1
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Phumiphanjarphak W, Aiewsakun P. Entourage: all-in-one sequence analysis software for genome assembly, virus detection, virus discovery, and intrasample variation profiling. BMC Bioinformatics 2024; 25:222. [PMID: 38914932 PMCID: PMC11197340 DOI: 10.1186/s12859-024-05846-y] [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: 08/08/2023] [Accepted: 06/14/2024] [Indexed: 06/26/2024] Open
Abstract
BACKGROUND Pan-virus detection, and virome investigation in general, can be challenging, mainly due to the lack of universally conserved genetic elements in viruses. Metagenomic next-generation sequencing can offer a promising solution to this problem by providing an unbiased overview of the microbial community, enabling detection of any viruses without prior target selection. However, a major challenge in utilising metagenomic next-generation sequencing for virome investigation is that data analysis can be highly complex, involving numerous data processing steps. RESULTS Here, we present Entourage to address this challenge. Entourage enables short-read sequence assembly, viral sequence search with or without reference virus targets using contig-based approaches, and intrasample sequence variation quantification. Several workflows are implemented in Entourage to facilitate end-to-end virus sequence detection analysis through a single command line, from read cleaning, sequence assembly, to virus sequence searching. The results generated are comprehensive, allowing for thorough quality control, reliability assessment, and interpretation. We illustrate Entourage's utility as a streamlined workflow for virus detection by employing it to comprehensively search for target virus sequences and beyond in raw sequence read data generated from HeLa cell culture samples spiked with viruses. Furthermore, we showcase its flexibility and performance on a real-world dataset by analysing a preassembled Tara Oceans dataset. Overall, our results show that Entourage performs well even with low virus sequencing depth in single digits, and it can be used to discover novel viruses effectively. Additionally, by using sequence data generated from a patient with chronic SARS-CoV-2 infection, we demonstrate Entourage's capability to quantify virus intrasample genetic variations, and generate publication-quality figures illustrating the results. CONCLUSIONS Entourage is an all-in-one, versatile, and streamlined bioinformatics software for virome investigation, developed with a focus on ease of use. Entourage is available at https://codeberg.org/CENMIG/Entourage under the MIT license.
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Affiliation(s)
- Worakorn Phumiphanjarphak
- Department of Microbiology, Faculty of Science, Mahidol University, Ratchathewi District, 272 Rama VI Road, Bangkok, 10400, Thailand
- Pornchai Matangkasombut Center for Microbial Genomics, Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand
| | - Pakorn Aiewsakun
- Department of Microbiology, Faculty of Science, Mahidol University, Ratchathewi District, 272 Rama VI Road, Bangkok, 10400, Thailand.
- Pornchai Matangkasombut Center for Microbial Genomics, Department of Microbiology, Faculty of Science, Mahidol University, Bangkok, Thailand.
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2
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Ortigas-Vasquez A, Pandey U, Renner DW, Bowen CD, Baigent SJ, Dunn J, Cheng H, Yao Y, Read AF, Nair V, Kennedy DA, Szpara ML. Comparative analysis of multiple consensus genomes of the same strain of Marek's disease virus reveals intrastrain variation. Virus Evol 2024; 10:veae047. [PMID: 39036034 PMCID: PMC11259760 DOI: 10.1093/ve/veae047] [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: 01/09/2024] [Revised: 04/24/2024] [Accepted: 06/17/2024] [Indexed: 07/23/2024] Open
Abstract
Current strategies to understand the molecular basis of Marek's disease virus (MDV) virulence primarily consist of cataloging divergent nucleotides between strains with different phenotypes. However, most comparative genomic studies of MDV rely on previously published consensus genomes despite the confirmed existence of MDV strains as mixed viral populations. To assess the reliability of interstrain genomic comparisons relying on published consensus genomes of MDV, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform three-way comparisons between multiple consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). By contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Notably, we were able to identify 3 single-nucleotide polymorphisms (SNPs) in the unique long region and 16 SNPs in the unique short (US) region of CVI988GenBank.BAC that were not present in either CVI988Pirbright.lab or CVI988USDA.PA.field. Recombination analyses of field strains previously described as natural recombinants of CVI988 yielded no evidence of crossover events in the US region when either CVI988Pirbright.lab or CVI988USDA.PA.field were used to represent CVI988 instead of CVI988GenBank.BAC. We were also able to confirm that both CVI988 and Md5 populations were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. However, we did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988GenBank.BAC. Taken together, our findings suggest that continued reliance on the same published consensus genome of CVI988 may have led to an overestimation of genomic divergence between CVI988 and virulent strains and that multiple consensus genomes per strain may be necessary to ensure the accuracy of interstrain genomic comparisons.
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Affiliation(s)
- Alejandro Ortigas-Vasquez
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Utsav Pandey
- Department of Biochemistry and Molecular Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Daniel W Renner
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Chris D Bowen
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Susan J Baigent
- Viral Oncogenesis Group, The Pirbright Institute, Woking GU24 0NF, UK
| | - John Dunn
- United States Department of Agriculture, Agricultural Research Service, US National Poultry Research Center, Southeast Poultry Research Laboratory, Athens, GA 30605, USA
| | - Hans Cheng
- United States Department of Agriculture, Agricultural Research Service, US National Poultry Research Center, Avian Disease and Oncology Laboratory, East Lansing, MI 48823, USA
| | - Yongxiu Yao
- Viral Oncogenesis Group, The Pirbright Institute, Woking GU24 0NF, UK
| | - Andrew F Read
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Venugopal Nair
- Viral Oncogenesis Group, The Pirbright Institute, Woking GU24 0NF, UK
| | - Dave A Kennedy
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
| | - Moriah L Szpara
- Department of Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
- Department of Biochemistry and Molecular Biology, Center for Infectious Disease Dynamics, Huck Institutes of the Life Sciences, Pennsylvania State University, University Park, PA 16802, USA
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3
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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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4
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Nelson CW, Poon LLM, Gu H. Reply to: Population genetic considerations regarding the interpretation of within-patient SARS-CoV-2 polymorphism data. Nat Commun 2024; 15:3239. [PMID: 38627383 PMCID: PMC11021549 DOI: 10.1038/s41467-024-46262-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Accepted: 02/21/2024] [Indexed: 04/19/2024] Open
Affiliation(s)
- Chase W Nelson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA
- Institute for Comparative Genomics, American Museum of Natural History, New York, NY, 10024, USA
| | - 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.
| | - Haogao Gu
- School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong SAR, China
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5
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Gao Y, Barton JP. A binary trait model reveals the fitness effects of HIV-1 escape from T cell responses. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.03.583183. [PMID: 38464239 PMCID: PMC10925374 DOI: 10.1101/2024.03.03.583183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Natural selection often acts on multiple traits simultaneously. For example, the virus HIV-1 faces pressure to evade host immunity while also preserving replicative fitness. While past work has studied selection during HIV-1 evolution, it is challenging to quantitatively separate different contributions to fitness. This task is made more difficult because a single mutation can affect both immune escape and replication. Here, we develop an evolutionary model that disentangles the effects of escaping CD8+ T cell-mediated immunity, which we model as a binary trait, from other contributions to fitness. After validation in simulations, we applied this model to study within-host HIV-1 evolution in a clinical data set. We observed strong selection for immune escape, sometimes greatly exceeding past estimates, especially early in infection. Conservative estimates suggest that roughly half of HIV-1 fitness gains during the first months to years of infection can be attributed to T cell escape. Our approach is not limited to HIV-1 or viruses, and could be adapted to study the evolution of quantitative traits in other contexts.
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Affiliation(s)
- Yirui Gao
- Department of Physics and Astronomy, University of California, Riverside, USA
| | - John P. Barton
- Department of Physics and Astronomy, University of California, Riverside, USA
- Department of Computational and Systems Biology, University of Pittsburgh School of Medicine, USA
- Department of Physics and Astronomy, University of Pittsburgh, USA
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6
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Mishra SK, Nelson CW, Zhu B, Pinheiro M, Lee HJ, Dean M, Burdett L, Yeager M, Mirabello L. Improved detection of low-frequency within-host variants from deep sequencing: A case study with human papillomavirus. Virus Evol 2024; 10:veae013. [PMID: 38455683 PMCID: PMC10919477 DOI: 10.1093/ve/veae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2023] [Revised: 01/19/2024] [Accepted: 02/01/2024] [Indexed: 03/09/2024] Open
Abstract
High-coverage sequencing allows the study of variants occurring at low frequencies within samples, but is susceptible to false-positives caused by sequencing error. Ion Torrent has a very low single nucleotide variant (SNV) error rate and has been employed for the majority of human papillomavirus (HPV) whole genome sequences. However, benchmarking of intrahost SNVs (iSNVs) has been challenging, partly due to limitations imposed by the HPV life cycle. We address this problem by deep sequencing three replicates for each of 31 samples of HPV type 18 (HPV18). Errors, defined as iSNVs observed in only one of three replicates, are dominated by C→T (G→A) changes, independently of trinucleotide context. True iSNVs, defined as those observed in all three replicates, instead show a more diverse SNV type distribution, with particularly elevated C→T rates in CCG context (CCG→CTG; CGG→CAG) and C→A rates in ACG context (ACG→AAG; CGT→CTT). Characterization of true iSNVs allowed us to develop two methods for detecting true variants: (1) VCFgenie, a dynamic binomial filtering tool which uses each variant's allele count and coverage instead of fixed frequency cut-offs; and (2) a machine learning binary classifier which trains eXtreme Gradient Boosting models on variant features such as quality and trinucleotide context. Each approach outperforms fixed-cut-off filtering of iSNVs, and performance is enhanced when both are used together. Our results provide improved methods for identifying true iSNVs in within-host applications across sequencing platforms, specifically using HPV18 as a case study.
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Affiliation(s)
- Sambit K Mishra
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, P.O. Box B, Bldg. 430, Frederick, MD 21702, USA
| | - Chase W Nelson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Bin Zhu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Maisa Pinheiro
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Hyo Jung Lee
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, P.O. Box B, Bldg. 430, Frederick, MD 21702, USA
| | - Michael Dean
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
| | - Laurie Burdett
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, P.O. Box B, Bldg. 430, Frederick, MD 21702, USA
| | - Meredith Yeager
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
- Cancer Genomics Research Laboratory, Leidos Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, P.O. Box B, Bldg. 430, Frederick, MD 21702, USA
| | - Lisa Mirabello
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, 9609 Medical Center Drive, Rockville, MD 20850, USA
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7
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Ortigas-Vasquez A, Pandey U, Renner D, Bowen C, Baigent SJ, Dunn J, Cheng H, Yao Y, Read AF, Nair V, Kennedy DA, Szpara ML. Comparative Analysis of Multiple Consensus Genomes of the Same Strain of Marek's Disease Virus Reveals Intrastrain Variation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2023.09.04.556264. [PMID: 37732198 PMCID: PMC10508761 DOI: 10.1101/2023.09.04.556264] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Current strategies to understand the molecular basis of Marek's disease virus (MDV) virulence primarily consist of cataloguing divergent nucleotides between strains with different phenotypes. However, each MDV strain is typically represented by a single consensus genome despite the confirmed existence of mixed viral populations. To assess the reliability of single-consensus interstrain genomic comparisons, we obtained two additional consensus genomes of vaccine strain CVI988 (Rispens) and two additional consensus genomes of the very virulent strain Md5 by sequencing viral stocks and cultured field isolates. In conjunction with the published genomes of CVI988 and Md5, this allowed us to perform 3-way comparisons between consensus genomes of the same strain. We found that consensus genomes of CVI988 can vary in as many as 236 positions involving 13 open reading frames (ORFs). In contrast, we found that Md5 genomes varied only in 11 positions involving a single ORF. Phylogenomic analyses showed all three Md5 consensus genomes clustered closely together, while also showing that CVI988 GenBank.BAC diverged from CVI988 Pirbright.lab and CVI988 USDA.PA.field . Comparison of CVI988 consensus genomes revealed 19 SNPs in the unique regions of CVI988 GenBank.BAC that were not present in either CVI988 Pirbright.lab or CVI988 USDA.PA.field . Finally, we evaluated the genomic heterogeneity of CVI988 and Md5 populations by identifying positions with >2% read support for alternative alleles in two ultra-deeply sequenced samples. We were able to confirm that both populations of CVI988 and Md5 were mixed, exhibiting a total of 29 and 27 high-confidence minor variant positions, respectively. We did not find any evidence of minor variants in the positions corresponding to the 19 SNPs in the unique regions of CVI988 GenBank.BAC . Taken together, our findings confirm that consensus genomes of the same strain of MDV can vary and suggest that multiple consensus genomes per strain are needed in order to maximize the accuracy of interstrain genomic comparisons.
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8
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Formentin M, Chignola R, Favretti M. Optimal entropic properties of SARS-CoV-2 RNA sequences. ROYAL SOCIETY OPEN SCIENCE 2024; 11:231369. [PMID: 38298394 PMCID: PMC10827432 DOI: 10.1098/rsos.231369] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 01/02/2024] [Indexed: 02/02/2024]
Abstract
The reaction of the scientific community against the COVID-19 pandemic has generated a huge (approx. 106 entries) dataset of genome sequences collected worldwide and spanning a relatively short time window. These unprecedented conditions together with the certain identification of the reference viral genome sequence allow for an original statistical study of mutations in the virus genome. In this paper, we compute the Shannon entropy of every sequence in the dataset as well as the relative entropy and the mutual information between the reference sequence and the mutated ones. These functions, originally developed in information theory, measure the information content of a sequence and allows us to study the random character of mutation mechanism in terms of its entropy and information gain or loss. We show that this approach allows us to set in new format known features of the SARS-CoV-2 mutation mechanism like the CT bias, but also to discover new optimal entropic properties of the mutation process in the sense that the virus mutation mechanism track closely theoretically computable lower bounds for the entropy decrease and the information transfer.
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Affiliation(s)
- Marco Formentin
- Department of Mathematics Tullio Levi-Civita, University of Padova, via Trieste 63 35131 Padova, Italy
| | - Roberto Chignola
- Department of Biotechnology, University of Verona, Strada le Grazie 15-CV1, 37134 Verona, Italy
| | - Marco Favretti
- Department of Mathematics Tullio Levi-Civita, University of Padova, via Trieste 63 35131 Padova, Italy
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9
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Yu H, Chen H, Li N, Yang CJ, Xiao HY, Chen G, Huang GH. Flexible changes to the Heliothis virescens ascovirus 3h (HvAV-3h) virion components affect pathogenicity against different host larvae species. Microbiol Spectr 2023; 11:e0248823. [PMID: 37943038 PMCID: PMC10714839 DOI: 10.1128/spectrum.02488-23] [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: 06/14/2023] [Accepted: 08/30/2023] [Indexed: 11/10/2023] Open
Abstract
IMPORTANCE Different pathogenic processes of a virus in different hosts are related to the host individual differences, which makes the virus undergoes different survival pressures. Here, we found that the virions of an insect virus, Heliothis virescens ascovirus 3h (HvAV-3h), had different protein composition when they were purified from different host larval species. These "adaptive changes" of the virions were analyzed in detail in this study, which mainly included the differences of the protein composition of virions and the differences in affinity between virions and different host proteins. The results of this study revealed the flexible changes of viruses to help themselves adapt to different hosts. Also, these interesting findings can provide new insights to improve our understanding of virus adaptability and virulence differentiation caused by the adaptation process.
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Affiliation(s)
- Huan Yu
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
| | - Hong Chen
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
| | - Ni Li
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
| | - Chang-Jin Yang
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
- Agriculture and Rural Bureau of Xinhuang Dong Autonomous County, Huaihua, Hunan, China
| | - Hua-Yan Xiao
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
| | - Gong Chen
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
| | - Guo-Hua Huang
- Hunan Provincial Key Laboratory for Biology and Control of Plant Diseases and Insect Pests, College of Plant Protection, Hunan Agricultural University, Changsha, Hunan, China
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10
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Schalkwijk HH, Georgala A, Gillemot S, Temblador A, Topalis D, Wittnebel S, Andrei G, Snoeck R. A Herpes Simplex Virus 1 DNA Polymerase Multidrug Resistance Mutation Identified in a Patient With Immunodeficiency and Confirmed by Gene Editing. J Infect Dis 2023; 228:1505-1515. [PMID: 37224525 DOI: 10.1093/infdis/jiad184] [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: 01/24/2023] [Revised: 04/24/2023] [Accepted: 05/21/2023] [Indexed: 05/26/2023] Open
Abstract
BACKGROUND Herpes simplex virus 1 can cause severe infections in individuals who are immunocompromised. In these patients, emergence of drug resistance mutations causes difficulties in infection management. METHODS Seventeen herpes simplex virus 1 isolates were obtained from orofacial/anogenital lesions in a patient with leaky severe combined immunodeficiency over 7 years, before and after stem cell transplantation. Spatial/temporal evolution of drug resistance was characterized genotypically-with Sanger and next-generation sequencing of viral thymidine kinase (TK) and DNA polymerase (DP)-and phenotypically. CRISPR/Cas9 was used to introduce the novel DP Q727R mutation, and dual infection-competition assays were performed to assess viral fitness. RESULTS Isolates had identical genetic backgrounds, suggesting that orofacial/anogenital infections derived from the same virus lineage. Eleven isolates proved heterogeneous TK virus populations by next-generation sequencing, undetectable by Sanger sequencing. Thirteen isolates were acyclovir resistant due to TK mutations, and the Q727R isolate additionally exhibited foscarnet/adefovir resistance. Recombinant Q727R mutant virus showed multidrug resistance and increased fitness under antiviral pressure. CONCLUSIONS Long-term follow-up of a patient with severe combined immunodeficiency revealed virus evolution and frequent reactivation of wild-type and TK mutant strains, mostly as heterogeneous populations. The DP Q727R resistance phenotype was confirmed with CRISPR/Cas9, a useful tool to validate novel drug resistance mutations.
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Affiliation(s)
| | - Aspasia Georgala
- Department of Infectious Diseases, Jules Bordet Institute, Université Libre de Bruxelles, Brussels
| | - Sarah Gillemot
- Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven
| | - Arturo Temblador
- Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven
| | - Dimitri Topalis
- Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven
| | - Sebastian Wittnebel
- Department of Hematology, Jules Bordet Institute, Université Libre de Bruxelles, Brussels, Belgium
| | - Graciela Andrei
- Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven
| | - Robert Snoeck
- Laboratory of Virology and Chemotherapy, Rega Institute for Medical Research, KU Leuven
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11
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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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12
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Roder AE, Johnson KEE, Knoll M, Khalfan M, Wang B, Schultz-Cherry S, Banakis S, Kreitman A, Mederos C, Youn JH, Mercado R, Wang W, Chung M, Ruchnewitz D, Samanovic MI, Mulligan MJ, Lässig M, Luksza M, Das S, Gresham D, Ghedin E. Optimized quantification of intra-host viral diversity in SARS-CoV-2 and influenza virus sequence data. mBio 2023; 14:e0104623. [PMID: 37389439 PMCID: PMC10470513 DOI: 10.1128/mbio.01046-23] [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: 04/25/2023] [Accepted: 05/02/2023] [Indexed: 07/01/2023] Open
Abstract
High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant-calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller and use of replicate sequencing have the most significant impact on single-nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false-negative rates. When replicates are not available, using a combination of multiple callers with more stringent cutoffs is recommended. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intra-host viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intra-host variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host cell, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus nor strongly beneficial can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in the inclusion of false-positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant-calling tools. We used simulated and synthetic data to test their performance against a true set of variants and then used these studies to inform variant identification in data from SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.
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Affiliation(s)
- A. E. Roder
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - K. E. E. Johnson
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - M. Knoll
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - M. Khalfan
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - B. Wang
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - S. Schultz-Cherry
- Department of Infectious Diseases, St Jude Children Research Hospital, Memphis, Tennessee, USA
| | - S. Banakis
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - A. Kreitman
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - C. Mederos
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - J.-H. Youn
- Department of Laboratory Medicine, NIH, Bethesda, Maryland, USA
| | - R. Mercado
- Department of Laboratory Medicine, NIH, Bethesda, Maryland, USA
| | - W. Wang
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - M. Chung
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
| | - D. Ruchnewitz
- Institute for Biological Physics, University of Cologne, Cologne, Germany
| | - M. I. Samanovic
- Department of Medicine, New York University Langone Vaccine Center, New York, New York, USA
| | - M. J. Mulligan
- Department of Medicine, New York University Langone Vaccine Center, New York, New York, USA
| | - M. Lässig
- Institute for Biological Physics, University of Cologne, Cologne, Germany
| | - M. Luksza
- Department of Oncological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - S. Das
- Department of Laboratory Medicine, NIH, Bethesda, Maryland, USA
| | - D. Gresham
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
| | - E. Ghedin
- Systems Genomics Section, Laboratory of Parasitic Diseases, DIR, NIAID, NIH, Bethesda, Maryland, USA
- Department of Biology, Center for Genomics and Systems Biology, New York University, New York, New York, USA
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13
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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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Noor F, Ashfaq UA, Bakar A, Qasim M, Masoud MS, Alshammari A, Alharbi M, Riaz MS. Identification and characterization of codon usage pattern and influencing factors in HFRS-causing hantaviruses. Front Immunol 2023; 14:1131647. [PMID: 37492567 PMCID: PMC10364125 DOI: 10.3389/fimmu.2023.1131647] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2022] [Accepted: 06/22/2023] [Indexed: 07/27/2023] Open
Abstract
Hemorrhagic fever with renal syndrome (HFRS) is an acute viral zoonosis carried and transmitted by infected rodents through urine, droppings, or saliva. The etiology of HFRS is complex due to the involvement of viral factors and host immune and genetic factors which hinder the development of potential therapeutic solutions for HFRS. Hantaan virus (HTNV), Dobrava-Belgrade virus (DOBV), Seoul virus (SEOV), and Puumala virus (PUUV) are predominantly found in hantaviral species that cause HFRS in patients. Despite ongoing prevention and control efforts, HFRS remains a serious economic burden worldwide. Furthermore, recent studies reported that the hantavirus nucleocapsid protein is a multi-functional protein and plays a major role in the replication cycle of the hantavirus. However, the precise mechanism of the nucleoproteins in viral pathogenesis is not completely understood. In the framework of the current study, various in silico approaches were employed to identify the factors influencing the codon usage pattern of hantaviral nucleoproteins. Based on the relative synonymous codon usage (RSCU) values, a comparative analysis was performed between HFRS-causing hantavirus and their hosts, suggesting that HTNV, DOBV, SEOV, and PUUV, were inclined to evolve their codon usage patterns that were comparable to those of their hosts. The results indicated that most of the overrepresented codons had AU-endings, which revealed that mutational pressure is the major force shaping codon usage patterns. However, the influence of natural selection and geographical factors cannot be ignored on viral codon usage bias. Further analysis also demonstrated that HFRS causing hantaviruses adapted host-specific codon usage patterns to sustain successful replication and transmission chains within hosts. To our knowledge, no study to date reported the factors influencing the codon usage pattern within hantaviral nucleoproteins. Thus, the proposed computational scheme can help in understanding the underlying mechanism of codon usage patterns in HFRS-causing hantaviruses which lend a helping hand in designing effective anti-HFRS treatments in future. This study, although comprehensive, relies on in silico methods and thus necessitates experimental validation for more solid outcomes. Beyond the identified factors influencing viral behavior, there could be other yet undiscovered influences. These potential factors should be targets for further research to improve HFRS therapeutic strategies.
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Affiliation(s)
- Fatima Noor
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Usman Ali Ashfaq
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Abu Bakar
- Centre of Agricultural Biochemistry and Biotechnology (CABB), University of Agriculture, Faisalabad, Pakistan
| | - Muhammad Qasim
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Muhammad Shareef Masoud
- Department of Bioinformatics and Biotechnology, Government College University, Faisalabad, Pakistan
| | - Abdulrahman Alshammari
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
| | - Metab Alharbi
- Department of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
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15
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Popović M, Nuskern L, Peranić K, Vuković R, Katanić Z, Krstin L, Ćurković-Perica M, Leigh DM, Poljak I, Idžojtić M, Rigling D, Ježić M. Physiological variations in hypovirus-infected wild and model long-term laboratory strains of Cryphonectria parasitica. Front Microbiol 2023; 14:1192996. [PMID: 37426020 PMCID: PMC10324583 DOI: 10.3389/fmicb.2023.1192996] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/24/2023] [Accepted: 05/25/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction Forest ecosystems are highly threatened by the simultaneous effects of climate change and invasive pathogens. Chestnut blight, caused by the invasive phytopathogenic fungus Cryphonectria parasitica, has caused severe damage to European chestnut groves and catastrophic dieback of American chestnut in North America. Within Europe, the impacts of the fungus are widely mitigated through biological control that utilizes the RNA mycovirus: Cryphonectria hypovirus 1 (CHV1). Viral infections, similarly to abiotic factors, can cause oxidative stress in their hosts leading to physiological attrition through stimulating ROS (reactive oxygen species) and NOx production. Methods To fully understand the interactions leading to the biocontrol of chestnut blight, it is vital to determine oxidative stress damage arising during CHV1 infection, especially considering that other abiotic factors, like long-term cultivation of model fungal strains, can also impact oxidative stress. Our study compared CHV1-infected C. parasitica isolates from two Croatian wild populations with CHV1-infected model strains (EP713, Euro7 and CR23) that have experienced long-term laboratory cultivation. Results and Discussion We determined the level of oxidative stress in the samples by measuring stress enzymes' activity and oxidative stress biomarkers. Furthermore, for the wild populations, we studied the activity of fungal laccases, expression of the laccase gene lac1, and a possible effect of CHV1 intra-host diversity on the observed biochemical responses. Relative to the wild isolates, the long-term model strains had lower enzymatic activities of superoxide dismutase (SOD) and glutathione S-transferase (GST), and higher content of malondialdehyde (MDA) and total non-protein thiols. This indicated generally higher oxidative stress, likely arising from their decades-long history of subculturing and freeze-thaw cycles. When comparing the two wild populations, differences between them in stress resilience and levels of oxidative stress were also observed, as evident from the different MDA content. The intra-host genetic diversity of the CHV1 had no discernible effect on the stress levels of the virus-infected fungal cultures. Our research indicated that an important determinant modulating both lac1 expression and laccase enzyme activity is intrinsic to the fungus itself, possibly related to the vc type of the fungus, i.e., vegetative incompatibility genotype.
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Affiliation(s)
- Maja Popović
- Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia
| | - Lucija Nuskern
- Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia
| | - Karla Peranić
- Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia
| | - Rosemary Vuković
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Zorana Katanić
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | - Ljiljana Krstin
- Department of Biology, Josip Juraj Strossmayer University of Osijek, Osijek, Croatia
| | | | | | - Igor Poljak
- Faculty of Forestry and Wood Technology, University of Zagreb, Zagreb, Croatia
| | - Marilena Idžojtić
- Faculty of Forestry and Wood Technology, University of Zagreb, Zagreb, Croatia
| | - Daniel Rigling
- Swiss Federal Research Institute WSL, Birmensdorf, Switzerland
| | - Marin Ježić
- Department of Biology, Faculty of Science, University of Zagreb, Zagreb, Croatia
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16
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Xu L, Liu W, Bie M, Hu T, Yan D, Xiao Z, Holmes EC, Shi W. Identification of bovine coronavirus in a Daurian ground squirrel expands the host range of Betacoronavirus 1. Virol Sin 2023; 38:321-323. [PMID: 36863412 PMCID: PMC10176439 DOI: 10.1016/j.virs.2023.02.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/09/2022] [Accepted: 02/23/2023] [Indexed: 03/04/2023] Open
Affiliation(s)
- Lin Xu
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Ji'nan, 250117, China; Key Laboratory of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Wei Liu
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Mengyu Bie
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Ji'nan, 250117, China; Key Laboratory of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Tao Hu
- Key Laboratory of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China
| | - Dong Yan
- Anti-plague Institute of Hebei Province, Zhangjiakou, 075000, China
| | - Zhishu Xiao
- State Key Laboratory of Integrated Management of Pest Insects and Rodents, Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China; University of Chinese Academy of Sciences, Beijing, 100049, China
| | - Edward C Holmes
- Sydney Institute for Infectious Diseases, School of Medical Sciences, The University of Sydney, Sydney, NSW 2006, Australia
| | - Weifeng Shi
- School of Public Health, Shandong First Medical University & Shandong Academy of Medical Sciences, Ji'nan, 250117, China; Key Laboratory of Emerging Infectious Diseases in Universities of Shandong, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, 271000, China.
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17
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Nelson CW, Mirabello L. Human papillomavirus genomics: Understanding carcinogenicity. Tumour Virus Res 2023; 15:200258. [PMID: 36812987 PMCID: PMC10063409 DOI: 10.1016/j.tvr.2023.200258] [Citation(s) in RCA: 19] [Impact Index Per Article: 19.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2022] [Revised: 02/01/2023] [Accepted: 02/17/2023] [Indexed: 02/22/2023] Open
Abstract
Human papillomavirus (HPV) causes virtually all cervical cancers and many cancers at other anatomical sites in both men and women. However, only 12 of 448 known HPV types are currently classified as carcinogens, and even the most carcinogenic type - HPV16 - only rarely leads to cancer. HPV is therefore necessary but insufficient for cervical cancer, with other contributing factors including host and viral genetics. Over the last decade, HPV whole genome sequencing has established that even fine-scale within-type HPV variation influences precancer/cancer risks, and that these risks vary by histology and host race/ethnicity. In this review, we place these findings in the context of the HPV life cycle and evolution at various levels of viral diversity: between-type, within-type, and within-host. We also discuss key concepts necessary for interpreting HPV genomic data, including features of the viral genome; events leading to carcinogenesis; the role of APOBEC3 in HPV infection and evolution; and methodologies that use deep (high-coverage) sequencing to characterize within-host variation, as opposed to relying on a single representative (consensus) sequence. Given the continued high burden of HPV-associated cancers, understanding HPV carcinogenicity remains important for better understanding, preventing, and treating cancers attributable to infection.
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Affiliation(s)
- Chase W Nelson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA; Institute for Comparative Genomics, American Museum of Natural History, New York, NY, 10024, USA.
| | - Lisa Mirabello
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, 20850, USA.
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18
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Gabrielaite M, Bennedbæk M, Rasmussen MS, Kan V, Furrer H, Flisiak R, Losso M, Lundgren JD, Marvig RL. Deep-sequencing of viral genomes from a large and diverse cohort of treatment-naive HIV-infected persons shows associations between intrahost genetic diversity and viral load. PLoS Comput Biol 2023; 19:e1010756. [PMID: 36595537 PMCID: PMC9838853 DOI: 10.1371/journal.pcbi.1010756] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Revised: 01/13/2023] [Accepted: 11/23/2022] [Indexed: 01/04/2023] Open
Abstract
BACKGROUND Infection with human immunodeficiency virus type 1 (HIV) typically results from transmission of a small and genetically uniform viral population. Following transmission, the virus population becomes more diverse because of recombination and acquired mutations through genetic drift and selection. Viral intrahost genetic diversity remains a major obstacle to the cure of HIV; however, the association between intrahost diversity and disease progression markers has not been investigated in large and diverse cohorts for which the majority of the genome has been deep-sequenced. Viral load (VL) is a key progression marker and understanding of its relationship to viral intrahost genetic diversity could help design future strategies for HIV monitoring and treatment. METHODS We analysed deep-sequenced viral genomes from 2,650 treatment-naive HIV-infected persons to measure the intrahost genetic diversity of 2,447 genomic codon positions as calculated by Shannon entropy. We tested for associations between VL and amino acid (AA) entropy accounting for sex, age, race, duration of infection, and HIV population structure. RESULTS We confirmed that the intrahost genetic diversity is highest in the env gene. Furthermore, we showed that mean Shannon entropy is significantly associated with VL, especially in infections of >24 months duration. We identified 16 significant associations between VL (p-value<2.0x10-5) and Shannon entropy at AA positions which in our association analysis explained 13% of the variance in VL. Finally, equivalent analysis based on variation in HIV consensus sequences explained only 2% of VL variance. CONCLUSIONS Our results elucidate that viral intrahost genetic diversity is associated with VL and could be used as a better disease progression marker than HIV consensus sequence variants, especially in infections of longer duration. We emphasize that viral intrahost diversity should be considered when studying viral genomes and infection outcomes. TRIAL REGISTRATION Samples included in this study were derived from participants who consented in the clinical trial, START (NCT00867048) (23), run by the International Network for Strategic Initiatives in Global HIV Trials (INSIGHT). All the participant sites are listed here: http://www.insight-trials.org/start/my_phpscript/participating.php?by=site.
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Affiliation(s)
- Migle Gabrielaite
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
- * E-mail: (MG); (MB)
| | - Marc Bennedbæk
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
- * E-mail: (MG); (MB)
| | - Malthe Sebro Rasmussen
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
- Section of Computational and RNA Biology, Department of Biology, University of Copenhagen, Copenhagen, Denmark
| | - Virginia Kan
- Veterans Affairs Medical Center and The George Washington University School of Medicine and Health Sciences, Washington, District of Columbia, United States of America
| | - Hansjakob Furrer
- Department of Infectious Diseases, Bern University Hospital, University of Bern, Bern, Switzerland
| | - Robert Flisiak
- Department of Infectious Diseases and Hepatology, Medical University of Bialystok, Bialystok, Poland
| | - Marcelo Losso
- Hospital General De Agudos J M Ramos Mejía, Buenos Aires, Argentina
| | - Jens D. Lundgren
- Centre of Excellence for Health, Immunity and Infections, Department of Infectious Diseases, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | | | - Rasmus L. Marvig
- Center for Genomic Medicine, Rigshospitalet, Copenhagen, Denmark
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19
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Bendall EE, Paz-Bailey G, Santiago GA, Porucznik CA, Stanford JB, Stockwell MS, Duque J, Jeddy Z, Veguilla V, Major C, Rivera-Amill V, Rolfes MA, Dawood FS, Lauring AS. SARS-CoV-2 Genomic Diversity in Households Highlights the Challenges of Sequence-Based Transmission Inference. mSphere 2022; 7:e0040022. [PMID: 36377913 PMCID: PMC9769559 DOI: 10.1128/msphere.00400-22] [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] [Indexed: 11/16/2022] Open
Abstract
The reliability of sequence-based inference of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) transmission is not clear. Sequence data from infections among household members can define the expected genomic diversity of a virus along a defined transmission chain. SARS-CoV-2 cases were identified prospectively among 2,369 participants in 706 households. Specimens with a reverse transcription-PCR cycle threshold of ≤30 underwent whole-genome sequencing. Intrahost single-nucleotide variants (iSNV) were identified at a ≥5% frequency. Phylogenetic trees were used to evaluate the relationship of household and community sequences. There were 178 SARS-CoV-2 cases in 706 households. Among 147 specimens sequenced, 106 yielded a whole-genome consensus with coverage suitable for identifying iSNV. Twenty-six households had sequences from multiple cases within 14 days. Consensus sequences were indistinguishable among cases in 15 households, while 11 had ≥1 consensus sequence that differed by 1 to 2 mutations. Sequences from households and the community were often interspersed on phylogenetic trees. Identification of iSNV improved inference in 2 of 15 households with indistinguishable consensus sequences and in 6 of 11 with distinct ones. In multiple-infection households, whole-genome consensus sequences differed by 0 to 1 mutations. Identification of shared iSNV occasionally resolved linkage, but the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. IMPORTANCE We performed whole-genome sequencing of SARS-CoV-2 from prospectively identified cases in three longitudinal household cohorts. In a majority of multi-infection households, SARS-CoV-2 consensus sequences were indistinguishable, and they differed by 1 to 2 mutations in the rest. Importantly, even with modest genomic surveillance of the community (3 to 5% of cases sequenced), it was not uncommon to find community sequences interspersed with household sequences on phylogenetic trees. Identification of shared minority variants only occasionally resolved these ambiguities in transmission linkage. Overall, the low genomic diversity of SARS-CoV-2 limits the utility of "sequence-only" transmission inference. Our work highlights the need to carefully consider both epidemiologic linkage and sequence data to define transmission chains in households, hospitals, and other transmission settings.
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Affiliation(s)
- Emily E. Bendall
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
| | - Gabriela Paz-Bailey
- Centers for Disease Control and Preventiongrid.416738.f, Atlanta, Georgia, USA
| | | | - Christina A. Porucznik
- Division of Public Health, Department of Family and Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Joseph B. Stanford
- Division of Public Health, Department of Family and Preventive Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
| | - Melissa S. Stockwell
- Division of Child and Adolescent Health, Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, Columbia University, New York, New York, USA
- Department of Population and Family Health, Mailman School of Public Health, Columbia University, New York, New York, USA
| | | | - Zuha Jeddy
- Abt Associates, Rockville, Maryland, USA
| | - Vic Veguilla
- Centers for Disease Control and Preventiongrid.416738.f, Atlanta, Georgia, USA
| | - Chelsea Major
- Centers for Disease Control and Preventiongrid.416738.f, Atlanta, Georgia, USA
| | - Vanessa Rivera-Amill
- Ponce Research Institute, Ponce Health Sciences University, Ponce, Puerto Rico, USA
| | - Melissa A. Rolfes
- Centers for Disease Control and Preventiongrid.416738.f, Atlanta, Georgia, USA
| | - Fatimah S. Dawood
- Centers for Disease Control and Preventiongrid.416738.f, Atlanta, Georgia, USA
| | - Adam S. Lauring
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, USA
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, USA
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20
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The Innovative Informatics Approaches of High-Throughput Technologies in Livestock: Spearheading the Sustainability and Resiliency of Agrigenomics Research. LIFE (BASEL, SWITZERLAND) 2022; 12:life12111893. [PMID: 36431028 PMCID: PMC9695872 DOI: 10.3390/life12111893] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/25/2022] [Revised: 11/09/2022] [Accepted: 11/14/2022] [Indexed: 11/17/2022]
Abstract
For more than a decade, next-generation sequencing (NGS) has been emerging as the mainstay of agrigenomics research. High-throughput technologies have made it feasible to facilitate research at the scale and cost required for using this data in livestock research. Scale frameworks of sequencing for agricultural and livestock improvement, management, and conservation are partly attributable to innovative informatics methodologies and advancements in sequencing practices. Genome-wide sequence-based investigations are often conducted worldwide, and several databases have been created to discover the connections between worldwide scientific accomplishments. Such studies are beginning to provide revolutionary insights into a new era of genomic prediction and selection capabilities of various domesticated livestock species. In this concise review, we provide selected examples of the current state of sequencing methods, many of which are already being used in animal genomic studies, and summarize the state of the positive attributes of genome-based research for cattle (Bos taurus), sheep (Ovis aries), pigs (Sus scrofa domesticus), horses (Equus caballus), chickens (Gallus gallus domesticus), and ducks (Anas platyrhyncos). This review also emphasizes the advantageous features of sequencing technologies in monitoring and detecting infectious zoonotic diseases. In the coming years, the continued advancement of sequencing technologies in livestock agrigenomics will significantly influence the sustained momentum toward regulatory approaches that encourage innovation to ensure continued access to a safe, abundant, and affordable food supplies for future generations.
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21
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Rodríguez‐Pastor R, Shafran Y, Knossow N, Gutiérrez R, Harrus S, Zaman L, Lenski RE, Barrick JE, Hawlena H. A road map for in vivo evolution experiments with blood-borne parasitic microbes. Mol Ecol Resour 2022; 22:2843-2859. [PMID: 35599628 PMCID: PMC9796859 DOI: 10.1111/1755-0998.13649] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2021] [Revised: 03/14/2022] [Accepted: 05/13/2022] [Indexed: 01/07/2023]
Abstract
Laboratory experiments in which blood-borne parasitic microbes evolve in their animal hosts offer an opportunity to study parasite evolution and adaptation in real time and under natural settings. The main challenge of these experiments is to establish a protocol that is both practical over multiple passages and accurately reflects natural transmission scenarios and mechanisms. We provide a guide to the steps that should be considered when designing such a protocol, and we demonstrate its use via a case study. We highlight the importance of choosing suitable ancestral genotypes, treatments, number of replicates per treatment, types of negative controls, dependent variables, covariates, and the timing of checkpoints for the experimental design. We also recommend specific preliminary experiments to determine effective methods for parasite quantification, transmission, and preservation. Although these methodological considerations are technical, they also often have conceptual implications. To this end, we encourage other researchers to design and conduct in vivo evolution experiments with blood-borne parasitic microbes, despite the challenges that the work entails.
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Affiliation(s)
- Ruth Rodríguez‐Pastor
- Jacob Blaustein Center for Scientific Cooperation, The Jacob Blaustein Institutes for Desert ResearchBen‐Gurion University of the NegevMidreshet Ben‐GurionIsrael
| | - Yarden Shafran
- Mitrani Department of Desert Ecology, Swiss Institute for Dryland Environmental and Energy Research, The Jacob Blaustein Institutes for Desert ResearchBen‐Gurion University of the NegevMidreshet Ben‐GurionIsrael
| | - Nadav Knossow
- Mitrani Department of Desert Ecology, Swiss Institute for Dryland Environmental and Energy Research, The Jacob Blaustein Institutes for Desert ResearchBen‐Gurion University of the NegevMidreshet Ben‐GurionIsrael
| | - Ricardo Gutiérrez
- Koret School of Veterinary Medicine, Faculty of Agricultural, Nutritional and Environmental SciencesThe Hebrew University of JerusalemRehovotIsrael
| | - Shimon Harrus
- Koret School of Veterinary Medicine, Faculty of Agricultural, Nutritional and Environmental SciencesThe Hebrew University of JerusalemRehovotIsrael
| | - Luis Zaman
- Department of Ecology and Evolutionary Biology, The Center for the Study of Complex Systems (CSCS)University of MichiganAnn ArborMichiganUSA
| | - Richard E. Lenski
- Department of Microbiology and Molecular GeneticsMichigan State UniversityEast LansingMichiganUSA
| | - Jeffrey E. Barrick
- Department of Molecular BiosciencesThe University of Texas AustinAustinTexasUSA
| | - Hadas Hawlena
- Mitrani Department of Desert Ecology, Swiss Institute for Dryland Environmental and Energy Research, The Jacob Blaustein Institutes for Desert ResearchBen‐Gurion University of the NegevMidreshet Ben‐GurionIsrael
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22
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Abstract
The virus-encoded RNA-dependent RNA polymerase (RdRp) is responsible for viral replication, and its fidelity is closely related to viral diversity, pathogenesis, virulence, and fitness. Hepatitis C virus (HCV) and the second human pegivirus (HPgV-2) belong to the family Flaviviridae and share some features, including similar viral genome structure. Unlike HCV, HPgV-2 preserves a highly conserved genome sequence and low intrahost variation. However, the underlying mechanism remains to be elucidated. In this study, we evaluated the fidelity of HPgV-2 and HCV RdRp in an in vitro RNA polymerase reaction system. The results showed higher fidelity of HPgV-2 RdRp than HCV NS5B with respect to the misincorporation rate due to their difference in recognizing nucleoside triphosphate (NTP) substrates. Furthermore, HPgV-2 RdRp showed lower sensitivity than HCV to sofosbuvir, a nucleotide inhibitor against HCV RdRp, which explained the insusceptibility of HPgV-2 to direct-acting antiviral (DAA) therapy against HCV infection. Our results indicate that HPgV-2 could be an excellent model for studying the mechanisms involved in viral polymerase fidelity as well as RNA virus diversity and evolution. IMPORTANCE RNA viruses represent the most important pathogens for humans and animals and exhibit rapid evolution and high adaptive capacity, which is due to the high mutation rates for using the error-prone RNA-dependent RNA polymerase (RdRp) during replication. The fidelity of RdRp is closely associated with viral diversity, fitness, and pathogenesis. Previous studies have shown that the second human pegivirus (HPgV-2) exhibits a highly conserved genome sequence and low intrahost variation, which might be due to the fidelity of HPgV-2 RdRp. In this work, we used a series of in vitro RNA polymerase assays to evaluate the in vitro fidelity of HPgV-2 RdRp and compared it with that of HCV RdRp. The results indicated that HPgV-2 RdRp preserves significantly higher fidelity than HCV RdRp, which might contribute to the conservation of the HPgV-2 genome. The unique feature of HPgV-2 RdRp fidelity provides a new model for investigation of viral RdRp fidelity.
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23
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Alamil M, Thébaud G, Berthier K, Soubeyrand S. Characterizing viral within-host diversity in fast and non-equilibrium demo-genetic dynamics. Front Microbiol 2022; 13:983938. [PMID: 36274731 PMCID: PMC9581327 DOI: 10.3389/fmicb.2022.983938] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 09/08/2022] [Indexed: 11/13/2022] Open
Abstract
High-throughput sequencing has opened the route for a deep assessment of within-host genetic diversity that can be used, e.g., to characterize microbial communities and to infer transmission links in infectious disease outbreaks. The performance of such characterizations and inferences cannot be analytically assessed in general and are often grounded on computer-intensive evaluations. Then, being able to simulate within-host genetic diversity across time under various demo-genetic assumptions is paramount to assess the performance of the approaches of interest. In this context, we built an original model that can be simulated to investigate the temporal evolution of genotypes and their frequencies under various demo-genetic assumptions. The model describes the growth and the mutation of genotypes at the nucleotide resolution conditional on an overall within-host viral kinetics, and can be tuned to generate fast non-equilibrium demo-genetic dynamics. We ran simulations of this model and computed classic diversity indices to characterize the temporal variation of within-host genetic diversity (from high-throughput amplicon sequences) of virus populations under three demographic kinetic models of viral infection. Our results highlight how demographic (viral load) and genetic (mutation, selection, or drift) factors drive variations in within-host diversity during the course of an infection. In particular, we observed a non-monotonic relationship between pathogen population size and genetic diversity, and a reduction of the impact of mutation on diversity when a non-specific host immune response is activated. The large variation in the diversity patterns generated in our simulations suggests that the underlying model provides a flexible basis to produce very diverse demo-genetic scenarios and test, for instance, methods for the inference of transmission links during outbreaks.
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Affiliation(s)
- Maryam Alamil
- INRAE, BioSP, Avignon, France
- Department of Mathematics and Computer Science, Alfaisal University, Riyadh, Saudi Arabia
- *Correspondence: Maryam Alamil ;
| | - Gaël Thébaud
- PHIM Plant Health Institute, INRAE, Univ Montpellier, CIRAD, Institut Agro, IRD, Montpellier, France
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24
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The Second Human Pegivirus, a Non-Pathogenic RNA Virus with Low Prevalence and Minimal Genetic Diversity. Viruses 2022; 14:v14091844. [PMID: 36146649 PMCID: PMC9503178 DOI: 10.3390/v14091844] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/07/2022] [Revised: 08/14/2022] [Accepted: 08/18/2022] [Indexed: 02/02/2023] Open
Abstract
The second human pegivirus (HPgV-2) is a virus discovered in the plasma of a hepatitis C virus (HCV)-infected patient in 2015 belonging to the pegiviruses of the family Flaviviridae. HPgV-2 has been proved to be epidemiologically associated with and structurally similar to HCV but unrelated to HCV disease and non-pathogenic, but its natural history and tissue tropism remain unclear. HPgV-2 is a unique RNA virus sharing the features of HCV and the first human pegivirus (HPgV-1 or GBV-C). Moreover, distinct from most RNA viruses such as HCV, HPgV-1 and human immunodeficiency virus (HIV), HPgV-2 exhibits much lower genomic diversity, with a high global sequence identity ranging from 93.5 to 97.5% and significantly lower intra-host variation than HCV. The mechanisms underlying the conservation of the HPgV-2 genome are not clear but may include efficient innate immune responses, low immune selection pressure and, possibly, the unique features of the viral RNA-dependent RNA polymerase (RdRP). In this review, we summarize the prevalence, pathogenicity and genetic diversity of HPgV-2 and discuss the possible reasons for the uniformity of its genome sequence, which should elucidate the implications of RNA virus fidelity for attenuated viral vaccines.
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25
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Data analysis of viral complementary DNA/RNA sequences for low-frequency intrahost-single nucleotide variants in COVID-19. Proc Natl Acad Sci U S A 2022; 119:e2205269119. [PMID: 35914186 PMCID: PMC9407639 DOI: 10.1073/pnas.2205269119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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26
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Roder AE, Johnson KEE, Knoll M, Khalfan M, Wang B, Schultz-Cherry S, Banakis S, Kreitman A, Mederos C, Youn JH, Mercado R, Wang W, Ruchnewitz D, Samanovic MI, Mulligan MJ, Lassig M, Łuksza M, Das S, Gresham D, Ghedin E. Optimized Quantification of Intrahost Viral Diversity in SARS-CoV-2 and Influenza Virus Sequence Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2022:2021.05.05.442873. [PMID: 36656775 PMCID: PMC9836620 DOI: 10.1101/2021.05.05.442873] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/21/2023]
Abstract
High error rates of viral RNA-dependent RNA polymerases lead to diverse intra-host viral populations during infection. Errors made during replication that are not strongly deleterious to the virus can lead to the generation of minority variants. However, accurate detection of minority variants in viral sequence data is complicated by errors introduced during sample preparation and data analysis. We used synthetic RNA controls and simulated data to test seven variant calling tools across a range of allele frequencies and simulated coverages. We show that choice of variant caller, and use of replicate sequencing have the most significant impact on single nucleotide variant (SNV) discovery and demonstrate how both allele frequency and coverage thresholds impact both false discovery and false negative rates. We use these parameters to find minority variants in sequencing data from SARS-CoV-2 clinical specimens and provide guidance for studies of intrahost viral diversity using either single replicate data or data from technical replicates. Our study provides a framework for rigorous assessment of technical factors that impact SNV identification in viral samples and establishes heuristics that will inform and improve future studies of intrahost variation, viral diversity, and viral evolution. IMPORTANCE When viruses replicate inside a host, the virus replication machinery makes mistakes. Over time, these mistakes create mutations that result in a diverse population of viruses inside the host. Mutations that are neither lethal to the virus, nor strongly beneficial, can lead to minority variants that are minor members of the virus population. However, preparing samples for sequencing can also introduce errors that resemble minority variants, resulting in inclusion of false positive data if not filtered correctly. In this study, we aimed to determine the best methods for identification and quantification of these minority variants by testing the performance of seven commonly used variant calling tools. We used simulated and synthetic data to test their performance against a true set of variants, and then used these studies to inform variant identification in data from clinical SARS-CoV-2 clinical specimens. Together, analyses of our data provide extensive guidance for future studies of viral diversity and evolution.
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27
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Nishimura L, Fujito N, Sugimoto R, Inoue I. Detection of Ancient Viruses and Long-Term Viral Evolution. Viruses 2022; 14:v14061336. [PMID: 35746807 PMCID: PMC9230872 DOI: 10.3390/v14061336] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2022] [Revised: 06/15/2022] [Accepted: 06/16/2022] [Indexed: 12/22/2022] Open
Abstract
The COVID-19 outbreak has reminded us of the importance of viral evolutionary studies as regards comprehending complex viral evolution and preventing future pandemics. A unique approach to understanding viral evolution is the use of ancient viral genomes. Ancient viruses are detectable in various archaeological remains, including ancient people's skeletons and mummified tissues. Those specimens have preserved ancient viral DNA and RNA, which have been vigorously analyzed in the last few decades thanks to the development of sequencing technologies. Reconstructed ancient pathogenic viral genomes have been utilized to estimate the past pandemics of pathogenic viruses within the ancient human population and long-term evolutionary events. Recent studies revealed the existence of non-pathogenic viral genomes in ancient people's bodies. These ancient non-pathogenic viruses might be informative for inferring their relationships with ancient people's diets and lifestyles. Here, we reviewed the past and ongoing studies on ancient pathogenic and non-pathogenic viruses and the usage of ancient viral genomes to understand their long-term viral evolution.
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Affiliation(s)
- Luca Nishimura
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan; (L.N.); (N.F.); (R.S.)
- Department of Genetics, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Mishima 411-8540, Japan
| | - Naoko Fujito
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan; (L.N.); (N.F.); (R.S.)
- Department of Genetics, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Mishima 411-8540, Japan
| | - Ryota Sugimoto
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan; (L.N.); (N.F.); (R.S.)
| | - Ituro Inoue
- Human Genetics Laboratory, National Institute of Genetics, Mishima 411-8540, Japan; (L.N.); (N.F.); (R.S.)
- Department of Genetics, School of Life Science, The Graduate University for Advanced Studies (SOKENDAI), Mishima 411-8540, Japan
- Correspondence: ; Tel.: +81-55-981-6795
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28
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Low Pathogenicity H7N3 Avian Influenza Viruses Have Higher Within-Host Genetic Diversity Than a Closely Related High Pathogenicity H7N3 Virus in Infected Turkeys and Chickens. Viruses 2022; 14:v14030554. [PMID: 35336961 PMCID: PMC8951284 DOI: 10.3390/v14030554] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/03/2022] [Accepted: 03/04/2022] [Indexed: 12/11/2022] Open
Abstract
Within-host viral diversity offers a view into the early stages of viral evolution occurring after a virus infects a host. In recent years, advances in deep sequencing have allowed for routine identification of low-frequency variants, which are important sources of viral genetic diversity and can potentially emerge as a major virus population under certain conditions. We examined within-host viral diversity in turkeys and chickens experimentally infected with closely related H7N3 avian influenza viruses (AIVs), specifically one high pathogenicity AIV (HPAIV) and two low pathogenicity AIV (LPAIVs) with different neuraminidase protein stalk lengths. Consistent with the high mutation rates of AIVs, an abundance of intra-host single nucleotide variants (iSNVs) at low frequencies of 2–10% was observed in all samples collected. Furthermore, a small number of common iSNVs were observed between turkeys and chickens, and between directly inoculated and contact-exposed birds. Notably, the LPAIVs have significantly higher iSNV diversities and frequencies of nonsynonymous changes than the HPAIV in both turkeys and chickens. These findings highlight the dynamics of AIV populations within hosts and the potential impact of genetic changes, including mutations in the hemagglutinin gene that confers the high pathogenicity pathotype, on AIV virus populations and evolution.
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29
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Assessment of Inter-Laboratory Differences in SARS-CoV-2 Consensus Genome Assemblies between Public Health Laboratories in Australia. Viruses 2022; 14:v14020185. [PMID: 35215779 PMCID: PMC8875182 DOI: 10.3390/v14020185] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Revised: 01/10/2022] [Accepted: 01/10/2022] [Indexed: 12/12/2022] Open
Abstract
Whole-genome sequencing of viral isolates is critical for informing transmission patterns and for the ongoing evolution of pathogens, especially during a pandemic. However, when genomes have low variability in the early stages of a pandemic, the impact of technical and/or sequencing errors increases. We quantitatively assessed inter-laboratory differences in consensus genome assemblies of 72 matched SARS-CoV-2-positive specimens sequenced at different laboratories in Sydney, Australia. Raw sequence data were assembled using two different bioinformatics pipelines in parallel, and resulting consensus genomes were compared to detect laboratory-specific differences. Matched genome sequences were predominantly concordant, with a median pairwise identity of 99.997%. Identified differences were predominantly driven by ambiguous site content. Ignoring these produced differences in only 2.3% (5/216) of pairwise comparisons, each differing by a single nucleotide. Matched samples were assigned the same Pango lineage in 98.2% (212/216) of pairwise comparisons, and were mostly assigned to the same phylogenetic clade. However, epidemiological inference based only on single nucleotide variant distances may lead to significant differences in the number of defined clusters if variant allele frequency thresholds for consensus genome generation differ between laboratories. These results underscore the need for a unified, best-practices approach to bioinformatics between laboratories working on a common outbreak problem.
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30
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Ferreri LM, Geiger G, Seibert B, Obadan A, Rajao D, Lowen AC, Perez DR. Intra- and inter-host evolution of H9N2 influenza A virus in Japanese quail. Virus Evol 2022; 8:veac001. [PMID: 35223084 PMCID: PMC8865083 DOI: 10.1093/ve/veac001] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Revised: 12/21/2021] [Accepted: 01/07/2022] [Indexed: 11/13/2022] Open
Abstract
Influenza A viruses (IAVs) are constantly evolving. Crucial steps in the infection cycle, such as sialic acid (SA) receptor binding on the host cell surface, can either promote or hamper the emergence of new variants. We previously assessed the relative fitness in Japanese quail of H9N2 variant viruses differing at a single amino acid position, residue 216 in the hemagglutinin (HA) viral surface protein. This site is known to modulate SA recognition. Our prior study generated a valuable set of longitudinal samples from quail transmission groups where the inoculum comprised different mixed populations of HA 216 variant viruses. Here, we leveraged these samples to examine the evolutionary dynamics of viral populations within and between inoculated and naïve contact quails. We found that positive selection dominated HA gene evolution, but fixation of the fittest variant depended on the competition mixture. Analysis of the whole genome revealed further evidence of positive selection acting both within and between hosts. Positive selection drove fixation of variants in non-HA segments within inoculated and contact quails. Importantly, transmission bottlenecks were modulated by the molecular signature at HA 216, revealing viral receptor usage as a determinant of transmitted diversity. Overall, we show that selection strongly shaped the evolutionary dynamics within and between quails. These findings support the notion that selective processes act effectively on IAV populations in poultry hosts, facilitating rapid viral evolution in this ecological niche.
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Affiliation(s)
| | - Ginger Geiger
- Department of Population Health, Poultry Diagnostic and Research Center, College of Veterinary Medicine, University of Georgia, 953 College Station Rd, Athens, GA 30602, USA
| | - Brittany Seibert
- Department of Population Health, Poultry Diagnostic and Research Center, College of Veterinary Medicine, University of Georgia, 953 College Station Rd, Athens, GA 30602, USA
| | | | - Daniela Rajao
- Department of Population Health, Poultry Diagnostic and Research Center, College of Veterinary Medicine, University of Georgia, 953 College Station Rd, Athens, GA 30602, USA
| | - Anice C Lowen
- Department of Microbiology and Immunology, Emory University School of Medicine, Atlanta, GA 30322, USA
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Deere JD, Carroll TD, Dutra J, Fritts L, Sammak RL, Yee JL, Olstad KJ, Reader JR, Kistler A, Kamm J, Di Germanio C, Shaan Lakshmanappa Y, Elizaldi SR, Roh JW, Simmons G, Watanabe J, Pollard RE, Usachenko J, Immareddy R, Schmidt BA, O’Connor SL, DeRisi J, Busch MP, Iyer SS, Van Rompay KKA, Hartigan-O’Connor DJ, Miller CJ. SARS-CoV-2 Infection of Rhesus Macaques Treated Early with Human COVID-19 Convalescent Plasma. Microbiol Spectr 2021; 9:e0139721. [PMID: 34817208 PMCID: PMC8612156 DOI: 10.1128/spectrum.01397-21] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2021] [Accepted: 10/22/2021] [Indexed: 12/15/2022] Open
Abstract
Human clinical studies investigating use of convalescent plasma (CP) for treatment of coronavirus disease 2019 (COVID-19) have produced conflicting results. Outcomes in these studies may vary at least partly due to different timing of CP administration relative to symptom onset. The mechanisms of action of CP include neutralizing antibodies but may extend beyond virus neutralization to include normalization of blood clotting and dampening of inflammation. Unresolved questions include the minimum therapeutic titer in the CP units or CP recipient as well as the optimal timing of administration. Here, we show that treatment of macaques with CP within 24 h of infection does not reduce viral shedding in nasal or lung secretions compared to controls and does not detectably improve any clinical endpoint. We also demonstrate that CP administration does not impact viral sequence diversity in vivo, although the selection of a viral sequence variant in both macaques receiving normal human plasma was suggestive of immune pressure. Our results suggest that CP, administered to medium titers, has limited efficacy, even when given very early after infection. Our findings also contribute information important for the continued development of the nonhuman primate model of COVID-19. These results should inform interpretation of clinical studies of CP in addition to providing insights useful for developing other passive immunotherapies and vaccine strategies. IMPORTANCE Antiviral treatment options for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) remain very limited. One treatment that was explored beginning early in the pandemic (and that is likely to be tested early in future pandemics) is plasma collected from people who have recovered from coronavirus disease 2019 (COVID-19), known as convalescent plasma (CP). We tested if CP reduces viral shedding or disease in a nonhuman primate model. Our results demonstrate that administration of CP 1 day after SARS-CoV-2 infection had no significant impact on viral loads, clinical disease, or sequence diversity, although treatment with normal human plasma resulted in selection of a specific viral variant. Our results demonstrate that passive immunization with CP, even during early infection, provided no significant benefit in a nonhuman primate model of SARS-CoV-2 infection.
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Affiliation(s)
- Jesse D. Deere
- Department of Medical Microbiology and Immunology, School of Medicine, University of California Davis, Davis, California, USA
| | - Timothy D. Carroll
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Joseph Dutra
- Department of Medical Microbiology and Immunology, School of Medicine, University of California Davis, Davis, California, USA
| | - Linda Fritts
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
| | - Rebecca Lee Sammak
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - JoAnn L. Yee
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Katherine J. Olstad
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - J. Rachel Reader
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Amy Kistler
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | - Jack Kamm
- Chan Zuckerberg Biohub, San Francisco, California, USA
| | | | | | - Sonny R. Elizaldi
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
| | - Jamin W. Roh
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
| | - Graham Simmons
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA
| | - Jennifer Watanabe
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Rachel E. Pollard
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Jodie Usachenko
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Ramya Immareddy
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Brian A. Schmidt
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
| | - Shelby L. O’Connor
- Department of Pathology and Laboratory Medicine, University of Wisconsin-Madison, Madison, Wisconsin, USA
- Wisconsin National Primate Research Center, University of Wisconsin-Madison, Madison, Wisconsin, USA
| | - Joseph DeRisi
- Chan Zuckerberg Biohub, San Francisco, California, USA
- Department of Biochemistry and Biophysics, University of California San Francisco, San Francisco, California, USA
| | - Michael P. Busch
- Vitalant Research Institute, San Francisco, California, USA
- Department of Laboratory Medicine, University of California San Francisco, San Francisco, California, USA
| | - Smita S. Iyer
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
- California National Primate Research Center, University of California Davis, Davis, California, USA
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California Davis, Davis, California, USA
| | - Koen K. A. Van Rompay
- California National Primate Research Center, University of California Davis, Davis, California, USA
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California Davis, Davis, California, USA
| | - Dennis J. Hartigan-O’Connor
- Department of Medical Microbiology and Immunology, School of Medicine, University of California Davis, Davis, California, USA
- California National Primate Research Center, University of California Davis, Davis, California, USA
| | - Christopher J. Miller
- Center for Immunology and Infectious Diseases, University of California Davis, Davis, California, USA
- California National Primate Research Center, University of California Davis, Davis, California, USA
- Department of Pathology, Microbiology, and Immunology, School of Veterinary Medicine, University of California Davis, Davis, California, USA
- Department of Internal Medicine, Division of Infectious Diseases, School of Medicine, University of California Davis, Davis, California, USA
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Bauer M, Gomez-Gonzalez A, Suomalainen M, Schilling N, Hemmi S, Greber UF. A viral ubiquitination switch attenuates innate immunity and triggers nuclear import of virion DNA and infection. SCIENCE ADVANCES 2021; 7:eabl7150. [PMID: 34919430 PMCID: PMC8682987 DOI: 10.1126/sciadv.abl7150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/04/2023]
Abstract
Antiviral defense and virus exclusion from the cell nucleus restrict foreign nucleic acid influx and infection. How the genomes of DNA viruses evade cytosolic pattern recognition and cross the nuclear envelope is incompletely understood. Here, we show that the virion protein V of adenovirus functions as a linchpin between the genome and the capsid, thereby securing particle integrity. Absence of protein V destabilizes cytoplasmic particles and promotes premature genome release, raising cytokine levels through the DNA sensor cGAS. Non-ubiquitinable V yields stable virions, genome misdelivery to the cytoplasm, and increased cytokine levels. In contrast, normal protein V is ubiquitinated at the nuclear pore complex, dissociates from the virion depending on the E3 ubiquitin ligase Mib1 and the proteasome, and allows genome delivery into the nucleus for infection. Our data uncover previously unknown cellular and viral mechanisms of viral DNA nuclear import in pathogenesis, vaccination, gene therapy, and synthetic biology.
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Affiliation(s)
- Michael Bauer
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich CH8057, Switzerland
| | - Alfonso Gomez-Gonzalez
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich CH8057, Switzerland
- Life Science Zurich Graduate School, ETH and University of Zurich, Zurich 8057, Switzerland
| | - Maarit Suomalainen
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich CH8057, Switzerland
| | - Nicolas Schilling
- Center for Microscopy and Image Analysis, University of Zurich, Winterthurerstrasse 190, Zurich CH-8057, Switzerland
| | - Silvio Hemmi
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich CH8057, Switzerland
| | - Urs F. Greber
- Department of Molecular Life Sciences, University of Zurich, Winterthurerstrasse 190, Zurich CH8057, Switzerland
- Corresponding author.
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33
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Leigh DM, Peranić K, Prospero S, Cornejo C, Ćurković-Perica M, Kupper Q, Nuskern L, Rigling D, Ježić M. Long-read sequencing reveals the evolutionary drivers of intra-host diversity across natural RNA mycovirus infections. Virus Evol 2021; 7:veab101. [PMID: 35299787 PMCID: PMC8923234 DOI: 10.1093/ve/veab101] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2021] [Revised: 11/23/2021] [Accepted: 12/01/2021] [Indexed: 01/05/2023] Open
Abstract
Intra-host dynamics are a core component of virus evolution but most intra-host data come from a narrow range of hosts or experimental infections. Gaining broader information on the intra-host diversity and dynamics of naturally occurring virus infections is essential to our understanding of evolution across the virosphere. Here we used PacBio long-read HiFi sequencing to characterize the intra-host populations of natural infections of the RNA mycovirus Cryphonectria hypovirus 1 (CHV1). CHV1 is a biocontrol agent for the chestnut blight fungus (Cryphonectria parasitica), which co-invaded Europe alongside the fungus. We characterized the mutational and haplotypic intra-host virus diversity of thirty-eight natural CHV1 infections spread across four locations in Croatia and Switzerland. Intra-host CHV1 diversity values were shaped by purifying selection and accumulation of mutations over time as well as epistatic interactions within the host genome at defense loci. Geographical landscape features impacted CHV1 inter-host relationships through restricting dispersal and causing founder effects. Interestingly, a small number of intra-host viral haplotypes showed high sequence similarity across large geographical distances unlikely to be linked by dispersal.
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Affiliation(s)
- Deborah M Leigh
- Phytopathology, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf CH-8903, Switzerland
| | - Karla Peranić
- Faculty of Science, University of Zagreb, Zagreb, Grad Zagreb 10000, Croatia
| | - Simone Prospero
- Phytopathology, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf CH-8903, Switzerland
| | - Carolina Cornejo
- Phytopathology, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf CH-8903, Switzerland
| | | | | | - Lucija Nuskern
- Faculty of Science, University of Zagreb, Zagreb, Grad Zagreb 10000, Croatia
| | - Daniel Rigling
- Phytopathology, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf CH-8903, Switzerland
| | - Marin Ježić
- Faculty of Science, University of Zagreb, Zagreb, Grad Zagreb 10000, Croatia
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Abstract
The success of many viruses depends upon cooperative interactions between viral genomes. However, whenever cooperation occurs, there is the potential for 'cheats' to exploit that cooperation. We suggest that: (1) the biology of viruses makes viral cooperation particularly susceptible to cheating; (2) cheats are common across a wide range of viruses, including viral entities that are already well studied, such as defective interfering genomes, and satellite viruses. Consequently, the evolutionary theory of cheating could help us understand and manipulate viral dynamics, while viruses also offer new opportunities to study the evolution of cheating.
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Affiliation(s)
- Asher Leeks
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK.
| | - Stuart A West
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
| | - Melanie Ghoul
- Department of Zoology, University of Oxford, Oxford, OX1 3PS, UK
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35
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Faleye TOC, Adams D, Adhikari S, Sandrolini H, Halden RU, Varsani A, Scotch M. Use of hemagglutinin and neuraminidase amplicon-based high-throughput sequencing with variant analysis to detect co-infection and resolve identical consensus sequences of seasonal influenza in a university setting. BMC Infect Dis 2021; 21:810. [PMID: 34388979 PMCID: PMC8360813 DOI: 10.1186/s12879-021-06526-5] [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: 03/01/2021] [Accepted: 08/04/2021] [Indexed: 11/25/2022] Open
Abstract
Background Local transmission of seasonal influenza viruses (IVs) can be difficult to resolve. Here, we study if coupling high-throughput sequencing (HTS) of hemagglutinin (HA) and neuraminidase (NA) genes with variant analysis can resolve strains from local transmission that have identical consensus genome. We analyzed 24 samples collected over four days in January 2020 at a large university in the US. We amplified complete hemagglutinin (HA) and neuraminidase (NA) genomic segments followed by Illumina sequencing. We identified consensus complete HA and NA segments using BLASTn and performed variant analysis on strains whose HA and NA segments were 100% similar. Results Twelve of the 24 samples were PCR positive, and we detected complete HA and/or NA segments by de novo assembly in 83.33% (10/12) of them. Similarity and phylogenetic analysis showed that 70% (7/10) of the strains were distinct while the remaining 30% had identical consensus sequences. These three samples also had IAV and IBV co-infection. However, subsequent variant analysis showed that they had distinct variant profiles. While the IAV HA of one sample had no variant, another had a T663C mutation and another had both C1379T and C1589A. Conclusion In this study, we showed that HTS coupled with variant analysis of only HA and NA genes can help resolve variants that are closely related. We also provide evidence that during a short time period in the 2019–2020 season, co-infection of IAV and IBV occurred on the university campus and both 2020/2021 and 2021/2022 WHO recommended H1N1 vaccine strains were co-circulating. Supplementary Information The online version contains supplementary material available at 10.1186/s12879-021-06526-5.
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Affiliation(s)
- Temitope O C Faleye
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA
| | - Deborah Adams
- Biodesign Center for Personalized Diagnostics, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA
| | - Sangeet Adhikari
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.,School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, 85287, USA
| | - Helen Sandrolini
- Arizona State University Health Services, Arizona State University, Tempe, AZ, 85287, USA
| | - Rolf U Halden
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA.,School of Sustainable Engineering and the Built Environment, Arizona State University, Tempe, AZ, 85287, USA
| | - Arvind Varsani
- Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ, 85287, USA
| | - Matthew Scotch
- Biodesign Center for Environmental Health Engineering, Biodesign Institute, Arizona State University, Tempe, AZ, 85287, USA. .,College of Health Solutions, Arizona State University, Phoenix, AZ, 85004, USA.
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36
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Roodgar M, Good BH, Garud NR, Martis S, Avula M, Zhou W, Lancaster SM, Lee H, Babveyh A, Nesamoney S, Pollard KS, Snyder MP. Longitudinal linked-read sequencing reveals ecological and evolutionary responses of a human gut microbiome during antibiotic treatment. Genome Res 2021; 31:1433-1446. [PMID: 34301627 PMCID: PMC8327913 DOI: 10.1101/gr.265058.120] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/24/2020] [Accepted: 06/25/2021] [Indexed: 01/01/2023]
Abstract
Gut microbial communities can respond to antibiotic perturbations by rapidly altering their taxonomic and functional composition. However, little is known about the strain-level processes that drive this collective response. Here, we characterize the gut microbiome of a single individual at high temporal and genetic resolution through a period of health, disease, antibiotic treatment, and recovery. We used deep, linked-read metagenomic sequencing to track the longitudinal trajectories of thousands of single nucleotide variants within 36 species, which allowed us to contrast these genetic dynamics with the ecological fluctuations at the species level. We found that antibiotics can drive rapid shifts in the genetic composition of individual species, often involving incomplete genome-wide sweeps of pre-existing variants. These genetic changes were frequently observed in species without obvious changes in species abundance, emphasizing the importance of monitoring diversity below the species level. We also found that many sweeping variants quickly reverted to their baseline levels once antibiotic treatment had concluded, demonstrating that the ecological resilience of the microbiota can sometimes extend all the way down to the genetic level. Our results provide new insights into the population genetic forces that shape individual microbiomes on therapeutically relevant timescales, with potential implications for personalized health and disease.
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Affiliation(s)
- Morteza Roodgar
- Department of Genetics, Stanford University, Stanford, California 94305, USA.,Institute for Stem Cell Biology and Regenerative Medicine, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Benjamin H Good
- Department of Applied Physics, Stanford University, Stanford, California 94305, USA
| | - Nandita R Garud
- Department of Ecology and Evolutionary Biology, University of California Los Angeles, Los Angeles, California 90095, USA
| | - Stephen Martis
- Department of Physics, University of California, Berkeley, California 94720, USA
| | - Mohan Avula
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Wenyu Zhou
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Samuel M Lancaster
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Hayan Lee
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Afshin Babveyh
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Sophia Nesamoney
- Department of Genetics, Stanford University, Stanford, California 94305, USA
| | - Katherine S Pollard
- Gladstone Institutes, San Francisco, California 94158, USA.,Department of Epidemiology and Biostatistics, University of California, San Francisco, California 94158, USA.,Chan Zuckerberg Biohub, San Francisco, California 94158, USA
| | - Michael P Snyder
- Department of Genetics, Stanford University, Stanford, California 94305, USA
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37
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Nitesh J, Kashyap R, Surani SR. What we learned in the past year in managing our COVID-19 patients in intensive care units? World J Crit Care Med 2021; 10:81-101. [PMID: 34316444 PMCID: PMC8291007 DOI: 10.5492/wjccm.v10.i4.81] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/16/2021] [Revised: 04/07/2021] [Accepted: 05/17/2021] [Indexed: 02/06/2023] Open
Abstract
Coronavirus disease 2019 is a pandemic, was first recognized at Wuhan province, China in December 2019. The disease spread quickly across the globe, spreading stealthily from human to human through both symptomatic and asymptomatic individuals. A multisystem disease which appears to primarily spread via bio aerosols, it has exhibited a wide clinical spectrum involving multiple organ systems with the respiratory system pathology being the prime cause of morbidity and mortality. Initially unleashing a huge destructive trail at Wuhan China, Lombardy Italy and New York City, it has now spread to all parts of the globe and has actively thrived and mutated into new forms. Health care systems and Governments responded initially with panic, with containment measures giving way to mitigation strategies. The global medical and scientific community has come together and responded to this huge challenge. Professional medical societies quickly laid out "expert" guidelines which were conservative in their approach. Many drugs were re formulated and tested quickly with the help of national and international collaborative groups, helping carve out effective treatment strategies and help build a good scientific foundation for evidence-based medicine. Out of the darkness of chaos, we now have an orderly approach to manage this disease both from a public health preventive and therapeutic standpoint. With preventive measures such as masking and social distancing to the development of highly effective and potent vaccines, the public health success of such measures has been tempered by behavioral responses and resource mobilization. From a therapy standpoint, we now have drugs that were promising but now proven ineffective, and those that are effective when given early during viral pathogenesis or later when immune dysregulation has established, and the goal is to help reign in the destructive cascade. It has been a fascinating journey for mankind and our work here recapitulates the evolution of various aspects of critical care and other inpatient practices which continue to evolve.
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Affiliation(s)
- Jain Nitesh
- Department of Medicine, Mayo Clinic Health System, Mankato, MN 56001, United States
| | - Rahul Kashyap
- Department of Anesthesiology, Mayo Clinic, Rochester, MN 55905, United States
| | - Salim R Surani
- Department of Medicine, Texas A&M University, Corpus Christi, TX 78404, United States
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38
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Fuhrmann L, Jablonski KP, Beerenwinkel N. Quantitative measures of within-host viral genetic diversity. Curr Opin Virol 2021; 49:157-163. [PMID: 34153841 DOI: 10.1016/j.coviro.2021.06.002] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2021] [Revised: 06/03/2021] [Accepted: 06/07/2021] [Indexed: 12/22/2022]
Abstract
The genetic diversity of virus populations within their hosts is known to influence disease progression, treatment outcome, drug resistance, cell tropism, and transmission risk, and the study of dynamic changes of genetic heterogeneity can provide insights into the evolution of viruses. Several measures to quantify within-host genetic diversity capturing different aspects of diversity patterns in a sample or population are used, based on incidence, relative frequencies, pairwise distances, or phylogenetic trees. Here, we review and compare several of these measures.
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Affiliation(s)
- Lara Fuhrmann
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland; SIB Swiss Institute of Bioinformatics, Basel, 4058, Switzerland
| | - Kim Philipp Jablonski
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland; SIB Swiss Institute of Bioinformatics, Basel, 4058, Switzerland
| | - Niko Beerenwinkel
- Department of Biosystems Science and Engineering, ETH Zurich, Basel, 4058, Switzerland; SIB Swiss Institute of Bioinformatics, Basel, 4058, Switzerland.
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39
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Pascall DJ, Tinsley MC, Clark BL, Obbard DJ, Wilfert L. Virus Prevalence and Genetic Diversity Across a Wild Bumblebee Community. Front Microbiol 2021; 12:650747. [PMID: 33967987 PMCID: PMC8100031 DOI: 10.3389/fmicb.2021.650747] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/24/2021] [Indexed: 12/16/2022] Open
Abstract
Viruses are key population regulators, but we have limited knowledge of the diversity and ecology of viruses. This is even the case in wild host populations that provide ecosystem services, where small fitness effects may have major ecological impacts in aggregate. One such group of hosts are the bumblebees, which have a major role in the pollination of food crops and have suffered population declines and range contractions in recent decades. In this study, we investigate the diversity of four recently discovered bumblebee viruses (Mayfield virus 1, Mayfield virus 2, River Liunaeg virus, and Loch Morlich virus), and two previously known viruses that infect both wild bumblebees and managed honeybees (Acute bee paralysis virus and Slow bee paralysis virus) from isolates in Scotland. We investigate the ecological and environmental factors that determine viral presence and absence. We show that the recently discovered bumblebee viruses were more genetically diverse than the viruses shared with honeybees. Coinfection is potentially important in shaping prevalence: we found a strong positive association between River Liunaeg virus and Loch Morlich virus presence after controlling for host species, location and other relevant ecological variables. We tested for a relationship between environmental variables (temperature, UV radiation, wind speed, and prevalence), but as we had few sampling sites, and thus low power for site-level analyses, we could not conclude anything regarding these variables. We also describe the relationship between the bumblebee communities at our sampling sites. This study represents a first step in the description of predictors of bumblebee infection in the wild.
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Affiliation(s)
- David J. Pascall
- Institute of Biodiversity, Animal Health and Comparative Medicine, Boyd Orr Centre for Population and Ecosystem Health, University of Glasgow, Glasgow, United Kingdom
- Centre for Ecology and Conservation, University of Exeter, Cornwall, United Kingdom
| | - Matthew C. Tinsley
- Biological and Environmental Sciences, University of Stirling, Stirling, United Kingdom
| | - Bethany L. Clark
- BirdLife International, The David Attenborough Building, Cambridge, United Kingdom
- Environment and Sustainability Institute, University of Exeter, Cornwall, United Kingdom
| | - Darren J. Obbard
- Institute of Evolutionary Biology, University of Edinburgh, Edinburgh, United Kingdom
| | - Lena Wilfert
- Centre for Ecology and Conservation, University of Exeter, Cornwall, United Kingdom
- Institute of Evolutionary Ecology and Conservation Genomics, Ulm University, Ulm, Germany
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40
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Pontremoli C, Forni D, Clerici M, Cagliani R, Sironi M. Alternation between taxonomically divergent hosts is not the major determinant of flavivirus evolution. Virus Evol 2021; 7:veab040. [PMID: 33976907 PMCID: PMC8093920 DOI: 10.1093/ve/veab040] [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] [Indexed: 01/21/2023] Open
Abstract
Flaviviruses display diverse epidemiological and ecological features. Tick-borne and mosquito-borne flaviviruses (TBFV and MBFV, respectively) are important human pathogens that alternate replication in invertebrate vectors and vertebrate hosts. The Flavivirus genus also includes insect-specific viruses (ISFVs) and viruses with unknown invertebrate hosts. It is generally accepted that viruses that alternate between taxonomically different hosts evolve slowly and that the evolution of MBFVs and TBFVs is dominated by strong constraints, with limited episodes of positive selection. We exploited the availability of flavivirus genomes to test these hypotheses and to compare their rates and patterns of evolution. We estimated the substitution rates of CFAV and CxFV (two ISFVs) and, by taking into account the time-frame of measurement, compared them with those of other flaviviruses. Results indicated that CFAV and CxFV display relatively different substitution rates. However, these data, together with estimates for single-host members of the Flaviviridae family, indicated that MBFVs do not display relatively slower evolution. Conversely, TBFVs displayed some of lowest substitution rates among flaviviruses. Analysis of selective patterns over longer evolutionary time-frames confirmed that MBFVs evolve under strong purifying selection. Interestingly, TBFVs and ISFVs did not show extremely different levels of constraint, although TBFVs alternate among hosts, whereas ISFVs do not. Additional results showed that episodic positive selection drove the evolution of MBFVs, despite their high constraint. Positive selection was also detected on two branches of the TBFVs phylogeny that define the seabird clade. Thus, positive selection was much more common during the evolution of arthropod-borne flaviviruses than previously thought. Overall, our data indicate that flavivirus evolutionary patterns are complex and most likely determined by multiple factors, not limited to the alternation between taxonomically divergent hosts. The frequency of both positive and purifying selection, especially in MBFVs, suggests that a minority of sites in the viral polyprotein experience weak constraint and can evolve to generate new viral phenotypes and possibly promote adaptation to new hosts.
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Affiliation(s)
| | - Diego Forni
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
| | - Mario Clerici
- Department of Physiopathology and Transplantation, University of Milan, Milan 20122, Italy,Don C. Gnocchi Foundation ONLUS, IRCCS, Milan 20121, Italy
| | - Rachele Cagliani
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
| | - Manuela Sironi
- Scientific Institute IRCCS E. MEDEA, Bioinformatics, Bosisio Parini 23842, Italy
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41
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Valesano AL, Rumfelt KE, Dimcheff DE, Blair CN, Fitzsimmons WJ, Petrie JG, Martin ET, Lauring AS. Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts. PLoS Pathog 2021; 17:e1009499. [PMID: 33826681 PMCID: PMC8055005 DOI: 10.1371/journal.ppat.1009499] [Citation(s) in RCA: 72] [Impact Index Per Article: 24.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 04/19/2021] [Accepted: 03/24/2021] [Indexed: 01/12/2023] Open
Abstract
Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified viral load as a critical factor in variant identification. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.
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Affiliation(s)
- Andrew L. Valesano
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Kalee E. Rumfelt
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Derek E. Dimcheff
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Christopher N. Blair
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - William J. Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Joshua G. Petrie
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Emily T. Martin
- Department of Epidemiology, School of Public Health, University of Michigan, Ann Arbor, Michigan, United States of America
| | - Adam S. Lauring
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, Michigan, United States of America
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, Michigan, United States of America
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42
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Daughenbaugh KF, Kahnonitch I, Carey CC, McMenamin AJ, Wiegand T, Erez T, Arkin N, Ross B, Wiedenheft B, Sadeh A, Chejanovsky N, Mandelik Y, Flenniken ML. Metatranscriptome Analysis of Sympatric Bee Species Identifies Bee Virus Variants and a New Virus, Andrena-Associated Bee Virus-1. Viruses 2021; 13:291. [PMID: 33673324 PMCID: PMC7917660 DOI: 10.3390/v13020291] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2020] [Revised: 01/22/2021] [Accepted: 02/03/2021] [Indexed: 12/11/2022] Open
Abstract
Bees are important plant pollinators in agricultural and natural ecosystems. High average annual losses of honey bee (Apis mellifera) colonies in some parts of the world, and regional population declines of some mining bee species (Andrena spp.), are attributed to multiple factors including habitat loss, lack of quality forage, insecticide exposure, and pathogens, including viruses. While research has primarily focused on viruses in honey bees, many of these viruses have a broad host range. It is therefore important to apply a community level approach in studying the epidemiology of bee viruses. We utilized high-throughput sequencing to evaluate viral diversity and viral sharing in sympatric, co-foraging bees in the context of habitat type. Variants of four common viruses (i.e., black queen cell virus, deformed wing virus, Lake Sinai virus 2, and Lake Sinai virus NE) were identified in honey bee and mining bee samples, and the high degree of nucleotide identity in the virus consensus sequences obtained from both taxa indicates virus sharing. We discovered a unique bipartite + ssRNA Tombo-like virus, Andrena-associated bee virus-1 (AnBV-1). AnBV-1 infects mining bees, honey bees, and primary honey bee pupal cells maintained in culture. AnBV-1 prevalence and abundance was greater in mining bees than in honey bees. Statistical modeling that examined the roles of ecological factors, including floral diversity and abundance, indicated that AnBV-1 infection prevalence in honey bees was greater in habitats with low floral diversity and abundance, and that interspecific virus transmission is strongly modulated by the floral community in the habitat. These results suggest that land management strategies that aim to enhance floral diversity and abundance may reduce AnBV-1 spread between co-foraging bees.
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Affiliation(s)
- Katie F. Daughenbaugh
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA; (K.F.D.); (B.R.)
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
| | - Idan Kahnonitch
- The Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 5290002, Israel; (I.K.); (Y.M.)
- Agroecology Lab, Newe Ya’ar Research Center, ARO, Ramat Yishay 30095, Israel; (N.A.); (A.S.)
| | - Charles C. Carey
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
| | - Alexander J. McMenamin
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA;
| | - Tanner Wiegand
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
| | - Tal Erez
- Entomology Department, ARO, The Volcani Center, Rishon Lezion 7528809, Israel; (T.E.); (N.C.)
| | - Naama Arkin
- Agroecology Lab, Newe Ya’ar Research Center, ARO, Ramat Yishay 30095, Israel; (N.A.); (A.S.)
- The Mina & Everard Goodman Faculty of Life Sciences, Bar Ilan University, Ramat Gan 5290002, Israel
| | - Brian Ross
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA; (K.F.D.); (B.R.)
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
| | - Blake Wiedenheft
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA;
| | - Asaf Sadeh
- Agroecology Lab, Newe Ya’ar Research Center, ARO, Ramat Yishay 30095, Israel; (N.A.); (A.S.)
| | - Nor Chejanovsky
- Entomology Department, ARO, The Volcani Center, Rishon Lezion 7528809, Israel; (T.E.); (N.C.)
| | - Yael Mandelik
- The Faculty of Agriculture, Food and Environment, The Hebrew University of Jerusalem, Rehovot 5290002, Israel; (I.K.); (Y.M.)
| | - Michelle L. Flenniken
- Department of Plant Sciences and Plant Pathology, Montana State University, Bozeman, MT 59717, USA; (K.F.D.); (B.R.)
- Pollinator Health Center, Montana State University, Bozeman, MT 59717, USA; (C.C.C.); (A.J.M.); (T.W.)
- Department of Microbiology and Immunology, Montana State University, Bozeman, MT 59717, USA;
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43
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Valesano AL, Rumfelt KE, Dimcheff DE, Blair CN, Fitzsimmons WJ, Petrie JG, Martin ET, Lauring AS. Temporal dynamics of SARS-CoV-2 mutation accumulation within and across infected hosts. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.01.19.427330. [PMID: 33501443 PMCID: PMC7836113 DOI: 10.1101/2021.01.19.427330] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Analysis of SARS-CoV-2 genetic diversity within infected hosts can provide insight into the generation and spread of new viral variants and may enable high resolution inference of transmission chains. However, little is known about temporal aspects of SARS-CoV-2 intrahost diversity and the extent to which shared diversity reflects convergent evolution as opposed to transmission linkage. Here we use high depth of coverage sequencing to identify within-host genetic variants in 325 specimens from hospitalized COVID-19 patients and infected employees at a single medical center. We validated our variant calling by sequencing defined RNA mixtures and identified a viral load threshold that minimizes false positives. By leveraging clinical metadata, we found that intrahost diversity is low and does not vary by time from symptom onset. This suggests that variants will only rarely rise to appreciable frequency prior to transmission. Although there was generally little shared variation across the sequenced cohort, we identified intrahost variants shared across individuals who were unlikely to be related by transmission. These variants did not precede a rise in frequency in global consensus genomes, suggesting that intrahost variants may have limited utility for predicting future lineages. These results provide important context for sequence-based inference in SARS-CoV-2 evolution and epidemiology.
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Affiliation(s)
- Andrew L. Valesano
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Kalee E. Rumfelt
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Derek E. Dimcheff
- Division of Hospital Medicine, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
| | - Christopher N. Blair
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - William J. Fitzsimmons
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
| | - Joshua G. Petrie
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Emily T. Martin
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | - Adam S. Lauring
- Division of Infectious Diseases, Department of Internal Medicine, University of Michigan, Ann Arbor, MI, USA
- Department of Microbiology and Immunology, University of Michigan, Ann Arbor, MI, USA
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44
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San JE, Ngcapu S, Kanzi AM, Tegally H, Fonseca V, Giandhari J, Wilkinson E, Nelson CW, Smidt W, Kiran AM, Chimukangara B, Pillay S, Singh L, Fish M, Gazy I, Martin DP, Khanyile K, Lessells R, de Oliveira T. Transmission dynamics of SARS-CoV-2 within-host diversity in two major hospital outbreaks in South Africa. Virus Evol 2021; 7:veab041. [PMID: 34035952 PMCID: PMC8135343 DOI: 10.1093/ve/veab041] [Citation(s) in RCA: 28] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes acute, highly transmissible respiratory infection in humans and a wide range of animal species. Its rapid global spread has resulted in a major public health emergency, necessitating commensurately rapid research to improve control strategies. In particular, the ability to effectively retrace transmission chains in outbreaks remains a major challenge, partly due to our limited understanding of the virus' underlying evolutionary dynamics within and between hosts. We used high-throughput sequencing whole-genome data coupled with bottleneck analysis to retrace the pathways of viral transmission in two nosocomial outbreaks that were previously characterised by epidemiological and phylogenetic methods. Additionally, we assessed the mutational landscape, selection pressures, and diversity at the within-host level for both outbreaks. Our findings show evidence of within-host selection and transmission of variants between samples. Both bottleneck and diversity analyses highlight within-host and consensus-level variants shared by putative source-recipient pairs in both outbreaks, suggesting that certain within-host variants in these outbreaks may have been transmitted upon infection rather than arising de novo independently within multiple hosts. Overall, our findings demonstrate the utility of combining within-host diversity and bottleneck estimations for elucidating transmission events in SARS-CoV-2 outbreaks, provide insight into the maintenance of viral genetic diversity, provide a list of candidate targets of positive selection for further investigation, and demonstrate that within-host variants can be transferred between patients. Together these results will help in developing strategies to understand the nature of transmission events and curtail the spread of SARS-CoV-2.
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Affiliation(s)
- James E San
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Sinaye Ngcapu
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Medical Microbiology, University of KwaZulu-Natal, Durban, South Africa
| | - Aquillah M Kanzi
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Houriiyah Tegally
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Vagner Fonseca
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Jennifer Giandhari
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Eduan Wilkinson
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Chase W Nelson
- Biodiversity Research Center, Academia Sinica, Taipei, Taiwan
- Institute for Comparative Genomics, American Museum of Natural History, New York, NY, USA
| | - Werner Smidt
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
- Africa Health Research Institute (AHRI), Durban, South Africa
| | - Anmol M Kiran
- Malawi-Liverpool-Wellcome Trust, Queen Elizabeth Central Hospital, College of Medicine, Blantyre, Malawi
- Centre for Inflammation Research, Queens Research Institute, University of Edinburgh, Edinburgh, UK
| | - Benjamin Chimukangara
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Sureshnee Pillay
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Lavanya Singh
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Maryam Fish
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Inbal Gazy
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Darren P Martin
- Institute of Infectious Diseases and Molecular Medicine, Division of Computational Biology, Department of Integrative Biomedical Sciences, University of Cape Town, South Africa
| | - Khulekani Khanyile
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Richard Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu- Natal, Durban, South Africa
- Department of Global Health, University of Washington, Seattle, WA, USA
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45
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The Early Evolution of Oral Poliovirus Vaccine Is Shaped by Strong Positive Selection and Tight Transmission Bottlenecks. Cell Host Microbe 2020; 29:32-43.e4. [PMID: 33212020 PMCID: PMC7815045 DOI: 10.1016/j.chom.2020.10.011] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 10/12/2020] [Accepted: 10/26/2020] [Indexed: 01/06/2023]
Abstract
The emergence of circulating vaccine-derived polioviruses through evolution of the oral polio vaccine (OPV) poses a significant obstacle to polio eradication. Understanding the early genetic changes that occur as OPV evolves and transmits is important for preventing future outbreaks. Here, we use deep sequencing to define the evolutionary trajectories of type 2 OPV in a vaccine trial. By sequencing 497 longitudinal stool samples from 271 OPV2 recipients and household contacts, we were able to examine the extent of convergent evolution in vaccinated individuals and the amount of viral diversity that is transmitted. In addition to rapid reversion of key attenuating mutations, we identify strong selection at 19 sites across the genome. We find that a tight transmission bottleneck limits the onward transmission of these early adaptive mutations. Our results highlight the distinct evolutionary dynamics of live attenuated virus vaccines and have important implications for the success of next-generation OPV.
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46
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James SE, Ngcapu S, Kanzi AM, Tegally H, Fonseca V, Giandhari J, Wilkinson E, Chimukangara B, Pillay S, Singh L, Fish M, Gazy I, Khanyile K, Lessells R, de Oliveira T. High Resolution analysis of Transmission Dynamics of Sars-Cov-2 in Two Major Hospital Outbreaks in South Africa Leveraging Intrahost Diversity. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2020:2020.11.15.20231993. [PMID: 33236025 PMCID: PMC7685338 DOI: 10.1101/2020.11.15.20231993] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes acute, highly transmissible respiratory infection in both humans and wide range of animal species. Its rapid spread globally and devasting effects have resulted into a major public health emergency prompting the need for methodological interventions to understand and control its spread. In particular, The ability to effectively retrace its transmission pathways in outbreaks remains a major challenge. This is further exacerbated by our limited understanding of its underlying evolutionary mechanism. Using NGS whole-genome data, we determined whether inter- and intra-host diversity coupled with bottleneck analysis can retrace the pathway of viral transmission in two epidemiologically well characterised nosocomial outbreaks in healthcare settings supported by phylogenetic analysis. Additionally, we assessed the mutational landscape, selection pressure and diversity of the identified variants. Our findings showed evidence of intrahost variant transmission and evolution of SARS-CoV-2 after infection These observations were consistent with the results from the bottleneck analysis suggesting that certain intrahost variants in this study could have been transmitted to recipients. In both outbreaks, we observed iSNVs and SNVs shared by putative source-recipients pairs. Majority of the observed iSNVs were positioned in the S and ORF1ab region. AG, CT and TC nucleotide changes were enriched across SARS-COV-2 genome. Moreover, SARS-COV-2 genome had limited diversity in some loci while being highly conserved in others. Overall, Our findings show that the synergistic effect of combining withinhost diversity and bottleneck estimations greatly enhances resolution of transmission events in Sars-Cov-2 outbreaks. They also provide insight into the genome diversity suggesting purifying selection may be involved in the transmission. Together these results will help in developing strategies to elucidate transmission events and curtail the spread of Sars-Cov-2.
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Affiliation(s)
- San Emmanuel James
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Sinaye Ngcapu
- Centre for the AIDS Programme of Research in South Africa (CAPRISA), Durban, South Africa
- Department of Medical Microbiology, University of KwaZulu-Natal, Durban, South Africa
| | - Aquillah M Kanzi
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Houriiyah Tegally
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Vagner Fonseca
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Jennifer Giandhari
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Eduan Wilkinson
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Benjamin Chimukangara
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Sureshnee Pillay
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Lavanya Singh
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Maryam Fish
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Inbal Gazy
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Khulekani Khanyile
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
| | - Richard Lessells
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
- Department of Global Health, University of Washington, Seattle, USA
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine & Medical Sciences, University of KwaZulu-Natal, Durban, South Africa
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