Search

Your search keyword '"Kellam, Paul"' showing total 919 results
Start Over Author "Kellam, Paul"
919 results on '"Kellam, Paul"'

1. Potent neutralization of SARS-CoV-2 variants by RBD nanoparticle and prefusion-stabilized spike immunogens

Author

Miranda, Marcos C., Kepl, Elizabeth, Navarro, Mary Jane, Chen, Chengbo, Johnson, Max, Sprouse, Kaitlin R., Stewart, Cameron, Palser, Anne, Valdez, Adian, Pettie, Deleah, Sydeman, Claire, Ogohara, Cassandra, Kraft, John C., Pham, Minh, Murphy, Michael, Wrenn, Sam, Fiala, Brooke, Ravichandran, Rashmi, Ellis, Daniel, Carter, Lauren, Corti, Davide, Kellam, Paul, Lee, Kelly, Walls, Alexandra C., Veesler, David, and King, Neil P.

Published
2024
Full Text
View/download PDF

2. Glycosylated nanoparticle-based PfCSP vaccine confers long-lasting antibody responses and sterile protection in mouse malaria model

Author

Ludwig, Julia, Scally, Stephen W., Costa, Giulia, Hoffmann, Sandro, Murugan, Rajagopal, Lossin, Jana, Prieto, Katherine, Obraztcova, Anna, Lobeto, Nina, Franke-Fayard, Blandine, Janse, Chris J., Lebas, Celia, Collin, Nicolas, Binter, Spela, Kellam, Paul, Levashina, Elena A., Wardemann, Hedda, and Julien, Jean-Philippe

Published
2023
Full Text
View/download PDF

3. Molecular determinants of cross-reactivity and potency by VH3-33 antibodies against the Plasmodium falciparum circumsporozoite protein

Author

Thai, Elaine, Murugan, Rajagopal, Binter, Špela, Burn Aschner, Clare, Prieto, Katherine, Kassardjian, Audrey, Obraztsova, Anna S., Kang, Ryu Won, Flores-Garcia, Yevel, Mathis-Torres, Shamika, Li, Kan, Horn, Gillian Q., Huntwork, Richard H.C., Bolscher, Judith M., de Bruijni, Marloes H.C., Sauerwein, Robert, Dennison, S. Moses, Tomaras, Georgia D., Zavala, Fidel, Kellam, Paul, Wardemann, Hedda, and Julien, Jean-Philippe

Published
2023
Full Text
View/download PDF

4. Inferring HIV-1 transmission networks and sources of epidemic spread in Africa with deep-sequence phylogenetic analysis.

Author

Ratmann, Oliver, Grabowski, M Kate, Hall, Matthew, Golubchik, Tanya, Wymant, Chris, Abeler-Dörner, Lucie, Bonsall, David, Hoppe, Anne, Brown, Andrew Leigh, de Oliveira, Tulio, Gall, Astrid, Kellam, Paul, Pillay, Deenan, Kagaayi, Joseph, Kigozi, Godfrey, Quinn, Thomas C, Wawer, Maria J, Laeyendecker, Oliver, Serwadda, David, Gray, Ronald H, Fraser, Christophe, and PANGEA Consortium and Rakai Health Sciences Program

Subjects
PANGEA Consortium and Rakai Health Sciences Program, Humans, HIV-1, HIV Infections, Phylogeny, Base Sequence, Adolescent, Adult, Middle Aged, Africa, Young Adult, Epidemics, High-Throughput Nucleotide Sequencing
Abstract

To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these 'source' populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8-28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.

Published
2019

6. Virus genomes reveal factors that spread and sustained the Ebola epidemic

Author

Dudas, Gytis, Carvalho, Luiz Max, Bedford, Trevor, Tatem, Andrew J, Baele, Guy, Faria, Nuno R, Park, Daniel J, Ladner, Jason T, Arias, Armando, Asogun, Danny, Bielejec, Filip, Caddy, Sarah L, Cotten, Matthew, D’Ambrozio, Jonathan, Dellicour, Simon, Di Caro, Antonino, Diclaro, Joseph W, Duraffour, Sophie, Elmore, Michael J, Fakoli, Lawrence S, Faye, Ousmane, Gilbert, Merle L, Gevao, Sahr M, Gire, Stephen, Gladden-Young, Adrianne, Gnirke, Andreas, Goba, Augustine, Grant, Donald S, Haagmans, Bart L, Hiscox, Julian A, Jah, Umaru, Kugelman, Jeffrey R, Liu, Di, Lu, Jia, Malboeuf, Christine M, Mate, Suzanne, Matthews, David A, Matranga, Christian B, Meredith, Luke W, Qu, James, Quick, Joshua, Pas, Suzan D, Phan, My VT, Pollakis, Georgios, Reusken, Chantal B, Sanchez-Lockhart, Mariano, Schaffner, Stephen F, Schieffelin, John S, Sealfon, Rachel S, Simon-Loriere, Etienne, Smits, Saskia L, Stoecker, Kilian, Thorne, Lucy, Tobin, Ekaete Alice, Vandi, Mohamed A, Watson, Simon J, West, Kendra, Whitmer, Shannon, Wiley, Michael R, Winnicki, Sarah M, Wohl, Shirlee, Wölfel, Roman, Yozwiak, Nathan L, Andersen, Kristian G, Blyden, Sylvia O, Bolay, Fatorma, Carroll, Miles W, Dahn, Bernice, Diallo, Boubacar, Formenty, Pierre, Fraser, Christophe, Gao, George F, Garry, Robert F, Goodfellow, Ian, Günther, Stephan, Happi, Christian T, Holmes, Edward C, Kargbo, Brima, Keïta, Sakoba, Kellam, Paul, Koopmans, Marion PG, Kuhn, Jens H, Loman, Nicholas J, Magassouba, N’Faly, Naidoo, Dhamari, Nichol, Stuart T, Nyenswah, Tolbert, Palacios, Gustavo, Pybus, Oliver G, Sabeti, Pardis C, Sall, Amadou, Ströher, Ute, Wurie, Isatta, Suchard, Marc A, Lemey, Philippe, and Rambaut, Andrew

Subjects
Infectious Diseases, Emerging Infectious Diseases, Biodefense, Vaccine Related, Prevention, Infection, Good Health and Well Being, Climate, Disease Outbreaks, Ebolavirus, Genome, Viral, Geography, Hemorrhagic Fever, Ebola, Humans, Internationality, Linear Models, Molecular Epidemiology, Phylogeny, Travel, General Science & Technology
Abstract

The 2013-2016 West African epidemic caused by the Ebola virus was of unprecedented magnitude, duration and impact. Here we reconstruct the dispersal, proliferation and decline of Ebola virus throughout the region by analysing 1,610 Ebola virus genomes, which represent over 5% of the known cases. We test the association of geography, climate and demography with viral movement among administrative regions, inferring a classic 'gravity' model, with intense dispersal between larger and closer populations. Despite attenuation of international dispersal after border closures, cross-border transmission had already sown the seeds for an international epidemic, rendering these measures ineffective at curbing the epidemic. We address why the epidemic did not spread into neighbouring countries, showing that these countries were susceptible to substantial outbreaks but at lower risk of introductions. Finally, we reveal that this large epidemic was a heterogeneous and spatially dissociated collection of transmission clusters of varying size, duration and connectivity. These insights will help to inform interventions in future epidemics.

Published
2017

7. Quantifying HIV transmission flow between high-prevalence hotspots and surrounding communities: a population-based study in Rakai, Uganda

Author

Ayles, Helen, Bowden, Rory, Calvez, Vincent, Cohen, Myron, Dennis, Anne, Essex, Max, Fidler, Sarah, Frampton, Dan, Hayes, Richard, Herbeck, Josh, Kaleebu, Pontiano, Kityo, Cissy, Lingappa, Jairam, Novitsky, Vladimir, Paton, Nick, Rambaut, Andrew, Seeley, Janet, Ssemwanga, Deogratius, Tanser, Frank, Lutalo, Tom, Galiwango, Ronald, Makumbi, Fred, Sewankambo, Nelson K., Nabukalu, Dorean, Ndyanabo, Anthony, Ssekasanvu, Joseph, Nakawooya, Hadijja, Nakukumba, Jessica, Kigozi, Grace N., Nantume, Betty S., Resty, Nampijja, Kambasu, Jedidah, Nalugemwa, Margaret, Nakabuye, Regina, Ssebanobe, Lawrence, Nankinga, Justine, Kayiira, Adrian, Nanfuka, Gorreth, Ahimbisibwe, Ruth, Tomusange, Stephen, Galiwango, Ronald M., Nakalanzi, Margaret, Otobi, Joseph O., Ankunda, Denis, Ssembatya, Joseph L., Ssemanda, John B., Kato, Emmanuel, Kairania, Robert, Kisakye, Alice, Batte, James, Ludigo, James, Nampijja, Abisagi, Watya, Steven, Nehemia, Kighoma, Anyokot, Sr. Margaret, Mwinike, Joshua, Kibumba, George, Ssebowa, Paschal, Mondo, George, Wasswa, Francis, Nantongo, Agnes, Kakembo, Rebecca, Galiwango, Josephine, Ssemango, Geoffrey, Redd, Andrew D., Santelli, John, Kennedy, Caitlin E., Wagman, Jennifer, Tobian, Aaron, Ratmann, Oliver, Kagaayi, Joseph, Hall, Matthew, Golubchick, Tanya, Kigozi, Godfrey, Xi, Xiaoyue, Wymant, Chris, Nakigozi, Gertrude, Abeler-Dörner, Lucie, Bonsall, David, Gall, Astrid, Hoppe, Anne, Kellam, Paul, Bazaale, Jeremiah, Kalibbala, Sarah, Laeyendecker, Oliver, Lessler, Justin, Nalugoda, Fred, Chang, Larry W, de Oliveira, Tulio, Pillay, Deenan, Quinn, Thomas C, Reynolds, Steven J, Spencer, Simon E F, Ssekubugu, Robert, Serwadda, David, Wawer, Maria J, Gray, Ronald H, Fraser, Christophe, and Grabowski, M Kate

Published
2020
Full Text
View/download PDF

8. Diverse competitor B cell responses to a germline-targeting priming immunogen in human Ig loci transgenic mice

Author

Schiffner, Torben, primary, Palser, Anne, additional, Jardine, Joseph G., additional, Liguori, Alessia, additional, Menis, Sergey, additional, Raemisch, Sebastian, additional, Hu, Xiaozhen, additional, Kulp, Daniel W., additional, Wang, Xiaoning, additional, Diedrich, Jolene K., additional, Groschel, Bettina, additional, Kalyuzhniy, Oleksandr, additional, Tingle, Ryan, additional, Le, Khoa, additional, Georgeson, Erik, additional, Adachi, Yumiko, additional, Kubitz, Michael, additional, Landais, Elise, additional, Yates, John R., additional, Paulson, James C., additional, Sok, Devin, additional, Kellam, Paul, additional, and Schief, William R., additional

Published
2024
Full Text
View/download PDF

11. A systematic review of definitions of extreme phenotypes of HIV control and progression.

Author

Gurdasani, Deepti, Iles, Louise, Dillon, David, Young, Elizabeth, Olson, Ashley, Naranbhai, Vivek, Fidler, Sarah, Gkrania-Klotsas, Effrossyni, Post, Frank, Kellam, Paul, Porter, Kholoud, and Sandhu, Manjinder

Subjects
Disease Progression, HIV Infections, HIV Long-Term Survivors, Humans, Phenotype, Terminology as Topic
Abstract

The study of individuals at opposite ends of the HIV clinical spectrum can provide invaluable insights into HIV biology. Heterogeneity in criteria used to define these individuals can introduce inconsistencies in results from research and make it difficult to identify biological mechanisms underlying these phenotypes. In this systematic review, we formally quantified the heterogeneity in definitions used for terms referring to extreme phenotypes in the literature, and identified common definitions and components used to describe these phenotypes. We assessed 714 definitions of HIV extreme phenotypes in 501 eligible studies published between 1 January 2000 and 15 March 2012, and identified substantial variation among these. This heterogeneity in definitions may represent important differences in biological endophenotypes and clinical progression profiles of individuals selected by these, suggesting the need for harmonized definitions. In this context, we were able to identify common components in existing definitions that may provide a framework for developing consensus definitions for these phenotypes in HIV infection.

Published
2014

14. Low frequency of genotypic resistance in HIV-1-infected patients failing an atazanavir-containing regimen: a clinical cohort study

Author

Dolling, David I, Dunn, David T, Sutherland, Katherine A, Pillay, Deenan, Mbisa, Jean L, Parry, Chris M, Post, Frank A, Sabin, Caroline A, Cane, Patricia A, Aitken, Celia, Asboe, David, Webster, Daniel, Cane, Patricia, Castro, Hannah, Dunn, David, Dolling, David, Chadwick, David, Churchill, Duncan, Clark, Duncan, Collins, Simon, Delpech, Valerie, Geretti, Anna Maria, Goldberg, David, Hale, Antony, Hué, Stéphane, Kaye, Steve, Kellam, Paul, Lazarus, Linda, Leigh-Brown, Andrew, Mackie, Nicola, Orkin, Chloe, Rice, Philip, Phillips, Andrew, Sabin, Caroline, Smit, Erasmus, Templeton, Kate, Tilston, Peter, Tong, William, Williams, Ian, Zhang, Hongyi, Zuckerman, Mark, Greatorex, Jane, Wildfire, Adrian, O'Shea, Siobhan, Mullen, Jane, Mbisa, Tamyo, Cox, Alison, Tandy, Richard, Hale, Tony, Fawcett, Tracy, Hopkins, Mark, Ashton, Lynn, Booth, Claire, Garcia-Diaz, Ana, Shepherd, Jill, Schmid, Matthias L, Payne, Brendan, Hay, Phillip, Rice, Phillip, Paynter, Mary, Bibby, David, Kirk, Stuart, MacLean, Alasdair, Gunson, Rory, Coughlin, Kate, Fearnhill, Esther, Fradette, Lorraine, Porter, Kholoud, Ainsworth, Jonathan, Anderson, Jane, Babiker, Abdel, Fisher, Martin, Gazzard, Brian, Gilson, Richard, Gompels, Mark, Hill, Teresa, Johnson, Margaret, Kegg, Stephen, Leen, Clifford, Nelson, Mark, Palfreeman, Adrian, Post, Frank, Sachikonye, Memory, Schwenk, Achim, Walsh, John, Huntington, Susie, Jose, Sophie, Thornton, Alicia, Glabay, Adam, Orkin, C, Garrett, N, Lynch, J, Hand, J, de Souza, C, Fisher, M, Perry, N, Tilbury, S, Gazzard, B, and Nelson, M

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Clinical Sciences, Clinical Trials and Supportive Activities, Infectious Diseases, Antimicrobial Resistance, Clinical Research, Infection, Adult, Anti-HIV Agents, Atazanavir Sulfate, Cohort Studies, Drug Resistance, Viral, Female, HIV Infections, HIV Protease, HIV-1, Humans, Male, Medication Adherence, Middle Aged, Mutation Rate, Mutation, Missense, Oligopeptides, Pyridines, Treatment Failure, United States, UK HIV Drug Resistance Database, UK Collaborative HIV Cohort Study, HIV, drug resistance mutations, naive patients, protease inhibitors, virological failure, Microbiology, Pharmacology and Pharmaceutical Sciences, Clinical sciences, Pharmacology and pharmaceutical sciences
Abstract

ObjectivesTo determine protease mutations that develop at viral failure for protease inhibitor (PI)-naive patients on a regimen containing the PI atazanavir.MethodsResistance tests on patients failing atazanavir, conducted as part of routine clinical care in a multicentre observational study, were randomly matched by subtype to resistance tests from PI-naive controls to account for natural polymorphisms. Mutations from the consensus B sequence across the protease region were analysed for association and defined using the IAS-USA 2011 classification list.ResultsFour hundred and five of 2528 (16%) patients failed therapy containing atazanavir as a first PI over a median (IQR) follow-up of 1.76 (0.84-3.15) years and 322 resistance tests were available for analysis. Recognized major atazanavir mutations were found in six atazanavir-experienced patients (P < 0.001), including I50L and N88S. The minor mutations most strongly associated with atazanavir experience were M36I, M46I, F53L, A71V, V82T and I85V (P < 0.05). Multiple novel mutations, I15S, L19T, K43T, L63P/V, K70Q, V77I and L89I/T/V, were also associated with atazanavir experience.ConclusionsViral failure on atazanavir-containing regimens was not common and major resistance mutations were rare, suggesting that adherence may be a major contributor to viral failure. Novel mutations were described that have not been previously documented.

Published
2013

16. Evaluating the Impact of Functional Genetic Variation on HIV-1 Control

Author

McLaren, Paul J., Pulit, Sara L., Gurdasani, Deepti, Bartha, Istvan, Shea, Patrick R., Pomilla, Cristina, Gupta, Namrata, Gkrania-Klotsas, Effrossyni, Young, Elizabeth H., Bannert, Norbert, Del Amo, Julia, Gill, M John, Gilmour, Jill, Kellam, Paul, Kelleher, Anthony D., Sönnerborg, Anders, Zangerle, Robert, Post, Frank A., Fisher, Martin, Haas, David W., Walker, Bruce D., Porter, Kholoud, Goldstein, David B., Sandhu, Manjinder S., de Bakker, Paul I.W., and Fellay, Jacques

Published
2017

22. Distinct genetic architectures and environmental factors associate with host response to the γ2-herpesvirus infections

Author

Sallah, Neneh, Miley, Wendell, Labo, Nazzarena, Carstensen, Tommy, Fatumo, Segun, Gurdasani, Deepti, Pollard, Martin O., Dilthey, Alexander T., Mentzer, Alexander J., Marshall, Vickie, Cornejo Castro, Elena M., Pomilla, Cristina, Young, Elizabeth H., Asiki, Gershim, Hibberd, Martin L., Sandhu, Manjinder, Kellam, Paul, Newton, Robert, Whitby, Denise, and Barroso, Inês

Published
2020
Full Text
View/download PDF

26. Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing

Author

Richardson, Eve; https://orcid.org/0000-0002-5499-6283, Binter, Špela, Kosmac, Miha; https://orcid.org/0000-0002-5372-7233, Ghraichy, Marie; https://orcid.org/0000-0002-7348-796X, von Niederhäusern, Valentin; https://orcid.org/0000-0001-9150-2361, Kovaltsuk, Aleksandr; https://orcid.org/0000-0003-3806-8302, Galson, Jacob D; https://orcid.org/0000-0003-4916-800X, Trück, Johannes; https://orcid.org/0000-0002-0418-7381, Kelly, Dominic F, Deane, Charlotte M; https://orcid.org/0000-0003-1388-2252, Kellam, Paul, Watson, Simon J, Richardson, Eve; https://orcid.org/0000-0002-5499-6283, Binter, Špela, Kosmac, Miha; https://orcid.org/0000-0002-5372-7233, Ghraichy, Marie; https://orcid.org/0000-0002-7348-796X, von Niederhäusern, Valentin; https://orcid.org/0000-0001-9150-2361, Kovaltsuk, Aleksandr; https://orcid.org/0000-0003-3806-8302, Galson, Jacob D; https://orcid.org/0000-0003-4916-800X, Trück, Johannes; https://orcid.org/0000-0002-0418-7381, Kelly, Dominic F, Deane, Charlotte M; https://orcid.org/0000-0003-1388-2252, Kellam, Paul, and Watson, Simon J

Abstract

Immunoglobulin loci-transgenic animals are widely used in antibody discovery and increasingly in vaccine response modelling. In this study, we phenotypically characterised B-cell populations from the Intelliselect® Transgenic mouse (Kymouse) demonstrating full B-cell development competence. Comparison of the naïve B-cell receptor (BCR) repertoires of Kymice BCRs, naïve human, and murine BCR repertoires revealed key differences in germline gene usage and junctional diversification. These differences result in Kymice having CDRH3 length and diversity intermediate between mice and humans. To compare the structural space explored by CDRH3s in each species' repertoire, we used computational structure prediction to show that Kymouse naïve BCR repertoires are more human-like than mouse-like in their predicted distribution of CDRH3 shape. Our combined sequence and structural analysis indicates that the naïve Kymouse BCR repertoire is diverse with key similarities to human repertoires, while immunophenotyping confirms that selected naïve B-cells are able to go through complete development.

Published
2023

27. Development of a candidate reference material for adventitious virus detection in vaccine and biologicals manufacturing by deep sequencing

Author

Huang, Xuening, Nguyen, Jenny, Wall, David, Hargrove, Stacey, Fu, Thomas, Xu, George, Li, Li, Cote, Colette, Delwart, Eric, Li, Linlin, Hewlett, Indira, Simonyan, Vahan, Ragupathy, Viswanath, Alin, Voskanian-Kordi, Mermod, Nicolas, Hill, Christiane, Ottenwälder, Birgit, Richter, Daniel C., Tehrani, Arman, Jacqueline, Weber-Lehmann, Cassart, Jean-Pol, Letellier, Carine, Vandeputte, Olivier, Ruelle, Jean-Louis, Deyati, Avisek, La Neve, Fabio, Modena, Chiara, Mee, Edward, Schepelmann, Silke, Preston, Mark, Minor, Philip, Eloit, Marc, Muth, Erika, Lamamy, Arnaud, Jagorel, Florence, Cheval, Justine, Anscombe, Catherine, Misra, Raju, Wooldridge, David, Gharbia, Saheer, Rose, Graham, Ng, Siemon H.S., Charlebois, Robert L., Gisonni-Lex, Lucy, Mallet, Laurent, Dorange, Fabien, Chiu, Charles, Naccache, Samia, Kellam, Paul, van der Hoek, Lia, Cotten, Matt, Mitchell, Christine, Baier, Brian S., Sun, Wenping, Malicki, Heather D., Mee, Edward T., Preston, Mark D., and Minor, Philip D.

Published
2016
Full Text
View/download PDF

29. Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing

Author

Richardson, Eve, primary, Binter, Špela, primary, Kosmac, Miha, additional, Ghraichy, Marie, additional, von Niederhäusern, Valentin, additional, Kovaltsuk, Aleksandr, additional, Galson, Jacob D, additional, Trück, Johannes, additional, Kelly, Dominic F, additional, Deane, Charlotte M, additional, Kellam, Paul, additional, and Watson, Simon J, additional

Published
2023
Full Text
View/download PDF

30. Frequency matters: comparison of drug resistance mutation detection by Sanger and next-generation sequencing in HIV-1

Author

Balakrishna, Suraj, primary, Loosli, Tom, additional, Zaheri, Maryam, additional, Frischknecht, Paul, additional, Huber, Michael, additional, Kusejko, Katharina, additional, Yerly, Sabine, additional, Leuzinger, Karoline, additional, Perreau, Matthieu, additional, Ramette, Alban, additional, Wymant, Chris, additional, Fraser, Christophe, additional, Kellam, Paul, additional, Gall, Astrid, additional, Hirsch, Hans H, additional, Stoeckle, Marcel, additional, Rauch, Andri, additional, Cavassini, Matthias, additional, Bernasconi, Enos, additional, Notter, Julia, additional, Calmy, Alexandra, additional, Günthard, Huldrych F, additional, Metzner, Karin J, additional, and Kouyos, Roger D, additional

Published
2023
Full Text
View/download PDF

31. Author response: Characterisation of the immune repertoire of a humanised transgenic mouse through immunophenotyping and high-throughput sequencing

Author

Richardson, Eve, primary, Binter, Špela, primary, Kosmac, Miha, additional, Ghraichy, Marie, additional, von Niederhäusern, Valentin, additional, Kovaltsuk, Aleksandr, additional, Galson, Jacob D, additional, Trück, Johannes, additional, Kelly, Dominic F, additional, Deane, Charlotte M, additional, Kellam, Paul, additional, and Watson, Simon J, additional

Published
2023
Full Text
View/download PDF

32. Genomic epidemiology of the rotavirus G2P[4] strains in coastal Kenya pre- and post-rotavirus vaccine introduction, 2012–8

Author

Makori, Timothy O, primary, Bargul, Joel L, additional, Lambisia, Arnold W, additional, Mwanga, Mike J, additional, Murunga, Nickson, additional, de Laurent, Zaydah R, additional, Lewa, Clement S, additional, Mutunga, Martin, additional, Kellam, Paul, additional, Cotten, Matthew, additional, Nokes, D James, additional, Phan, My, additional, and Agoti, Charles N, additional

Published
2023
Full Text
View/download PDF

33. Frequency matters: comparison of drug resistance mutation detection by Sanger and next-generation sequencing in HIV-1

Author

Balakrishna, Suraj, Loosli, Tom, Zaheri, Maryam, Frischknecht, Paul, Huber, Michael, Kusejko, Katharina, Yerly, Sabine, Leuzinger, Karoline, Perreau, Matthieu, Ramette, Alban, Wymant, Chris, Fraser, Christophe, Kellam, Paul, Gall, Astrid, Hirsch, Hans H, Stoeckle, Marcel, Rauch, Andri, Cavassini, Matthias, Bernasconi, Enos, Notter, Julia, Calmy, Alexandra, Günthard, Huldrych F, Metzner, Karin J, and Kouyos, Roger D

Subjects
Pharmacology, Microbiology (medical), Infectious Diseases, Pharmacology (medical), 610 Medizin und Gesundheit, 570 Biowissenschaften, Biologie
Abstract

BackgroundNext-generation sequencing (NGS) is gradually replacing Sanger sequencing (SS) as the primary method for HIV genotypic resistance testing. However, there are limited systematic data on comparability of these methods in a clinical setting for the presence of low-abundance drug resistance mutations (DRMs) and their dependency on the variant-calling thresholds.MethodsTo compare the HIV-DRMs detected by SS and NGS, we included participants enrolled in the Swiss HIV Cohort Study (SHCS) with SS and NGS sequences available with sample collection dates ≤7 days apart. We tested for the presence of HIV-DRMs and compared the agreement between SS and NGS at different variant-calling thresholds.ResultsWe included 594 pairs of SS and NGS from 527 SHCS participants. Males accounted for 80.5% of the participants, 76.3% were ART naive at sample collection and 78.1% of the sequences were subtype B. Overall, we observed a good agreement (Cohen’s kappa >0.80) for HIV-DRMs for variant-calling thresholds ≥5%. We observed an increase in low-abundance HIV-DRMs detected at lower thresholds [28/417 (6.7%) at 10%–25% to 293/812 (36.1%) at 1%–2% threshold]. However, such low-abundance HIV-DRMs were overrepresented in ART-naive participants and were in most cases not detected in previously sampled sequences suggesting high sequencing error for thresholds ConclusionsWe found high concordance between SS and NGS but also a substantial number of low-abundance HIV-DRMs detected only by NGS at lower variant-calling thresholds. Our findings suggest that a substantial fraction of the low-abundance HIV-DRMs detected at thresholds

Published
2023
Full Text
View/download PDF

34. The antiviral restriction factor IFN-induced transmembrane protein 3 prevents cytokine-driven CMV pathogenesis

Author

Stacey, Maria A., Clare, Simon, Clement, Mathew, Marsden, Morgan, Abdul-Karim, Juneid, Kane, Leanne, Harcourt, Katherine, Brandt, Cordelia, Fielding, Ceri A., Smith, Sarah E., Wash, Rachael S., Brias, Silvia Gimeno, Stack, Gabrielle, Notley, George, Cambridge, Emma L., Isherwood, Christopher, Speak, Anneliese O., Johnson, Zoe, Ferlin, Walter, Jones, Simon A., Kellam, Paul, and Humphreys, Ian R.

Subjects
Cytokines -- Health aspects, Herpesvirus infections -- Risk factors -- Development and progression, Membrane proteins -- Properties, Health care industry
Abstract

The antiviral restriction factor IFN-induced transmembrane protein 3 (IFITM3) inhibits cell entry of a number of viruses, and genetic diversity within IFITM3 determines susceptibility to viral disease in humans. Here, we used the murine CMV (MCMV) model of infection to determine that IFITM3 limits herpesvirus-associated pathogenesis without directly preventing virus replication. Instead, IFITM3 promoted antiviral cellular immunity through the restriction of virus-induced lymphopenia, apoptosis-independent NK cell death, and loss of T cells. Viral disease in [Ifitm3.sup.-/-] mice was accompanied by elevated production of cytokines, most notably IL-6. IFITM3 inhibited IL-6 production by myeloid cells in response to replicating and nonreplicating virus as well as following stimulation with the TLR ligands Poly(I:C) and CpG. Although IL-6 promoted virus-specific T cell responses, uncontrolled IL-6 expression in [Ifitm3.sup.-/-] mice triggered the loss of NK cells and subsequently impaired control of MCMV replication. Thus, IFITM3 represents a checkpoint regulator of antiviral immunity that controls cytokine production to restrict viral pathogenesis. These data suggest the utility of cytokine-targeting strategies in the treatment of virus-infected individuals with impaired IFITM3 activity., Introduction Antiviral immune responses elicited following acute viral infections are tightly regulated to limit uncontrolled immune pathology, while ensuring adequate control of the primary infection. Herpesvirus infections are typically controlled [...]

Published
2017
Full Text
View/download PDF

37. High-density binding to Plasmodium falciparum circumsporozoite protein repeats by inhibitory antibody elicited in mouse with human immunoglobulin repertoire

Author

Kucharska, Iga, primary, Binter, Špela, additional, Murugan, Rajagopal, additional, Scally, Stephen W., additional, Ludwig, Julia, additional, Prieto, Katherine, additional, Thai, Elaine, additional, Costa, Giulia, additional, Li, Kan, additional, Horn, Gillian Q., additional, Flores-Garcia, Yevel, additional, Bosch, Alexandre, additional, Sicard, Taylor, additional, Rubinstein, John L., additional, Zavala, Fidel, additional, Dennison, S. Moses, additional, Tomaras, Georgia D., additional, Levashina, Elena A., additional, Kellam, Paul, additional, Wardemann, Hedda, additional, and Julien, Jean-Philippe, additional

Published
2022
Full Text
View/download PDF

38. Genomic epidemiology of the rotavirus G2P[4] strains in coastal Kenya pre- and post-rotavirus vaccine introduction, 2012 – 2018

Author

Makori, Timothy O., primary, Bargul, Joel L., additional, Lambisia, Arnold W., additional, Mwanga, Mike J., additional, Murunga, Nickson, additional, de Laurent, Zaydah R., additional, Lewa, Clement S., additional, Mutunga, Martin, additional, Kellam, Paul, additional, Cotten, Matthew, additional, Nokes, D. James, additional, Phan, My, additional, and Agoti, Charles N., additional

Published
2022
Full Text
View/download PDF

42. Noise Filtering and Microarray Image Reconstruction Via Chained Fouriers

Author

Fraser, Karl, Wang, Zidong, Li, Yongmin, Kellam, Paul, Liu, Xiaohui, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, R. Berthold, Michael, editor, Shawe-Taylor, John, editor, and Lavrač, Nada, editor

Published
2007
Full Text
View/download PDF

43. Improved Robustness in Time Series Analysis of Gene Expression Data by Polynomial Model Based Clustering

Author

Hirsch, Michael, Tucker, Allan, Swift, Stephen, Martin, Nigel, Orengo, Christine, Kellam, Paul, Liu, Xiaohui, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Dough, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Istrail, Sorin, editor, Pevzner, Pavel, editor, Waterman, Michael, editor, R. Berthold, Michael, editor, Glen, Robert C., editor, and Fischer, Ingrid, editor

Published
2006
Full Text
View/download PDF

44. Transmission and evolution of the Middle East respiratory syndrome coronavirus in Saudi Arabia: a descriptive genomic study

Author

Cotten, Matthew, Watson, Simon J, Kellam, Paul, Al-Rabeeah, Abdullah A, Makhdoom, Hatem Q, Assiri, Abdullah, Al-Tawfiq, Jaffar A, Alhakeem, Rafat F, Madani, Hossam, AlRabiah, Fahad A, Hajjar, Sami Al, Al-nassir, Wafa N, Albarrak, Ali, Flemban, Hesham, Balkhy, Hanan H, Alsubaie, Sarah, Palser, Anne L, Gall, Astrid, Bashford-Rogers, Rachael, Rambaut, Andrew, Zumla, Alimuddin I, and Memish, Ziad A

Published
2013
Full Text
View/download PDF

49. HIV-phyloTSI: Subtype-independent estimation of time since HIV-1 infection for cross-sectional measures of population incidence using deep sequence data

Author

Golubchik, Tanya, Abeler-Dörner, Lucie, Hall, Matthew, Wymant, Chris, Bonsall, David, Macintyre-Cockett, George, Thomson, Laura, Baeten, Jared, Celum, Connie, Galiwango, Ronald, Kosloff, Barry, Limbada, Mohammed, Mujugira, Andrew, Mugo, Nelly, Gall, Astrid, Blanquart, François, Bakker, Margreet, Bezemer, Daniela, Ong, Swee Hoe, Albert, Jan, Bannert, Norbert, Fellay, Jacques, Gunsenheimer-Bartmeyer, Barbara, Günthard, Huldrych, Kivelä, Pia, Kouyos, Roger, Meyer, Laurence, Porter, Kholoud, van Sighem, Ard, van der Valk, Mark, Berkhout, Ben, Kellam, Paul, Cornelissen, Marion, Reiss, Peter, Ayles, Helen, Burns, David, Fidler, Sarah, Grabowski, Mary Kate, Hayes, Richard, Herbeck, Joshua, Kagaayi, Joseph, Kaleebu, Pontiano, Lingappa, Jairam, Ssemwanga, Deogratius, Eshleman, Susan, Cohen, Myron, Ratmann, Oliver, Laeyendecker, Oliver, Fraser, Christophe, Blanquart, François, Centre interdisciplinaire de recherche en biologie (CIRB), Labex MemoLife, École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Collège de France (CdF (institution))-Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Université Paris sciences et lettres (PSL)-École normale supérieure - Paris (ENS-PSL), Université Paris sciences et lettres (PSL)-Institut National de la Santé et de la Recherche Médicale (INSERM)-Centre National de la Recherche Scientifique (CNRS), Infection, Anti-microbiens, Modélisation, Evolution (IAME (UMR_S_1137 / U1137)), Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris Cité (UPCité)-Université Sorbonne Paris Nord, Centre de recherche en épidémiologie et santé des populations (CESP), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP)-Hôpital Paul Brousse-Institut National de la Santé et de la Recherche Médicale (INSERM)-Université Paris-Saclay, and On behalf of the HPTN 071 (PopART) Phylogenetics protocol team, the BEEHIVE collaboration and the PANGEA consortium

Subjects
[SDV] Life Sciences [q-bio], [SDV]Life Sciences [q-bio]
Abstract

Estimating the time since HIV infection (TSI) at population level is essential for tracking changes in the global HIV epidemic. Most methods for determining duration of infection classify samples into recent and non-recent and are unable to give more granular TSI estimates. These binary classifications have a limited recency time window of several months, therefore requiring large sample sizes, and cannot assess the cumulative impact of an intervention. We developed a Random Forest Regression model, HIV-phyloTSI, that combines measures of within-host diversity and divergence to generate TSI estimates from viral deep-sequencing data, with no need for additional variables. HIV-phyloTSI provides a continuous measure of TSI up to 9 years, with a mean absolute error of less than 12 months overall and less than 5 months for infections with a TSI of up to a year. It performed equally well for all major HIV subtypes based on data from African and European cohorts. We demonstrate how HIV-phyloTSI can be used for incidence estimates on a population level.

Published
2022
Full Text
View/download PDF

50. Phylogenetic estimation of the viral fitness landscape of HIV-1 set-point viral load

Author

Zhao, Lele; https://orcid.org/0000-0002-2807-1914, Wymant, Chris; https://orcid.org/0000-0002-9847-8226, Blanquart, François; https://orcid.org/0000-0003-0591-2466, Golubchik, Tanya; https://orcid.org/0000-0003-2765-9828, Gall, Astrid, Bakker, Margreet, Bezemer, Daniela; https://orcid.org/0000-0001-9304-0877, Hall, Matthew, Ong, Swee Hoe; https://orcid.org/0000-0002-3629-5387, Albert, Jan, Bannert, Norbert, Fellay, Jacques; https://orcid.org/0000-0002-8240-939X, Grabowski, M Kate, Gunsenheimer-Bartmeyer, Barbara, Günthard, Huldrych F; https://orcid.org/0000-0002-1142-6723, Kivelä, Pia, Kouyos, Roger D; https://orcid.org/0000-0002-9220-8348, Laeyendecker, Oliver, Meyer, Laurence, Porter, Kholoud, van Sighem, Ard; https://orcid.org/0000-0002-6656-0516, van der Valk, Marc, Berkhout, Ben; https://orcid.org/0000-0002-1905-8486, Kellam, Paul, Cornelissen, Marion, Reiss, Peter, Fraser, Christophe, Ferretti, Luca; https://orcid.org/0000-0001-7578-7301, Zhao, Lele; https://orcid.org/0000-0002-2807-1914, Wymant, Chris; https://orcid.org/0000-0002-9847-8226, Blanquart, François; https://orcid.org/0000-0003-0591-2466, Golubchik, Tanya; https://orcid.org/0000-0003-2765-9828, Gall, Astrid, Bakker, Margreet, Bezemer, Daniela; https://orcid.org/0000-0001-9304-0877, Hall, Matthew, Ong, Swee Hoe; https://orcid.org/0000-0002-3629-5387, Albert, Jan, Bannert, Norbert, Fellay, Jacques; https://orcid.org/0000-0002-8240-939X, Grabowski, M Kate, Gunsenheimer-Bartmeyer, Barbara, Günthard, Huldrych F; https://orcid.org/0000-0002-1142-6723, Kivelä, Pia, Kouyos, Roger D; https://orcid.org/0000-0002-9220-8348, Laeyendecker, Oliver, Meyer, Laurence, Porter, Kholoud, van Sighem, Ard; https://orcid.org/0000-0002-6656-0516, van der Valk, Marc, Berkhout, Ben; https://orcid.org/0000-0002-1905-8486, Kellam, Paul, Cornelissen, Marion, Reiss, Peter, Fraser, Christophe, and Ferretti, Luca; https://orcid.org/0000-0001-7578-7301

Abstract

Set-point viral load (SPVL), a common measure of human immunodeficiency virus (HIV)-1 virulence, is partially determined by viral genotype. Epidemiological evidence suggests that this viral property has been under stabilising selection, with a typical optimum for the virus between 10$^{4}$ and 10$^{5}$ copies of viral RNA per ml. Here we aimed to detect transmission fitness differences between viruses from individuals with different SPVLs directly from phylogenetic trees inferred from whole-genome sequences. We used the local branching index (LBI) as a proxy for transmission fitness. We found that LBI is more sensitive to differences in infectiousness than to differences in the duration of the infectious state. By analysing subtype-B samples from the Bridging the Evolution and Epidemiology of HIV in Europe project, we inferred a significant positive relationship between SPVL and LBI up to approximately 10$^{5}$ copies/ml, with some evidence for a peak around this value of SPVL. This is evidence of selection against low values of SPVL in HIV-1 subtype-B strains, likely related to lower infectiousness, and perhaps a peak in the transmission fitness in the expected range of SPVL. The less prominent signatures of selection against higher SPVL could be explained by an inherent limit of the method or the deployment of antiretroviral therapy.

Published
2022

Catalog

Books, media, physical & digital resources
See catalog results