. Conclusions This study provides empirical evidence for the existence of important tradeoffs between within-host replication and between-host transmission shaping the fitness landscape of SARS-CoV-2. This method may be used as a fast and scalable means to shortlist large sequence databases for sites under putative multilevel selection which may warrant subsequent confirmatory analyses and experimental confirmation.
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Affiliation(s)
- Vinicius Bonetti Franceschi
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, England, W2 1PG, UK
| | - Erik Volz
- Department of Infectious Disease Epidemiology, School of Public Health, Imperial College London, London, England, W2 1PG, UK
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12
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Machkovech HM, Hahn AM, Garonzik Wang J, Grubaugh ND, Halfmann PJ, Johnson MC, Lemieux JE, O'Connor DH, Piantadosi A, Wei W, Friedrich TC. Persistent SARS-CoV-2 infection: significance and implications. THE LANCET. INFECTIOUS DISEASES 2024; 24:e453-e462. [PMID: 38340735 DOI: 10.1016/s1473-3099(23)00815-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2023] [Revised: 12/14/2023] [Accepted: 12/15/2023] [Indexed: 02/12/2024]
Abstract
SARS-CoV-2 causes persistent infections in a subset of individuals, which is a major clinical and public health problem that should be prioritised for further investigation for several reasons. First, persistent SARS-CoV-2 infection often goes unrecognised, and therefore might affect a substantial number of people, particularly immunocompromised individuals. Second, the formation of tissue reservoirs (including in non-respiratory tissues) might underlie the pathophysiology of the persistent SARS-CoV-2 infection and require new strategies for diagnosis and treatment. Finally, persistent SARS-CoV-2 replication, particularly in the setting of suboptimal immune responses, is a possible source of new, divergent virus variants that escape pre-existing immunity on the individual and population levels. Defining optimal diagnostic and treatment strategies for patients with persistent virus replication and monitoring viral evolution are therefore urgent medical and public health priorities.
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Affiliation(s)
- Heather M Machkovech
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne M Hahn
- Department of Epidemiology of Microbial Diseases, School of Public Health, Yale University, New Haven, CT, USA
| | | | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, School of Public Health, Yale University, New Haven, CT, USA
| | - Peter J Halfmann
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Marc C Johnson
- Department of Molecular Microbiology and Immunology, University of Missouri-School of Medicine, Columbia, MO, USA
| | - Jacob E Lemieux
- Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - David H O'Connor
- Department of Pathology and Laboratory Medicine, School of Medicine and Public Health, School of Veterinary Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Anne Piantadosi
- Department of Pathology and Laboratory Medicine, Emory University School of Medicine, Atlanta, GA, USA
| | - Wanting Wei
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA
| | - Thomas C Friedrich
- Department of Pathobiological Sciences, University of Wisconsin-Madison, Madison, WI, USA.
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13
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Kakee S, Kanai K, Tsuneki-Tokunaga A, Okuno K, Namba N, Tomita K, Chikumi H, Kageyama S. Difference in TMPRSS2 usage by Delta and Omicron variants of SARS-CoV-2: Implication for a sudden increase among children. PLoS One 2024; 19:e0299445. [PMID: 38870131 PMCID: PMC11175390 DOI: 10.1371/journal.pone.0299445] [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: 02/11/2024] [Accepted: 05/07/2024] [Indexed: 06/15/2024] Open
Abstract
It has been postulated from a combination of evidence that a sudden increase in COVID-19 cases among pediatric patients after onset of the Omicron wave was attributed to a reduced requirement for TMPRSS2-mediated entry in pediatric airways with lower expression levels of TMPRSS2. Epidemic strains were isolated from the indigenous population in an area, and the levels of TMPRSS2 required for Delta and Omicron variants were assessed. As a result, Delta variants proliferated fully in cultures of TMPRSS2-positive Vero cells but not in TMPRSS2-negative Vero cell culture (350-fold, Delta vs 9.6-fold, Omicron). There was no obvious age-dependent selection of Omicron strains affected by the TMPRSS2 (9.6-fold, Adults vs. 12-fold, Children). A phylogenetic tree was generated and Blast searches (up to 100 references) for the spread of strains in the study area showed that each strain had almost identical homology (>99.5%) with foreign isolates, although indigenous strains had obvious differences from each other. This suggested that the differences had been present abroad for a long period. Therefore, the lower requirement for TMPRSS2 by Omicron strains might be applicable to epidemic strains globally. In conclusion, the property of TMPRSS2-independent cleavage makes Omicron proliferate with ease and allows epidemics among children with fewer TMPRSS2 on epithelial surfaces of the respiratory organs.
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Affiliation(s)
- Sosuke Kakee
- Division of Virology, Department of Microbiology and Immunology, Faculty of Medicine, Tottori University, Yonago, Japan
- Division of Pediatrics and Perinatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Kyosuke Kanai
- Division of Virology, Department of Microbiology and Immunology, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Akeno Tsuneki-Tokunaga
- Division of Virology, Department of Microbiology and Immunology, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Keisuke Okuno
- Division of Pediatrics and Perinatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Noriyuki Namba
- Division of Pediatrics and Perinatology, Department of Multidisciplinary Internal Medicine, Faculty of Medicine, Tottori University, Yonago, Japan
| | - Katsuyuki Tomita
- Department of Respiratory Medicine, National Hospital Organization Yonago Medical Center, Yonago, Japan
| | | | - Seiji Kageyama
- Division of Virology, Department of Microbiology and Immunology, Faculty of Medicine, Tottori University, Yonago, Japan
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14
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Paull JS, Petros BA, Brock-Fisher TM, Jalbert SA, Selser VM, Messer KS, Dobbins ST, DeRuff KC, Deng D, Springer M, Sabeti PC. Optimisation and evaluation of viral genomic sequencing of SARS-CoV-2 rapid diagnostic tests: a laboratory and cohort-based study. THE LANCET. MICROBE 2024; 5:e468-e477. [PMID: 38621394 PMCID: PMC11322816 DOI: 10.1016/s2666-5247(23)00399-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Revised: 12/04/2023] [Accepted: 12/05/2023] [Indexed: 04/17/2024]
Abstract
BACKGROUND Sequencing of SARS-CoV-2 from rapid diagnostic tests (RDTs) can bolster viral genomic surveillance efforts; however, approaches to maximise and standardise pathogen genome recovery from RDTs remain underdeveloped. We aimed to systematically optimise the elution of genetic material from RDT components and to evaluate the efficacy of RDT sequencing for outbreak investigation. METHODS In this laboratory and cohort-based study we seeded RDTs with inactivated SARS-CoV-2 to optimise the elution of genomic material from RDT lateral flow strips. We measured the effect of changes in buffer type, time in buffer, and rotation on PCR cycle threshold (Ct) value. We recruited individuals older than 18 years residing in the greater Boston area, MA, USA, from July 18 to Nov 5, 2022, via email advertising to students and staff at Harvard University, MA, USA, and via broad social media advertising. All individuals recruited were within 5 days of a positive diagnostic test for SARS-CoV-2; no other relevant exclusion criteria were applied. Each individual completed two RDTs and one PCR swab. On Dec 29, 2022, we also collected RDTs from a convenience sample of individuals who were positive for SARS-CoV-2 and associated with an outbreak at a senior housing facility in MA, USA. We extracted all returned PCR swabs and RDT components (ie, swab, strip, or buffer); samples with a Ct of less than 40 were subject to amplicon sequencing. We compared the efficacy of elution and sequencing across RDT brands and components and used RDT-derived sequences to infer transmission links within the outbreak at the senior housing facility. We conducted metagenomic sequencing of negative RDTs from symptomatic individuals living in the senior housing facility. FINDINGS Neither elution duration of greater than 10 min nor rotation during elution impacted viral titres. Elution in Buffer AVL (Ct=31·4) and Tris-EDTA Buffer (Ct=30·8) were equivalent (p=0·34); AVL outperformed elution in lysis buffer and 50% lysis buffer (Ct=40·0, p=0·0029 for both) as well as Universal Viral Transport Medium (Ct=36·7, p=0·079). Performance of RDT strips was poorer than that of matched PCR swabs (mean Ct difference 10·2 [SD 4·3], p<0·0001); however, RDT swabs performed similarly to PCR swabs (mean Ct difference 4·1 [5·2], p=0·055). No RDT brand significantly outperformed another. Across sample types, viral load predicted the viral genome assembly length. We assembled greater than 80% complete genomes from 12 of 17 RDT-derived swabs, three of 18 strips, and four of 11 residual buffers. We generated outbreak-associated SARS-CoV-2 genomes using both amplicon and metagenomic sequencing and identified multiple introductions of the virus that resulted in downstream transmission. INTERPRETATION RDT-derived swabs are a reasonable alternative to PCR swabs for viral genomic surveillance and outbreak investigation. RDT-derived lateral flow strips yield accurate, but significantly fewer, viral reads than matched PCR swabs. Metagenomic sequencing of negative RDTs can identify viruses that might underlie patient symptoms. FUNDING The National Science Foundation, the Hertz Foundation, the National Institute of General Medical Sciences, Harvard Medical School, the Howard Hughes Medical Institute, the US Centers for Disease Control and Prevention, the Broad Institute and the National Institute of Allergy and Infectious Diseases.
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Affiliation(s)
- Jillian S Paull
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Brittany A Petros
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Division of Health Sciences and Technology, Harvard Medical School and MIT, Cambridge, MA, USA; Harvard/MIT MD-PhD Program, Harvard Medical School, Boston, MA, USA.
| | - Taylor M Brock-Fisher
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA
| | | | | | | | | | | | - Davy Deng
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA, USA
| | - Pardis C Sabeti
- Broad Institute of MIT and Harvard, Cambridge, MA, USA; Howard Hughes Medical Institute, Chevy Chase, MD, USA; Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, USA; Department of Immunology and Infectious Diseases, Harvard T H Chan School of Public Health, Harvard University, Boston, MA, USA.
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15
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Sobel Leonard A, Mendoza L, McFarland AG, Marques AD, Everett JK, Moncla L, Bushman FD, Odom John AR, Hensley SE. Within-host influenza viral diversity in the pediatric population as a function of age, vaccine, and health status. Virus Evol 2024; 10:veae034. [PMID: 38859985 PMCID: PMC11163376 DOI: 10.1093/ve/veae034] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2023] [Revised: 02/23/2024] [Accepted: 04/22/2024] [Indexed: 06/12/2024] Open
Abstract
Seasonal influenza virus predominantly evolves through antigenic drift, marked by the accumulation of mutations at antigenic sites. Because of antigenic drift, influenza vaccines are frequently updated, though their efficacy may still be limited due to strain mismatches. Despite the high levels of viral diversity observed across populations, most human studies reveal limited intrahost diversity, leaving the origin of population-level viral diversity unclear. Previous studies show host characteristics, such as immunity, might affect within-host viral evolution. Here we investigate influenza A viral diversity in children aged between 6 months and 18 years. Influenza virus evolution in children is less well characterized than in adults, yet may be associated with higher levels of viral diversity given the lower level of pre-existing immunity and longer durations of infection in children. We obtained influenza isolates from banked influenza A-positive nasopharyngeal swabs collected at the Children's Hospital of Philadelphia during the 2017-18 influenza season. Using next-generation sequencing, we evaluated the population of influenza viruses present in each sample. We characterized within-host viral diversity using the number and frequency of intrahost single-nucleotide variants (iSNVs) detected in each sample. We related viral diversity to clinical metadata, including subjects' age, vaccination status, and comorbid conditions, as well as sample metadata such as virus strain and cycle threshold. Consistent with previous studies, most samples contained low levels of diversity with no clear association between the subjects' age, vaccine status, or health status. Further, there was no enrichment of iSNVs near known antigenic sites. Taken together, these findings are consistent with previous observations that the majority of intrahost influenza virus infection is characterized by low viral diversity without evidence of diversifying selection.
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Affiliation(s)
- Ashley Sobel Leonard
- Division of Infectious Diseases, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Lydia Mendoza
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Alexander G McFarland
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Andrew D Marques
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - John K Everett
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Louise Moncla
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, 3800 Spruce St., Philadelphia, PA 19104, USA
| | - Frederic D Bushman
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Audrey R Odom John
- Division of Infectious Diseases, Children’s Hospital of Philadelphia, 3401 Civic Center Blvd., Philadelphia, PA 19104, USA
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
- Department of Pathobiology, School of Veterinary Medicine, University of Pennsylvania, 3800 Spruce St., Philadelphia, PA 19104, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
| | - Scott E Hensley
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, 3400 Civic Center Blvd., Philadelphia, PA 19104, USA
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16
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Iketani S, Ho DD. SARS-CoV-2 resistance to monoclonal antibodies and small-molecule drugs. Cell Chem Biol 2024; 31:632-657. [PMID: 38640902 PMCID: PMC11084874 DOI: 10.1016/j.chembiol.2024.03.008] [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: 09/07/2023] [Revised: 03/18/2024] [Accepted: 03/21/2024] [Indexed: 04/21/2024]
Abstract
Over four years have passed since the beginning of the COVID-19 pandemic. The scientific response has been rapid and effective, with many therapeutic monoclonal antibodies and small molecules developed for clinical use. However, given the ability for viruses to become resistant to antivirals, it is perhaps no surprise that the field has identified resistance to nearly all of these compounds. Here, we provide a comprehensive review of the resistance profile for each of these therapeutics. We hope that this resource provides an atlas for mutations to be aware of for each agent, particularly as a springboard for considerations for the next generation of antivirals. Finally, we discuss the outlook and thoughts for moving forward in how we continue to manage this, and the next, pandemic.
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Affiliation(s)
- Sho Iketani
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Division of Infectious Diseases, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA
| | - David D Ho
- Aaron Diamond AIDS Research Center, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Division of Infectious Diseases, Department of Medicine, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA; Department of Microbiology and Immunology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA.
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17
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Marques AD, Graham-Wooten J, Fitzgerald AS, Sobel Leonard A, Cook EJ, Everett JK, Rodino KG, Moncla LH, Kelly BJ, Collman RG, Bushman FD. SARS-CoV-2 evolution during prolonged infection in immunocompromised patients. mBio 2024; 15:e0011024. [PMID: 38364100 PMCID: PMC10936176 DOI: 10.1128/mbio.00110-24] [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: 01/23/2024] [Accepted: 01/25/2024] [Indexed: 02/18/2024] Open
Abstract
Prolonged infection with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in immunocompromised patients provides an opportunity for viral evolution, potentially leading to the generation of new pathogenic variants. To investigate the pathways of viral evolution, we carried out a study on five patients experiencing prolonged SARS-CoV-2 infection (quantitative polymerase chain reaction-positive for 79-203 days) who were immunocompromised due to treatment for lymphoma or solid organ transplantation. For each timepoint analyzed, we generated at least two independent viral genome sequences to assess the heterogeneity and control for sequencing error. Four of the five patients likely had prolonged infection; the fifth apparently experienced a reinfection. The rates of accumulation of substitutions in the viral genome per day were higher in hospitalized patients with prolonged infection than those estimated for the community background. The spike coding region accumulated a significantly greater number of unique mutations than other viral coding regions, and the mutation density was higher. Two patients were treated with monoclonal antibodies (bebtelovimab and sotrovimab); by the next sampled timepoint, each virus population showed substitutions associated with monoclonal antibody resistance as the dominant forms (spike K444N and spike E340D). All patients received remdesivir, but remdesivir-resistant substitutions were not detected. These data thus help elucidate the trends of emergence, evolution, and selection of mutational variants within long-term infected immunocompromised individuals. IMPORTANCE SARS-CoV-2 is responsible for a global pandemic, driven in part by the emergence of new viral variants. Where do these new variants come from? One model is that long-term viral persistence in infected individuals allows for viral evolution in response to host pressures, resulting in viruses more likely to replicate efficiently in humans. In this study, we characterize replication in several hospitalized and long-term infected individuals, documenting efficient pathways of viral evolution.
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Affiliation(s)
- Andrew D. Marques
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Jevon Graham-Wooten
- Division of Pulmonary, Allergy, and Critical Care, Philadelphia, Pennsylvania, USA
| | | | - Ashley Sobel Leonard
- Division of Infectious Diseases, Children’s Hospital of Philadelphia, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Emma J. Cook
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - John K. Everett
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Kyle G. Rodino
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Louise H. Moncla
- Department of Pathobiology, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Brendan J. Kelly
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Ronald G. Collman
- Division of Pulmonary, Allergy, and Critical Care, Philadelphia, Pennsylvania, USA
| | - Frederic D. Bushman
- Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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18
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Delgado S, Somovilla P, Ferrer-Orta C, Martínez-González B, Vázquez-Monteagudo S, Muñoz-Flores J, Soria ME, García-Crespo C, de Ávila AI, Durán-Pastor A, Gadea I, López-Galíndez C, Moran F, Lorenzo-Redondo R, Verdaguer N, Perales C, Domingo E. Incipient functional SARS-CoV-2 diversification identified through neural network haplotype maps. Proc Natl Acad Sci U S A 2024; 121:e2317851121. [PMID: 38416684 PMCID: PMC10927536 DOI: 10.1073/pnas.2317851121] [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: 10/16/2023] [Accepted: 01/08/2024] [Indexed: 03/01/2024] Open
Abstract
Since its introduction in the human population, SARS-CoV-2 has evolved into multiple clades, but the events in its intrahost diversification are not well understood. Here, we compare three-dimensional (3D) self-organized neural haplotype maps (SOMs) of SARS-CoV-2 from thirty individual nasopharyngeal diagnostic samples obtained within a 19-day interval in Madrid (Spain), at the time of transition between clades 19 and 20. SOMs have been trained with the haplotype repertoire present in the mutant spectra of the nsp12- and spike (S)-coding regions. Each SOM consisted of a dominant neuron (displaying the maximum frequency), surrounded by a low-frequency neuron cloud. The sequence of the master (dominant) neuron was either identical to that of the reference Wuhan-Hu-1 genome or differed from it at one nucleotide position. Six different deviant haplotype sequences were identified among the master neurons. Some of the substitutions in the neural clouds affected critical sites of the nsp12-nsp8-nsp7 polymerase complex and resulted in altered kinetics of RNA synthesis in an in vitro primer extension assay. Thus, the analysis has identified mutations that are relevant to modification of viral RNA synthesis, present in the mutant clouds of SARS-CoV-2 quasispecies. These mutations most likely occurred during intrahost diversification in several COVID-19 patients, during an initial stage of the pandemic, and within a brief time period.
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Affiliation(s)
- Soledad Delgado
- Departamento de Sistemas Informáticos, Escuela Técnica Superior de Ingeniería de Sistemas Informáticos, Universidad Politécnica de Madrid, Madrid28031, Spain
| | - Pilar Somovilla
- Microbes in Health and Welfare Program, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
- Departamento de Biología Molecular, Universidad Autónoma de Madrid, Madrid28049, Spain
| | - Cristina Ferrer-Orta
- Structural and Molecular Biology Department, Institut de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas, Barcelona08028, Spain
| | - Brenda Martínez-González
- Department of Molecular and Cell Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid, Madrid28040, Spain
| | - Sergi Vázquez-Monteagudo
- Structural and Molecular Biology Department, Institut de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas, Barcelona08028, Spain
| | | | - María Eugenia Soria
- Microbes in Health and Welfare Program, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid, Madrid28040, Spain
| | - Carlos García-Crespo
- Microbes in Health and Welfare Program, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
| | - Ana Isabel de Ávila
- Microbes in Health and Welfare Program, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
| | - Antoni Durán-Pastor
- Department of Molecular and Cell Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
| | - Ignacio Gadea
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid, Madrid28040, Spain
| | - Cecilio López-Galíndez
- Unidad de Virología Molecular, Laboratorio de Referencia e Investigación en retrovirus, Centro Nacional de Microbiología, Instituto de salud Carlos III, Majadahonda28222, Spain
| | - Federico Moran
- Departamento de Bioquímica y Biología Molecular, Universidad Complutense de Madrid, Madrid28040, Spain
| | - Ramon Lorenzo-Redondo
- Department of Medicine, Division of Infectious Diseases, Northwestern University Feinberg School of Medicine, Center for Pathogen Genomics and Microbial Evolution, Northwestern University Havey Institute for Global Health, Chicago, IL60611
| | - Nuria Verdaguer
- Structural and Molecular Biology Department, Institut de Biología Molecular de Barcelona, Consejo Superior de Investigaciones Científicas, Barcelona08028, Spain
| | - Celia Perales
- Department of Molecular and Cell Biology, Centro Nacional de Biotecnología, Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid, Madrid28040, Spain
| | - Esteban Domingo
- Microbes in Health and Welfare Program, Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas, Madrid28049, Spain
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19
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Atamer Balkan B, Chang Y, Sparnaaij M, Wouda B, Boschma D, Liu Y, Yuan Y, Daamen W, de Jong MCM, Teberg C, Schachtschneider K, Sikkema RS, van Veen L, Duives D, ten Bosch QA. The multi-dimensional challenges of controlling respiratory virus transmission in indoor spaces: Insights from the linkage of a microscopic pedestrian simulation and SARS-CoV-2 transmission model. PLoS Comput Biol 2024; 20:e1011956. [PMID: 38547311 PMCID: PMC11003685 DOI: 10.1371/journal.pcbi.1011956] [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: 07/17/2023] [Revised: 04/09/2024] [Accepted: 02/29/2024] [Indexed: 04/11/2024] Open
Abstract
SARS-CoV-2 transmission in indoor spaces, where most infection events occur, depends on the types and duration of human interactions, among others. Understanding how these human behaviours interface with virus characteristics to drive pathogen transmission and dictate the outcomes of non-pharmaceutical interventions is important for the informed and safe use of indoor spaces. To better understand these complex interactions, we developed the Pedestrian Dynamics-Virus Spread model (PeDViS), an individual-based model that combines pedestrian behaviour models with virus spread models incorporating direct and indirect transmission routes. We explored the relationships between virus exposure and the duration, distance, respiratory behaviour, and environment in which interactions between infected and uninfected individuals took place and compared this to benchmark 'at risk' interactions (1.5 metres for 15 minutes). When considering aerosol transmission, individuals adhering to distancing measures may be at risk due to the buildup of airborne virus in the environment when infected individuals spend prolonged time indoors. In our restaurant case, guests seated at tables near infected individuals were at limited risk of infection but could, particularly in poorly ventilated places, experience risks that surpass that of benchmark interactions. Combining interventions that target different transmission routes can aid in accumulating impact, for instance by combining ventilation with face masks. The impact of such combined interventions depends on the relative importance of transmission routes, which is hard to disentangle and highly context dependent. This uncertainty should be considered when assessing transmission risks upon different types of human interactions in indoor spaces. We illustrated the multi-dimensionality of indoor SARS-CoV-2 transmission that emerges from the interplay of human behaviour and the spread of respiratory viruses. A modelling strategy that incorporates this in risk assessments can help inform policy makers and citizens on the safe use of indoor spaces with varying inter-human interactions.
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Affiliation(s)
- Büsra Atamer Balkan
- Quantitative Veterinary Epidemiology, Wageningen University & Research, Wageningen, The Netherlands
| | - You Chang
- Quantitative Veterinary Epidemiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Martijn Sparnaaij
- Department of Transport & Planning, Delft University of Technology, Delft, The Netherlands
| | - Berend Wouda
- Gamelab, Delft University of Technology, Delft, The Netherlands
| | - Doris Boschma
- Gamelab, Delft University of Technology, Delft, The Netherlands
| | - Yangfan Liu
- Quantitative Veterinary Epidemiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Yufei Yuan
- Department of Transport & Planning, Delft University of Technology, Delft, The Netherlands
| | - Winnie Daamen
- Department of Transport & Planning, Delft University of Technology, Delft, The Netherlands
| | - Mart C. M. de Jong
- Quantitative Veterinary Epidemiology, Wageningen University & Research, Wageningen, The Netherlands
| | - Colin Teberg
- Steady State Scientific Computing, Chicago, Illinois, United States of America
| | | | | | - Linda van Veen
- Gamelab, Delft University of Technology, Delft, The Netherlands
| | - Dorine Duives
- Department of Transport & Planning, Delft University of Technology, Delft, The Netherlands
| | - Quirine A. ten Bosch
- Quantitative Veterinary Epidemiology, Wageningen University & Research, Wageningen, The Netherlands
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20
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Korosec CS, Wahl LM, Heffernan JM. Within-host evolution of SARS-CoV-2: how often are de novo mutations transmitted from symptomatic infections? Virus Evol 2024; 10:veae006. [PMID: 38425472 PMCID: PMC10904108 DOI: 10.1093/ve/veae006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Revised: 12/20/2023] [Accepted: 01/12/2024] [Indexed: 03/02/2024] Open
Abstract
Despite a relatively low mutation rate, the large number of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections has allowed for substantial genetic change, leading to a multitude of emerging variants. Using a recently determined mutation rate (per site replication), as well as within-host parameter estimates for symptomatic SARS-CoV-2 infection, we apply a stochastic transmission-bottleneck model to describe the survival probability of de novo SARS-CoV-2 mutations as a function of bottleneck size and selection coefficient. For narrow bottlenecks, we find that mutations affecting per-target-cell attachment rate (with phenotypes associated with fusogenicity and ACE2 binding) have similar transmission probabilities to mutations affecting viral load clearance (with phenotypes associated with humoral evasion). We further find that mutations affecting the eclipse rate (with phenotypes associated with reorganization of cellular metabolic processes and synthesis of viral budding precursor material) are highly favoured relative to all other traits examined. We find that mutations leading to reduced removal rates of infected cells (with phenotypes associated with innate immune evasion) have limited transmission advantage relative to mutations leading to humoral evasion. Predicted transmission probabilities, however, for mutations affecting innate immune evasion are more consistent with the range of clinically estimated household transmission probabilities for de novo mutations. This result suggests that although mutations affecting humoral evasion are more easily transmitted when they occur, mutations affecting innate immune evasion may occur more readily. We examine our predictions in the context of a number of previously characterized mutations in circulating strains of SARS-CoV-2. Our work offers both a null model for SARS-CoV-2 mutation rates and predicts which aspects of viral life history are most likely to successfully evolve, despite low mutation rates and repeated transmission bottlenecks.
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Affiliation(s)
- Chapin S Korosec
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
- Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
| | - Lindi M Wahl
- Applied Mathematics, Western University, 1151 Richmond St, London, ON N6A 5B7, Canada
| | - Jane M Heffernan
- Modelling Infection and Immunity Lab, Mathematics and Statistics, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
- Centre for Disease Modelling, Mathematics and Statistics, York University, 4700 Keele St, Toronto, ON M3J 1P3, Canada
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21
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Banga J, Brock-Fisher T, Petros BA, Dai EY, Leonelli AT, Dobbins ST, Messer KS, Nathanson AB, Capone A, Littlehale N, Appiah-Danquah V, Dim S, Moreno GK, Crowther M, Lee KA, DeRuff KC, MacInnis BL, Springer M, Sabeti PC, Stephenson KE. Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Household Transmission during the Omicron Era in Massachusetts: A Prospective, Case-Ascertained Study using Genomic Epidemiology. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.02.05.24302348. [PMID: 38370621 PMCID: PMC10871383 DOI: 10.1101/2024.02.05.24302348] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/20/2024]
Abstract
Background Households are a major setting for SARS-CoV-2 infections, but there remains a lack of knowledge regarding the dynamics of viral transmission, particularly in the setting of widespread pre-existing SARS-CoV-2 immunity and evolving variants. Methods We conducted a prospective, case-ascertained household transmission study in the greater Boston area in March-July 2022. Anterior nasal swabs, along with clinical and demographic data, were collected for 14 days. Nasal swabs were tested for SARS-CoV-2 by PCR. Whole genome sequencing was performed on high-titer samples. Results We enrolled 33 households in a primary analysis set, with a median age of participants of 25 years old (range 2-66); 98% of whom had received at least 2 doses of a COVID-19 vaccine. 58% of households had a secondary case during follow up and the secondary attack rate (SAR) for contacts infected was 39%. We further examined a strict analysis set of 21 households that had only 1 PCR+ case at baseline, finding an SAR of 22.5%. Genomic epidemiology further determined that there were multiple sources of infection for household contacts, including the index case and outside introductions. When limiting estimates to only highly probable transmissions given epidemiologic and genomic data, the SAR was 18.4%. Conclusions Household contacts of a person newly diagnosed with COVID-19 are at high risk for SARS-CoV-2 infection in the following 2 weeks. This is, however, not only due to infection from the household index case, but also because the presence of an infected household member implies increased SARS-CoV-2 community transmission. Further studies to understand and mitigate household transmission are needed.
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Affiliation(s)
- Jaspreet Banga
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Taylor Brock-Fisher
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA
| | - Brittany A. Petros
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard/MIT MD-PhD Program, Boston, MA, USA
| | - Eric Y. Dai
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Ariana T. Leonelli
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | | | - Audrey B. Nathanson
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Amelia Capone
- Beth Israel Lahey Health Primary Care, Chelsea, MA, USA
| | | | - Viola Appiah-Danquah
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Siang Dim
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Gage K. Moreno
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Maura Crowther
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | - Kannon A. Lee
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | | | - Michael Springer
- Department of Systems Biology, Harvard Medical School, Boston, MA, USA
| | - Pardis C. Sabeti
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Organismic and Evolutionary Biology, Faculty of Arts and Sciences, Harvard University, Cambridge, MA, USA
- Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Howard Hughes Medical Institute, Chevy Chase, MD, USA
| | - Kathryn E. Stephenson
- Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Boston, MA, USA
- Harvard Medical School, Boston, MA, USA
- Ragon Institute of Massachusetts General Hospital (MGH), Massachusetts Institute of Technology (MIT) and Harvard, Cambridge, MA, USA
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22
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Hodoameda P, Ebel GD, Mukhopadhyay S, Clem RJ. Extreme infectious titer variability in individual Aedes aegypti mosquitoes infected with Sindbis virus is associated with both differences in virus population structure and dramatic disparities in specific infectivity. PLoS Pathog 2024; 20:e1012047. [PMID: 38412195 PMCID: PMC10923411 DOI: 10.1371/journal.ppat.1012047] [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: 07/15/2023] [Revised: 03/08/2024] [Accepted: 02/13/2024] [Indexed: 02/29/2024] Open
Abstract
Variability in how individuals respond to pathogens is a hallmark of infectious disease, yet the basis for individual variation in host response is often poorly understood. The titer of infectious virus among individual mosquitoes infected with arboviruses is frequently observed to vary by several orders of magnitude in a single experiment, even when the mosquitoes are highly inbred. To better understand the basis for this titer variation, we sequenced populations of Sindbis virus (SINV) obtained from individual infected Aedes aegypti mosquitoes that, despite being from a highly inbred laboratory colony, differed in their titers of infectious virus by approximately 10,000-fold. We observed genetic differences between these virus populations that indicated the virus present in the midguts of low titer mosquitoes was less fit than that of high titer mosquitoes, possibly due to founder effects that occurred during midgut infection. Furthermore, we found dramatic differences in the specific infectivity or SI (the ratio of infectious units/viral genome equivalents) between these virus populations, with the SI of low titer mosquitoes being up to 10,000-fold lower than that of high titer mosquitoes. Despite having similar amounts of viral genomes, low titer mosquitoes appeared to contain less viral particles, suggesting that viral genomes were packaged into virions less efficiently than in high titer mosquitoes. Finally, antibiotic treatment, which has been shown to suppress mosquito antiviral immunity, caused an increase in SI. Our results indicate that the extreme variation that is observed in SINV infectious titer between individual Ae. aegypti mosquitoes is due to both genetic differences between virus populations and to differences in the proportion of genomes that are packaged into infectious particles.
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Affiliation(s)
- Peter Hodoameda
- Division of Biology, Kansas State University, Manhattan, Kansas United States of America
| | - Gregory D. Ebel
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, Colorado United States of America
| | - Suchetana Mukhopadhyay
- Department of Biology, Indiana University, Bloomington, Indiana United States of America
| | - Rollie J. Clem
- Division of Biology, Kansas State University, Manhattan, Kansas United States of America
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23
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Ghafari M, Hall M, Golubchik T, Ayoubkhani D, House T, MacIntyre-Cockett G, Fryer HR, Thomson L, Nurtay A, Kemp SA, Ferretti L, Buck D, Green A, Trebes A, Piazza P, Lonie LJ, Studley R, Rourke E, Smith DL, Bashton M, Nelson A, Crown M, McCann C, Young GR, Santos RAND, Richards Z, Tariq MA, Cahuantzi R, Barrett J, Fraser C, Bonsall D, Walker AS, Lythgoe K. Prevalence of persistent SARS-CoV-2 in a large community surveillance study. Nature 2024; 626:1094-1101. [PMID: 38383783 PMCID: PMC10901734 DOI: 10.1038/s41586-024-07029-4] [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: 01/29/2023] [Accepted: 01/04/2024] [Indexed: 02/23/2024]
Abstract
Persistent SARS-CoV-2 infections may act as viral reservoirs that could seed future outbreaks1-5, give rise to highly divergent lineages6-8 and contribute to cases with post-acute COVID-19 sequelae (long COVID)9,10. However, the population prevalence of persistent infections, their viral load kinetics and evolutionary dynamics over the course of infections remain largely unknown. Here, using viral sequence data collected as part of a national infection survey, we identified 381 individuals with SARS-CoV-2 RNA at high titre persisting for at least 30 days, of which 54 had viral RNA persisting at least 60 days. We refer to these as 'persistent infections' as available evidence suggests that they represent ongoing viral replication, although the persistence of non-replicating RNA cannot be ruled out in all. Individuals with persistent infection had more than 50% higher odds of self-reporting long COVID than individuals with non-persistent infection. We estimate that 0.1-0.5% of infections may become persistent with typically rebounding high viral loads and last for at least 60 days. In some individuals, we identified many viral amino acid substitutions, indicating periods of strong positive selection, whereas others had no consensus change in the sequences for prolonged periods, consistent with weak selection. Substitutions included mutations that are lineage defining for SARS-CoV-2 variants, at target sites for monoclonal antibodies and/or are commonly found in immunocompromised people11-14. This work has profound implications for understanding and characterizing SARS-CoV-2 infection, epidemiology and evolution.
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Affiliation(s)
- Mahan Ghafari
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Department of Biology, University of Oxford, Oxford, UK.
- Pandemic Science Institute, University of Oxford, Oxford, UK.
| | - Matthew Hall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
| | - Tanya Golubchik
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Sydney Infectious Diseases Institute (Sydney ID), School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Sydney, New South Wales, Australia
| | - Daniel Ayoubkhani
- Office for National Statistics, Newport, UK
- Leicester Real World Evidence Unit, Diabetes Research Centre, University of Leicester, Leicester, UK
| | - Thomas House
- Department of Mathematics, University of Manchester, Manchester, UK
| | - George MacIntyre-Cockett
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Helen R Fryer
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Laura Thomson
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
| | - Anel Nurtay
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Steven A Kemp
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Biology, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
| | - Luca Ferretti
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
| | - David Buck
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Angie Green
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Amy Trebes
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Paolo Piazza
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | - Lorne J Lonie
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
| | | | | | - Darren L Smith
- The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Matthew Bashton
- The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Andrew Nelson
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Matthew Crown
- The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Clare McCann
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Gregory R Young
- The Hub for Biotechnology in the Built Environment, Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Rui Andre Nunes Dos Santos
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Zack Richards
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | - Mohammad Adnan Tariq
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Newcastle upon Tyne, UK
| | | | | | - Christophe Fraser
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
- Wellcome Sanger Institute, Cambridge, UK
| | - David Bonsall
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Pandemic Science Institute, University of Oxford, Oxford, UK
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, NIHR Biomedical Research Centre, University of Oxford, Oxford, UK
- Oxford University Hospitals NHS Foundation Trust, John Radcliffe Hospital, Headington, Oxford, UK
| | - Ann Sarah Walker
- Nuffield Department of Medicine, University of Oxford, Oxford, UK
- The National Institute for Health Research Health Protection Research Unit in Healthcare Associated Infections and Antimicrobial Resistance at the University of Oxford, Oxford, UK
- The National Institute for Health Research Oxford Biomedical Research Centre, University of Oxford, Oxford, UK
- MRC Clinical Trials Unit at UCL, UCL, London, UK
| | - Katrina Lythgoe
- Big Data Institute, Nuffield Department of Medicine, University of Oxford, Oxford, UK.
- Department of Biology, University of Oxford, Oxford, UK.
- Pandemic Science Institute, University of Oxford, Oxford, UK.
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24
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Li Y, Choudhary MC, Regan J, Boucau J, Nathan A, Speidel T, Liew MY, Edelstein GE, Kawano Y, Uddin R, Deo R, Marino C, Getz MA, Reynolds Z, Barry M, Gilbert RF, Tien D, Sagar S, Vyas TD, Flynn JP, Hammond SP, Novack LA, Choi B, Cernadas M, Wallace ZS, Sparks JA, Vyas JM, Seaman MS, Gaiha GD, Siedner MJ, Barczak AK, Lemieux JE, Li JZ. SARS-CoV-2 viral clearance and evolution varies by type and severity of immunodeficiency. Sci Transl Med 2024; 16:eadk1599. [PMID: 38266109 PMCID: PMC10982957 DOI: 10.1126/scitranslmed.adk1599] [Citation(s) in RCA: 32] [Impact Index Per Article: 32.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2023] [Accepted: 12/18/2023] [Indexed: 01/26/2024]
Abstract
Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection, but the immune defects that predispose an individual to persistent coronavirus disease 2019 (COVID-19) remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median times to nasal viral RNA and culture clearance in individuals with severe immunosuppression due to hematologic malignancy or transplant (S-HT) were 72 and 40 days, respectively, both of which were significantly longer than clearance rates in individuals with severe immunosuppression due to autoimmunity or B cell deficiency (S-A), individuals with nonsevere immunodeficiency, and nonimmunocompromised groups (P < 0.01). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing resistance against therapeutic monoclonal antibodies. Both S-HT and S-A participants had diminished SARS-CoV-2-specific humoral responses, whereas only the S-HT group had reduced T cell-mediated responses. This highlights the varied risk of persistent COVID-19 across distinct immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.
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Affiliation(s)
- Yijia Li
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- University of Pittsburgh Medical Center, Pittsburgh, PA 15213, USA
| | - Manish C. Choudhary
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - James Regan
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
- Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Julie Boucau
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Anusha Nathan
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
- Program in Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Boston, MA 02115, USA
| | - Tessa Speidel
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - May Yee Liew
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Gregory E. Edelstein
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Yumeko Kawano
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Rockib Uddin
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Rinki Deo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Caitlin Marino
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Matthew A. Getz
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Zahra Reynolds
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Mamadou Barry
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Rebecca F. Gilbert
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Dessie Tien
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Shruti Sagar
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Tammy D. Vyas
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - James P. Flynn
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Sarah P. Hammond
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Lewis A. Novack
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Bina Choi
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Manuela Cernadas
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Zachary S. Wallace
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Jeffrey A. Sparks
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
| | - Jatin M. Vyas
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Michael S. Seaman
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA 02215, USA
| | - Gaurav D. Gaiha
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Mark J. Siedner
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
| | - Amy K. Barczak
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
| | - Jacob E. Lemieux
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA 02114, USA
- Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | - Jonathan Z. Li
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA
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25
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Farjo M, Koelle K, Martin MA, Gibson LL, Walden KKO, Rendon G, Fields CJ, Alnaji FG, Gallagher N, Luo CH, Mostafa HH, Manabe YC, Pekosz A, Smith RL, McManus DD, Brooke CB. Within-host evolutionary dynamics and tissue compartmentalization during acute SARS-CoV-2 infection. J Virol 2024; 98:e0161823. [PMID: 38174928 PMCID: PMC10805032 DOI: 10.1128/jvi.01618-23] [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: 10/16/2023] [Accepted: 12/01/2023] [Indexed: 01/05/2024] Open
Abstract
The global evolution of SARS-CoV-2 depends in part upon the evolutionary dynamics within individual hosts with varying immune histories. To characterize the within-host evolution of acute SARS-CoV-2 infection, we sequenced saliva and nasal samples collected daily from vaccinated and unvaccinated individuals early during infection. We show that longitudinal sampling facilitates high-confidence genetic variant detection and reveals evolutionary dynamics missed by less-frequent sampling strategies. Within-host dynamics in both unvaccinated and vaccinated individuals appeared largely stochastic; however, in rare cases, minor genetic variants emerged to frequencies sufficient for forward transmission. Finally, we detected significant genetic compartmentalization of viral variants between saliva and nasal swab sample sites in many individuals. Altogether, these data provide a high-resolution profile of within-host SARS-CoV-2 evolutionary dynamics.IMPORTANCEWe detail the within-host evolutionary dynamics of SARS-CoV-2 during acute infection in 31 individuals using daily longitudinal sampling. We characterized patterns of mutational accumulation for unvaccinated and vaccinated individuals, and observed that temporal variant dynamics in both groups were largely stochastic. Comparison of paired nasal and saliva samples also revealed significant genetic compartmentalization between tissue environments in multiple individuals. Our results demonstrate how selection, genetic drift, and spatial compartmentalization all play important roles in shaping the within-host evolution of SARS-CoV-2 populations during acute infection.
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Affiliation(s)
- Mireille Farjo
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, Georgia, USA
| | - Michael A. Martin
- Department of Biology, Emory University, Atlanta, Georgia, USA
- Population Biology, Ecology, and Evolution Graduate Program, Emory University, Atlanta, Georgia, USA
| | - Laura L. Gibson
- Division of Infectious Diseases and Immunology, Department of Medicine, University of Massachusetts Medical School, Worcester, Massachusetts, USA
- Department of Pediatrics, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Kimberly K. O. Walden
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Gloria Rendon
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Christopher J. Fields
- High-Performance Biological Computing at the Roy J. Carver Biotechnology Center, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Fadi G. Alnaji
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - Nicholas Gallagher
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Chun Huai Luo
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Heba H. Mostafa
- Division of Medical Microbiology, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | - Yukari C. Manabe
- Division of Infectious Disease, Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland, USA
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Andrew Pekosz
- W. Harry Feinstone Department of Molecular Microbiology and Immunology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
| | - Rebecca L. Smith
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Department of Pathobiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carle Illinois College of Medicine, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
| | - David D. McManus
- Division of Cardiology, University of Massachusetts Medical School, Worcester, Massachusetts, USA
| | - Christopher B. Brooke
- Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
- Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA
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26
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Shi YT, Harris JD, Martin MA, Koelle K. Transmission Bottleneck Size Estimation from De Novo Viral Genetic Variation. Mol Biol Evol 2024; 41:msad286. [PMID: 38158742 PMCID: PMC10798134 DOI: 10.1093/molbev/msad286] [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: 08/14/2023] [Revised: 12/15/2023] [Accepted: 12/19/2023] [Indexed: 01/03/2024] Open
Abstract
Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, these approaches have the potential to substantially underestimate true transmission bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arise de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these 2 respiratory viruses.
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Affiliation(s)
| | | | - Michael A Martin
- Department of Biology, Emory University, Atlanta, GA, USA
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, GA, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, USA
- Emory Center of Excellence for Influenza Research and Response (CEIRR), Atlanta, GA, USA
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27
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Holmes KE, VanInsberghe D, Ferreri LM, Elie B, Ganti K, Lee CY, Lowen AC. Viral expansion after transfer is a primary driver of influenza A virus transmission bottlenecks. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.11.19.567585. [PMID: 38014182 PMCID: PMC10680852 DOI: 10.1101/2023.11.19.567585] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/29/2023]
Abstract
For many viruses, narrow bottlenecks acting during transmission sharply reduce genetic diversity in a recipient host relative to the donor. Since genetic diversity represents adaptive potential, such losses of diversity are though to limit the opportunity for viral populations to undergo antigenic change and other adaptive processes. Thus, a detailed picture of evolutionary dynamics during transmission is critical to understanding the forces driving viral evolution at an epidemiologic scale. To advance this understanding, we used a novel barcoded virus library and a guinea pig model of transmission to decipher where in the transmission process diversity is lost for influenza A viruses. In inoculated guinea pigs, we show that a high level of viral genetic diversity is maintained across time. Continuity in the barcodes detected furthermore indicates that stochastic effects are not pronounced within inoculated hosts. Importantly, in both aerosol-exposed and direct contact-exposed animals, we observed many barcodes at the earliest time point(s) positive for infectious virus, indicating robust transfer of diversity through the environment. This high viral diversity is short-lived, however, with a sharp decline seen 1-2 days after initiation of infection. Although major losses of diversity at transmission are well described for influenza A virus, our data indicate that events that occur following viral transfer and during the earliest stages of natural infection have a predominant role in this process. This finding suggests that immune selection may have greater opportunity to operate during influenza A transmission than previously recognized.
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Affiliation(s)
- Katie E. Holmes
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
| | - David VanInsberghe
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
| | - Lucas M. Ferreri
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
| | - Baptiste Elie
- MIVEGEC, CNRS, IRD, Université de Montpellier, Montpellier, France
| | - Ketaki Ganti
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
| | - Chung-Young Lee
- Department of Microbiology, School of Medicine, Kyungpook National University, Jung-gu, Daegu, Republic of Korea
| | - Anice C. Lowen
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA, USA
- Emory Center of Excellence for Influenza Research and Response (CEIRR), Atlanta, GA, USA
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28
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Domingo E, Martínez-González B, García-Crespo C, Somovilla P, de Ávila AI, Soria ME, Durán-Pastor A, Perales C. Puzzles, challenges, and information reservoir of SARS-CoV-2 quasispecies. J Virol 2023; 97:e0151123. [PMID: 38092661 PMCID: PMC10734546 DOI: 10.1128/jvi.01511-23] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2023] Open
Abstract
Upon the emergence of SARS-CoV-2 in the human population, it was conjectured that for this coronavirus the dynamic intra-host heterogeneity typical of RNA viruses would be toned down. Nothing of this sort is observed. Here we review the main observations on the complexity and diverse composition of SARS-CoV-2 mutant spectra sampled from infected patients, within the framework of quasispecies dynamics. The analyses suggest that the information provided by myriads of genomic sequences within infected individuals may have a predictive value of the genomic sequences that acquire epidemiological relevance. Possibilities to reconcile the presence of broad mutant spectra in the large RNA coronavirus genome with its encoding a 3' to 5' exonuclease proofreading-repair activity are considered. Indeterminations in the behavior of individual viral genomes provide a benefit for the survival of the ensemble. We propose that this concept falls in the domain of "stochastic thinking," a notion that applies also to cellular processes, as a means for biological systems to face unexpected needs.
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Affiliation(s)
- Esteban Domingo
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Brenda Martínez-González
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Carlos García-Crespo
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Pilar Somovilla
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Departamento de Biología Molecular, Universidad Autónoma de Madrid, Campus de Cantoblanco, Madrid, Spain
| | - Ana Isabel de Ávila
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - María Eugenia Soria
- Centro de Biología Molecular “Severo Ochoa” (CSIC-UAM), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
| | - Antoni Durán-Pastor
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
| | - Celia Perales
- Centro Nacional de Biotecnología (CNB-CSIC), Consejo Superior de Investigaciones Científicas (CSIC), Campus de Cantoblanco, Madrid, Spain
- Department of Clinical Microbiology, Instituto de Investigación Sanitaria-Fundación Jiménez Díaz University Hospital, Universidad Autónoma de Madrid (IIS-FJD, UAM), Madrid, Spain
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29
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Terbot JW, Cooper BS, Good JM, Jensen JD. A Simulation Framework for Modeling the Within-Patient Evolutionary Dynamics of SARS-CoV-2. Genome Biol Evol 2023; 15:evad204. [PMID: 37950882 PMCID: PMC10664409 DOI: 10.1093/gbe/evad204] [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] [Revised: 10/31/2023] [Accepted: 11/07/2023] [Indexed: 11/13/2023] Open
Abstract
The global impact of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for rarely acting positive selection are best performed via comparison of empirical data with simulated data wherein commonly acting evolutionary factors, including mutation and recombination, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. Although there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intrahost evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them with existing empirical data. Of these, 592 models (∼5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intrahost SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed toward strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.
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Affiliation(s)
- John W Terbot
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, Arizona, USA
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Brandon S Cooper
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Jeffrey M Good
- Division of Biological Sciences, University of Montana, Missoula, Montana, USA
| | - Jeffrey D Jensen
- School of Life Sciences, Center for Evolution & Medicine, Arizona State University, Tempe, Arizona, USA
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30
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Bennett RP, Yoluç Y, Salter JD, Ripp A, Jessen HJ, Kaiser SM, Smith HC. Sangivamycin is preferentially incorporated into viral RNA by the SARS-CoV-2 polymerase. Antiviral Res 2023; 218:105716. [PMID: 37690700 DOI: 10.1016/j.antiviral.2023.105716] [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: 07/12/2023] [Revised: 09/05/2023] [Accepted: 09/08/2023] [Indexed: 09/12/2023]
Abstract
Sangivamycin (S) is an adenosine (A) nucleoside analog with low nanomolar antiviral activity against SARS-CoV-2 in vitro. Previously, low nanomolar antiviral efficacy was revealed when tested against multiple viral variants in several cell types. SARS-CoV-2 RNA isolated from live virus infected cells and the virions released from these cells was analyzed by mass spectrometry (MS) for S incorporation. Dose-dependent incorporation occurred up to 1.8 S per 1,000 nucleotides (49 S per genome) throughout the viral genomes isolated from both infected cells and viral particles, but this incorporation did not change the viral mutation rate. In contrast, host mRNA, affinity purified from the same infected and treated cells, contained little or no S. Sangivamycin triphosphate (STP) was synthesized to evaluate its incorporation into RNA by recombinant SARS-CoV-2 RNA-dependent RNA polymerase (RdRp) under defined in vitro conditions. SARS-CoV-2 RdRp showed that S was not a chain terminator and S containing oligonucleotides templated as A. Though the antiviral mechanism remains to be determined, the data suggests that SARS-CoV-2 RdRp incorporates STP into SARS-CoV-2 RNA, which does not significantly impair viral RNA synthesis or the mutation rate.
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Affiliation(s)
| | - Yasemin Yoluç
- Department of Pharmaceutical Chemistry, Goethe University Frankfurt, Frankfurt, Germany.
| | | | - Alexander Ripp
- Institute of Organic Chemistry Albert-Ludwigs-University, Freiburg, Germany.
| | - Henning J Jessen
- Institute of Organic Chemistry Albert-Ludwigs-University, Freiburg, Germany.
| | - Stefanie M Kaiser
- Department of Pharmaceutical Chemistry, Goethe University Frankfurt, Frankfurt, Germany.
| | - Harold C Smith
- OyaGen, Inc., Rochester, NY, USA; Department of Biochemistry and Biophysics, Center for RNA Biology, Center for AIDS Research, University of Rochester School of Medicine and Dentistry, Rochester, NY, USA.
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31
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El-Haddad K, Adhikari TM, Tu ZJ, Cheng YW, Leng X, Zhang X, Rhoads D, Ko JS, Worley S, Li J, Rubin BP, Esper FP. Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave. Virus Genes 2023; 59:653-661. [PMID: 37310519 DOI: 10.1007/s11262-023-02011-0] [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: 04/17/2023] [Accepted: 05/22/2023] [Indexed: 06/14/2023]
Abstract
SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.
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Affiliation(s)
- Kim El-Haddad
- Center for Pediatric Infectious Disease, Cleveland Clinic Children's, R3, 9500 Euclid Avenue, Cleveland, 44195 , OH, USA.
| | - Thamali M Adhikari
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Zheng Jin Tu
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Yu-Wei Cheng
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Xiaoyi Leng
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Xiangyi Zhang
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Daniel Rhoads
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Jennifer S Ko
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Sarah Worley
- Department of Quantitative Health Sciences, Cleveland Clinic, Cleveland, OH, USA
| | - Jing Li
- Department of Computer and Data Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Brian P Rubin
- Robert J. Tomsich Pathology and Laboratory Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
| | - Frank P Esper
- Center for Pediatric Infectious Disease, Cleveland Clinic Children's, R3, 9500 Euclid Avenue, Cleveland, 44195 , OH, USA.
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32
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Bacsik DJ, Dadonaite B, Butler A, Greaney AJ, Heaton NS, Bloom JD. Influenza virus transcription and progeny production are poorly correlated in single cells. eLife 2023; 12:RP86852. [PMID: 37675839 PMCID: PMC10484525 DOI: 10.7554/elife.86852] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 09/08/2023] Open
Abstract
The ultimate success of a viral infection at the cellular level is determined by the number of progeny virions produced. However, most single-cell studies of infection quantify the expression of viral transcripts and proteins, rather than the amount of progeny virions released from infected cells. Here, we overcome this limitation by simultaneously measuring transcription and progeny production from single influenza virus-infected cells by embedding nucleotide barcodes in the viral genome. We find that viral transcription and progeny production are poorly correlated in single cells. The cells that transcribe the most viral mRNA do not produce the most viral progeny and often represent aberrant infections that fail to express the influenza NS gene. However, only some of the discrepancy between transcription and progeny production can be explained by viral gene absence or mutations: there is also a wide range of progeny production among cells infected by complete unmutated virions. Overall, our results show that viral transcription is a relatively poor predictor of an infected cell's contribution to the progeny population.
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Affiliation(s)
- David J Bacsik
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Department of Genome Sciences & Medical Scientist Training Program, University of WashingtonSeattleUnited States
| | - Bernadeta Dadonaite
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
| | - Andrew Butler
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
| | - Allison J Greaney
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Department of Genome Sciences & Medical Scientist Training Program, University of WashingtonSeattleUnited States
| | - Nicholas S Heaton
- Department of Molecular Genetics and Microbiology, Duke University School of MedicineDurhamUnited States
- Duke Human Vaccine Institute, Duke University School of MedicineDurhamUnited States
| | - Jesse D Bloom
- Basic Sciences Division and Computational Biology Program, Fred Hutchinson Cancer CenterSeattleUnited States
- Howard Hughes Medical InstituteChevy ChaseUnited States
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33
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Xi B, Zeng X, Chen Z, Zeng J, Huang L, Du H. SARS-CoV-2 within-host diversity of human hosts and its implications for viral immune evasion. mBio 2023; 14:e0067923. [PMID: 37273216 PMCID: PMC10470530 DOI: 10.1128/mbio.00679-23] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2023] [Accepted: 04/17/2023] [Indexed: 06/06/2023] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is continuously evolving, bringing great challenges to the control of the virus. In the present study, we investigated the characteristics of SARS-CoV-2 within-host diversity of human hosts and its implications for immune evasion using about 2,00,000 high-depth next-generation genome sequencing data of SARS-CoV-2. A total of 44% of the samples showed within-host variations (iSNVs), and the average number of iSNVs in the samples with iSNV was 1.90. C-to-U is the dominant substitution pattern for iSNVs. C-to-U/G-to-A and A-to-G/U-to-C preferentially occur in 5'-CG-3' and 5'-AU-3' motifs, respectively. In addition, we found that SARS-CoV-2 within-host variations are under negative selection. About 15.6% iSNVs had an impact on the content of the CpG dinucleotide (CpG) in SARS-CoV-2 genomes. We detected signatures of faster loss of CpG-gaining iSNVs, possibly resulting from zinc-finger antiviral protein-mediated antiviral activities targeting CpG, which could be the major reason for CpG depletion in SARS-CoV-2 consensus genomes. The non-synonymous iSNVs in the S gene can largely alter the S protein's antigenic features, and many of these iSNVs are distributed in the amino-terminal domain (NTD) and receptor-binding domain (RBD). These results suggest that SARS-CoV-2 interacts actively with human hosts and attempts to take different evolutionary strategies to escape human innate and adaptive immunity. These new findings further deepen and widen our understanding of the within-host evolutionary features of SARS-CoV-2. IMPORTANCE Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the causative pathogen of the coronavirus disease 2019, has evolved rapidly since it was discovered. Recent studies have pointed out that some mutations in the SARS-CoV-2 S protein could confer SARS-CoV-2 the ability to evade the human adaptive immune system. In addition, it is observed that the content of the CpG dinucleotide in SARS-CoV-2 genome sequences has decreased over time, reflecting the adaptation to the human host. The significance of our research is revealing the characteristics of SARS-CoV-2 within-host diversity of human hosts, identifying the causes of CpG depletion in SARS-CoV-2 consensus genomes, and exploring the potential impacts of non-synonymous within-host variations in the S gene on immune escape, which could further deepen and widen our understanding of the evolutionary features of SARS-CoV-2.
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Affiliation(s)
- Binbin Xi
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Xi Zeng
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Zixi Chen
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Jiong Zeng
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Lizhen Huang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
| | - Hongli Du
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, China
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Raglow Z, Surie D, Chappell JD, Zhu Y, Martin ET, Kwon JH, Frosch AE, Mohamed A, Gilbert J, Bendall EE, Bahr A, Halasa N, Talbot HK, Grijalva CG, Baughman A, Womack KN, Johnson C, Swan SA, Koumans E, McMorrow ML, Harcourt JL, Atherton LJ, Burroughs A, Thornburg NJ, Self WH, Lauring AS. SARS-CoV-2 shedding and evolution in immunocompromised hosts during the Omicron period: a multicenter prospective analysis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.08.22.23294416. [PMID: 37662226 PMCID: PMC10473782 DOI: 10.1101/2023.08.22.23294416] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/05/2023]
Abstract
Background Prolonged SARS-CoV-2 infections in immunocompromised hosts may predict or source the emergence of highly mutated variants. The types of immunosuppression placing patients at highest risk for prolonged infection and associated intrahost viral evolution remain unclear. Methods Adults aged ≥18 years were enrolled at 5 hospitals and followed from 4/11/2022 - 2/1/2023. Eligible patients were SARS-CoV-2-positive in the previous 14 days and had a moderate or severely immunocompromising condition or treatment. Nasal specimens were tested by rRT-PCR every 2-4 weeks until negative in consecutive specimens. Positive specimens underwent viral culture and whole genome sequencing. A Cox proportional hazards model was used to assess factors associated with duration of infection. Results We enrolled 150 patients with: B cell malignancy or anti-B cell therapy (n=18), solid organ or hematopoietic stem cell transplant (SOT/HSCT) (n=59), AIDS (n=5), non-B cell malignancy (n=23), and autoimmune/autoinflammatory conditions (n=45). Thirty-eight (25%) were rRT-PCR-positive and 12 (8%) were culture-positive ≥21 days after initial SARS-CoV-2 detection or illness onset. Patients with B cell dysfunction had longer duration of rRT-PCR-positivity compared to those with autoimmune/autoinflammatory conditions (aHR 0.32, 95% CI 0.15-0.64). Consensus (>50% frequency) spike mutations were identified in 5 individuals who were rRT-PCR-positive >56 days; 61% were in the receptor-binding domain (RBD). Mutations shared by multiple individuals were rare (<5%) in global circulation. Conclusions In this cohort, prolonged replication-competent Omicron SARS-CoV-2 infections were uncommon. Within-host evolutionary rates were similar across patients, but individuals with infections lasting >56 days accumulated spike mutations, which were distinct from those seen globally.
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Affiliation(s)
- Zoe Raglow
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Diya Surie
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - James D Chappell
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Yuwei Zhu
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Emily T Martin
- School of Public Health, University of Michigan, Ann Arbor, Michigan
| | - Jennie H Kwon
- Department of Medicine, Washington University, St. Louis, Missouri
| | - Anne E Frosch
- Department of Medicine, Hennepin County Medical Center, Minneapolis, Minnesota
| | - Amira Mohamed
- Department of Medicine, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York
| | - Julie Gilbert
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Emily E Bendall
- Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan
| | - Auden Bahr
- Computational Medicine and Bioinformatics, University of Michigan, Ann Arbor, Michigan
| | - Natasha Halasa
- Department of Pediatrics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - H Keipp Talbot
- Departments of Medicine and Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Carlos G Grijalva
- Department of Health Policy, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Adrienne Baughman
- Department of Emergency Medicine, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Kelsey N Womack
- Vanderbilt Institute for Clinical and Translational Research, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Cassandra Johnson
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Sydney A Swan
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Emilia Koumans
- Division of STD Prevention, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Meredith L McMorrow
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Jennifer L Harcourt
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Lydia J Atherton
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Ashley Burroughs
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Natalie J Thornburg
- National Center for Immunization and Respiratory Diseases, Centers for Disease Control and Prevention (CDC), Atlanta, Georgia
| | - Wesley H Self
- Vanderbilt Institute for Clinical and Translational Research and Department of Emergency Medicine and, Vanderbilt University Medical Center, Nashville, Tennessee
| | - Adam S Lauring
- Departments of Internal Medicine and Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan
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N’Guessan A, Kailasam S, Mostefai F, Poujol R, Grenier JC, Ismailova N, Contini P, De Palma R, Haber C, Stadler V, Bourque G, Hussin JG, Shapiro BJ, Fritz JH, Piccirillo CA. Selection for immune evasion in SARS-CoV-2 revealed by high-resolution epitope mapping and sequence analysis. iScience 2023; 26:107394. [PMID: 37599818 PMCID: PMC10433132 DOI: 10.1016/j.isci.2023.107394] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2022] [Revised: 02/10/2023] [Accepted: 07/10/2023] [Indexed: 08/22/2023] Open
Abstract
Here, we exploit a deep serological profiling strategy coupled with an integrated, computational framework for the analysis of SARS-CoV-2 humoral immune responses. Applying a high-density peptide array (HDPA) spanning the entire proteomes of SARS-CoV-2 and endemic human coronaviruses allowed identification of B cell epitopes and relate them to their evolutionary and structural properties. We identify hotspots of pre-existing immunity and identify cross-reactive epitopes that contribute to increasing the overall humoral immune response to SARS-CoV-2. Using a public dataset of over 38,000 viral genomes from the early phase of the pandemic, capturing both inter- and within-host genetic viral diversity, we determined the evolutionary profile of epitopes and the differences across proteins, waves, and SARS-CoV-2 variants. Lastly, we show that mutations in spike and nucleocapsid epitopes are under stronger selection between than within patients, suggesting that most of the selective pressure for immune evasion occurs upon transmission between hosts.
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Affiliation(s)
- Arnaud N’Guessan
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill Genome Centre, McGill University, Montréal, QC, Canada
| | - Senthilkumar Kailasam
- Canadian Center for Computational Genomics, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Fatima Mostefai
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
- Département de Biochimie et Médecine Moléculaire, Université de Montréal, Montréal, QC, Canada
| | - Raphaël Poujol
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
| | | | - Nailya Ismailova
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Paola Contini
- Department of Internal Medicine, University of Genoa and IRCCS IST-Ospedale San Martino, Genoa, Italy
| | - Raffaele De Palma
- Department of Internal Medicine, University of Genoa and IRCCS IST-Ospedale San Martino, Genoa, Italy
| | | | | | - Guillaume Bourque
- Canadian Center for Computational Genomics, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Julie G. Hussin
- Research Centre, Montreal Heart Institute, Montreal, QC, Canada
- Département de Médecine, Université de Montréal, Montréal, QC, Canada
| | - B. Jesse Shapiro
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill Genome Centre, McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Jörg H. Fritz
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
| | - Ciriaco A. Piccirillo
- Department of Microbiology and Immunology, McGill University, Montréal, QC, Canada
- McGill University Research Center on Complex Traits (MRCCT), McGill University, Montréal, QC, Canada
- Infectious Diseases and Immunity in Global Health Program of the Research Institute of McGill Health Center, Montréal, QC, Canada
- Dahdaleh Institute of Genomic Medicine (DIgM), McGill University, Montréal, QC, Canada
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36
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Shi T, Harris JD, Martin MA, Koelle K. Transmission bottleneck size estimation from de novo viral genetic variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.14.553219. [PMID: 37645981 PMCID: PMC10462048 DOI: 10.1101/2023.08.14.553219] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Sequencing of viral infections has become increasingly common over the last decade. Deep sequencing data in particular have proven useful in characterizing the roles that genetic drift and natural selection play in shaping within-host viral populations. They have also been used to estimate transmission bottleneck sizes from identified donor-recipient pairs. These bottleneck sizes quantify the number of viral particles that establish genetic lineages in the recipient host and are important to estimate due to their impact on viral evolution. Current approaches for estimating bottleneck sizes exclusively consider the subset of viral sites that are observed as polymorphic in the donor individual. However, allele frequencies can change dramatically over the course of an individual's infection, such that sites that are polymorphic in the donor at the time of transmission may not be polymorphic in the donor at the time of sampling and allele frequencies at donor-polymorphic sites may change dramatically over the course of a recipient's infection. Because of this, transmission bottleneck sizes estimated using allele frequencies observed at a donor's polymorphic sites may be considerable underestimates of true bottleneck sizes. Here, we present a new statistical approach for instead estimating bottleneck sizes using patterns of viral genetic variation that arose de novo within a recipient individual. Specifically, our approach makes use of the number of clonal viral variants observed in a transmission pair, defined as the number of viral sites that are monomorphic in both the donor and the recipient but carry different alleles. We first test our approach on a simulated dataset and then apply it to both influenza A virus sequence data and SARS-CoV-2 sequence data from identified transmission pairs. Our results confirm the existence of extremely tight transmission bottlenecks for these two respiratory viruses, using an approach that does not tend to underestimate transmission bottleneck sizes.
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Affiliation(s)
- Teresa Shi
- Department of Biology, Emory University, Atlanta, GA, USA
| | - Jeremy D. Harris
- Department of Biology, Emory University, Atlanta, GA, USA
- Department of Mathematics, Rose-Hulman Institute of Technology, Terre Haute, IN, USA
| | - Michael A. Martin
- Department of Biology, Emory University, Atlanta, GA, USA
- Department of Pathology, Johns Hopkins School of Medicine, Baltimore, MD, USA
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, GA, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, USA
- Emory Center of Excellence for Influenza Research and Response (CEIRR), Atlanta GA, USA
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37
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Li Y, Choudhary MC, Regan J, Boucau J, Nathan A, Speidel T, Liew MY, Edelstein GE, Kawano Y, Uddin R, Deo R, Marino C, Getz MA, Reynold Z, Barry M, Gilbert RF, Tien D, Sagar S, Vyas TD, Flynn JP, Hammond SP, Novack LA, Choi B, Cernadas M, Wallace ZS, Sparks JA, Vyas JM, Seaman MS, Gaiha GD, Siedner MJ, Barczak AK, Lemieux JE, Li JZ. SARS-CoV-2 Viral Clearance and Evolution Varies by Extent of Immunodeficiency. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.07.31.23293441. [PMID: 37577493 PMCID: PMC10418302 DOI: 10.1101/2023.07.31.23293441] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
Despite vaccination and antiviral therapies, immunocompromised individuals are at risk for prolonged SARS-CoV-2 infection, but the immune defects that predispose to persistent COVID-19 remain incompletely understood. In this study, we performed detailed viro-immunologic analyses of a prospective cohort of participants with COVID-19. The median time to nasal viral RNA and culture clearance in the severe hematologic malignancy/transplant group (S-HT) were 72 and 40 days, respectively, which were significantly longer than clearance rates in the severe autoimmune/B-cell deficient (S-A), non-severe, and non-immunocompromised groups (P<0.001). Participants who were severely immunocompromised had greater SARS-CoV-2 evolution and a higher risk of developing antiviral treatment resistance. Both S-HT and S-A participants had diminished SARS-CoV-2-specific humoral, while only the S-HT group had reduced T cell-mediated responses. This highlights the varied risk of persistent COVID-19 across immunosuppressive conditions and suggests that suppression of both B and T cell responses results in the highest contributing risk of persistent infection.
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Affiliation(s)
- Yijia Li
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Manish C Choudhary
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - James Regan
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Julie Boucau
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Anusha Nathan
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
- Program in Health Sciences and Technology, Harvard Medical School and Massachusetts Institute of Technology, Boston, MA 02115, USA
| | - Tessa Speidel
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - May Yee Liew
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Gregory E Edelstein
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Yumeko Kawano
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Rockib Uddin
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Rinki Deo
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Caitlin Marino
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Matthew A Getz
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Zahra Reynold
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Mamadou Barry
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Rebecca F Gilbert
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Dessie Tien
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Shruti Sagar
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Tammy D Vyas
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - James P Flynn
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Sarah P Hammond
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Lewis A Novack
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Bina Choi
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Manuela Cernadas
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Zachary S Wallace
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Jeffrey A Sparks
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jatin M Vyas
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Michael S Seaman
- Center for Virology and Vaccine Research, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, MA, USA
| | - Gaurav D Gaiha
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Mark J Siedner
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
| | - Amy K Barczak
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA, USA
| | - Jacob E Lemieux
- Department of Medicine, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Jonathan Z Li
- Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
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Terbot JW, Cooper BS, Good JM, Jensen JD. A simulation framework for modeling the within-patient evolutionary dynamics of SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.13.548462. [PMID: 37503016 PMCID: PMC10370031 DOI: 10.1101/2023.07.13.548462] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/29/2023]
Abstract
The global impact of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has led to considerable interest in detecting novel beneficial mutations and other genomic changes that may signal the development of variants of concern (VOCs). The ability to accurately detect these changes within individual patient samples is important in enabling early detection of VOCs. Such genomic scans for positive selection are best performed via comparison of empirical data to simulated data wherein evolutionary factors, including mutation and recombination rates, reproductive and infection dynamics, and purifying and background selection, can be carefully accounted for and parameterized. While there has been work to quantify these factors in SARS-CoV-2, they have yet to be integrated into a baseline model describing intra-host evolutionary dynamics. To construct such a baseline model, we develop a simulation framework that enables one to establish expectations for underlying levels and patterns of patient-level variation. By varying eight key parameters, we evaluated 12,096 different model-parameter combinations and compared them to existing empirical data. Of these, 592 models (~5%) were plausible based on the resulting mean expected number of segregating variants. These plausible models shared several commonalities shedding light on intra-host SARS-CoV-2 evolutionary dynamics: severe infection bottlenecks, low levels of reproductive skew, and a distribution of fitness effects skewed towards strongly deleterious mutations. We also describe important areas of model uncertainty and highlight additional sequence data that may help to further refine a baseline model. This study lays the groundwork for the improved analysis of existing and future SARS-CoV-2 within-patient data.
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Affiliation(s)
- John W Terbot
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Brandon S. Cooper
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey M. Good
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey D. Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
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Rouzine IM, Rozhnova G. Evolutionary implications of SARS-CoV-2 vaccination for the future design of vaccination strategies. COMMUNICATIONS MEDICINE 2023; 3:86. [PMID: 37336956 PMCID: PMC10279745 DOI: 10.1038/s43856-023-00320-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Accepted: 06/07/2023] [Indexed: 06/21/2023] Open
Abstract
Once the first SARS-CoV-2 vaccine became available, mass vaccination was the main pillar of the public health response to the COVID-19 pandemic. It was very effective in reducing hospitalizations and deaths. Here, we discuss the possibility that mass vaccination might accelerate SARS-CoV-2 evolution in antibody-binding regions compared to natural infection at the population level. Using the evidence of strong genetic variation in antibody-binding regions and taking advantage of the similarity between the envelope proteins of SARS-CoV-2 and influenza, we assume that immune selection pressure acting on these regions of the two viruses is similar. We discuss the consequences of this assumption for SARS-CoV-2 evolution in light of mathematical models developed previously for influenza. We further outline the implications of this phenomenon, if our assumptions are confirmed, for the future design of SARS-CoV-2 vaccination strategies.
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Affiliation(s)
- Igor M Rouzine
- Immunogenetics, Sechenov Institute of Evolutionary Physiology and Biochemistry of Russian Academy of Sciences, Saint-Petersburg, Russia.
| | - Ganna Rozhnova
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, The Netherlands.
- BioISI - Biosystems & Integrative Sciences Institute, Faculdade de Ciências, Universidade de Lisboa, Lisboa, Portugal.
- Center for Complex Systems Studies (CCSS), Utrecht University, Utrecht, The Netherlands.
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40
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Messali S, Rondina A, Giovanetti M, Bonfanti C, Ciccozzi M, Caruso A, Caccuri F. Traceability of SARS-CoV-2 transmission through quasispecies analysis. J Med Virol 2023; 95:e28848. [PMID: 37294038 DOI: 10.1002/jmv.28848] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Revised: 05/18/2023] [Accepted: 05/24/2023] [Indexed: 06/10/2023]
Abstract
During COVID-19 pandemic, consensus genomic sequences were used for rapidly monitor the spread of the virus worldwide. However, less attention was paid to intrahost genetic diversity. In fact, in the infected host, SARS-CoV-2 consists in an ensemble of replicating and closely related viral variants so-called quasispecies. Here we show that intrahost single nucleotide variants (iSNVs) represent a target for contact tracing analysis. Our data indicate that in the acute phase of infection, in highly likely transmission links, the number of viral particles transmitted from one host to another (bottleneck size) is large enough to propagate iSNVs among individuals. Furthermore, we demonstrate that, during SARS-CoV-2 outbreaks when the consensus sequences are identical, it is possible to reconstruct the transmission chains by genomic investigations of iSNVs. Specifically, we found that it is possible to identify transmission chains by limiting the analysis of iSNVs to only three well-conserved genes, namely nsp2, ORF3, and ORF7.
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Affiliation(s)
- Serena Messali
- Department of Molecular and Translational Medicine, Section of Microbiology, University of Brescia, Brescia, Italy
| | - Alessandro Rondina
- Department of Molecular and Translational Medicine, Section of Microbiology, University of Brescia, Brescia, Italy
| | - Marta Giovanetti
- Instituto Rene Rachou, Fundação Oswaldo Cruz, Belo Horizonte, Minas Gerais, Brazil
- Sciences and Technologies for Sustainable Development and One Health, University of Campus Bio-Medico, Rome, Italy
| | - Carlo Bonfanti
- Department of Molecular and Translational Medicine, Section of Microbiology, University of Brescia, Brescia, Italy
| | - Massimo Ciccozzi
- Clinical Pathology and Microbiology Laboratory, Unit of Medical Statistics and Molecular Epidemiology, University Hospital Campus Biomedico, Rome, Italy
| | - Arnaldo Caruso
- Department of Molecular and Translational Medicine, Section of Microbiology, University of Brescia, Brescia, Italy
| | - Francesca Caccuri
- Department of Molecular and Translational Medicine, Section of Microbiology, University of Brescia, Brescia, Italy
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41
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Park Y, Martin MA, Koelle K. Epidemiological inference for emerging viruses using segregating sites. Nat Commun 2023; 14:3105. [PMID: 37248255 PMCID: PMC10226718 DOI: 10.1038/s41467-023-38809-7] [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: 09/08/2022] [Accepted: 05/16/2023] [Indexed: 05/31/2023] Open
Abstract
Epidemiological models are commonly fit to case and pathogen sequence data to estimate parameters and to infer unobserved disease dynamics. Here, we present an inference approach based on sequence data that is well suited for model fitting early on during the expansion of a viral lineage. Our approach relies on a trajectory of segregating sites to infer epidemiological parameters within a Sequential Monte Carlo framework. Using simulated data, we first show that our approach accurately recovers key epidemiological quantities under a single-introduction scenario. We then apply our approach to SARS-CoV-2 sequence data from France, estimating a basic reproduction number of approximately 2.3-2.7 under an epidemiological model that allows for multiple introductions. Our approach presented here indicates that inference approaches that rely on simple population genetic summary statistics can be informative of epidemiological parameters and can be used for reconstructing infectious disease dynamics during the early expansion of a viral lineage.
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Affiliation(s)
- Yeongseon Park
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, GA, 30322, USA
| | - Michael A Martin
- Graduate Program in Population Biology, Ecology, and Evolution, Emory University, Atlanta, GA, 30322, USA
- Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Katia Koelle
- Department of Biology, Emory University, Atlanta, GA, 30322, USA.
- Emory Center of Excellence for Influenza Research and Response (CEIRR), Atlanta, GA, USA.
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42
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Cheng Y, Ji C, Zhou HY, Zheng H, Wu A. Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking. Viruses 2023; 15:1158. [PMID: 37243244 PMCID: PMC10222785 DOI: 10.3390/v15051158] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Revised: 05/10/2023] [Accepted: 05/10/2023] [Indexed: 05/28/2023] Open
Abstract
The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.
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Affiliation(s)
- Yexiao Cheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Chengyang Ji
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Hang-Yu Zhou
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
| | - Heng Zheng
- School of Life Science and Technology, China Pharmaceutical University, Nanjing 211100, China
| | - Aiping Wu
- Institute of Systems Medicine, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100005, China
- Suzhou Institute of Systems Medicine, Suzhou 215123, China
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Naveca FG, Nascimento VA, Nascimento F, Ogrzewalska M, Pauvolid-Corrêa A, Araújo MF, Arantes I, Batista ÉR, Magalhães AÁ, Vinhal F, Mattos TP, Riediger I, Debur MDC, Grinsztejn B, Veloso VG, Brasil P, Rodrigues RR, Rovaris DB, Fernandes SB, Fernandes C, Santos JHA, Abdalla LF, Costa-Filho R, Silva M, Souza V, Costa ÁA, Mejía M, Brandão MJ, Gonçalves LF, Silva GA, de Jesus MS, Pessoa K, Corado ADLG, Duarte DCG, Machado AB, Zukeram KDA, Valente N, Lopes RS, Pereira EC, Appolinario LR, Rocha AS, Tort LFL, Sekizuka T, Itokawa K, Hashino M, Kuroda M, Dezordi FZ, Wallau GL, Delatorre E, Gräf T, Siqueira MM, Bello G, Resende PC. SARS-CoV-2 intra-host diversity, antibody response, and disease severity after reinfection by the variant of concern Gamma in Brazil. Sci Rep 2023; 13:7306. [PMID: 37147348 PMCID: PMC10160723 DOI: 10.1038/s41598-023-33443-1] [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: 07/01/2022] [Accepted: 04/12/2023] [Indexed: 05/07/2023] Open
Abstract
The rapid spread of the SARS-CoV-2 Variant of Concern (VOC) Gamma in Amazonas during early 2021 fueled a second large COVID-19 epidemic wave and raised concern about the potential role of reinfections. Very few cases of reinfection associated with the VOC Gamma have been reported to date, and their potential impact on clinical, immunological, and virological parameters remains largely unexplored. Here we describe 25 cases of SARS-CoV-2 reinfection in Brazil. SARS-CoV-2 genomic analysis confirmed that individuals were primo-infected with distinct viral lineages between March and December 2020 (B.1.1, B.1.1.28, B.1.1.33, B.1.195, and P.2) and reinfected with the VOC Gamma between 3 to 12 months after primo-infection. We found a similar mean cycle threshold (Ct) value and limited intra-host viral diversity in both primo-infection and reinfection samples. Sera of 14 patients tested 10-75 days after reinfection displayed detectable neutralizing antibodies (NAb) titers against SARS-CoV-2 variants that circulated before (B.1.*), during (Gamma), and after (Delta and Omicron) the second epidemic wave in Brazil. All individuals had milder or no symptoms after reinfection, and none required hospitalization. These findings demonstrate that individuals reinfected with the VOC Gamma may display relatively high RNA viral loads at the upper respiratory tract after reinfection, thus contributing to onward viral transmissions. Despite this, our study points to a low overall risk of severe Gamma reinfections, supporting that the abrupt increase in hospital admissions and deaths observed in Amazonas and other Brazilian states during the Gamma wave was mostly driven by primary infections. Our findings also indicate that most individuals analyzed developed a high anti-SARS-CoV-2 NAb response after reinfection that may provide some protection against reinfection or disease by different SARS-CoV-2 variants.
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Affiliation(s)
- Felipe Gomes Naveca
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil.
- Laboratório de Flavivírus, Instituto Oswaldo Cruz, Fiocruz, Rio de Janeiro, Rio de Janeiro, Brazil.
| | - Valdinete Alves Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Fernanda Nascimento
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Maria Ogrzewalska
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Alex Pauvolid-Corrêa
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- Department of Veterinary Integrative Biosciences, Texas A&M University, College Station, TX, USA
| | - Mia Ferreira Araújo
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ighor Arantes
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | | | | | | | - Tirza Peixoto Mattos
- Laboratório Central de Saúde Pública do Amazonas (LACEN-AM, Manaus, Amazonas, Brazil
| | - Irina Riediger
- Laboratório Central de Saúde Pública do Paraná (LACEN-PR) Curitiba, Paraná, Brazil
| | - Maria do Carmo Debur
- Laboratório Central de Saúde Pública do Paraná (LACEN-PR) Curitiba, Paraná, Brazil
| | - Beatriz Grinsztejn
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | - Valdiléa G Veloso
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | - Patrícia Brasil
- Instituto Nacional de Infectologia Evandro Chagas (INI), Fiocruz, Rio de Janeiro, Brazil
| | | | - Darcita Buerger Rovaris
- Laboratório Central de Saúde Pública do Estado de Santa Catarina (LACEN-SC), Florianópolis, Santa Catarina, Brazil
| | - Sandra Bianchini Fernandes
- Laboratório Central de Saúde Pública do Estado de Santa Catarina (LACEN-SC), Florianópolis, Santa Catarina, Brazil
| | - Cristiano Fernandes
- Fundação de Vigilância em Saúde do Amazonas-Dra Rosemary Costa Pinto, Manaus, Amazonas, Brazil
| | | | | | | | - Marineide Silva
- Laboratório Central de Saúde Pública do Amazonas (LACEN-AM, Manaus, Amazonas, Brazil
| | - Victor Souza
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Ágatha Araújo Costa
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Matilde Mejía
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Maria Júlia Brandão
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Luciana Fé Gonçalves
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
- Fundação de Vigilância em Saúde do Amazonas-Dra Rosemary Costa Pinto, Manaus, Amazonas, Brazil
| | - George Allan Silva
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Michele Silva de Jesus
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Karina Pessoa
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - André de Lima Guerra Corado
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Debora Camila Gomes Duarte
- Laboratório de Ecologia de Doenças Transmissíveis na Amazônia, Instituto Leônidas e Maria Deane, Fiocruz, Manaus, Brazil
| | - Ana Beatriz Machado
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Ketiuce de Azevedo Zukeram
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Natalia Valente
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Renata Serrano Lopes
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Elisa Cavalcante Pereira
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Luciana Reis Appolinario
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Alice Sampaio Rocha
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Luis Fernando Lopez Tort
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
- CENUR Litoral Norte, Universidad de la República, Salto, Uruguay
| | - Tsuyoshi Sekizuka
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Kentaro Itokawa
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Masanori Hashino
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | - Makoto Kuroda
- Pathogen Genomics Center, National Institute of Infectious Diseases, 1-23-1 Toyama, Shinjuku-Ku, Tokyo, 162-8640, Japan
| | | | - Gabriel Luz Wallau
- Instituto Aggeu Magalhães, Fundação Oswaldo Cruz, Recife, Pernambuco, Brazil
| | - Edson Delatorre
- Departamento de Biologia, Centro de Ciências Exatas, Naturais e da Saúde, Universidade Federal do Espírito Santo, Alegre, Brazil
| | - Tiago Gräf
- Instituto Gonçalo Moniz, Fundação Oswaldo Cruz, Salvador, Brazil
| | - Marilda Mendonça Siqueira
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
| | - Gonzalo Bello
- Laboratório de AIDS e Imunologia Molecular, Instituto Oswaldo Cruz, FIOCRUZ, Rio de Janeiro, Brazil
| | - Paola Cristina Resende
- Laboratory of Respiratory Viruses and Measles, Oswaldo Cruz Institute (IOC), Oswaldo Cruz Foundation (FIOCRUZ), Rio de Janeiro, RJ, Brazil
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Riddell AC, Cutino-Moguel T. The origins of new SARS-COV-2 variants in immunocompromised individuals. Curr Opin HIV AIDS 2023; 18:148-156. [PMID: 36977190 DOI: 10.1097/coh.0000000000000794] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
PURPOSE OF REVIEW To explore the origins of new severe acute respiratory coronavirus 2 (SARS-CoV-2) variants in immunocompromised individuals and whether the emergence of novel mutations in these individuals is responsible for the development of variants of concern (VOC). RECENT FINDINGS Next generation sequencing of samples from chronically infected immunocompromised patients has enabled identification of VOC- defining mutations in individuals prior to the emergence of these variants worldwide. Whether these individuals are the source of variant generation is uncertain. Vaccine effectiveness in immunocompromised individuals and with respect to VOCs is also discussed. SUMMARY Current evidence on chronic SARS-CoV-2 infection in immunocompromised populations is reviewed including the relevance of this to the generation of novel variants. Continued viral replication in the absence of an effective immune response at an individual level or high levels of viral infection at the population level are likely to have contributed to the appearance of the main VOC.
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Affiliation(s)
- Anna C Riddell
- Department of Virology, Division of Infection, Barts Health NHS Trust, London, UK
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Yurkovetskiy L, Egri S, Kurhade C, Diaz-Salinas MA, Jaimes JA, Nyalile T, Xie X, Choudhary MC, Dauphin A, Li JZ, Munro JB, Shi PY, Shen K, Luban J. S:D614G and S:H655Y are gateway mutations that act epistatically to promote SARS-CoV-2 variant fitness. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.03.30.535005. [PMID: 37034621 PMCID: PMC10081308 DOI: 10.1101/2023.03.30.535005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/29/2023]
Abstract
SARS-CoV-2 variants bearing complex combinations of mutations that confer increased transmissibility, COVID-19 severity, and immune escape, were first detected after S:D614G had gone to fixation, and likely originated during persistent infection of immunocompromised hosts. To test the hypothesis that S:D614G facilitated emergence of such variants, S:D614G was reverted to the ancestral sequence in the context of sequential Spike sequences from an immunocompromised individual, and within each of the major SARS-CoV-2 variants of concern. In all cases, infectivity of the S:D614G revertants was severely compromised. The infectivity of atypical SARS-CoV-2 lineages that propagated in the absence of S:D614G was found to be dependent upon either S:Q613H or S:H655Y. Notably, Gamma and Omicron variants possess both S:D614G and S:H655Y, each of which contributed to infectivity of these variants. Among sarbecoviruses, S:Q613H, S:D614G, and S:H655Y are only detected in SARS-CoV-2, which is also distinguished by a polybasic S1/S2 cleavage site. Genetic and biochemical experiments here showed that S:Q613H, S:D614G, and S:H655Y each stabilize Spike on virions, and that they are dispensable in the absence of S1/S2 cleavage, consistent with selection of these mutations by the S1/S2 cleavage site. CryoEM revealed that either S:D614G or S:H655Y shift the Spike receptor binding domain (RBD) towards the open conformation required for ACE2-binding and therefore on pathway for infection. Consistent with this, an smFRET reporter for RBD conformation showed that both S:D614G and S:H655Y spontaneously adopt the conformation that ACE2 induces in the parental Spike. Data from these orthogonal experiments demonstrate that S:D614G and S:H655Y are convergent adaptations to the polybasic S1/S2 cleavage site which stabilize S1 on the virion in the open RBD conformation and act epistatically to promote the fitness of variants bearing complex combinations of clinically significant mutations.
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Affiliation(s)
- Leonid Yurkovetskiy
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
- These authors contributed equally
| | - Shawn Egri
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- These authors contributed equally
| | - Chaitanya Kurhade
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA
- These authors contributed equally
| | - Marco A. Diaz-Salinas
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01605, USA
- These authors contributed equally
| | - Javier A. Jaimes
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
- These authors contributed equally
| | - Thomas Nyalile
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
| | - Xuping Xie
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA
| | - Manish C. Choudhary
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - Ann Dauphin
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
| | - Jonathan Z. Li
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA 02115, USA
| | - James B. Munro
- Department of Microbiology and Physiological Systems, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Medical School, Worcester, MA 01605, USA
| | - Pei-Yong Shi
- Department of Biochemistry and Molecular Biology, University of Texas Medical Branch, Galveston, Texas, USA
| | - Kuang Shen
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
| | - Jeremy Luban
- Program in Molecular Medicine, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Massachusetts Consortium on Pathogen Readiness, Boston, MA, 02115
- Department of Biochemistry and Molecular Biotechnology, University of Massachusetts Medical School, Worcester, MA 01605, USA
- Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA
- Ragon Institute of MGH, MIT and Harvard, Cambridge, MA 02139, USA
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46
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Taha TY, Chen IP, Hayashi JM, Tabata T, Walcott K, Kimmerly GR, Syed AM, Ciling A, Suryawanshi RK, Martin HS, Bach BH, Tsou CL, Montano M, Khalid MM, Sreekumar BK, Renuka Kumar G, Wyman S, Doudna JA, Ott M. Rapid assembly of SARS-CoV-2 genomes reveals attenuation of the Omicron BA.1 variant through NSP6. Nat Commun 2023; 14:2308. [PMID: 37085489 PMCID: PMC10120482 DOI: 10.1038/s41467-023-37787-0] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2023] [Accepted: 03/31/2023] [Indexed: 04/23/2023] Open
Abstract
Although the SARS-CoV-2 Omicron variant (BA.1) spread rapidly across the world and effectively evaded immune responses, its viral fitness in cell and animal models was reduced. The precise nature of this attenuation remains unknown as generating replication-competent viral genomes is challenging because of the length of the viral genome (~30 kb). Here, we present a plasmid-based viral genome assembly and rescue strategy (pGLUE) that constructs complete infectious viruses or noninfectious subgenomic replicons in a single ligation reaction with >80% efficiency. Fully sequenced replicons and infectious viral stocks can be generated in 1 and 3 weeks, respectively. By testing a series of naturally occurring viruses as well as Delta-Omicron chimeric replicons, we show that Omicron nonstructural protein 6 harbors critical attenuating mutations, which dampen viral RNA replication and reduce lipid droplet consumption. Thus, pGLUE overcomes remaining barriers to broadly study SARS-CoV-2 replication and reveals deficits in nonstructural protein function underlying Omicron attenuation.
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Affiliation(s)
- Taha Y Taha
- Gladstone Institutes, San Francisco, CA, USA.
| | - Irene P Chen
- Gladstone Institutes, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, CA, USA
| | | | | | | | | | - Abdullah M Syed
- Gladstone Institutes, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
| | - Alison Ciling
- Gladstone Institutes, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
| | | | - Hannah S Martin
- Gladstone Institutes, San Francisco, CA, USA
- Department of Chemistry, University of California, Berkeley, CA, USA
| | - Bryan H Bach
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
| | | | | | | | | | | | - Stacia Wyman
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
| | - Jennifer A Doudna
- Gladstone Institutes, San Francisco, CA, USA
- Innovative Genomics Institute, University of California, Berkeley, CA, USA
- Department of Chemistry, University of California, Berkeley, CA, USA
- Department of Molecular and Cell Biology, University of California, Berkeley, CA, USA
- Howard Hughes Medical Institute, University of California, Berkeley, CA, USA
- Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA
- California Institute for Quantitative Biosciences (QB3), University of California, Berkeley, CA, USA
| | - Melanie Ott
- Gladstone Institutes, San Francisco, CA, USA.
- Department of Medicine, University of California, San Francisco, CA, USA.
- Chan Zuckerberg Biohub - San Francisco, San Francisco, CA, USA.
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47
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Terbot JW, Johri P, Liphardt SW, Soni V, Pfeifer SP, Cooper BS, Good JM, Jensen JD. Developing an appropriate evolutionary baseline model for the study of SARS-CoV-2 patient samples. PLoS Pathog 2023; 19:e1011265. [PMID: 37018331 PMCID: PMC10075409 DOI: 10.1371/journal.ppat.1011265] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/06/2023] Open
Abstract
Over the past 3 years, Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) has spread through human populations in several waves, resulting in a global health crisis. In response, genomic surveillance efforts have proliferated in the hopes of tracking and anticipating the evolution of this virus, resulting in millions of patient isolates now being available in public databases. Yet, while there is a tremendous focus on identifying newly emerging adaptive viral variants, this quantification is far from trivial. Specifically, multiple co-occurring and interacting evolutionary processes are constantly in operation and must be jointly considered and modeled in order to perform accurate inference. We here outline critical individual components of such an evolutionary baseline model-mutation rates, recombination rates, the distribution of fitness effects, infection dynamics, and compartmentalization-and describe the current state of knowledge pertaining to the related parameters of each in SARS-CoV-2. We close with a series of recommendations for future clinical sampling, model construction, and statistical analysis.
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Affiliation(s)
- John W Terbot
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Parul Johri
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Schuyler W Liphardt
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Vivak Soni
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Susanne P Pfeifer
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
| | - Brandon S Cooper
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey M Good
- University of Montana, Division of Biological Sciences, Missoula, Montana, United States of America
| | - Jeffrey D Jensen
- Arizona State University, School of Life Sciences, Center for Evolution & Medicine, Tempe, Arizona, United States of America
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Gu H, Quadeer AA, Krishnan P, Ng DYM, Chang LDJ, Liu GYZ, Cheng SMS, Lam TTY, Peiris M, McKay MR, Poon LLM. Within-host genetic diversity of SARS-CoV-2 lineages in unvaccinated and vaccinated individuals. Nat Commun 2023; 14:1793. [PMID: 37002233 PMCID: PMC10063955 DOI: 10.1038/s41467-023-37468-y] [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: 02/02/2023] [Accepted: 03/13/2023] [Indexed: 04/03/2023] Open
Abstract
Viral and host factors can shape SARS-CoV-2 evolution. However, little is known about lineage-specific and vaccination-specific mutations that occur within individuals. Here, we analysed deep sequencing data from 2,820 SARS-CoV-2 respiratory samples with different viral lineages to describe the patterns of within-host diversity under different conditions, including vaccine-breakthrough infections. In unvaccinated individuals, variant of Concern (VOC) Alpha, Delta, and Omicron respiratory samples were found to have higher within-host diversity and were under neutral to purifying selection at the full genome level compared to non-VOC SARS-CoV-2. Breakthrough infections in 2-dose or 3-dose Comirnaty and CoronaVac vaccinated individuals did not increase levels of non-synonymous mutations and did not change the direction of selection pressure. Vaccine-induced antibody or T cell responses did not appear to have significant impact on within-host SARS-CoV-2 sequence diversification. Our findings suggest that vaccination does not increase exploration of SARS-CoV-2 protein sequence space and may not facilitate emergence of viral variants.
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Affiliation(s)
- Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Ahmed Abdul Quadeer
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Pavithra Krishnan
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Daisy Y M Ng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Lydia D J Chang
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Gigi Y Z Liu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Samuel M S Cheng
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Tommy T Y Lam
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China
- Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong SAR, China
| | - Malik Peiris
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
| | - Matthew R McKay
- Department of Electronic and Computer Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
- Department of Electrical and Electronic Engineering, University of Melbourne, Parkville, VIC, 3010, Australia
- Department of Microbiology and Immunology, The Peter Doherty Institute for Infection and Immunity, University of Melbourne, Melbourne, VIC, 3000, Australia
- Department of Chemical and Biological Engineering, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Leo L M Poon
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
- Centre for Immunology & Infection, Hong Kong Science and Technology Park, Hong Kong SAR, China.
- HKU-Pasteur Research Pole, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China.
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Gupta A, Konnova A, Smet M, Berkell M, Savoldi A, Morra M, Van Averbeke V, De Winter FH, Peserico D, Danese E, Hotterbeekx A, Righi E, De Nardo P, Tacconelli E, Malhotra-Kumar S, Kumar-Singh S. Host immunological responses facilitate development of SARS-CoV-2 mutations in patients receiving monoclonal antibody treatments. J Clin Invest 2023; 133:166032. [PMID: 36727404 PMCID: PMC10014108 DOI: 10.1172/jci166032] [Citation(s) in RCA: 21] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2022] [Accepted: 01/05/2023] [Indexed: 02/03/2023] Open
Abstract
BackgroundThe role of host immunity in emergence of evasive SARS-CoV-2 Spike mutations under therapeutic monoclonal antibody (mAb) pressure remains to be explored.MethodsIn a prospective, observational, monocentric ORCHESTRA cohort study, conducted between March 2021 and November 2022, mild-to-moderately ill COVID-19 patients (n = 204) receiving bamlanivimab, bamlanivimab/etesevimab, casirivimab/imdevimab, or sotrovimab were longitudinally studied over 28 days for viral loads, de novo Spike mutations, mAb kinetics, seroneutralization against infecting variants of concern, and T cell immunity. Additionally, a machine learning-based circulating immune-related biomarker (CIB) profile predictive of evasive Spike mutations was constructed and confirmed in an independent data set (n = 19) that included patients receiving sotrovimab or tixagevimab/cilgavimab.ResultsPatients treated with various mAbs developed evasive Spike mutations with remarkable speed and high specificity to the targeted mAb-binding sites. Immunocompromised patients receiving mAb therapy not only continued to display significantly higher viral loads, but also showed higher likelihood of developing de novo Spike mutations. Development of escape mutants also strongly correlated with neutralizing capacity of the therapeutic mAbs and T cell immunity, suggesting immune pressure as an important driver of escape mutations. Lastly, we showed that an antiinflammatory and healing-promoting host milieu facilitates Spike mutations, where 4 CIBs identified patients at high risk of developing escape mutations against therapeutic mAbs with high accuracy.ConclusionsOur data demonstrate that host-driven immune and nonimmune responses are essential for development of mutant SARS-CoV-2. These data also support point-of-care decision making in reducing the risk of mAb treatment failure and improving mitigation strategies for possible dissemination of escape SARS-CoV-2 mutants.FundingThe ORCHESTRA project/European Union's Horizon 2020 research and innovation program.
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Affiliation(s)
- Akshita Gupta
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and.,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Angelina Konnova
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and.,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Mathias Smet
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and.,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Matilda Berkell
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and.,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Alessia Savoldi
- Division of Infectious Diseases, Department of Diagnostics and Public Health and
| | - Matteo Morra
- Division of Infectious Diseases, Department of Diagnostics and Public Health and
| | - Vincent Van Averbeke
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and
| | - Fien Hr De Winter
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and
| | - Denise Peserico
- Section of Clinical Biochemistry, University of Verona, Verona, Italy
| | - Elisa Danese
- Section of Clinical Biochemistry, University of Verona, Verona, Italy
| | - An Hotterbeekx
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and
| | - Elda Righi
- Division of Infectious Diseases, Department of Diagnostics and Public Health and
| | | | - Pasquale De Nardo
- Division of Infectious Diseases, Department of Diagnostics and Public Health and
| | - Evelina Tacconelli
- Division of Infectious Diseases, Department of Diagnostics and Public Health and
| | - Surbhi Malhotra-Kumar
- Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
| | - Samir Kumar-Singh
- Molecular Pathology Group, Cell Biology & Histology, Faculty of Medicine and Health Sciences and.,Laboratory of Medical Microbiology, Vaccine & Infectious Disease Institute, University of Antwerp, Antwerp, Belgium
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Chaguza C, Hahn AM, Petrone ME, Zhou S, Ferguson D, Breban MI, Pham K, Peña-Hernández MA, Castaldi C, Hill V, Schulz W, Swanstrom RI, Roberts SC, Grubaugh ND. Accelerated SARS-CoV-2 intrahost evolution leading to distinct genotypes during chronic infection. Cell Rep Med 2023; 4:100943. [PMID: 36791724 PMCID: PMC9906997 DOI: 10.1016/j.xcrm.2023.100943] [Citation(s) in RCA: 26] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2022] [Revised: 10/12/2022] [Accepted: 01/20/2023] [Indexed: 01/28/2023]
Abstract
The chronic infection hypothesis for novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variant emergence is increasingly gaining credence following the appearance of Omicron. Here, we investigate intrahost evolution and genetic diversity of lineage B.1.517 during a SARS-CoV-2 chronic infection lasting for 471 days (and still ongoing) with consistently recovered infectious virus and high viral genome copies. During the infection, we find an accelerated virus evolutionary rate translating to 35 nucleotide substitutions per year, approximately 2-fold higher than the global SARS-CoV-2 evolutionary rate. This intrahost evolution results in the emergence and persistence of at least three genetically distinct genotypes, suggesting the establishment of spatially structured viral populations continually reseeding different genotypes into the nasopharynx. Finally, we track the temporal dynamics of genetic diversity to identify advantageous mutations and highlight hallmark changes for chronic infection. Our findings demonstrate that untreated chronic infections accelerate SARS-CoV-2 evolution, providing an opportunity for the emergence of genetically divergent variants.
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Affiliation(s)
- Chrispin Chaguza
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA.
| | - Anne M Hahn
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Mary E Petrone
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; School of Life and Environmental Sciences, University of Sydney, Sydney, NSW, Australia
| | - Shuntai Zhou
- Department of Microbiology and Immunology, University of North Carolina, Chapel Hill, NC, USA; Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - David Ferguson
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA
| | - Mallery I Breban
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Kien Pham
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Mario A Peña-Hernández
- Department of Biological and Biomedical Sciences, Yale School of Medicine, New Haven, CT, USA
| | | | - Verity Hill
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA
| | - Wade Schulz
- Department of Laboratory Medicine, Yale School of Medicine, New Haven, CT, USA; Center for Outcomes Research and Evaluation, Yale New Haven Hospital, New Haven, CT, USA
| | - Ronald I Swanstrom
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA; Department of Biochemistry and Biophysics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Scott C Roberts
- Infectious Disease, Yale School of Medicine, New Haven, CT, USA
| | - Nathan D Grubaugh
- Department of Epidemiology of Microbial Diseases, Yale School of Public Health, New Haven, CT, USA; Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT, USA.
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