1
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Sonela N, Mann J, Godwe C, Goni OH, Tchakoute M, Nkoue N, de Oliveira T, Brockman MA, Brumme ZL, Ndung'u T, Tongo M. No detectable differences in Nef-mediated downregulation of HLA-I and CD4 molecules among HIV-1 group M lineages circulating in Cameroon, where the pandemic originated. FRONTIERS IN VIROLOGY (LAUSANNE, SWITZERLAND) 2024; 4:fviro.2024.1379217. [PMID: 38883214 PMCID: PMC7616105 DOI: 10.3389/fviro.2024.1379217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/18/2024]
Abstract
HIV-1 group M (HIV-1M) lineages downregulate HLA-I and CD4 expression via their Nef proteins. We hypothesized that these Nef functions may be partially responsible for the differences in prevalence of viruses from different lineages that co-circulate within an epidemic. Here, we characterized these two Nef activities in HIV-1M isolates from Cameroon, where multiple variants have been circulating since the pandemic's origin. Single HIV-1 Nef clones from 234 HIV-1-ART naïve individuals living in remote villages and two cosmopolitan cities of Cameroon, sampled between 2000 and 2013, were isolated from plasma HIV RNA and analyzed for their capacity to downregulate HLA-I and CD4 molecules. We found that, despite a large degree of within- and inter- lineage variation, the ability of Nef to downregulate HLA-I was similar across these different viruses. Moreover, Nef-mediated CD4 downregulation activity was also well conserved across the different lineages found in Cameroon. In addition, we observed a trend towards higher HLA-I downregulation activity of viruses circulating in the cosmopolitan cities versus the remote villages, whereas the CD4 downregulation activities were similar across the two settings. Furthermore, we noted a significant decline of HLA-I downregulation activity from 2000 to 2013, providing additional evidence supporting the attenuation of the global HIV-1M population over time. Finally, we identified 18 amino acids associated with differential HLA-I downregulation and 13 amino acids associated with differential CD4 downregulation within the dominant CRF02_AG lineage. Our lack of observation of HIV lineage-related differences in Nef-mediated HLA-I and CD4 downregulation function suggests that these activities do not substantively influence the prevalence of different HIV-1M lineages in Cameroon.
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Affiliation(s)
- Nelson Sonela
- Center of Research for Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon
- Chantal BIYA International Reference Centre for Research on HIV/AIDS prevention and management (CIRCB), Yaoundé, Cameroon
- Department of Medicine, Weill Cornell Medical College, Cornell University, New York, NY, United States
| | - Jaclyn Mann
- HIV Pathogenesis Programme, University of KwaZulu-Natal, Durban, South Africa
| | - Celestin Godwe
- Center of Research for Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon
- Départment of Biochemistry, University of Douala, Douala, Cameroon
| | - Oumarou H Goni
- Center of Research for Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon
- Départment of Microbiology, Faculty of Sciences, University of Yaoundé 1, Yaoundé, Cameroon
| | - Mérime Tchakoute
- Programmes de Santé et développement au sein du Groupement de la Filière Bois du Cameroun, Yaoundé, Cameroon
| | - Nathalie Nkoue
- Programmes de Santé et développement au sein du Groupement de la Filière Bois du Cameroun, Yaoundé, Cameroon
| | - Tulio de Oliveira
- Centre for Epidemic Response and Innovation (CERI), School of Data Science and Computational Thinking, Stellenbosch University, Stellenbosch, South Africa
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, Nelson R Mandela School of Medicine, University of KwaZulu-Natal, Durban, South Africa
| | - Mark A Brockman
- Molecular Biology and Biochemistry, Simon Fraser University, Burnaby, BC, Canada
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
| | - Zabrina L Brumme
- Faculty of Health Sciences, Simon Fraser University, Burnaby, BC, Canada
- British Columbia Centre for Excellence in HIV/AIDS, Vancouver, BC, Canada
| | - Thumbi Ndung'u
- HIV Pathogenesis Programme, University of KwaZulu-Natal, Durban, South Africa
- Max Planck Institute for Infection Biology, Berlin, Germany
- Africa Health Research Institute (AHRI), Durban, South Africa
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, United States
- Division of Infection and Immunity, University College London, London, United Kingdom
| | - Marcel Tongo
- Center of Research for Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon
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2
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Gupta S. Darwin review: the evolution of virulence in human pathogens. Proc Biol Sci 2024; 291:20232043. [PMID: 38320607 PMCID: PMC10846939 DOI: 10.1098/rspb.2023.2043] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2023] [Accepted: 01/10/2024] [Indexed: 02/08/2024] Open
Abstract
By definition, all pathogens cause some level of harm to their hosts. If this harm occurs while the pathogen is transmitting, it can negatively affect the pathogen's fitness by shortening the duration over which transmission can occur. However, many of the factors that increase virulence (i.e. harm to host) also promote transmission, driving the pathogen population towards an optimal state of intermediate virulence. A wider spectrum of virulence may be maintained among pathogen populations which are structured into multiple discrete strains though direct resource and immune-mediated competition. These various evolutionary outcomes, and the effects of medical and public health interventions, are best understood within a framework that recognizes the complex relationship between transmission and virulence in the context of the antigenic diversity of the pathogen population.
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Affiliation(s)
- Sunetra Gupta
- Department of Biology, University of Oxford, Oxford, UK
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3
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Lindsay RJ, Holder PJ, Talbot NJ, Gudelj I. Metabolic efficiency reshapes the seminal relationship between pathogen growth rate and virulence. Ecol Lett 2023; 26:896-907. [PMID: 37056166 PMCID: PMC10947253 DOI: 10.1111/ele.14218] [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: 11/16/2022] [Revised: 03/14/2023] [Accepted: 03/15/2023] [Indexed: 04/15/2023]
Abstract
A cornerstone of classical virulence evolution theories is the assumption that pathogen growth rate is positively correlated with virulence, the amount of damage pathogens inflict on their hosts. Such theories are key for incorporating evolutionary principles into sustainable disease management strategies. Yet, empirical evidence raises doubts over this central assumption underpinning classical theories, thus undermining their generality and predictive power. In this paper, we identify a key component missing from current theories which redefines the growth-virulence relationship in a way that is consistent with data. By modifying the activity of a single metabolic gene, we engineered strains of Magnaporthe oryzae with different nutrient acquisition and growth rates. We conducted in planta infection studies and uncovered an unexpected non-monotonic relationship between growth rate and virulence that is jointly shaped by how growth rate and metabolic efficiency interact. This novel mechanistic framework paves the way for a much-needed new suite of virulence evolution theories.
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Affiliation(s)
| | | | - Nicholas J. Talbot
- The Sainsbury LaboratoryUniversity of East Anglia, Norwich Research ParkNorwichUK
| | - Ivana Gudelj
- Biosciences and Living Systems InstituteUniversity of ExeterExeterUK
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4
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Kun Á, Hubai AG, Král A, Mokos J, Mikulecz BÁ, Radványi Á. Do pathogens always evolve to be less virulent? The virulence–transmission trade-off in light of the COVID-19 pandemic. Biol Futur 2023:10.1007/s42977-023-00159-2. [PMID: 37002448 PMCID: PMC10066022 DOI: 10.1007/s42977-023-00159-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/21/2022] [Accepted: 03/09/2023] [Indexed: 04/03/2023]
Abstract
AbstractThe direction the evolution of virulence takes in connection with any pathogen is a long-standing question. Formerly, it was theorized that pathogens should always evolve to be less virulent. As observations were not in line with this theoretical outcome, new theories emerged, chief among them the transmission–virulence trade-off hypotheses, which predicts an intermediate level of virulence as the endpoint of evolution. At the moment, we are very much interested in the future evolution of COVID-19’s virulence. Here, we show that the disease does not fulfill all the assumptions of the hypothesis. In the case of COVID-19, a higher viral load does not mean a higher risk of death; immunity is not long-lasting; other hosts can act as reservoirs for the virus; and death as a consequence of viral infection does not shorten the infectious period. Consequently, we cannot predict the short- or long-term evolution of the virulence of COVID-19.
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5
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Grant HE, Roy S, Williams R, Tutill H, Ferns B, Cane PA, Carswell JW, Ssemwanga D, Kaleebu P, Breuer J, Leigh Brown AJ. A large population sample of African HIV genomes from the 1980s reveals a reduction in subtype D over time associated with propensity for CXCR4 tropism. Retrovirology 2022; 19:28. [PMID: 36514107 PMCID: PMC9746199 DOI: 10.1186/s12977-022-00612-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2022] [Accepted: 11/12/2022] [Indexed: 12/15/2022] Open
Abstract
We present 109 near full-length HIV genomes amplified from blood serum samples obtained during early 1986 from across Uganda, which to our knowledge is the earliest and largest population sample from the initial phase of the HIV epidemic in Africa. Consensus sequences were made from paired-end Illumina reads with a target-capture approach to amplify HIV material following poor success with standard approaches. In comparisons with a smaller 'intermediate' genome dataset from 1998 to 1999 and a 'modern' genome dataset from 2007 to 2016, the proportion of subtype D was significantly higher initially, dropping from 67% (73/109), to 57% (26/46) to 17% (82/465) respectively (p < 0.0001). Subtype D has previously been shown to have a faster rate of disease progression than other subtypes in East African population studies, and to have a higher propensity to use the CXCR4 co-receptor ("X4 tropism"); associated with a decrease in time to AIDS. Here we find significant differences in predicted tropism between A1 and D subtypes in all three sample periods considered, which is particularly striking the 1986 sample: 66% (53/80) of subtype D env sequences were predicted to be X4 tropic compared with none of the 24 subtype A1. We also analysed the frequency of subtype in the envelope region of inter-subtype recombinants, and found that subtype A1 is over-represented in env, suggesting recombination and selection have acted to remove subtype D env from circulation. The reduction of subtype D frequency over three decades therefore appears to be a result of selective pressure against X4 tropism and its higher virulence. Lastly, we find a subtype D specific codon deletion at position 24 of the V3 loop, which may explain the higher propensity for subtype D to utilise X4 tropism.
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Affiliation(s)
- Heather E Grant
- Institute of Ecology and Evolution, University of Edinburgh, Edinburgh, UK.
| | - Sunando Roy
- Division of Infection and Immunity, University College London, London, UK
| | - Rachel Williams
- UCL Great Ormond Street Institute of Child Health, London, UK
| | - Helena Tutill
- Division of Infection and Immunity, University College London, London, UK
| | - Bridget Ferns
- Department of Virology, University College London Hospitals NHS Foundation Trust, London, UK
| | | | | | - Deogratius Ssemwanga
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe, Uganda
| | - Pontiano Kaleebu
- Medical Research Council (MRC)/Uganda Virus Research Institute (UVRI) and London School of Hygiene and Tropical Medicine (LSHTM) Uganda Research Unit, Entebbe, Uganda
| | - Judith Breuer
- Division of Infection and Immunity, University College London, London, UK
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6
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Viral proteases as therapeutic targets. Mol Aspects Med 2022; 88:101159. [PMID: 36459838 PMCID: PMC9706241 DOI: 10.1016/j.mam.2022.101159] [Citation(s) in RCA: 15] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2022] [Revised: 11/21/2022] [Accepted: 11/23/2022] [Indexed: 11/30/2022]
Abstract
Some medically important viruses-including retroviruses, flaviviruses, coronaviruses, and herpesviruses-code for a protease, which is indispensable for viral maturation and pathogenesis. Viral protease inhibitors have become an important class of antiviral drugs. Development of the first-in-class viral protease inhibitor saquinavir, which targets HIV protease, started a new era in the treatment of chronic viral diseases. Combining several drugs that target different steps of the viral life cycle enables use of lower doses of individual drugs (and thereby reduction of potential side effects, which frequently occur during long term therapy) and reduces drug-resistance development. Currently, several HIV and HCV protease inhibitors are routinely used in clinical practice. In addition, a drug including an inhibitor of SARS-CoV-2 main protease, nirmatrelvir (co-administered with a pharmacokinetic booster ritonavir as Paxlovid®), was recently authorized for emergency use. This review summarizes the basic features of the proteases of human immunodeficiency virus (HIV), hepatitis C virus (HCV), and SARS-CoV-2 and discusses the properties of their inhibitors in clinical use, as well as development of compounds in the pipeline.
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7
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Durmaz V, Köchl K, Krassnigg A, Parigger L, Hetmann M, Singh A, Nutz D, Korsunsky A, Kahler U, König C, Chang L, Krebs M, Bassetto R, Pavkov-Keller T, Resch V, Gruber K, Steinkellner G, Gruber CC. Structural bioinformatics analysis of SARS-CoV-2 variants reveals higher hACE2 receptor binding affinity for Omicron B.1.1.529 spike RBD compared to wild type reference. Sci Rep 2022; 12:14534. [PMID: 36008461 PMCID: PMC9406262 DOI: 10.1038/s41598-022-18507-y] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2021] [Accepted: 08/08/2022] [Indexed: 01/16/2023] Open
Abstract
To date, more than 263 million people have been infected with SARS-CoV-2 during the COVID-19 pandemic. In many countries, the global spread occurred in multiple pandemic waves characterized by the emergence of new SARS-CoV-2 variants. Here we report a sequence and structural-bioinformatics analysis to estimate the effects of amino acid substitutions on the affinity of the SARS-CoV-2 spike receptor binding domain (RBD) to the human receptor hACE2. This is done through qualitative electrostatics and hydrophobicity analysis as well as molecular dynamics simulations used to develop a high-precision empirical scoring function (ESF) closely related to the linear interaction energy method and calibrated on a large set of experimental binding energies. For the latest variant of concern (VOC), B.1.1.529 Omicron, our Halo difference point cloud studies reveal the largest impact on the RBD binding interface compared to all other VOC. Moreover, according to our ESF model, Omicron achieves a much higher ACE2 binding affinity than the wild type and, in particular, the highest among all VOCs except Alpha and thus requires special attention and monitoring.
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Affiliation(s)
| | | | | | | | - Michael Hetmann
- Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria.,Austrian Centre of Industrial Biotechnology, 8010, Graz, Austria
| | - Amit Singh
- Innophore GmbH, 8010, Graz, Austria.,Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria
| | | | | | | | | | - Lee Chang
- AWS Diagnostic Development Initiative-Global Social Impact, Seattle, WA, 98109, USA
| | - Marius Krebs
- Amazon Web Services EMEA SARL, 80807, Muenchen, Germany
| | | | - Tea Pavkov-Keller
- Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria
| | | | - Karl Gruber
- Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria.,Field of Excellence BioHealth-University of Graz, 8010, Graz, Austria
| | - Georg Steinkellner
- Innophore GmbH, 8010, Graz, Austria. .,Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria.
| | - Christian C Gruber
- Innophore GmbH, 8010, Graz, Austria. .,Institute of Molecular Biosciences, University of Graz, 8010, Graz, Austria.
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8
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Fofana AM, Hurford A. Parasite-induced shifts in host movement may explain the transient coexistence of high- and low-pathogenic disease strains. J Evol Biol 2022; 35:1072-1086. [PMID: 35789020 DOI: 10.1111/jeb.14053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2018] [Revised: 05/30/2022] [Accepted: 06/02/2022] [Indexed: 11/27/2022]
Abstract
Many parasites induce decreased host movement, known as lethargy, which can impact disease spread and the evolution of virulence. Mathematical models have investigated virulence evolution when parasites cause host death, but disease-induced decreased host movement has received relatively less attention. Here, we consider a model where, due to the within-host parasite replication rate, an infected host can become lethargic and shift from a moving to a resting state, where it can die. We find that when the lethargy and disease-induced mortality costs to the parasites are not high, then evolutionary bistability can arise, and either moderate or high virulence can evolve depending on the initial virulence and the magnitude of mutation. These results suggest, firstly, the coexistence of strains with different virulence, which may explain the transient coexistence of low- and high-pathogenic strains of avian influenza viruses, and secondly, that medical interventions to treat the symptoms of lethargy or prevent disease-induced host deaths can result in a large jump in virulence and the rapid evolution of high virulence. In complement to existing results that show bistability when hosts are heterogeneous at the population level, we show that evolutionary bistability may arise due to transmission heterogeneity at the individual host level.
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Affiliation(s)
- Abdou Moutalab Fofana
- Biology, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
| | - Amy Hurford
- Biology, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada.,Mathematics and Statistics, Memorial University of Newfoundland, St. John's, Newfoundland and Labrador, Canada
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9
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Sheppard SK. Strain wars and the evolution of opportunistic pathogens. Curr Opin Microbiol 2022; 67:102138. [DOI: 10.1016/j.mib.2022.01.009] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/29/2021] [Revised: 01/13/2022] [Accepted: 01/20/2022] [Indexed: 01/28/2023]
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10
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Susi H, Sallinen S, Laine AL. Coinfection with a virus constrains within-host infection load but increases transmission potential of a highly virulent fungal plant pathogen. Ecol Evol 2022; 12:e8673. [PMID: 35342557 PMCID: PMC8928890 DOI: 10.1002/ece3.8673] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2022] [Revised: 02/07/2022] [Accepted: 02/07/2022] [Indexed: 12/23/2022] Open
Abstract
The trade‐off between within‐host infection rate and transmission to new hosts is predicted to constrain pathogen evolution, and to maintain polymorphism in pathogen populations. Pathogen life‐history stages and their correlations that underpin infection development may change under coinfection with other parasites as they compete for the same limited host resources. Cross‐kingdom interactions are common among pathogens in both natural and cultivated systems, yet their impacts on disease ecology and evolution are rarely studied. The host plant Plantago lanceolata is naturally infected by both Phomopsis subordinaria, a seed killing fungus, as well as Plantago lanceolata latent virus (PlLV) in the Åland Islands, SW Finland. We performed an inoculation assay to test whether coinfection with PlLV affects performance of two P. subordinaria strains, and the correlation between within‐host infection rate and transmission potential. The strains differed in the measured life‐history traits and their correlations. Moreover, we found that under virus coinfection, within‐host infection rate of P. subordinaria was smaller but transmission potential was higher compared to strains under single infection. The negative correlation between within‐host infection rate and transmission potential detected under single infection became positive under coinfection with PlLV. To understand whether within‐host and between‐host dynamics are correlated in wild populations, we surveyed 260 natural populations of P. lanceolata for P. subordinaria infection occurrence. When infections were found, we estimated between‐hosts dynamics by determining pathogen population size as the proportion of infected individuals, and within‐host dynamics by counting the proportion of infected flower stalks in 10 infected plants. In wild populations, the proportion of infected flower stalks was positively associated with pathogen population size. Jointly, our results suggest that the trade‐off between within‐host infection load and transmission may be strain specific, and that the pathogen life‐history that underpin epidemics may change depending on the diversity of infection, generating variation in disease dynamics.
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Affiliation(s)
- Hanna Susi
- Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme University of Helsinki Helsinki Finland
| | - Suvi Sallinen
- Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme University of Helsinki Helsinki Finland
| | - Anna-Liisa Laine
- Research Centre for Ecological Change, Organismal and Evolutionary Biology Research Programme University of Helsinki Helsinki Finland.,Department of Evolutionary Biology and Environmental Studies University of Zurich Zurich Switzerland
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11
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Abstract
[Figure: see text].
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Affiliation(s)
- Joel O Wertheim
- Department of Medicine, University of California, San Diego, La Jolla, CA, USA
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12
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Wymant C, Bezemer D, Blanquart F, Ferretti L, Gall A, Hall M, Golubchik T, Bakker M, Ong SH, Zhao L, Bonsall D, de Cesare M, MacIntyre-Cockett G, Abeler-Dörner L, Albert J, Bannert N, Fellay J, Grabowski MK, Gunsenheimer-Bartmeyer B, Günthard HF, Kivelä P, Kouyos RD, Laeyendecker O, Meyer L, Porter K, Ristola M, van Sighem A, Berkhout B, Kellam P, Cornelissen M, Reiss P, Fraser C, Aubert V, Battegay M, Bernasconi E, Böni J, Braun DL, Bucher HC, Burton-Jeangros C, Calmy A, Cavassini M, Dollenmaier G, Egger M, Elzi L, Fehr J, Fellay J, Furrer H, Fux CA, Gorgievski M, Günthard H, Haerry D, Hasse B, Hirsch HH, Hoffmann M, Hösli I, Kahlert C, Kaiser L, Keiser O, Klimkait T, Kouyos R, Kovari H, Ledergerber B, Martinetti G, de Tejada BM, Marzolini C, Metzner K, Müller N, Nadal D, Nicca D, Pantaleo G, Rauch A, Regenass S, Rudin C, Schöni-Affolter F, Schmid P, Speck R, Stöckle M, Tarr P, Trkola A, Vernazza P, Weber R, Yerly S, van der Valk M, Geerlings SE, Goorhuis A, Hovius JW, Lempkes B, Nellen FJB, van der Poll T, Prins JM, Reiss P, van Vugt M, Wiersinga WJ, Wit FWMN, van Duinen M, van Eden J, Hazenberg A, van Hes AMH, Rajamanoharan S, Robinson T, Taylor B, Brewer C, Mayr C, Schmidt W, Speidel A, Strohbach F, Arastéh K, Cordes C, Pijnappel FJJ, Stündel M, Claus J, Baumgarten A, Carganico A, Ingiliz P, Dupke S, Freiwald M, Rausch M, Moll A, Schleehauf D, Smalhout SY, Hintsche B, Klausen G, Jessen H, Jessen A, Köppe S, Kreckel P, Schranz D, Fischer K, Schulbin H, Speer M, Weijsenfeld AM, Glaunsinger T, Wicke T, Bieniek B, Hillenbrand H, Schlote F, Lauenroth-Mai E, Schuler C, Schürmann D, Wesselmann H, Brockmeyer N, Jurriaans S, Gehring P, Schmalöer D, Hower M, Spornraft-Ragaller P, Häussinger D, Reuter S, Esser S, Markus R, Kreft B, Berzow D, Back NKT, Christl A, Meyer A, Plettenberg A, Stoehr A, Graefe K, Lorenzen T, Adam A, Schewe K, Weitner L, Fenske S, Zaaijer HL, Hansen S, Stellbrink HJ, Wiemer D, Hertling S, Schmidt R, Arbter P, Claus B, Galle P, Jäger H, Jä Gel-Guedes E, Berkhout B, Postel N, Fröschl M, Spinner C, Bogner J, Salzberger B, Schölmerich J, Audebert F, Marquardt T, Schaffert A, Schnaitmann E, Cornelissen MTE, Trein A, Frietsch B, Müller M, Ulmer A, Detering-Hübner B, Kern P, Schubert F, Dehn G, Schreiber M, Güler C, Schinkel CJ, Gunsenheimer-Bartmeyer B, Schmidt D, Meixenberger K, Bannert N, Wolthers KC, Peters EJG, van Agtmael MA, Autar RS, Bomers M, Sigaloff KCE, Heitmuller M, Laan LM, Ang CW, van Houdt R, Jonges M, Kuijpers TW, Pajkrt D, Scherpbier HJ, de Boer C, van der Plas A, van den Berge M, Stegeman A, Baas S, Hage de Looff L, Buiting A, Reuwer A, Veenemans J, Wintermans B, Pronk MJH, Ammerlaan HSM, van den Bersselaar DNJ, de Munnik ES, Deiman B, Jansz AR, Scharnhorst V, Tjhie J, Wegdam MCA, van Eeden A, Nellen J, Brokking W, Elsenburg LJM, Nobel H, van Kasteren MEE, Berrevoets MAH, Brouwer AE, Adams A, van Erve R, de Kruijf-van de Wiel BAFM, Keelan-Phaf S, van de Ven B, van der Ven B, Buiting AGM, Murck JL, de Vries-Sluijs TEMS, Bax HI, van Gorp ECM, de Jong-Peltenburg NC, de Mendonç A Melo M, van Nood E, Nouwen JL, Rijnders BJA, Rokx C, Schurink CAM, Slobbe L, Verbon A, Bassant N, van Beek JEA, Vriesde M, van Zonneveld LM, de Groot J, Boucher CAB, Koopmans MPG, van Kampen JJA, Fraaij PLA, van Rossum AMC, Vermont CL, van der Knaap LC, Visser E, Branger J, Douma RA, Cents-Bosma AS, Duijf-van de Ven CJHM, Schippers EF, van Nieuwkoop C, van Ijperen JM, Geilings J, van der Hut G, van Burgel ND, Leyten EMS, Gelinck LBS, Mollema F, Davids-Veldhuis S, Tearno C, Wildenbeest GS, Heikens E, Groeneveld PHP, Bouwhuis JW, Lammers AJJ, Kraan S, van Hulzen AGW, Kruiper MSM, van der Bliek GL, Bor PCJ, Debast SB, Wagenvoort GHJ, Kroon FP, de Boer MGJ, Jolink H, Lambregts MMC, Roukens AHE, Scheper H, Dorama W, van Holten N, Claas ECJ, Wessels E, den Hollander JG, El Moussaoui R, Pogany K, Brouwer CJ, Smit JV, Struik-Kalkman D, van Niekerk T, Pontesilli O, Lowe SH, Oude Lashof AML, Posthouwer D, van 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Summerfield H, Evans M, White C, Robertson R, Lean C, Morris S, Winter A, Faulkner S, Goorney B, Howard L, Fairley I, Stemp C, Short L, Gomez M, Young F, Roberts M, Green S, Sivakumar K, Minton J, Siminoni A, Calderwood J, Greenhough D, DeSouza C, Muthern L, Orkin C, Murphy S, Truvedi M, McLean K, Hawkins D, Higgs C, Moyes A, Antonucci S, McCormack S, Lynn W, Bevan M, Fox J, Teague A, Anderson J, Mguni S, Post F, Campbell L, Mazhude C, Russell H, Gilson R, Carrick G, Ainsworth J, Waters A, Byrne P, Johnson M, Fidler S, Kuldanek K, Mullaney S, Lawlor V, Melville R, Sukthankar A, Thorpe S, Murphy C, Wilkins E, Ahmad S, Green P, Tayal S, Ong E, Meaden J, Riddell L, Loay D, Peacock K, Blackman H, Harindra V, Saeed AM, Allen S, Natarajan U, Williams O, Lacey H, Care C, Bowman C, Herman S, Devendra SV, Wither J, Bridgwood A, Singh G, Bushby S, Kellock D, Young S, Rooney G, Snart B, Currie J, Fitzgerald M, Arumainayyagam J, Chandramani S. A highly virulent variant of HIV-1 circulating in the Netherlands. Science 2022; 375:540-545. [PMID: 35113714 DOI: 10.1126/science.abk1688] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We discovered a highly virulent variant of subtype-B HIV-1 in the Netherlands. One hundred nine individuals with this variant had a 0.54 to 0.74 log10 increase (i.e., a ~3.5-fold to 5.5-fold increase) in viral load compared with, and exhibited CD4 cell decline twice as fast as, 6604 individuals with other subtype-B strains. Without treatment, advanced HIV-CD4 cell counts below 350 cells per cubic millimeter, with long-term clinical consequences-is expected to be reached, on average, 9 months after diagnosis for individuals in their thirties with this variant. Age, sex, suspected mode of transmission, and place of birth for the aforementioned 109 individuals were typical for HIV-positive people in the Netherlands, which suggests that the increased virulence is attributable to the viral strain. Genetic sequence analysis suggests that this variant arose in the 1990s from de novo mutation, not recombination, with increased transmissibility and an unfamiliar molecular mechanism of virulence.
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Affiliation(s)
- Chris Wymant
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - François Blanquart
- Centre for Interdisciplinary Research in Biology (CIRB), Collège de France, CNRS, INSERM, PSL Research University, Paris, France.,IAME, UMR 1137, INSERM, Université de Paris, Paris, France
| | - Luca Ferretti
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Astrid Gall
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridge, UK
| | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Tanya Golubchik
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Swee Hoe Ong
- Wellcome Sanger Institute, Wellcome Genome Campus, Cambridge, UK
| | - Lele Zhao
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - David Bonsall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Mariateresa de Cesare
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - George MacIntyre-Cockett
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Lucie Abeler-Dörner
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden.,Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
| | - Norbert Bannert
- Division for HIV and Other Retroviruses, Department of Infectious Diseases, Robert Koch Institute, Berlin, Germany
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.,Swiss Institute of Bioinformatics, Lausanne, Switzerland.,Precision Medicine Unit, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
| | - M Kate Grabowski
- Department of Pathology, John Hopkins University, Baltimore, MD, USA
| | | | - Huldrych F Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Pia Kivelä
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Roger D Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland.,Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | | | - Laurence Meyer
- INSERM CESP U1018, Université Paris Saclay, APHP, Service de Santé Publique, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | - Kholoud Porter
- Institute for Global Health, University College London, London, UK
| | - Matti Ristola
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | | | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Paul Kellam
- Kymab Ltd., Cambridge, UK.,Department of Infectious Diseases, Faculty of Medicine, Imperial College London, London, UK
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands.,Molecular Diagnostic Unit, Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, Netherlands
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, Netherlands.,Department of Global Health, Amsterdam University Medical Centers, University of Amsterdam and Amsterdam Institute for Global Health and Development, Amsterdam, Netherlands
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, UK.,Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
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Focosi D, Maggi F, Casadevall A. Mucosal Vaccines, Sterilizing Immunity, and the Future of SARS-CoV-2 Virulence. Viruses 2022; 14:187. [PMID: 35215783 PMCID: PMC8878800 DOI: 10.3390/v14020187] [Citation(s) in RCA: 53] [Impact Index Per Article: 26.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2021] [Revised: 01/15/2022] [Accepted: 01/17/2022] [Indexed: 02/01/2023] Open
Abstract
Sterilizing immunity after vaccination is desirable to prevent the spread of infection from vaccinees, which can be especially dangerous in hospital settings while managing frail patients. Sterilizing immunity requires neutralizing antibodies at the site of infection, which for respiratory viruses such as SARS-CoV-2 implies the occurrence of neutralizing IgA in mucosal secretions. Systemic vaccination by intramuscular delivery induces no or low-titer neutralizing IgA against vaccine antigens. Mucosal priming or boosting, is needed to provide sterilizing immunity. On the other side of the coin, sterilizing immunity, by zeroing interhuman transmission, could confine SARS-CoV-2 in animal reservoirs, preventing spontaneous attenuation of virulence in humans as presumably happened with the endemic coronaviruses. We review here the pros and cons of each vaccination strategy, the current mucosal SARS-CoV-2 vaccines under development, and their implications for public health.
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Affiliation(s)
- Daniele Focosi
- North-Western Tuscany Blood Bank, Pisa University Hospital, 56124 Pisa, Italy
| | - Fabrizio Maggi
- Department of Medicine and Surgery, University of Insubria, 21100 Varese, Italy;
| | - Arturo Casadevall
- Department of Medicine, Johns Hopkins School of Public Health and School of Medicine, Baltimore, MD 21218, USA;
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14
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Virulence management: Closing the feedback loop between healthcare interventions and virulence evolution. J Theor Biol 2021; 531:110900. [PMID: 34530031 DOI: 10.1016/j.jtbi.2021.110900] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2020] [Revised: 08/30/2021] [Accepted: 09/06/2021] [Indexed: 11/22/2022]
Abstract
We study the evolution of virulence of an endemic pathogen in response to healthcare interventions which affect host recovery and pathogen transmission. By anticipating the evolutionary response of the pathogen we may develop effective long-term management strategies for controlling the impact of the endemic on the society. To that end, we use standard Adaptive Dynamics techniques in an SIS model. The recovery rate and the transmission rate, both of which can be affected by healthcare interventions, are used as evolutionary control variables. The effect of interventions may be density-independent (self-help based on healthcare instructions) or density-dependent (when assistance of a healthcare worker is required). We consider the evolutionary response of the pathogen both to abrupt changes and to gradual changes in the level of healthcare intervention. Healthcare intervention is optimised for three alternative objectives: minimisation of virulence, minimisation of the probability that an infected individual dies of the disease, and total eradication of the endemic. We find that the optimal strategy may depend on the objective. High levels of healthcare intervention may eradicate the pathogen, but this option may not be available for budgetary reasons or otherwise. Counterintuitively, to minimise virulence, one should keep healthcare interventions at a minimum, while to minimise the probability for an infected individual to die of the disease, both low and high levels of healthcare intervention suffice. Changes in the level of healthcare intervention should be implemented fast (not gradually) in order to avoid sudden changes in pathogen evolution and the possible emergence of multiple simultaneously coexisting pathogen strains.
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15
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Tolo IE, Bajer PG, Wolf TM, Mor SK, Phelps NBD. Investigation of Cyprinid Herpesvirus 3 (CyHV-3) Disease Periods and Factors Influencing CyHV-3 Transmission in A Low Stocking Density Infection Trial. Animals (Basel) 2021; 12:ani12010002. [PMID: 35011108 PMCID: PMC8749781 DOI: 10.3390/ani12010002] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2021] [Revised: 12/08/2021] [Accepted: 12/10/2021] [Indexed: 12/01/2022] Open
Abstract
Simple Summary Pathogens are the primary limitation to aquaculture production of fish and a major issue in consideration of the interface between cultured and wild populations of fishes worldwide. While rapid spread of fish pathogens between populations (wild or farmed) is generally anthropogenic and the result of trade, the mechanisms of transmission once a pathogen has been introduced to a fish population are not well understood. The most widespread pathogen impacting both aquaculture and wild populations of common carp (Cyprinus carpio, carp) is Cyprinid herpesvirus 3 (CyHV-3). To understand how CyHV-3 is transmitted in a population we conducted a series of infection trials, designed to determine the kinetics CyHV-3 infections, identify the contributions of direct and indirect forms of CyHV-3 transmission, and to determine the contributions of contact rate, viral load, pathogenicity, and contact type. We found that direct contact between fish was the primary mechanism of CyHV-3 transmission rather than transmission through contaminated water. Additionally, CyHV-3 transmission occurred primarily during the incubation period of CyHV-3, prior to the appearance of disease signs and disease-associated reduction in contact rate. Abstract Cyprinid herpesvirus 3 (CyHV-3) is the etiological agent of koi herpesvirus disease (KHVD) and important pathogen of aquaculture and wild populations of common carp worldwide. Understanding the relative contributions of direct and indirect transmission of CyHV-3 as well as the factors that drive CyHV-3 transmission can clarify the importance of environmental disease vectors and is valuable for informing disease modeling efforts. To study the mechanisms and factors driving CyHV-3 transmission we conducted infection trials that determined the kinetics of KHVD and the contributions of direct and indirect forms of CyHV-3 transmission, as well as the contributions of contact rate, viral load, pathogenicity and contact type. The incubation period of KHVD was 5.88 + 1.75 days and the symptomatic period was 5.31 + 0.87 days. Direct transmission was determined to be the primary mechanism of CyHV-3 transmission (OR = 25.08, 95%CI = 10.73–99.99, p = 4.29 × 10−18) and transmission primarily occurred during the incubation period of KHVD. Direct transmission decreased in the symptomatic period of disease. Transmissibility of CyHV-3 and indirect transmission increased during the symptomatic period of disease, correlating with increased viral loads. Additionally, potential virulence-transmission tradeoffs and disease avoidance behaviors relevant to CyHV-3 transmission were identified.
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Affiliation(s)
- Isaiah E. Tolo
- Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St. Paul, MN 55108, USA; (I.E.T.); (P.G.B.); (S.K.M.)
- Department of Fisheries, Wildlife, and Conservation Biology, College of Food, Agriculture and Natural Resource Sciences, University of Minnesota, St. Paul, MN 55108, USA
| | - Przemyslaw G. Bajer
- Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St. Paul, MN 55108, USA; (I.E.T.); (P.G.B.); (S.K.M.)
- Department of Fisheries, Wildlife, and Conservation Biology, College of Food, Agriculture and Natural Resource Sciences, University of Minnesota, St. Paul, MN 55108, USA
| | - Tiffany M. Wolf
- Department of Veterinary Population Medicine and Veterinary Diagnostic Laboratory, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA;
| | - Sunil K. Mor
- Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St. Paul, MN 55108, USA; (I.E.T.); (P.G.B.); (S.K.M.)
- Department of Veterinary Population Medicine and Veterinary Diagnostic Laboratory, College of Veterinary Medicine, University of Minnesota, St. Paul, MN 55108, USA;
| | - Nicholas B. D. Phelps
- Minnesota Aquatic Invasive Species Research Center, University of Minnesota, St. Paul, MN 55108, USA; (I.E.T.); (P.G.B.); (S.K.M.)
- Department of Fisheries, Wildlife, and Conservation Biology, College of Food, Agriculture and Natural Resource Sciences, University of Minnesota, St. Paul, MN 55108, USA
- Correspondence:
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16
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Díaz AV, Walker M, Webster JP. Surveillance and control of SARS-CoV-2 in mustelids: An evolutionary perspective. Evol Appl 2021; 14:2715-2725. [PMID: 34899977 PMCID: PMC8652926 DOI: 10.1111/eva.13310] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/02/2021] [Revised: 09/28/2021] [Accepted: 09/29/2021] [Indexed: 01/18/2023] Open
Abstract
The relevance of mustelids in SARS-CoV-2 transmission has become increasingly evident. Alongside experimental demonstration of airborne transmission among ferrets, the major animal model for human respiratory diseases, transmission of SARS-CoV-2 within- and/or between-commercial mink farms has occurred and continues to occur. The number of mink reared for the luxury fur trade is approximately 60.5 million, across 36 mustelid-farming countries. By July 2021, SARS-CoV-2 outbreaks have been reported in 12 of these countries, at 412 European and 20 North American mink farms. Reverse zoonotic transmission events (from humans to mink) have introduced the virus to farms with subsequent extensive mink-to-mink transmission as well as further zoonotic (mink-to-human) transmission events generating cases among both farm workers and the broader community. Overcrowded housing conditions inherent within intensive mink farms, often combined with poor sanitation and welfare, both guarantee spread of SARS-CoV-2 and facilitate opportunities for viral variants, thereby effectively representing biotic hubs for viral transmission and evolution of virulence. Adequate preventative, surveillance and control measures within the mink industry are imperative both for the control of the current global pandemic and to mitigate against future outbreaks.
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Affiliation(s)
- Adriana V Díaz
- Department of Pathobiology and Population Sciences Royal Veterinary College University of London Herts UK
| | - Martin Walker
- Department of Pathobiology and Population Sciences Royal Veterinary College University of London Herts UK
| | - Joanne P Webster
- Department of Pathobiology and Population Sciences Royal Veterinary College University of London Herts UK
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17
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Farinre O, Gounder K, Reddy T, Tongo M, Hare J, Chaplin B, Gilmour J, Kanki P, Mann JK, Ndung'u T. Subtype-specific differences in Gag-protease replication capacity of HIV-1 isolates from East and West Africa. Retrovirology 2021; 18:11. [PMID: 33952315 PMCID: PMC8097975 DOI: 10.1186/s12977-021-00554-4] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2021] [Accepted: 04/12/2021] [Indexed: 11/24/2022] Open
Abstract
BACKGROUND The HIV-1 epidemic in sub-Saharan Africa is heterogeneous with diverse unevenly distributed subtypes and regional differences in prevalence. Subtype-specific differences in disease progression rate and transmission efficiency have been reported, but the underlying biological mechanisms have not been fully characterized. Here, we tested the hypothesis that the subtypes prevalent in the East Africa, where adult prevalence rate is higher, have lower viral replication capacity (VRC) than their West African counterparts where adult prevalence rates are lower. RESULTS Gag-protease sequencing was performed on 213 and 160 antiretroviral-naïve chronically infected participants from West and East Africa respectively and bioinformatic tools were used to infer subtypes and recombination patterns. VRC of patient-derived gag-protease chimeric viruses from West (n = 178) and East (n = 114) Africa were determined using a green fluorescent protein reporter-based cell assay. Subtype and regional differences in VRC and amino acid variants impacting VRC were identified by statistical methods. CRF02_AG (65%, n = 139), other recombinants (14%, n = 30) and pure subtypes (21%, n = 44) were identified in West Africa. Subtypes A1 (64%, n = 103), D (22%, n = 35), or recombinants (14%, n = 22) were identified in East Africa. Viruses from West Africa had significantly higher VRC compared to those from East Africa (p < 0.0001), with subtype-specific differences found among strains within West and East Africa (p < 0.0001). Recombination patterns showed a preference for subtypes D, G or J rather than subtype A in the p6 region of gag, with evidence that subtype-specific differences in this region impact VRC. Furthermore, the Gag A83V polymorphism was associated with reduced VRC in CRF02_AG. HLA-A*23:01 (p = 0.0014) and HLA-C*07:01 (p = 0.002) were associated with lower VRC in subtype A infected individuals from East Africa. CONCLUSIONS Although prevalent viruses from West Africa displayed higher VRC than those from East Africa consistent with the hypothesis that lower VRC is associated with higher population prevalence, the predominant CRF02_AG strain in West Africa displayed higher VRC than other prevalent strains suggesting that VRC alone does not explain population prevalence. The study identified viral and host genetic determinants of virus replication capacity for HIV-1 CRF02_AG and subtype A respectively, which may have relevance for vaccine strategies.
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Affiliation(s)
- Omotayo Farinre
- HIV Pathogenesis Programme, The Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa
| | - Kamini Gounder
- HIV Pathogenesis Programme, The Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa
- Africa Health Research Institute, Durban, 4001, South Africa
| | - Tarylee Reddy
- Biostatistics Research Unit, South African Medical Research Council, Durban, South Africa
| | - Marcel Tongo
- Centre of Research for Emerging and Re-Emerging Diseases (CREMER), Yaoundé, Cameroon
| | - Jonathan Hare
- International AIDS Vaccine Initiative (IAVI) Human Immunology Laboratory (HIL), Imperial College, London, UK
- IAVI Global Headquarters, 125 Broad Street, 9th Floor,, New York, NY, USA
| | - Beth Chaplin
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jill Gilmour
- International AIDS Vaccine Initiative (IAVI) Human Immunology Laboratory (HIL), Imperial College, London, UK
- IAVI Global Headquarters, 125 Broad Street, 9th Floor,, New York, NY, USA
| | - Phyllis Kanki
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jaclyn K Mann
- HIV Pathogenesis Programme, The Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa
| | - Thumbi Ndung'u
- HIV Pathogenesis Programme, The Doris Duke Medical Research Institute, University of KwaZulu-Natal, Durban, South Africa.
- Africa Health Research Institute, Durban, 4001, South Africa.
- Ragon Institute of Massachusetts General Hospital, Massachusetts Institute of Technology and Harvard University, Cambridge, MA, USA.
- Max Planck Institute for Infection Biology, Berlin, Germany.
- Division of Infection and Immunity, University College London, London, UK.
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18
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Stansfield SE, Herbeck JT, Gottlieb GS, Abernethy NF, Murphy JT, Mittler JE, Goodreau SM. Test-and-treat coverage and HIV virulence evolution among men who have sex with men. Virus Evol 2021; 7:veab011. [PMID: 33633867 PMCID: PMC7893213 DOI: 10.1093/ve/veab011] [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] [Indexed: 11/13/2022] Open
Abstract
HIV set point viral load (SPVL), the viral load established shortly after initial infection, is a proxy for HIV virulence: higher SPVLs lead to higher risk of transmission and faster disease progression. Three models of test-and-treat scenarios, mainly in heterosexual populations, found that increasing treatment coverage selected for more virulent viruses. We modeled virulence evolution in a population of men who have sex with men (MSM) with increasing test-and-treat coverage. We extended a stochastic, dynamic network model (EvoNetHIV). We varied relationship patterns (MSM vs. heterosexual), HIV transmission models (increasing vs. plateauing probability of transmission at very high viral loads), and treatment roll-out (with explicit testing or fixed intervals between infection and treatment). In scenarios most similar to previous models (longer relational durations and the plateauing transmission function), we replicated trends previously found: increasing treatment coverage led to increased virulence (0.12 log10 increase in mean population SPVL between 20% and 100% treatment coverage). In scenarios reflecting MSM behavioral data using the increasing transmission function, increasing treatment coverage selected for viruses with lower virulence (0.16 log10 decrease in mean population SPVL between 20% and 100% treatment coverage). These findings emphasize the impact of sexual network conditions and transmission function details on predicted epidemiological and evolutionary outcomes. Varying these features creates very different evolutionary environments, which in turn lead to opposite effects in mean population SPVL evolution. Our results suggest that, under some realistic conditions, effective test-and-treat strategies may not face the previously reported tradeoff in which increasing coverage leads to evolution of greater virulence. This suggests instead that a virtuous cycle of increasing treatment coverage and diminishing virulence is possible.
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Affiliation(s)
- Sarah E Stansfield
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
| | - Joshua T Herbeck
- Department of Global Health, University of Washington, Seattle, WA 98195, USA
| | - Geoffrey S Gottlieb
- Departments of Medicine & Global Health, University of Washington, Seattle, WA 98195, USA
| | - Neil F Abernethy
- Department of Biomedical Informatics and Medical Education, University of Washington, Seattle, WA 98195, USA
| | - James T Murphy
- Department of Microbiology, University of Washington, Seattle, WA 98195, USA
| | - John E Mittler
- Department of Microbiology, University of Washington, Seattle, WA 98195, USA
| | - Steven M Goodreau
- Department of Anthropology, University of Washington, Seattle, WA 98195, USA
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Wang C, Zhou L, Chen J, Yang Y, Huang T, Fu M, Li Y, George DM, Chen X. The differences of clinical characteristics and outcomes between imported and local patients of COVID-19 in Hunan: a two-center retrospective study. Respir Res 2020; 21:313. [PMID: 33243215 PMCID: PMC7689384 DOI: 10.1186/s12931-020-01551-5] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2020] [Accepted: 10/19/2020] [Indexed: 01/19/2023] Open
Abstract
BACKGROUND The clinical characteristics and outcomes of the 2019 novel coronavirus (COVID-19) pneumonia are different in Hubei compared to other regions in China. But there are few comparative studies on the differences between imported and local patients which may provide information of the different courses of the virus after transmission. METHODS We investigated 169 cases of COVID-19 pneumonia in two centers in Hunan Province, and divided them into two groups according to epidemiological history, "imported patients" refers to patient with a clear history of travel in Wuhan within 14 days before onset, and " local patients" refers to local resident without a recent history of travel in Wuhan, aiming to analyze the difference in clinical characteristics and outcomes between the two groups. All the epidemiological, clinical, imaging, and laboratory data were analyzed and contrasted. RESULTS The incidence of fever on admission in imported patients was significantly higher than local patients. There was a significantly higher proportion of abnormal pulmonary signs, hypokalemia, hyponatremia, prolonged PT, elevated D-dimer and elevated blood glucose in imported patients. Compared with local patients, the proportion using antibiotics, glucocorticoids and gamma globulin were significantly higher in imported patients. The moderate type was more common in local patients, and the severe type were more frequent in imported patients. In addition, the median duration of viral clearance was longer in imported patients. CONCLUSIONS In summary, we found that imported cases were more likely to develop into severe cases, compared with local patients and required more powerful treatments. Trial registration Registered 21st March 2020, and this study has been approved by the Medical Ethics Committee (Approved Number. 2020017).
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Affiliation(s)
- Chang Wang
- Department of Nephrology, The Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan China
| | - Lizhi Zhou
- Department of Urology, The Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan China
| | - Juan Chen
- Department of Radiology, The Central Hospital of Xiangtan, Xiangtan, 410011 Hunan China
| | - Yong Yang
- Department of Intensive Care Unit, The Central Hospital of Changsha, Nanhua University, Hengyang, 410011 Hunan China
| | - Tianlong Huang
- Department of Orthopaedics, The Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan China
| | - Min Fu
- Department of Neurology, the Fourth Hospital of Changsha, Changsha, 410011 Hunan China
| | - Ya Li
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan China
| | | | - Xiangyu Chen
- Department of Radiology, The Second Xiangya Hospital, Central South University, Changsha, 410011 Hunan China
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Cai Y, Huang T, Liu X, Xu G. The effects of "Fangcang, Huoshenshan, and Leishenshan" hospitals and environmental factors on the mortality of COVID-19. PeerJ 2020; 8:e9578. [PMID: 32742816 PMCID: PMC7380280 DOI: 10.7717/peerj.9578] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 06/30/2020] [Indexed: 12/17/2022] Open
Abstract
Background In December 2019, a novel coronavirus disease (COVID-19) broke out in Wuhan, China; however, the factors affecting the mortality of COVID-19 remain unclear. Methods Thirty-two days of data (the growth rate/mortality of COVID-19 cases) that were shared by Chinese National Health Commission and Chinese Weather Net were collected by two authors independently. Student’s t-test or Mann-Whitney U test was used to test the difference in the mortality of confirmed/severe cases before and after the use of “Fangcang, Huoshenshan, and Leishenshan” makeshift hospitals (MSHs). We also studied whether the above outcomes of COVID-19 cases were related to air temperature (AT), relative humidity (RH), or air quality index (AQI) by performing Pearson’s analysis or Spearman’s analysis. Results Eight days after the use of MSHs, the mortality of confirmed cases was significantly decreased both in Wuhan (t = 4.5, P < 0.001) and Hubei (U = 0, P < 0.001), (t and U are the test statistic used to test the significance of the difference). In contrast, the mortality of confirmed cases remained unchanged in non-Hubei regions (U = 76, P = 0.106). While on day 12 and day 16 after the use of MSHs, the reduce in mortality was still significant both in Wuhan and Hubei; but in non-Hubei regions, the reduce also became significant this time (U = 123, P = 0.036; U = 171, P = 0.015, respectively). Mortality of confirmed cases was found to be negatively correlated with AT both in Wuhan (r = − 0.441, P = 0.012) and Hubei (r = − 0.440, P = 0.012). Also, both the growth rate and the mortality of COVID-19 cases were found to be significantly correlated with AQI in Wuhan and Hubei. However, no significant correlation between RH and the growth rate/mortality of COVID-19 cases was found in our study. Conclusions Our findings indicated that both the use of MSHs, the rise of AT, and the improvement of air quality were beneficial to the survival of COVID-19 patients.
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Affiliation(s)
- Yuwen Cai
- Department of Nephrology, the Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China.,Second Clinical Medical College of Nanchang University, Nanchang, China
| | - Tianlun Huang
- Department of Nephrology, the Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China
| | - Xin Liu
- Department of Nephrology, the Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China
| | - Gaosi Xu
- Department of Nephrology, the Second Affiliated Hospital of Nanchang University, Nanchang University, Nanchang, China
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21
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Capoferri AA, Lamers SL, Grabowski MK, Rose R, Wawer MJ, Serwadda D, Gray RH, Quinn TC, Kigozi G, Kagaayi J, Laeyendecker O, Abeler-Dörner L, Ayles H, Bonsall D, Bowden R, Calvez V, Cohen M, Denis A, Frampton D, de Oliveira T, Essex M, Fidler S, Fraser C, Golubchik T, Hayes R, Herbeck JT, Hoppe A, Kaleebu P, Kellam P, Kityo C, Leigh-Brown A, Lingappa JR, Novitsky V, Paton N, Pillay D, Rambaut A, Ratmann O, Seeley J, Ssemwanga D, Tanser F. Recombination Analysis of Near Full-Length HIV-1 Sequences and the Identification of a Potential New Circulating Recombinant Form from Rakai, Uganda. AIDS Res Hum Retroviruses 2020; 36:467-474. [PMID: 31914792 DOI: 10.1089/aid.2019.0150] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
The Phylogenetics And Networks for Generalized HIV Epidemics in Africa (PANGEA-HIV) consortium has been vital in the generation and examination of near full-length HIV-1 sequences generated from Sub-Saharan Africa. In this study, we examined a subset (n = 275) of sequences from Rakai, Uganda, collected between August 2011 and January 2015. Sequences were initially screened with COMET for subtyping and then evaluated using bootscanning and phylogenetic inference. Among 275 sequences, 38.6% were subtype D, 19.3% were subtype A, 2.9% were subtype C, and 39.3% were recombinant. The recombinants were structurally diverse in the number of breakpoints observed, the location of recombinant segments, and represented subtypes, with AD recombinants accounting for the majority of all recombinants (29.8%). Within the AD subpopulation, we identified a potential new circulating recombinant form in five individuals where the polymerase gene was subtype D and most of env was subtype A (D-A junctures at HXB2 6760 and 8709). While the breakpoints were identical for the viruses from these individuals, the viral fragments did not cluster together. These results suggest selection for a viral strain where properties of the subtype A and subtype D portions of the virus confer a survival advantage. The continued study of recombinants will increase our breadth of knowledge for the genetic diversity and evolution of HIV-1, which can further contribute to our understanding toward a universal HIV-1 vaccine.
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Affiliation(s)
- Adam A. Capoferri
- The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
| | | | - Mary Kate Grabowski
- The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Rakai Health Sciences Program, Entebbe, Uganda
| | | | - Maria J. Wawer
- The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Rakai Health Sciences Program, Entebbe, Uganda
| | - David Serwadda
- Rakai Health Sciences Program, Entebbe, Uganda
- Makerere University School of Public Health, Kampala, Uganda
| | - Ronald H. Gray
- The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Rakai Health Sciences Program, Entebbe, Uganda
| | - Thomas C. Quinn
- The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, USA
| | | | | | - Oliver Laeyendecker
- The Johns Hopkins University School of Medicine, Baltimore, Maryland, USA
- The Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, USA
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22
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Lamers SL, Rose R, Cross S, Rodriguez CW, Redd AD, Quinn TC, Serwadda D, Kagaayi J, Kigozi G, Galiwango R, Gray RH, Grabowski MK, Laeyendecker O. HIV-1 Subtype Distribution and Diversity Over 18 Years in Rakai, Uganda. AIDS Res Hum Retroviruses 2020; 36:522-526. [PMID: 32281387 DOI: 10.1089/aid.2020.0062] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/13/2022] Open
Abstract
The Rakai Community Cohort Study in south central Uganda has surveyed people aged 15-49 since 1994. Antiretroviral therapy (ART) was introduced in 2004. HIV p24 and gp41 subtype distribution and viral diversity were studied from blood samples collected at three surveys in 1994-1995, 2002-2003, and 2008-2009, which were compared with a new survey round from 2011 to 2012. These included 1364 HIV+ individuals. For both p24 and gp41 domains, the genetic diversity within subtypes A and D was significantly increasing in the pre-ART era and decreased between the last two survey rounds in the ART era (p < .01). This study suggests that despite ongoing mixing of viral subtypes, an association with the introduction of ART to a reduction of intra-subtype viral genomic diversity may be occurring, which can be explored in ongoing studies.
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Affiliation(s)
| | | | - Sissy Cross
- BioInfoExperts LLC, Thibodaux, Louisiana, USA
| | | | - Andrew D. Redd
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - Thomas C. Quinn
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
| | - David Serwadda
- Makerere University, School of Medicine, Kampala, Uganda
- Rakai Health Sciences Program, Kalisizo, Uganda
| | | | | | | | - Ronald H. Gray
- Rakai Health Sciences Program, Kalisizo, Uganda
- Department of Epidemiology, JHSPH, Baltimore, Maryland, USA
| | - M. Kate Grabowski
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
- Rakai Health Sciences Program, Kalisizo, Uganda
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore, Maryland, USA
- Department of Medicine, Johns Hopkins University, Baltimore, Maryland, USA
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23
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Clinical and evolutionary consequences of HIV adaptation to HLA: implications for vaccine and cure. Curr Opin HIV AIDS 2020; 14:194-204. [PMID: 30925534 DOI: 10.1097/coh.0000000000000541] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
PURPOSE OF REVIEW The purpose of this review is to summarize recent advances in our understanding of HIV adaptation to human leukocyte antigen (HLA)-associated immune pressures and its relevance to HIV prevention and cure research. RECENT FINDINGS Recent research has confirmed that HLA is a major driver of individual and population-level HIV evolution, that HIV strains are adapting to the immunogenetic profiles of the different human ethnic groups in which they circulate, and that HIV adaptation has substantial clinical and immunologic consequences. As such, adaptation represents a major challenge to HIV prevention and cure. At the same time, there are opportunities: Studies of HIV adaptation are revealing why certain HLA alleles are protective in some populations and not others; they are identifying immunogenic viral epitopes that harbor high mutational barriers to escape, and they may help illuminate novel, vaccine-relevant HIV epitopes in regions where circulating adaptation is extensive. Elucidation of HLA-driven adapted and nonadapted viral forms in different human populations and HIV subtypes also renders 'personalized' immunogen selection, as a component of HIV cure strategies, conceptually feasible. SUMMARY Though adaptation represents a major challenge to HIV prevention and cure, achieving an in-depth understanding of this phenomenon can help move the design of such strategies forward.
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24
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Abstract
Recent discoveries of contemporary genotypes of hepatitis B virus and parvovirus B19 in ancient human remains demonstrate that little genetic change has occurred in these viruses over 4,500-6,000 years. Endogenous viral elements in host genomes provide separate evidence that viruses similar to many major contemporary groups circulated 100 million years ago or earlier. In this Opinion article, we argue that the extraordinary conservation of virus genome sequences is best explained by a niche-filling model in which fitness optimization is rapidly achieved in their specific hosts. Whereas short-term substitution rates reflect the accumulation of tolerated sequence changes within adapted genomes, longer-term rates increasingly resemble those of their hosts as the evolving niche moulds and effectively imprisons the virus in co-adapted virus-host relationships. Contrastingly, viruses that jump hosts undergo strong and stringent adaptive selection as they maximize their fit to their new niche. This adaptive capability may paradoxically create evolutionary stasis in long-term host relationships. While viruses can evolve and adapt rapidly, their hosts may ultimately shape their longer-term evolution.
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25
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Greischar MA, Beck-Johnson LM, Mideo N. Partitioning the influence of ecology across scales on parasite evolution. Evolution 2019; 73:2175-2188. [PMID: 31495911 DOI: 10.1111/evo.13840] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2019] [Accepted: 08/31/2019] [Indexed: 11/30/2022]
Abstract
Vector-borne parasites must succeed at three scales to persist: they must proliferate within a host, establish in vectors, and transmit back to hosts. Ecology outside the host undergoes dramatic seasonal and human-induced changes, but predicting parasite evolutionary responses requires integrating their success across scales. We develop a novel, data-driven model to titrate the evolutionary impact of ecology at multiple scales on human malaria parasites. We investigate how parasites invest in transmission versus proliferation, a life-history trait that influences disease severity and spread. We find that transmission investment controls the pattern of host infectiousness over the course of infection: a trade-off emerges between early and late infectiousness, and the optimal resolution of that trade-off depends on ecology outside the host. An expanding epidemic favors rapid proliferation, and can overwhelm the evolutionary influence of host recovery rates and mosquito population dynamics. If transmission investment and recovery rate are positively correlated, then ecology outside the host imposes potent selection for aggressive parasite proliferation at the expense of transmission. Any association between transmission investment and recovery represents a key unknown, one that is likely to influence whether the evolutionary consequences of interventions are beneficial or costly for human health.
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Affiliation(s)
- Megan A Greischar
- Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, Ontario, M5S 3B2, Canada
| | | | - Nicole Mideo
- Department of Ecology & Evolutionary Biology, University of Toronto, Toronto, Ontario, M5S 3B2, Canada
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26
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Ogden NH, Wilson JRU, Richardson DM, Hui C, Davies SJ, Kumschick S, Le Roux JJ, Measey J, Saul WC, Pulliam JRC. Emerging infectious diseases and biological invasions: a call for a One Health collaboration in science and management. ROYAL SOCIETY OPEN SCIENCE 2019; 6:181577. [PMID: 31032015 PMCID: PMC6458372 DOI: 10.1098/rsos.181577] [Citation(s) in RCA: 39] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/18/2018] [Accepted: 02/18/2019] [Indexed: 05/11/2023]
Abstract
The study and management of emerging infectious diseases (EIDs) and of biological invasions both address the ecology of human-associated biological phenomena in a rapidly changing world. However, the two fields work mostly in parallel rather than in concert. This review explores how the general phenomenon of an organism rapidly increasing in range or abundance is caused, highlights the similarities and differences between research on EIDs and invasions, and discusses shared management insights and approaches. EIDs can arise by: (i) crossing geographical barriers due to human-mediated dispersal, (ii) crossing compatibility barriers due to evolution, and (iii) lifting of environmental barriers due to environmental change. All these processes can be implicated in biological invasions, but only the first defines them. Research on EIDs is embedded within the One Health concept-the notion that human, animal and ecosystem health are interrelated and that holistic approaches encompassing all three components are needed to respond to threats to human well-being. We argue that for sustainable development, biological invasions should be explicitly considered within One Health. Management goals for the fields are the same, and direct collaborations between invasion scientists, disease ecologists and epidemiologists on modelling, risk assessment, monitoring and management would be mutually beneficial.
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Affiliation(s)
- Nick H. Ogden
- National Microbiology Laboratory, Public Health Agency of Canada, Canada
- South African DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, South Africa
| | - John R. U. Wilson
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
- South African National Biodiversity Institute, Kirstenbosch Research Centre, Claremont, Cape Town, South Africa
| | - David M. Richardson
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
| | - Cang Hui
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland 7602, South Africa
- Mathematical and Physical Biosciences, African Institute for Mathematical Sciences (AIMS), Muizenberg 7945, South Africa
| | - Sarah J. Davies
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
| | - Sabrina Kumschick
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
- South African National Biodiversity Institute, Kirstenbosch Research Centre, Claremont, Cape Town, South Africa
| | - Johannes J. Le Roux
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
- Department of Biological Sciences, Macquarie University, Sydney 2109, Australia
| | - John Measey
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
| | - Wolf-Christian Saul
- Centre for Invasion Biology, Department of Botany and Zoology, Stellenbosch University, South Africa
- Centre for Invasion Biology, Department of Mathematical Sciences, Stellenbosch University, Matieland 7602, South Africa
| | - Juliet R. C. Pulliam
- South African DST-NRF Centre of Excellence in Epidemiological Modelling and Analysis (SACEMA), Stellenbosch University, South Africa
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27
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Yang CC, Chien WC, Chung CH, Liu YP, Yeh CB, Chen KH, Yang SN, Chang HA, Kao YC, Lu WC, Tzeng NS. No Association Between Human Immunodeficiency Virus Infections And Dementia: A Nationwide Cohort Study In Taiwan. Neuropsychiatr Dis Treat 2019; 15:3155-3166. [PMID: 31814723 PMCID: PMC6863184 DOI: 10.2147/ndt.s225584] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Accepted: 09/27/2019] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND The associations between the human immunodeficiency virus (HIV) and dementias are as yet to be studied in Taiwan. The aim of this study is to clarify as to whether HIV infections are associated with the risk of dementia. METHODS A total of 1,261 HIV-infected patients and 3,783 controls (1:3) matched for age and sex were selected between January 1 and December 31, 2000 from Taiwan's National Health Insurance Research Database (NHIRD). Fine and Gray's survival analysis (competing with mortality) analyzed the risk of dementias during the 15-year follow up. The association between the highly active antiretroviral therapy (HAART) and dementia was analyzed by stratifying the HAART status among the HIV subjects. RESULTS During the follow-up period, 25 in the HIV group (N= 1,261) and 227 in the control group (N= 3,783) developed dementia (656.25 vs 913.15 per 100,000 person-years). Fine and Gray's survival analysis revealed that the HIV patients were not associated with an increased risk of dementia, with the adjusted hazard ratio (HR) as 0.852 (95% confidence interval [CI]: 0.189-2.886, p=0.415) after adjusting for sex, age, comorbidities, geographical region, and the urbanization level of residence. There was no significant difference between the two groups of HIV-infected patients with or without HAART in the risk of dementia. CONCLUSION This study found that HIV infections, either with or without HAART, were not associated with increased diagnoses of neurodegenerative dementias in patients older than 50 in Taiwan.
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Affiliation(s)
- Chuan-Chi Yang
- Department of Psychiatry, Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan, ROC.,Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Wu-Chien Chien
- Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.,School of Public Health, National Defense Medical Center, Taipei, Taiwan, ROC.,Graduate Institute of Life Sciences, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Chi-Hsiang Chung
- Department of Medical Research, Tri-Service General Hospital, National Defense Medical Center, Taipei, Taiwan, ROC.,School of Public Health, National Defense Medical Center, Taipei, Taiwan, ROC.,Taiwanese Injury Prevention and Safety Promotion Association, Taipei, Taiwan, ROC
| | - Yia-Ping Liu
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.,Department of Psychiatry, Chen-Hsin General Hospital, Taipei, Taiwan, ROC.,Institute of Physiology and Biophysics, National Defense Medical Center, Taipei, Taiwan, ROC.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Chin-Bin Yeh
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Kuang-Huei Chen
- Department of Psychiatry, Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan, ROC
| | - Szu-Nian Yang
- Department of Psychiatry, Taoyuan Armed Forces General Hospital, Taoyuan, Taiwan, ROC.,Graduate Institute of Medical Sciences, National Defense Medical Center, Taipei, Taiwan, ROC.,Headquarters, Tri-Service General Hospital, Beitou Branch, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Hsin-An Chang
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.,Student Counseling Center, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Yu-Chen Kao
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.,Department of Psychiatry, Tri-Service General Hospital, Song-Shan Branch, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Wan-Chun Lu
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC
| | - Nian-Sheng Tzeng
- Department of Psychiatry, Tri-Service General Hospital, School of Medicine, National Defense Medical Center, Taipei, Taiwan, ROC.,Student Counseling Center, National Defense Medical Center, Taipei, Taiwan, ROC
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28
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Abstract
How virulence evolves after a virus jumps to a new host species is central to disease emergence. Our current understanding of virulence evolution is based on insights drawn from two perspectives that have developed largely independently: long-standing evolutionary theory based on limited real data examples that often lack a genomic basis, and experimental studies of virulence-determining mutations using cell culture or animal models. A more comprehensive understanding of virulence mutations and their evolution can be achieved by bridging the gap between these two research pathways through the phylogenomic analysis of virus genome sequence data as a guide to experimental study.
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Affiliation(s)
- Jemma L Geoghegan
- Department of Biological Sciences, Macquarie University, Sydney, New South Wales, Australia
| | - Edward C Holmes
- Marie Bashir Institute for Infectious Diseases and Biosecurity, Charles Perkins Centre, School of Life and Environmental Sciences and Sydney Medical School, The University of Sydney, Sydney, New South Wales, Australia.
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29
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Lumby CK, Nene NR, Illingworth CJR. A novel framework for inferring parameters of transmission from viral sequence data. PLoS Genet 2018; 14:e1007718. [PMID: 30325921 PMCID: PMC6203404 DOI: 10.1371/journal.pgen.1007718] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2018] [Revised: 10/26/2018] [Accepted: 09/26/2018] [Indexed: 11/18/2022] Open
Abstract
Transmission between hosts is a critical part of the viral lifecycle. Recent studies of viral transmission have used genome sequence data to evaluate the number of particles transmitted between hosts, and the role of selection as it operates during the transmission process. However, the interpretation of sequence data describing transmission events is a challenging task. We here present a novel and comprehensive framework for using short-read sequence data to understand viral transmission events, designed for influenza virus, but adaptable to other viral species. Our approach solves multiple shortcomings of previous methods for this purpose; for example, we consider transmission as an event involving whole viruses, rather than sets of independent alleles. We demonstrate how selection during transmission and noisy sequence data may each affect naive inferences of the population bottleneck, accounting for these in our framework so as to achieve a correct inference. We identify circumstances in which selection for increased viral transmission may or may not be identified from data. Applying our method to experimental data in which transmission occurs in the presence of strong selection, we show that our framework grants a more quantitative insight into transmission events than previous approaches, inferring the bottleneck in a manner that accounts for selection, both for within-host virulence, and for inherent viral transmissibility. Our work provides new opportunities for studying transmission processes in influenza, and by extension, in other infectious diseases.
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Affiliation(s)
- Casper K. Lumby
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Nuno R. Nene
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
| | - Christopher J. R. Illingworth
- Department of Genetics, University of Cambridge, Cambridge, United Kingdom
- Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge, United Kingdom
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30
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Goodreau SM, Stansfield SE, Murphy JT, Peebles KC, Gottlieb GS, Abernethy NF, Herbeck JT, Mittler JE. Relational concurrency, stages of infection, and the evolution of HIV set point viral load. Virus Evol 2018; 4:vey032. [PMID: 30483403 PMCID: PMC6249390 DOI: 10.1093/ve/vey032] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
HIV viral load (VL) predicts both transmission potential and rate of disease progression. For reasons that are still not fully understood, the set point viral load (SPVL) established after acute infection varies across individuals and populations. Previous studies have suggested that population mean SPVL (MSPVL) has evolved near an optimum that reflects a trade-off between transmissibility and host survival. Sexual network structures affect rates of potential exposure during different within-host phases of infection marked by different transmission probabilities, and thus affect the number and timing of transmission events. These structures include relational concurrency, which has been argued to explain key differences in HIV burden across populations. We hypothesize that concurrency will alter the fitness landscape for SPVL in ways that differ from other network features whose impacts accrue at other times during infection. To quantitatively test this hypothesis, we developed a dynamic, stochastic, data-driven network model of HIV transmission, and evolution to assess the impact of key sexual network phenomena on MSPVL evolution. Experiments were repeated in sensitivity runs that made different assumptions about transmissibility during acute infection, SPVL heritability, and the functional form of the relationship between VL and transmissibility. For our main transmission model, scenarios yielded MSPVLs ranging from 4.4 to 4.75 log10 copies/ml, covering much of the observed empirical range. MSPVL evolved to be higher in populations with high concurrency and shorter relational durations, with values varying over a clinically significant range. In linear regression analyses on these and other predictors, main effects were significant (P < 0.05), as were interaction terms, indicating that effects are interdependent. We also noted a strong correlation between two key emergent properties measured at the end of the simulations-MSPVL and HIV prevalence-most clearly for phenomena that affect transmission networks early in infection. Controlling for prevalence, high concurrency yielded higher MSPVL than other network phenomena. Interestingly, we observed lower prevalence in runs in which SPVL heritability was zero, indicating the potential for viral evolution to exacerbate disease burden over time. Future efforts to understand empirical variation in MSPVL should consider local HIV burden and basic sexual behavioral and network structure.
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Affiliation(s)
- Steven M Goodreau
- Department of Anthropology, Campus Box 353100, Seattle, WA 98195, USA
| | | | - James T Murphy
- Department of Microbiology, Campus Box 357735, Seattle, WA 98195, USA
| | - Kathryn C Peebles
- Department of Epidemiology, Campus Box 357236, Seattle, WA 98195, USA
| | - Geoffrey S Gottlieb
- Departments of Medicine and Global Health, Campus Box 356420, Seattle, WA 98195, USA
| | - Neil F Abernethy
- Department of Biomedical Informatics and Medical Education, Campus Box 358047, Seattle, WA 98195, USA
| | - Joshua T Herbeck
- Department of Global Health, University of Washington, Campus Box 353100, Seattle, WA 98195, USA
| | - John E Mittler
- Department of Microbiology, Campus Box 357735, Seattle, WA 98195, USA
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31
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Raghwani J, Redd AD, Longosz AF, Wu CH, Serwadda D, Martens C, Kagaayi J, Sewankambo N, Porcella SF, Grabowski MK, Quinn TC, Eller MA, Eller LA, Wabwire-Mangen F, Robb ML, Fraser C, Lythgoe KA. Evolution of HIV-1 within untreated individuals and at the population scale in Uganda. PLoS Pathog 2018; 14:e1007167. [PMID: 30052678 PMCID: PMC6082572 DOI: 10.1371/journal.ppat.1007167] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2017] [Revised: 08/08/2018] [Accepted: 06/20/2018] [Indexed: 12/15/2022] Open
Abstract
HIV-1 undergoes multiple rounds of error-prone replication between transmission events, resulting in diverse viral populations within and among individuals. In addition, the virus experiences different selective pressures at multiple levels: during the course of infection, at transmission, and among individuals. Disentangling how these evolutionary forces shape the evolution of the virus at the population scale is important for understanding pathogenesis, how drug- and immune-escape variants are likely to spread in populations, and the development of preventive vaccines. To address this, we deep-sequenced two regions of the HIV-1 genome (p24 and gp41) from 34 longitudinally-sampled untreated individuals from Rakai District in Uganda, infected with subtypes A, D, and inter-subtype recombinants. This dataset substantially increases the availability of HIV-1 sequence data that spans multiple years of untreated infection, in particular for different geographical regions and viral subtypes. In line with previous studies, we estimated an approximately five-fold faster rate of evolution at the within-host compared to the population scale for both synonymous and nonsynonymous substitutions, and for all subtypes. We determined the extent to which this mismatch in evolutionary rates can be explained by the evolution of the virus towards population-level consensus, or the transmission of viruses similar to those that establish infection within individuals. Our findings indicate that both processes are likely to be important.
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Affiliation(s)
- Jayna Raghwani
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Department of Zoology, Peter Medawar Building, University of Oxford, Oxford, United Kingdom
| | - Andrew D. Redd
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore MD, United States of America
- Department of Medicine, Johns Hopkins Medical Institute, Johns Hopkins University, Baltimore MD, United States of America
| | - Andrew F. Longosz
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore MD, United States of America
| | - Chieh-Hsi Wu
- Department of Statistics, University of Oxford, Oxford, United Kingdom
| | - David Serwadda
- Rakai Health Sciences Program, Kalisizo, Uganda
- School of Public Health, Makerere University, Kampala, Uganda
| | - Craig Martens
- Genomics Unit, RTS, RTB, Rocky Mountain Laboratories, Division of Intramural Research, NIAID, NIH, Hamilton MT, United States of America
| | | | - Nelson Sewankambo
- Rakai Health Sciences Program, Kalisizo, Uganda
- School of Medicine, Makerere University, Kampala, Uganda
| | - Stephen F. Porcella
- Genomics Unit, RTS, RTB, Rocky Mountain Laboratories, Division of Intramural Research, NIAID, NIH, Hamilton MT, United States of America
| | - Mary K. Grabowski
- Department of Pathology, Johns Hopkins Medical Institute, Johns Hopkins University, Baltimore, MD, United States of America
| | - Thomas C. Quinn
- Laboratory of Immunoregulation, Division of Intramural Research, NIAID, NIH, Baltimore MD, United States of America
- Department of Medicine, Johns Hopkins Medical Institute, Johns Hopkins University, Baltimore MD, United States of America
| | - Michael A. Eller
- U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, United States of America
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States of America
| | - Leigh Anne Eller
- U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, United States of America
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States of America
| | - Fred Wabwire-Mangen
- U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, United States of America
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States of America
| | - Merlin L. Robb
- U.S. Military HIV Research Program, Walter Reed Army Institute of Research, Silver Spring, MD, United States of America
- Henry M. Jackson Foundation for the Advancement of Military Medicine, Bethesda, MD, United States of America
| | - Christophe Fraser
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Katrina A. Lythgoe
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
- Department of Zoology, Peter Medawar Building, University of Oxford, Oxford, United Kingdom
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Transmission-clearance trade-offs indicate that dengue virulence evolution depends on epidemiological context. Nat Commun 2018; 9:2355. [PMID: 29907741 PMCID: PMC6003961 DOI: 10.1038/s41467-018-04595-w] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2017] [Accepted: 05/09/2018] [Indexed: 12/20/2022] Open
Abstract
An extensive body of theory addresses the topic of pathogen virulence evolution, yet few studies have empirically demonstrated the presence of fitness trade-offs that would select for intermediate virulence. Here we show the presence of transmission-clearance trade-offs in dengue virus using viremia measurements. By fitting a within-host model to these data, we further find that the interaction between dengue and the host immune response can account for the observed trade-offs. Finally, we consider dengue virulence evolution when selection acts on the virus’s production rate. By combining within-host model simulations with empirical findings on how host viral load affects human-to-mosquito transmission success, we show that the virus’s transmission potential is maximized at production rates associated with intermediate virulence and that the optimal production rate critically depends on dengue’s epidemiological context. These results indicate that long-term changes in dengue’s global distribution impact the invasion and spread of virulent dengue virus genotypes. Theory predicts that pathogens will evolve towards intermediate virulence, yet the necessary trade-offs invoked by this theory have rarely been demonstrated empirically. Here, the authors show that dengue virus dynamics exhibit a trade-off between transmission and clearance rates.
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Tongo M, de Oliveira T, Martin DP. Patterns of genomic site inheritance in HIV-1M inter-subtype recombinants delineate the most likely genomic sites of subtype-specific adaptation. Virus Evol 2018; 4:vey015. [PMID: 29942655 PMCID: PMC6007327 DOI: 10.1093/ve/vey015] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022] Open
Abstract
Recombination between different HIV-1 group M (HIV-1M) subtypes is a major contributor to the ongoing genetic diversification of HIV-1M. However, it remains unclear whether the different genome regions of recombinants are randomly inherited from the different subtypes. To elucidate this, we analysed the distribution within 82 circulating and 201 unique recombinant forms (CRFs/URFs), of genome fragments derived from HIV-1M Subtypes A, B, C, D, F, and G and CRF01_AE. We found that viruses belonging to the analysed HIV-1M subtypes and CRF01_AE contributed certain genome fragments more frequently during recombination than other fragments. Furthermore, we identified statistically significant hot-spots of Subtype A sequence inheritance in genomic regions encoding portions of Gag and Nef, Subtype B in Pol, Tat and Env, Subtype C in Vif, Subtype D in Pol and Env, Subtype F in Gag, Subtype G in Vpu-Env and Nef, and CRF01_AE inheritance in Vpu and Env. The apparent non-randomness in the frequencies with which different subtypes have contributed specific genome regions to known HIV-1M recombinants is consistent with selection strongly impacting the survival of inter-subtype recombinants. We propose that hotspots of genomic region inheritance are likely to demarcate the locations of subtype-specific adaptive genetic variations.
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Affiliation(s)
- Marcel Tongo
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, Nelson R Mandela School of Medicine, University of KwaZulu-Natal (UKZN), 719 Umbilo Road, Durban 4001, South Africa
- Center of Research for Emerging and Re-Emerging Diseases (CREMER), Institute of Medical Research and Study of Medicinal Plants (IMPM), Yaoundé, Cameroon
| | - Tulio de Oliveira
- KwaZulu-Natal Research Innovation and Sequencing Platform (KRISP), School of Laboratory Medicine and Medical Sciences, College of Health Sciences, Nelson R Mandela School of Medicine, University of KwaZulu-Natal (UKZN), 719 Umbilo Road, Durban 4001, South Africa
| | - Darren P Martin
- Division of Computational Biology, Department of Integrative Biomedical Sciences and Institute of Infectious Disease and Molecular Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town 7925, South Africa
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Johnson LF, May MT, Dorrington RE, Cornell M, Boulle A, Egger M, Davies MA. Estimating the impact of antiretroviral treatment on adult mortality trends in South Africa: A mathematical modelling study. PLoS Med 2017; 14:e1002468. [PMID: 29232366 PMCID: PMC5726614 DOI: 10.1371/journal.pmed.1002468] [Citation(s) in RCA: 89] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/13/2017] [Accepted: 11/07/2017] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Substantial reductions in adult mortality have been observed in South Africa since the mid-2000s, but there has been no formal evaluation of how much of this decline is attributable to the scale-up of antiretroviral treatment (ART), as previous models have not been calibrated to vital registration data. We developed a deterministic mathematical model to simulate the mortality trends that would have been expected in the absence of ART, and with earlier introduction of ART. METHODS AND FINDINGS Model estimates of mortality rates in ART patients were obtained from the International Epidemiology Databases to Evaluate AIDS-Southern Africa (IeDEA-SA) collaboration. The model was calibrated to HIV prevalence data (1997-2013) and mortality data from the South African vital registration system (1997-2014), using a Bayesian approach. In the 1985-2014 period, 2.70 million adult HIV-related deaths occurred in South Africa. Adult HIV deaths peaked at 231,000 per annum in 2006 and declined to 95,000 in 2014, a reduction of 74.7% (95% CI: 73.3%-76.1%) compared to the scenario without ART. However, HIV mortality in 2014 was estimated to be 69% (95% CI: 46%-97%) higher in 2014 (161,000) if the model was calibrated only to HIV prevalence data. In the 2000-2014 period, the South African ART programme is estimated to have reduced the cumulative number of HIV deaths in adults by 1.72 million (95% CI: 1.58 million-1.84 million) and to have saved 6.15 million life years in adults (95% CI: 5.52 million-6.69 million). This compares with a potential saving of 8.80 million (95% CI: 7.90 million-9.59 million) life years that might have been achieved if South Africa had moved swiftly to implement WHO guidelines (2004-2013) and had achieved high levels of ART uptake in HIV-diagnosed individuals from 2004 onwards. The model is limited by its reliance on all-cause mortality data, given the lack of reliable cause-of-death reporting, and also does not allow for changes over time in tuberculosis control programmes and ART effectiveness. CONCLUSIONS ART has had a dramatic impact on adult mortality in South Africa, but delays in the rollout of ART, especially in the early stages of the ART programme, have contributed to substantial loss of life. This is the first study to our knowledge to calibrate a model of ART impact to population-level recorded death data in Africa; models that are not calibrated to population-level death data may overestimate HIV-related mortality.
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Affiliation(s)
- Leigh F. Johnson
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
- * E-mail:
| | - Margaret T. May
- School of Social and Community Medicine, University of Bristol, Bristol, United Kingdom
| | - Rob E. Dorrington
- Centre for Actuarial Research, University of Cape Town, Cape Town, South Africa
| | - Morna Cornell
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - Andrew Boulle
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
| | - Matthias Egger
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
- Institute of Social and Preventive Medicine, University of Bern, Bern, Switzerland
| | - Mary-Ann Davies
- Centre for Infectious Disease Epidemiology and Research, University of Cape Town, Cape Town, South Africa
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Blanquart F, Wymant C, Cornelissen M, Gall A, Bakker M, Bezemer D, Hall M, Hillebregt M, Ong SH, Albert J, Bannert N, Fellay J, Fransen K, Gourlay AJ, Grabowski MK, Gunsenheimer-Bartmeyer B, Günthard HF, Kivelä P, Kouyos R, Laeyendecker O, Liitsola K, Meyer L, Porter K, Ristola M, van Sighem A, Vanham G, Berkhout B, Kellam P, Reiss P, Fraser C. Viral genetic variation accounts for a third of variability in HIV-1 set-point viral load in Europe. PLoS Biol 2017; 15:e2001855. [PMID: 28604782 PMCID: PMC5467800 DOI: 10.1371/journal.pbio.2001855] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2016] [Accepted: 05/09/2017] [Indexed: 12/20/2022] Open
Abstract
HIV-1 set-point viral load-the approximately stable value of viraemia in the first years of chronic infection-is a strong predictor of clinical outcome and is highly variable across infected individuals. To better understand HIV-1 pathogenesis and the evolution of the viral population, we must quantify the heritability of set-point viral load, which is the fraction of variation in this phenotype attributable to viral genetic variation. However, current estimates of heritability vary widely, from 6% to 59%. Here we used a dataset of 2,028 seroconverters infected between 1985 and 2013 from 5 European countries (Belgium, Switzerland, France, the Netherlands and the United Kingdom) and estimated the heritability of set-point viral load at 31% (CI 15%-43%). Specifically, heritability was measured using models of character evolution describing how viral load evolves on the phylogeny of whole-genome viral sequences. In contrast to previous studies, (i) we measured viral loads using standardized assays on a sample collected in a strict time window of 6 to 24 months after infection, from which the viral genome was also sequenced; (ii) we compared 2 models of character evolution, the classical "Brownian motion" model and another model ("Ornstein-Uhlenbeck") that includes stabilising selection on viral load; (iii) we controlled for covariates, including age and sex, which may inflate estimates of heritability; and (iv) we developed a goodness of fit test based on the correlation of viral loads in cherries of the phylogenetic tree, showing that both models of character evolution fit the data well. An overall heritability of 31% (CI 15%-43%) is consistent with other studies based on regression of viral load in donor-recipient pairs. Thus, about a third of variation in HIV-1 virulence is attributable to viral genetic variation.
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Affiliation(s)
- François Blanquart
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
| | - Chris Wymant
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Marion Cornelissen
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, the Netherlands
| | - Astrid Gall
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Margreet Bakker
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, the Netherlands
| | | | - Matthew Hall
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | | | - Swee Hoe Ong
- Wellcome Trust Sanger Institute, Wellcome Genome Campus, Hinxton, Cambridge, United Kingdom
| | - Jan Albert
- Department of Microbiology, Tumor and Cell Biology, Karolinska Institutet, Stockholm, Sweden
- Department of Clinical Microbiology, Karolinska University Hospital, Stockholm, Sweden
| | - Norbert Bannert
- Division for HIV and other Retroviruses, Robert Koch Institute, Berlin, Germany
| | - Jacques Fellay
- School of Life Sciences, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Katrien Fransen
- HIV/STI reference laboratory, WHO collaborating centre, Institute of Tropical Medicine, Department of Clinical Science, Antwerpen, Belgium
| | - Annabelle J. Gourlay
- Department of Infection and Population Health, University College London, London, United Kingdom
| | - M. Kate Grabowski
- Department of Epidemiology, John Hopkins University, Baltimore, Maryland, United States of America
| | | | - Huldrych F. Günthard
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Pia Kivelä
- Department of Infectious Diseases, Helsinki University Hospital, Helsinki, Finland
| | - Roger Kouyos
- Division of Infectious Diseases and Hospital Epidemiology, University Hospital Zurich, Zurich, Switzerland
- Institute of Medical Virology, University of Zurich, Zurich, Switzerland
| | - Oliver Laeyendecker
- Laboratory of Immunoregulation, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Baltimore, Maryland, United States of America
| | - Kirsi Liitsola
- Department of Health Security, National Institute for Health and Welfare, Helsinki, Finland
| | - Laurence Meyer
- INSERM CESP U1018, Université Paris Sud, Université Paris Saclay, APHP, Service de Santé Publique, Hôpital de Bicêtre, Le Kremlin-Bicêtre, France
| | - Kholoud Porter
- Department of Infection and Population Health, University College London, London, United Kingdom
| | - Matti Ristola
- Department of Health Security, National Institute for Health and Welfare, Helsinki, Finland
| | | | - Guido Vanham
- Virology Unit, Immunovirology Research Pole, Biomedical Sciences Department, Institute of Tropical Medicine, Antwerpen, Belgium
| | - Ben Berkhout
- Laboratory of Experimental Virology, Department of Medical Microbiology, Center for Infection and Immunity Amsterdam (CINIMA), Academic Medical Center of the University of Amsterdam, Amsterdam, the Netherlands
| | - Paul Kellam
- Kymab Ltd, Cambridge, United Kingdom
- Division of Infectious Diseases, Department of Medicine, Imperial College London, London, United Kingdom
| | - Peter Reiss
- Stichting HIV Monitoring, Amsterdam, the Netherlands
- Department of Global Health, Academic Medical Center, Amsterdam, the Netherlands
| | - Christophe Fraser
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
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Park SW, Bolker BM. Effects of contact structure on the transient evolution of HIV virulence. PLoS Comput Biol 2017; 13:e1005453. [PMID: 28362805 PMCID: PMC5391972 DOI: 10.1371/journal.pcbi.1005453] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2016] [Revised: 04/14/2017] [Accepted: 03/10/2017] [Indexed: 02/07/2023] Open
Abstract
Early in an epidemic, high densities of susceptible hosts select for relatively high parasite virulence; later in the epidemic, lower susceptible densities select for lower virulence. Thus over the course of a typical epidemic the average virulence of parasite strains increases initially, peaks partway through the epidemic, then declines again. However, precise quantitative outcomes, such as the peak virulence reached and its timing, may depend sensitively on epidemiological details. Fraser et al. proposed a model for the eco-evolutionary dynamics of HIV that incorporates the tradeoffs between transmission and virulence (mediated by set-point viral load, SPVL) and their heritability between hosts. Their model used implicit equations to capture the effects of partnership dynamics that are at the core of epidemics of sexually transmitted diseases. Our models combine HIV virulence tradeoffs with a range of contact models, explicitly modeling partnership formation and dissolution and allowing for individuals to transmit disease outside of partnerships. We assess summary statistics such as the peak virulence (corresponding to the maximum value of population mean log10 SPVL achieved throughout the epidemic) across models for a range of parameters applicable to the HIV epidemic in sub-Saharan Africa. Although virulence trajectories are broadly similar across models, the timing and magnitude of the virulence peak vary considerably. Previously developed implicit models predicted lower virulence and slower progression at the peak (a maximum of 3.5 log10 SPVL) compared both to more realistic models and to simple random-mixing models with no partnership structure at all (both with a maximum of ≈ 4.7 log10 SPVL). In this range of models, the simplest random-mixing structure best approximates the most realistic model; this surprising outcome occurs because the dominance of extra-pair contact in the realistic model swamps the effects of partnership structure. Pathogens such as HIV can evolve rapidly when the environment changes. One important aspect of a pathogen’s environment is the probability that an infectious contact (a sneeze for a respiratory disease, or an unprotected sex act for a sexually transmitted disease) encounters an uninfected person and thus has a chance to transmit the pathogen. As an epidemic grows the number of uninfected people shrinks, changing evolutionary pressures on the pathogen. While researchers have used models to explore pathogen evolution during epidemics, their models usually neglect important processes such as people entering and leaving sexual partnerships. We compared several evolutionary models for HIV that include partnership dynamics as well as sexual contact outside of stable partnerships. Models of intermediate complexity predicted lower virulence midway through the epidemic (a minimum of 15 years to progress to AIDS) than either more realistic models or simple models with no partnership structure (both with a minimum of 7.25 years to progress to AIDS), because random sexual contacts tended to wash out the effects of stable partnerships. Researchers trying to predict the evolution of pathogens must try to understand the implications of their modeling choices; models of intermediate complexity may not produce intermediate conclusions.
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Affiliation(s)
- Sang Woo Park
- Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada
| | - Benjamin M. Bolker
- Department of Mathematics & Statistics, McMaster University, Hamilton, Ontario, Canada
- Department of Biology, McMaster University, Hamilton, Ontario, Canada
- Institute for Infectious Disease Research, McMaster University, Hamilton, Ontario, Canada
- * E-mail:
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Smith DRM, Mideo N. Modelling the evolution of HIV-1 virulence in response to imperfect therapy and prophylaxis. Evol Appl 2017; 10:297-309. [PMID: 28250813 PMCID: PMC5322411 DOI: 10.1111/eva.12458] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2016] [Accepted: 12/15/2016] [Indexed: 12/11/2022] Open
Abstract
Average HIV-1 virulence appears to have evolved in different directions in different host populations since antiretroviral therapy first became available, and models predict that HIV drugs can select for either higher or lower virulence, depending on how treatment is administered. However, HIV virulence evolution in response to "leaky" therapy (treatment that imperfectly suppresses viral replication) and the use of preventive drugs (pre-exposure prophylaxis) has not been explored. Using adaptive dynamics, we show that higher virulence can evolve when antiretroviral therapy is imperfectly effective and that this evolution erodes some of the long-term clinical and epidemiological benefits of HIV treatment. The introduction of pre-exposure prophylaxis greatly reduces infection prevalence, but can further amplify virulence evolution when it, too, is leaky. Increasing the uptake rate of these imperfect interventions increases selection for higher virulence and can lead to counterintuitive increases in infection prevalence in some scenarios. Although populations almost always fare better with access to interventions than without, untreated individuals could experience particularly poor clinical outcomes when virulence evolves. These findings predict that antiretroviral drugs may have underappreciated evolutionary consequences, but that maximizing drug efficacy can prevent this evolutionary response. We suggest that HIV virulence evolution should be closely monitored as access to interventions continues to improve.
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Affiliation(s)
- David R. M. Smith
- Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoONCanada
| | - Nicole Mideo
- Department of Ecology and Evolutionary BiologyUniversity of TorontoTorontoONCanada
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Doekes HM, Fraser C, Lythgoe KA. Effect of the Latent Reservoir on the Evolution of HIV at the Within- and Between-Host Levels. PLoS Comput Biol 2017; 13:e1005228. [PMID: 28103248 PMCID: PMC5245781 DOI: 10.1371/journal.pcbi.1005228] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2016] [Accepted: 10/31/2016] [Indexed: 02/06/2023] Open
Abstract
The existence of long-lived reservoirs of latently infected CD4+ T cells is the major barrier to curing HIV, and has been extensively studied in this light. However, the effect of these reservoirs on the evolutionary dynamics of the virus has received little attention. Here, we present a within-host quasispecies model that incorporates a long-lived reservoir, which we then nest into an epidemiological model of HIV dynamics. For biologically plausible parameter values, we find that the presence of a latent reservoir can severely delay evolutionary dynamics within a single host, with longer delays associated with larger relative reservoir sizes and/or homeostatic proliferation of cells within the reservoir. These delays can fundamentally change the dynamics of the virus at the epidemiological scale. In particular, the delay in within-host evolutionary dynamics can be sufficient for the virus to evolve intermediate viral loads consistent with maximising transmission, as is observed, and not the very high viral loads that previous models have predicted, an effect that can be further enhanced if viruses similar to those that initiate infection are preferentially transmitted. These results depend strongly on within-host characteristics such as the relative reservoir size, with the evolution of intermediate viral loads observed only when the within-host dynamics are sufficiently delayed. In conclusion, we argue that the latent reservoir has important, and hitherto under-appreciated, roles in both within- and between-host viral evolution.
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Affiliation(s)
- Hilje M. Doekes
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Theoretical Biology, Utrecht University, Utrecht, The Netherlands
| | - Christophe Fraser
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Oxford Big Data Institute, Li Ka Shing Centre for Health Information and Discovery, Nuffield Department of Medicine, University of Oxford, Oxford, United Kingdom
| | - Katrina A. Lythgoe
- Department of Infectious Disease Epidemiology, Imperial College London, London, United Kingdom
- Department of Zoology, University of Oxford, Oxford, United Kingdom
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