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Jutzeler KS, Le Clec'h W, Chevalier FD, Anderson TJC. Contribution of parasite and host genotype to immunopathology of schistosome infections. Parasit Vectors 2024; 17:203. [PMID: 38711063 PMCID: PMC11073996 DOI: 10.1186/s13071-024-06286-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Accepted: 04/18/2024] [Indexed: 05/08/2024] Open
Abstract
BACKGROUND The role of pathogen genotype in determining disease severity and immunopathology has been studied intensively in microbial pathogens including bacteria, fungi, protozoa and viruses but is poorly understood in parasitic helminths. The medically important blood fluke Schistosoma mansoni is an excellent model system to study the impact of helminth genetic variation on immunopathology. Our laboratory has demonstrated that laboratory schistosome populations differ in sporocyst growth and cercarial production in the intermediate snail host and worm establishment and fecundity in the vertebrate host. Here, we (i) investigate the hypothesis that schistosome genotype plays a significant role in immunopathology and related parasite life history traits in the vertebrate mouse host and (ii) quantify the relative impact of parasite and host genetics on infection outcomes. METHODS We infected BALB/c and C57BL/6 mice with four different laboratory schistosome populations from Africa and the Americas. We quantified disease progression in the vertebrate host by measuring body weight and complete blood count (CBC) with differential over a 12-week infection period. On sacrifice, we assessed parasitological (egg and worm counts, fecundity), immunopathological (organ measurements and histopathology) and immunological (CBC with differential and cytokine profiles) characteristics to determine the impact of parasite and host genetics. RESULTS We found significant variation between parasite populations in worm numbers, fecundity, liver and intestine egg counts, liver and spleen weight, and fibrotic area but not in granuloma size. Variation in organ weight was explained by egg burden and intrinsic parasite factors independent of egg burden. We found significant variation between infected mouse lines in cytokine levels (IFN-γ, TNF-α), eosinophils, lymphocytes and monocyte counts. CONCLUSIONS This study showed that both parasite and host genotype impact the outcome of infection. While host genotype explains most of the variation in immunological traits, parasite genotype explains most of the variation in parasitological traits, and both host and parasite genotypes impact immunopathology outcomes.
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Affiliation(s)
- Kathrin S Jutzeler
- Host Parasite Interaction Program, Texas Biomedical Research Institute, P.O. Box 760549, San Antonio, TX, 78245, USA.
- UT Health, Microbiology, Immunology & Molecular Genetics, San Antonio, TX, 78229, USA.
| | - Winka Le Clec'h
- Host Parasite Interaction Program, Texas Biomedical Research Institute, P.O. Box 760549, San Antonio, TX, 78245, USA
| | - Frédéric D Chevalier
- Host Parasite Interaction Program, Texas Biomedical Research Institute, P.O. Box 760549, San Antonio, TX, 78245, USA
| | - Timothy J C Anderson
- Disease Intervention and Prevention Program, Texas Biomedical Research Institute, P.O. Box 760549, San Antonio, TX, 78245, USA.
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Okoh OS, Nii-Trebi NI, Jakkari A, Olaniran TT, Senbadejo TY, Kafintu-kwashie AA, Dairo EO, Ganiyu TO, Akaninyene IE, Ezediuno LO, Adeosun IJ, Ockiya MA, Jimah EM, Spiro DJ, Oladipo EK, Trovão NS. Epidemiology and genetic diversity of SARS-CoV-2 lineages circulating in Africa. iScience 2022; 25:103880. [PMID: 35156006 PMCID: PMC8817759 DOI: 10.1016/j.isci.2022.103880] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2021] [Revised: 11/29/2021] [Accepted: 02/03/2022] [Indexed: 12/15/2022] Open
Abstract
There is a dearth of information on COVID-19 disease dynamics in Africa. To fill this gap, we investigated the epidemiology and genetic diversity of SARS-CoV-2 lineages circulating in the continent. We retrieved 5229 complete genomes collected in 33 African countries from the GISAID database. We investigated the circulating diversity, reconstructed the viral evolutionary divergence and history, and studied the case and death trends in the continent. Almost a fifth (144/782, 18.4%) of Pango lineages found worldwide circulated in Africa, with five different lineages dominating over time. Phylogenetic analysis revealed that African viruses cluster more closely with those from Europe. We also identified two motifs that could function as integrin-binding sites and N-glycosylation domains. These results shed light on the epidemiological and evolutionary dynamics of the circulating viral diversity in Africa. They also emphasize the need to expand surveillance efforts in Africa to help inform and implement better public health measures.
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Affiliation(s)
| | - Nicholas Israel Nii-Trebi
- Department of Medical Laboratory Sciences, School of Biomedical and Allied Health Sciences, University of Ghana, Accra, Ghana
| | - Abdulrokeeb Jakkari
- Department of Microbiology, Faculty of Science, Lagos State University, Ojo, Lagos, Nigeria
| | - Tosin Titus Olaniran
- Department of Pure and Applied Biology (Microbiology Unit), Ladoke Akintola University of Technology, Ogbomoso, Nigeria
- Helix Biogen Institute, Ogbomoso, Nigeria
| | - Tosin Yetunde Senbadejo
- Department of Biological Sciences, College of Natural and Applied Sciences, Fountain University, Osogbo, Nigeria
| | - Anna Aba Kafintu-kwashie
- Department of Medical Microbiology, Clinical Virology Unit, University of Ghana Medical School, Accra, Ghana
| | - Emmanuel Oluwatobi Dairo
- Helix Biogen Institute, Ogbomoso, Nigeria
- Department of Virology, College of Medicine, University of Ibadan, Ibadan, Nigeria
| | - Tajudeen Oladunni Ganiyu
- Department of Biological Sciences, College of Natural and Applied Sciences, Fountain University, Osogbo, Nigeria
| | - Ifiokakaninyene Ekpo Akaninyene
- Department of Pure and Applied Biology (Microbiology Unit), Ladoke Akintola University of Technology, Ogbomoso, Nigeria
- Helix Biogen Institute, Ogbomoso, Nigeria
| | - Louis Odinakaose Ezediuno
- Department of Microbiology, Faculty of Life Sciences, University of Ilorin,1515 P.M.B, Ilorin, Nigeria
| | - Idowu Jesulayomi Adeosun
- Department of Microbiology, Laboratory of Molecular Biology, Immunology and Bioinformatics, Adeleke University, Ede, Osun, Nigeria
- Division of Microbiology, Department of Biochemistry, Genetics and Microbiology, University of Pretoria, Private Bag X20, Hatfield Pretoria 0028, South Africa
| | - Michael Asebake Ockiya
- Department of Animal Science, Niger Delta University, Wilberforce Island, Bayelsa, Nigeria
| | - Esther Moradeyo Jimah
- Helix Biogen Institute, Ogbomoso, Nigeria
- Department of Medical Microbiology and Parasitology, University of Ilorin 1515, P.M.B, Ilorin, Nigeria
| | - David J. Spiro
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
| | - Elijah Kolawole Oladipo
- Helix Biogen Institute, Ogbomoso, Nigeria
- Department of Microbiology, Laboratory of Molecular Biology, Immunology and Bioinformatics, Adeleke University, Ede, Osun, Nigeria
| | - Nídia S. Trovão
- Fogarty International Center, National Institutes of Health, Bethesda, MD, USA
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Yin R, Luo Z, Kwoh CK. Exploring the Lethality of Human-Adapted Coronavirus Through Alignment-Free Machine Learning Approaches Using Genomic Sequences. Curr Genomics 2021; 22:583-595. [PMID: 35386190 PMCID: PMC8922323 DOI: 10.2174/1389202923666211221110857] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2021] [Revised: 12/02/2021] [Accepted: 12/14/2021] [Indexed: 11/29/2022] Open
Abstract
Background A newly emerging novel coronavirus appeared and rapidly spread worldwide and World Health Organization declared a pandemic on March 11, 2020. The roles and characteristics of coronavirus have captured much attention due to its power of causing a wide variety of infectious diseases, from mild to severe, on humans. The detection of the lethality of human coronavirus is key to estimate the viral toxicity and provide perspectives for treatment. Methods We developed an alignment-free framework that utilizes machine learning approaches for an ultra-fast and highly accurate prediction of the lethality of human-adapted coronavirus using genomic sequences. We performed extensive experiments through six different feature transformation and machine learning algorithms combining digital signal processing to identify the lethality of possible future novel coronaviruses using existing strains. Results The results tested on SARS-CoV, MERS-CoV and SARS-CoV-2 datasets show an average 96.7% prediction accuracy. We also provide preliminary analysis validating the effectiveness of our models through other human coronaviruses. Our framework achieves high levels of prediction performance that is alignment-free and based on RNA sequences alone without genome annotations and specialized biological knowledge. Conclusion The results demonstrate that, for any novel human coronavirus strains, this study can offer a reliable real-time estimation for its viral lethality.
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Affiliation(s)
- Rui Yin
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore
- Department of Biomedical Informatics, Harvard University, Boston, MA 02138, USA
| | - Zihan Luo
- School of Electronic Information and Communications, Huazhong University of Science and Technology, Wuhan, 430074, China
| | - Chee Keong Kwoh
- School of Computer Science and Engineering, Nanyang Technological University, 50 Nanyang Avenue, 639798, Singapore
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