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1. Gene expression data visualization tool on the o²S²PARC platform [version 2; peer review: 2 approved]

Author

Hiba Ben Aribi, Mengyuan Ding, and Anmol Kiran

Subjects
Visualization, Gene expression, Ontology, o²S²PARC, eng, Medicine, Science
Abstract

Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are essential for genetic disease studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an o²S²PARC template to instantiate an interactive pipeline for gene expression data visualization, ontological mapping, and statistical evaluation. To demonstrate the tool's usefulness, we performed a case study on a publicly available dataset. Results: The tool enables users to identify the differentially expressed genes (DEGs) and visualize them in a volcano plot format. Ontologies associated with the DEGs are assigned and visualized in barplots. Conclusions: The “Expression data visualization” template is publicly available on the o²S²PARC platform.

Published
2023
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2. Genomic Characteristics of Invasive Serotype 1 in New Caledonia Prior to the Introduction of PCV13

Author

Mariem Hanachi, Anmol Kiran, Jennifer Cornick, Emna Harigua-Souiai, Dean Everett, Alia Benkahla, and Oussama Souiai

Subjects
Biology (General), QH301-705.5
Abstract

Streptococcus pneumoniae serotype 1 is a common cause of global invasive pneumococcal disease. In New Caledonia, serotype 1 is the most prevalent serotype and led to two major outbreaks reported in the 2000s. The pneumococcal conjugate vaccine 13 (PCV13) was introduced into the vaccination routine, intending to prevent the expansion of serotype 1 in New Caledonia. Aiming to provide a baseline for monitoring the post-PCV13 changes, we performed a whole-genome sequence analysis on 67 serotype 1 isolates collected prior to the PCV13 introduction. To highlight the S. pneumoniae serotype 1 population structure, we performed a multilocus sequence typing (MLST) analysis revealing that NC serotype 1 consisted of 2 sequence types: ST3717 and the highly dominant ST306. Both sequence types harbored the same resistance genes to beta-lactams, macrolide, streptogramin B, fluoroquinolone, and lincosamide antibiotics. We have also identified 36 virulence genes that were ubiquitous to all the isolates. Among these virulence genes, the pneumolysin sequence presented an allelic profile associated with disease outbreaks and reduced hemolytic activity. Moreover, recombination hotspots were identified in 4 virulence genes and more notably in the cps locus ( cps2L ), potentially leading to capsular switching, a major mechanism of the emergence of nonvaccine types. In summary, this study represents the first overview of the genomic characteristics of S. pneumoniae serotype 1 in New Caledonia prior to the introduction of PCV13. This preliminary description represents a baseline to assess the impact of PCV13 on serotype 1 population structure and genomic diversity.

Published
2020
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3. Genetic diversity of Mycobacterium tuberculosis clinical isolates in Blantyre, Malawi

Author

Victor Ndhlovu, Anmol Kiran, Derek Sloan, Wilson Mandala, Konstantina Kontogianni, Mercy Kamdolozi, Maxine Caws, and Gerry Davies

Subjects
Clinical genetics, Genetics, Bioinformatics, Infectious disease, Microbiology, Single molecule real time sequencing, Science (General), Q1-390, Social sciences (General), H1-99
Abstract

Despite the high burden of tuberculosis (TB) worldwide, specific factors influencing disease transmission remain elusive. Long term epidemiological studies and in vitro experimental models provide evidence of variable relative fitness of Mycobacterium tuberculosis (Mtb) strains but few such studies are available. Large sequence polymorphisms (LSP) are a robust molecular marker and are feasible as an epidemiological investigative tool. Few Mtb molecular epidemiological studies have been reported in Malawi owing to lack of laboratories with molecular tools. We characterized the genetic diversity of Mtb clinical isolates amongst TB patients in Blantyre, Malawi. We genotyped 64 Mtb clinical isolates using LSP-PCR, assigned specific lineages and confirmed 18 of the isolates using SMRT sequencing. The 64 isolates clustered into 4 lineages (L1-L4) with L4 predominating. There were 10/64 (16%) isolates belonging to L1, 6/64 (9%) belonging to L2, 2/64 (3%) belonging to L3 and 46/64 (72%) belonging to L4. Comparison with a previous study done in Karonga revealed concordance in L1 and L4 but discodance in L2 and L3. The phylogenetic tree constructed, comprised of 3/4 lineages present in Blantyre with 3/18 belonging to L1, 3/18 belonging to L2 and 12/18 belonging to L4. Four Mtb lineages were present in Blantyre with L4 predominating. Larger studies are needed to understand the molecular epidemiology of TB in Blantyre in light of increased bi-directional migration with South Africa.

Published
2019
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4. Gene expression data visualization tool on the o²S²PARC platform [version 1; peer review: 2 approved with reservations]

Author

Hiba Ben Aribi, Mengyuan Ding, and Anmol Kiran

Subjects
Software Tool Article, Articles, Visualization, Gene expression, Ontology, o²S²PARC
Abstract

Background: The identification of differentially expressed genes and their associated biological processes, molecular function, and cellular components are important for genetic diseases studies because they present potential biomarkers and therapeutic targets. Methods: In this study, we developed an o²S²PARC template representing an interactive pipeline for the gene expression data visualization and ontologies data analysis and visualization. To demonstrate the usefulness of the tool, we performed a case study on a publicly available dataset. Results: The tool enables users to identify the differentially expressed genes (DEGs) and visualize them in a volcano plot format. The ontologies associated with the DEGs are determined and visualized in barplots. Conclusions: The “Expression data visualization” template is publicly available on the o²S²PARC platform.

Published
2022
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5. KnowMore: an automated knowledge discovery tool for the FAIR SPARC datasets [version 1; peer review: 2 approved with reservations]

Author

Ryan Quey, Matthew A. Schiefer, Anmol Kiran, and Bhavesh Patel

Subjects
Software Tool Article, Articles, Data standards, Data Science, Metadata, Natural Language Processing, Knowledge graph, Cloud computing, Python
Abstract

Background: This manuscript provides the methods and outcomes of KnowMore, the Grand Prize winning automated knowledge discovery tool developed by our team during the 2021 NIH SPARC FAIR Data Codeathon. The National Institutes of Health Stimulating Peripheral Activity to Relieve Conditions (NIH SPARC) program generates rich datasets from neuromodulation researches, curated according to the Findable, Accessible, Interoperable, and Reusable (FAIR) SPARC data standards. Currently, the process of simultaneously comparing and analyzing multiple SPARC datasets is tedious because it requires investigating each dataset of interest individually and downloading all of them to conduct cross-analyses. It is crucial to enhance this process to enable rapid discoveries across SPARC datasets. Methods: To fill this need, we created KnowMore, a tool integrated into the SPARC Portal that only requires the user to select their datasets of interest to launch an automated discovery process. KnowMore uses several SPARC resources (Pennsieve, o²S²PARC, SciCrunch, protocols.io, Biolucida), data science methods, and machine learning algorithms in the back end to generate various visualizations in the front end intended to help the user identify potential similarities, differences, and relations across the datasets. These visualizations can lead to a new discovery, new hypothesis, or simply guide the user to the next logical step in their discovery process. Results: The outcome of this project is a SPARC portal-ready code architecture that helps researchers to use SPARC datasets more efficiently and fully leverages their FAIR characteristics. The tool has been built and documented such that more data analysis methods and visualization items could be easily added. Conclusions: The potential for automated discoveries from SPARC datasets is huge given the unique SPARC data ecosystem promoting FAIR data practices, and KnowMore has only demonstrated a small highlight of what could be achieved to speed up discoveries from SPARC datasets.

Published
2021
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6. Emergence of a multidrug-resistant and virulent Streptococcus pneumoniae lineage mediates serotype replacement after PCV13: an international whole-genome sequencing study

Author

Stephanie W Lo, Kate Mellor, Robert Cohen, Alba Redin Alonso, Sophie Belman, Narender Kumar, Paulina A Hawkins, Rebecca A Gladstone, Anne von Gottberg, Balaji Veeraraghavan, K L Ravikumar, Rama Kandasamy, Sir Andrew J Pollard, Samir K Saha, Godfrey Bigogo, Martin Antonio, Brenda Kwambana-Adams, Shaper Mirza, Sadia Shakoor, Imran Nisar, Jennifer E Cornick, Deborah Lehmann, Rebecca L Ford, Betuel Sigauque, Paul Turner, Jennifer Moïsi, Stephen K Obaro, Ron Dagan, Idrissa Diawara, Anna Skoczyńska, Hui Wang, Philip E Carter, Keith P Klugman, Gail Rodgers, Robert F Breiman, Lesley McGee, Stephen D Bentley, Carmen Muñoz-Almagro, Emmanuelle Varon, Abdullah Brooks, Alejandra Corso, Alexander Davydov, Alison Maguire, Anmol Kiran, Benild Moiane, Bernard Beall, Chunjiang Zhao, David Aanensen, Dean Everett, Diego Faccone, Ebenezer Foster-Nyarko, Ebrima Bojang, Ekaterina Egorova, Elena Voropaeva, Eric Sampane-Donkor, Ewa Sadowy, Geetha Nagaraj, Helio Mucavele, Houria Belabbès, Naima Elmdaghri, Jennifer Verani, Jeremy Keenan, John Lees, Jyothish N Nair Thulasee Bhai, Kedibone Ndlangisa, Khalid Zerouali, Leon Bentley, Leonid Titov, Linda De Gouveia, Maaike Alaerts, Margaret Ip, Maria Cristina de Cunto Brandileone, Md Hasanuzzaman, Metka Paragi, Michele Nurse-Lucas, Mignon du Plessis, Mushal Ali, Nicholas Croucher, Nicole Wolter, Noga Givon-Lavi, Nurit Porat, Özgen Köseoglu Eser, Pak-Leung Ho, Patrick Eberechi Akpaka, Paula Gagetti, Peggy-Estelle Tientcheu, Pierra Law, Rachel Benisty, Rafal Mostowy, Roly Malaker, Samanta Cristine Grassi Almeida, Sanjay Doiphode, Shabir Madhi, Shamala Devi Sekaran, Stuart Clarke, Somporn Srifuengfung, Susan Nzenze, Tamara Kastrin, Theresa Ochoa, Waleria Hryniewicz, and Yulia Urban

Subjects
Microbiology (medical), Centros para el Control y la Prevención de Enfermedades de EE.UU, Vaccines, Conjugate, Bill & Melinda Gates Foundation, Serogroup, Microbiology, Pneumococcal Infections, Centres per al Control i la Prevenció de Malalties dels EUA, Streptococcus pneumoniae, Infectious Diseases, US Centers for Disease Control and Prevention, Virology, Humans, Genoma, Phylogeny
Abstract

Background Serotype 24F is one of the emerging pneumococcal serotypes after the introduction of pneumococcal conjugate vaccine (PCV). We aimed to identify lineages driving the increase of serotype 24F in France and place these findings into a global context. Methods Whole-genome sequencing was performed on a collection of serotype 24F pneumococci from asymptomatic colonisation (n=229) and invasive disease (n=190) isolates among individuals younger than 18 years in France, from 2003 to 2018. To provide a global context, we included an additional collection of 24F isolates in the Global Pneumococcal Sequencing (GPS) project database for analysis. A Global Pneumococcal Sequence Cluster (GPSC) and a clonal complex (CC) were assigned to each genome. Phylogenetic, evolutionary, and spatiotemporal analysis were conducted using the same 24F collection and supplemented with a global collection of genomes belonging to the lineage of interest from the GPS project database (n=25 590). Findings Serotype 24F was identified in numerous countries mainly due to the clonal spread of three lineages: GPSC10 (CC230), GPSC16 (CC156), and GPSC206 (CC7701). GPSC10 was the only multidrug-resistant lineage. GPSC10 drove the increase in 24F in France and had high invasive disease potential. The international dataset of GPSC10 (n=888) revealed that this lineage expressed 16 other serotypes, with only six included in 13-valent PCV (PCV13). All serotype 24F isolates were clustered in a single clade within the GPSC10 phylogeny and long-range transmissions were detected from Europe to other continents. Spatiotemporal analysis showed GPSC10-24F took 3–5 years to spread across France and a rapid change of serotype composition from PCV13 serotype 19A to 24F during the introduction of PCV13 was observed in neighbouring country Spain. Interpretation Our work reveals that GPSC10 alone is a challenge for serotype-based vaccine strategy. More systematic investigation to identify lineages like GPSC10 will better inform and improve next-generation preventive strategies against pneumococcal diseases. Funding Bill & Melinda Gates Foundation, Wellcome Sanger Institute, and the US Centers for Disease Control and Prevention.

Published
2022
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7. Defective Monocyte Enzymatic Function and an Inhibitory Immune Phenotype in Human Immunodeficiency Virus-Exposed Uninfected African Infants in the Era of Antiretroviral Therapy

Author

Louise Afran, Kondwani C Jambo, Wilfred Nedi, David J C Miles, Anmol Kiran, Dominic H Banda, Ralph Kamg’ona, Dumizulu Tembo, Annette Pachnio, Eleni Nastouli, Brigit Ferne, Henry C Mwandumba, Paul Moss, David Goldblatt, Sarah Rowland-Jones, Adam Finn, and Robert S Heyderman

Subjects
Infectious Diseases, Phenotype, Pregnancy, Immunoglobulin G, Tetanus Toxoid, Immunology and Allergy, HIV, Humans, Infant, Female, HIV Infections, Monocytes
Abstract

Background Human immunodeficiency virus-exposed uninfected (HEU) infants are a rapidly expanding population in sub-Saharan Africa and are highly susceptible to encapsulated bacterial disease in the first year of life. The mechanism of this increased risk is still poorly understood. We investigated whether human immunodeficiency virus (HIV)-exposure dysregulates HEU immunity, vaccine-antibody production, and human herpes virus amplify this effect. Methods Thirty-four HIV-infected and 44 HIV-uninfected pregnant women were recruited into the birth cohort and observed up to 6 weeks of age; and then a subsequent 43 HIV-infected and 61 HIV-uninfected mother-infant pairs were recruited into a longitudinal infant cohort at either: 5–7 to 14–15; or 14–15 to 18–23 weeks of age. We compared monocyte function, innate and adaptive immune cell phenotype, and vaccine-induced antibody responses between HEU and HIV-unexposed uninfected (HU) infants. Results We demonstrate (1) altered monocyte phagosomal function and B-cell subset homeostasis and (2) lower vaccine-induced anti-Haemophilus influenzae type b (Hib) and anti-tetanus toxoid immunoglobulin G titers in HEU compared with HU infants. Human herpes virus infection was similar between HEU and HU infants. Conclusions In the era of antiretroviral therapy-mediated viral suppression, HIV exposure may dysregulate monocyte and B-cell function, during the vulnerable period of immune maturation. This may contribute to the high rates of invasive bacterial disease and pneumonia in HEU infants.

Published
2021

8. Supplementary_table_S5_xyz47336611a7bb5 – Supplemental material for Genomic Characteristics of Invasive Streptococcus pneumoniae Serotype 1 in New Caledonia Prior to the Introduction of PCV13

Author

Mariem Hanachi, Anmol Kiran, Cornick, Jennifer, Emna Harigua-Souiai, Everett, Dean, Benkahla, Alia, and Souiai, Oussama

Subjects
FOS: Biological sciences, 69999 Biological Sciences not elsewhere classified
Abstract

Supplemental material, Supplementary_table_S5_xyz47336611a7bb5 for Genomic Characteristics of Invasive Streptococcus pneumoniae Serotype 1 in New Caledonia Prior to the Introduction of PCV13 by Mariem Hanachi, Anmol Kiran, Jennifer Cornick, Emna Harigua-Souiai, Dean Everett, Alia Benkahla and Oussama Souiai in Bioinformatics and Biology Insights

Published
2020
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9. H3ABioNet, a sustainable pan-African bioinformatics network for human heredity and health in Africa

Author

Samson Pandam Salifu, Radhika Khetani, Jelili Oyelade, Anmol Kiran, Cornelis Victor Jongeneel, Raphael Zozimus Sangeda, Kais Ghedira, Faisal M. Fadlelmola, Ayton Pierre Meintjes, Jen Cornick, Daniel Masiga, Khalid SADKI, Shakuntala Baichoo, Samar Kamal Kassim, Scott Hazelhurst, Azeddine Ibrahimi, Ozlem Tastan Bishop, Judit Kumuthini, Arox Wadson Kamng'ona, Rehab Ahmed, Nicola J Mulder, Dean Everett, Ahmed Moussa, Julie Makani, Chimusa Emile Rugamika, Jean-Baka Domelevo Entfellner, Phelelani Mpangase, Marion Adebiyi, Mohamed Alibi, Peter Van Heusden, Winston Hide, Victor Osamor, Hugh-George Patterton, Christopher Fields, Benjamin Kumwenda, Itunuoluwa Isewon, Souiai Oussama, Niklas Blomberg, Bruno Mmbando, Benard Kulohoma, Nicki Tiffin, Zahra Mungloo-Dilmohamud, Shaun Aron, Patrick Musicha, Stochastic Studies and Statistics, University of Cape Town, Department of Computer and Information Sciences, Covenant University, Centre National de Transfusion Sanguine, Rabat, Institut Pasteur de Tunis, Réseau International des Instituts Pasteur (RIIP), Noguchi Memorial Institute for Medical Research [Accra, Ghana] (NMIMR), University of Ghana, University of Sciences, Techniques and Technology of Bamako, University of Liverpool, University of Khartoum, Institut National de Recherche Agronomique, Rabat, Botswana Harvard AIDS Institute Partnership, Université Mohammed Premier [Oujda], University of the Witwatersrand [Johannesburg] (WITS), University of Sheffield, Sheffield Institute for Translational Neuroscience, Department of Biotechnology Laboratory (Med-Biotech), Mohammed V University in Rabat, University of Mauritius, University of Illinois at Urbana-Champaign [Urbana], University of Illinois System, Université Grenoble Alpes - UFR Médecine (UGA UFRM), Université Grenoble Alpes [2016-2019] (UGA [2016-2019]), Medical Biochemistry and Molecular Biology Department, Faculty of Medicine, Ain Shams University, Cairo, Egypt, Uganda Virus Research Institute, Entebbe, Uganda, Centre for Proteomic and Genomic Research, Cape Town, South Africa, University of Dar es Salaam, Dar es Salaam, Tanzania, Muhimbili University of Health and Allied Sciences, Zagazig University, International Centre of Insect Physiology and Ecology, Nairobi, Kenya, Institut de Chimie de Strasbourg, Université de Strasbourg (UNISTRA)-Institut de Chimie du CNRS (INC)-Centre National de la Recherche Scientifique (CNRS), National Biotechnology Development Agency, Abuja, Nigeria, Centre de Recherche Médicale et Sanitaire (Niamey, Niger) (CERMES), Kumasi Centre for Collaborative Research in Tropical Medicine (KCCR), Department of Biomedical Sciences, University of Cape Town, Faculty of Health Sciences, University of the Free State [South Africa], Institut Pasteur du Maroc, Faculty of Sciences of Rabat, University Mohammed V of Rabat, Rabat, Morocco, Institut National d'Hygiène, Rabat, Morocco, Rhodes University, Grahamstown, University of the Western Cape, Cape Town, Management and Development for Health, Dar es Salaam, Tanzania, and Musicha, P

Subjects
Resource, 0301 basic medicine, Genetics, Medical, Genomic research, [SDV]Life Sciences [q-bio], Black People, Genomics, Health Promotion, Biology, MESH: Africa, SUSCEPTIBILITY, ANCESTRY, Bioinformatics, TUBERCULOSIS, DISEASE, 03 medical and health sciences, Human health, Computer Systems, Genetics, Humans, MESH: Genetics, Medical, MESH: Genetic Variation, GENOME-WIDE ASSOCIATION, Human heredity, Genetics (clinical), 2. Zero hunger, MESH: Humans, Pan african, MESH: Genomics, 1. No poverty, MESH: Computer Systems, Computational Biology, Genetic Variation, Popularity, Human genetics, 3. Good health, 030104 developmental biology, Health promotion, Africa, MESH: Health Promotion, MESH: African Continental Ancestry Group, MESH: Computational Biology
Abstract

International audience; The application of genomics technologies to medicine and biomedical research is increasing in popularity, made possible by new high-throughput genotyping and sequencing technologies and improved data analysis capabilities. Some of the greatest genetic diversity among humans, animals, plants, and microbiota occurs in Africa, yet genomic research outputs from the continent are limited. The Human Heredity and Health in Africa (H3Africa) initiative was established to drive the development of genomic research for human health in Africa, and through recognition of the critical role of bioinformatics in this process, spurred the establishment of H3ABioNet, a pan-African bioinformatics network for H3Africa. The limitations in bioinformatics capacity on the continent have been a major contributory factor to the lack of notable outputs in high-throughput biology research. Although pockets of high-quality bioinformatics teams have existed previously, the majority of research institutions lack experienced faculty who can train and supervise bioinformatics students. H3ABioNet aims to address this dire need, specifically in the area of human genetics and genomics, but knock-on effects are ensuring this extends to other areas of bioinformatics. Here, we describe the emergence of genomics research and the development of bioinformatics in Africa through H3ABioNet.

Published
2016
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10. Additional file 8: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Summary of the genes found in the genetic recombination regions in clade SC2-WA. Genes present in the regions with recombination events in each clade are summarised. (DOCX 124Â kb)

Published
2016
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11. Additional file 13: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Distribution of the accessory genes and antibiotic resistance conferring elements in the ST217 isolates. a) Maximum likelihood phylogeny of the isolates rooted using isolates from ST615 as an outgroup (not shown). b) Number of shared accessory open reading frames (ORFs) or genes between pairs of isolates in the phylogeny on the left side and at the top. c) Colour strips showing the continent and country of origin of the isolates and their SCs. d) A heatmap showing the number of shared accessory genes between each pair of isolates in the phylogeny (panel [a] and [e]). (PDF 4076Â kb)

Published
2016
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12. Additional file 6: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Recombination events identified in the South East African clade (SC3-SEA). (a) Maximum likelihood phylogeny showing genetic relationship of the isolates in the SC. Color strips labeled (b) and (c) shows country and continent of origin of the isolates respectively. (d) Annotations in the reference serotype 1 genome. (e) Horizontal tracks from the phylogenetic tips represent each genome. The coloured blocks shows locations of the recombination events in the chromosome. Red blocks show shared recombination events identified in at least two isolate while the blue blocks show strain specific (unique) recombination events. (PDF 1077Â kb)

Published
2016
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13. Additional file 7: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Summary of the genes found in the genetic recombination regions in clade SC1-SA. Genes present in the regions with recombination events in each clade are summarised. (DOCX 85Â kb)

Published
2016
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14. Additional file 5: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Recombination events identified in the West African clade (SC2-WA). (a) Maximum likelihood phylogeny showing genetic relationship of the isolates in the SC. Color strips labeled (b) and (c) shows country and continent of origin of the isolates respectively. (d) Annotations in the reference serotype 1 genome. (e) Horizontal tracks from the phylogenetic tips represent each genome. The coloured blocks shows locations of the recombination events in the chromosome. Red blocks show shared recombination events identified in at least two isolate while the blue blocks show strain specific (unique) recombination events. (PDF 1452Â kb)

Published
2016
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15. Additional file 3: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Estimated evolutionary parameters for all the clades. Each parameter estimate was calculated using MEGA. (DOC 80Â kb)

Published
2016
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16. Additional file 9: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Summary of the genes found in the genetic recombination regions in clade SC3-SEA. Genes present in the regions with recombination events in each clade are summarised. (DOCX 133Â kb)

Published
2016
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17. Additional file 2: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Clade specific phylogenies showing country of origin of the ST217 isolates. Maximum likelihood phylogenetic trees for clade (a) SC1-SA, (b) SC2-WA and (c) SC3-SEA. (PDF 292Â kb)

Published
2016
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18. Additional file 4: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Abstract

Recombination events identified in the South African clade (SC1-SA). (a) Maximum likelihood phylogeny showing genetic relationship of the isolates in the SC. Color strips labeled (b) and (c) shows country and continent of origin of the isolates respectively. (d) Annotations in the reference serotype 1 genome. (e) Horizontal tracks from the phylogenetic tips represent each genome. The coloured blocks shows locations of the recombination events in the chromosome. Red blocks show shared recombination events identified in at least two isolate while the blue blocks show strain specific (unique) recombination events. (PDF 641Â kb)

Published
2016
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19. Additional file 1: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Characteristics and assembly statistics for the ST217 study isolates. (DOCX 166Â kb)

20. Additional file 1: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Characteristics and assembly statistics for the ST217 study isolates. (DOCX 166Â kb)

21. Additional file 11: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Distribution of genes associated with virulence and colonisation in the ST217 in serotype 1 isolates. Presence of the genes was screened in all the isolates using BLAST as described in the methods section. (PDF 1702Â kb)

22. Additional file 12: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Deletion of the immunoglobulin A (iga) protease gene in the ST217 isolates. Genomic comparison of one of the serotype 1 isolates (ERS194295) that lacked the iga gene against the TIGR4 reference S. pneumoniae genome with an intact iga gene in its chromosome to determine the location and structure of the genomic deletion in the ST217 isolates. Sequence comparison was performed by BLASTN and visualised with Artemis Comparison Tool (ACT). (PDF 528Â kb)

23. Additional file 10: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Intragenic number of observed and expected numbers of SNPs in the ST217 isolates. All the genes in the ST217 isolates, sizes, observed (OSNP) and expected (ESNP) number of SNPs, ratio OSNP to ESNP and products of each gene are summarised. (DOCX 315Â kb)

24. Additional file 12: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Deletion of the immunoglobulin A (iga) protease gene in the ST217 isolates. Genomic comparison of one of the serotype 1 isolates (ERS194295) that lacked the iga gene against the TIGR4 reference S. pneumoniae genome with an intact iga gene in its chromosome to determine the location and structure of the genomic deletion in the ST217 isolates. Sequence comparison was performed by BLASTN and visualised with Artemis Comparison Tool (ACT). (PDF 528Â kb)

25. Additional file 10: of Understanding pneumococcal serotype 1 biology through population genomic analysis

Author

Chrispin Chaguza, Cornick, Jennifer, Harris, Simon, Andam, Cheryl, Bricio-Moreno, Laura, Yang, Marie, Feyruz Yalcin, Sani Ousmane, Shanil Govindpersad, Madikay Senghore, Chinelo Ebruke, Plessis, Mignon Du, Anmol Kiran, Pluschke, Gerd, Betuel Sigauque, McGee, Lesley, Klugman, Keith, Turner, Paul, Corander, Jukka, Parkhill, Julian, Jean-Marc Collard, Antonio, Martin, Gottberg, Anne Von, Heyderman, Robert, French, Neil, Kadioglu, Aras, Hanage, William, Everett, Dean, and Bentley, Stephen

Subjects
3. Good health
Abstract

Intragenic number of observed and expected numbers of SNPs in the ST217 isolates. All the genes in the ST217 isolates, sizes, observed (OSNP) and expected (ESNP) number of SNPs, ratio OSNP to ESNP and products of each gene are summarised. (DOCX 315Â kb)

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