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Moraes DCA, Cezar GA, Magalhães ES, Nicolino RR, Rupasinghe K, Chandra S, Silva GS, Almeida MN, Crim B, Burrough ER, Gauger PC, Madson D, Thomas J, Zeller MA, Main R, Thurn M, Lages P, Corzo CA, Sturos M, Naikare H, McGaughey R, Matias Ferreyra F, Retallick J, Gebhardt J, McReynolds S, Greseth J, Kersey D, Clement T, Pillatzki A, Christopher-Hennings J, Thompson BS, Prarat M, Summers D, Bowen C, Boyle J, Hendrix K, Lyons J, Werling K, Arruda AG, Schwartz M, Yeske P, Murray D, Mason B, Schneider P, Copeland S, Dufresne L, Boykin D, Fruge C, Hollis W, Robbins RC, Petznick T, Kuecker K, Glowzenski L, Niederwerder M, Linhares DCL, Trevisan G. Macroepidemiological trends of Influenza A virus detection through reverse transcription real-time polymerase chain reaction (RT-rtPCR) in porcine samples in the United States over the last 20 years. Front Vet Sci 2025; 12:1572237. [PMID: 40343366 PMCID: PMC12061026 DOI: 10.3389/fvets.2025.1572237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/06/2025] [Accepted: 04/04/2025] [Indexed: 05/11/2025] Open
Abstract
Influenza A virus (IAV) in swine is a major respiratory pathogen with global significance. This study aimed to characterize the macroepidemiological patterns of IAV detection using reverse transcription real-time polymerase chain reaction (RT-rtPCR) assays, including subtype identification, in samples submitted between January 2004 and December 2024 to veterinary diagnostic laboratories (VDLs) participating in the Swine Disease Reporting System (SDRS). A secondary objective was establishing an IAV monitoring capability to inform stakeholders of weekly changes in IAV detection patterns. Of the 372,659 samples submitted, 31% tested positive for IAV RNA via RT-rtPCR. The most frequent sample types were oral fluids (44.1%) and lung tissue (38.7%). Submissions from the wean-to-market category had a higher positivity rate (34.4%) than those from the adult/sow farm category (26.9%). IAV detection followed a seasonal pattern, with peaks in spring and fall and lower positivity rates in summer. Of the total of 118,490 samples tested for IAV subtyping using RT-rtPCR, the most frequently detected subtypes were H1N1 (33.1%), H3N2 (25.5%), H1N2 (24.3%), H3N1 (0.2%), mixed subtypes (5.4%), and partial subtype detection (11.5%). Mixed IAV subtypes were detected in individual samples-including lung tissue, nasal swabs, and bronchoalveolar lavage-indicating co-infection with two or more IAV strains. For IAV forecasting, a combined model using dynamic regression and a neural network outperformed individual models in 2023, achieving the lowest root mean square error (RMSE) and an improved overall skill score. This study highlights the importance of using laboratory submission data for IAV surveillance and macroepidemiological analysis. The findings provide valuable insights into IAV dynamics and highlight the need for standardized monitoring systems in VDLs to enhance understanding of IAV in swine populations across the United States.
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Affiliation(s)
- Daniel C. A. Moraes
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Guilherme A. Cezar
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Edison S. Magalhães
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Rafael R. Nicolino
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Kinath Rupasinghe
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Srijita Chandra
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Gustavo S. Silva
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Marcelo N. Almeida
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Bret Crim
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Eric R. Burrough
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Phillip C. Gauger
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Darin Madson
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Joseph Thomas
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Michael A. Zeller
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Rodger Main
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Mary Thurn
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Paulo Lages
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Cezar A. Corzo
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Mattew Sturos
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Hemant Naikare
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
| | - Rob McGaughey
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
| | - Franco Matias Ferreyra
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
| | - Jamie Retallick
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
| | - Jordan Gebhardt
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
| | - Sara McReynolds
- Kansas State Veterinary Diagnostic Laboratory, Kansas State University, Manhattan, KS, United States
| | - Jon Greseth
- Veterinary and Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
| | - Darren Kersey
- Veterinary and Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
| | - Travis Clement
- Veterinary and Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
| | - Angela Pillatzki
- Veterinary and Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
| | - Jane Christopher-Hennings
- Veterinary and Biomedical Sciences Department, South Dakota State University, Brookings, SD, United States
| | | | - Melanie Prarat
- Ohio Animal Disease and Diagnostic Laboratory, Reynoldsburg, OH, United States
| | - Dennis Summers
- Ohio Animal Disease and Diagnostic Laboratory, Reynoldsburg, OH, United States
| | - Craig Bowen
- College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - Joseph Boyle
- College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - Kenitra Hendrix
- College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - James Lyons
- College of Veterinary Medicine, Purdue University, West Lafayette, IN, United States
| | - Kelli Werling
- Indiana State Board of Animal Health, Indianapolis, IN, United States
| | - Andreia G. Arruda
- Department of Veterinary Preventive Medicine, College of Veterinary Medicine, The Ohio State University, Columbus, OH, United States
| | - Mark Schwartz
- Veterinary Population Medicine, University of Minnesota, Saint Paul, MN, United States
- Schwartz Farms Inc., Sleepy Eye, MN, United States
| | - Paul Yeske
- Swine Vet Center, St. Peter, MN, United States
| | | | - Brigitte Mason
- Country View Family Farms, Middletown, PA, United States
| | - Peter Schneider
- Innovative Agriculture Solutions, LLC, Waterloo, IA, United States
| | | | | | | | | | - William Hollis
- Carthage Veterinary Service LTD, Carthage, IL, United States
| | | | | | | | | | | | - Daniel C. L. Linhares
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
| | - Giovani Trevisan
- Veterinary Diagnostic and Production Animal Medicine, Iowa State University, Ames, IA, United States
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AbuBakar U, Amrani L, Kamarulzaman FA, Karsani SA, Hassandarvish P, Khairat JE. Avian Influenza Virus Tropism in Humans. Viruses 2023; 15:833. [PMID: 37112812 PMCID: PMC10142937 DOI: 10.3390/v15040833] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2023] [Revised: 03/12/2023] [Accepted: 03/17/2023] [Indexed: 03/29/2023] Open
Abstract
An influenza pandemic happens when a novel influenza A virus is able to infect and transmit efficiently to a new, distinct host species. Although the exact timing of pandemics is uncertain, it is known that both viral and host factors play a role in their emergence. Species-specific interactions between the virus and the host cell determine the virus tropism, including binding and entering cells, replicating the viral RNA genome within the host cell nucleus, assembling, maturing and releasing the virus to neighboring cells, tissues or organs before transmitting it between individuals. The influenza A virus has a vast and antigenically varied reservoir. In wild aquatic birds, the infection is typically asymptomatic. Avian influenza virus (AIV) can cross into new species, and occasionally it can acquire the ability to transmit from human to human. A pandemic might occur if a new influenza virus acquires enough adaptive mutations to maintain transmission between people. This review highlights the key determinants AIV must achieve to initiate a human pandemic and describes how AIV mutates to establish tropism and stable human adaptation. Understanding the tropism of AIV may be crucial in preventing virus transmission in humans and may help the design of vaccines, antivirals and therapeutic agents against the virus.
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Affiliation(s)
- Umarqayum AbuBakar
- Institute of Biological Sciences (ISB), Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Lina Amrani
- Institute of Biological Sciences (ISB), Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Farah Ayuni Kamarulzaman
- Institute of Biological Sciences (ISB), Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Saiful Anuar Karsani
- Institute of Biological Sciences (ISB), Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Pouya Hassandarvish
- Tropical Infectious Diseases Research and Education Center, Universiti Malaya, Kuala Lumpur 50603, Malaysia
| | - Jasmine Elanie Khairat
- Institute of Biological Sciences (ISB), Faculty of Science, Universiti Malaya, Kuala Lumpur 50603, Malaysia
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Li X, Zhang L, Liu Y, Ma L, Zhang N, Xia C. Structures of the MHC-I molecule BF2*1501 disclose the preferred presentation of an H5N1 virus-derived epitope. J Biol Chem 2020; 295:5292-5306. [PMID: 32152225 PMCID: PMC7170506 DOI: 10.1074/jbc.ra120.012713] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/28/2020] [Revised: 03/06/2020] [Indexed: 01/05/2023] Open
Abstract
Lethal infections by strains of the highly-pathogenic avian influenza virus (HPAIV) H5N1 pose serious threats to both the poultry industry and public health worldwide. A lack of confirmed HPAIV epitopes recognized by cytotoxic T lymphocytes (CTLs) has hindered the utilization of CD8+ T-cell-mediated immunity and has precluded the development of effectively diversified epitope-based vaccination approaches. In particular, an HPAIV H5N1 CTL-recognized epitope based on the peptide MHC-I-β2m (pMHC-I) complex has not yet been designed. Here, screening a collection of selected peptides of several HPAIV strains against a specific pathogen-free pMHC-I (pBF2*1501), we identified a highly-conserved HPAIV H5N1 CTL epitope, named HPAIV-PA123-130 We determined the structure of the BF2*1501-PA123-130 complex at 2.1 Å resolution to elucidate the molecular mechanisms of a preferential presentation of the highly-conserved PA123-130 epitope in the chicken B15 lineage. Conformational characteristics of the PA123-130 epitope with a protruding Tyr-7 residue indicated that this epitope has great potential to be recognized by specific TCRs. Moreover, significantly increased numbers of CD8+ T cells specific for the HPAIV-PA123-130 epitope in peptide-immunized chickens indicated that a repertoire of CD8+ T cells can specifically respond to this epitope. We anticipate that the identification and structural characterization of the PA123-130 epitope reported here could enable further studies of CTL immunity against HPAIV H5N1. Such studies may aid in the development of vaccine development strategies using well-conserved internal viral antigens in chickens.
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Affiliation(s)
- Xiaoying Li
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China; School of Basic Medical Sciences, Xinxiang Medical University, Xinxiang 453003, People's Republic of China
| | - Lijie Zhang
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China
| | - Yanjie Liu
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China; Key Laboratory for Insect-Pollinator Biology of the Ministry of Agriculture, Institute of Apiculture, Chinese Academy of Agricultural Sciences, Beijing 100093, People's Republic of China
| | - Lizhen Ma
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China
| | - Nianzhi Zhang
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China
| | - Chun Xia
- Department of Microbiology and Immunology, College of Veterinary Medicine, China Agricultural University, Beijing 100094, People's Republic of China; Key Laboratory of Animal Epidemiology of the Ministry of Agriculture, China Agricultural University, Beijing 100094, People's Republic of China.
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Elhakim M, Hafiz Rasooly M, Fahim M, Sheikh Ali S, Haddad N, Cherkaoui I, Hjaija D, Nadeem S, Assiri A, Aljifri A, Elkholy A, Barakat A, Shrestha B, Abubakar A, Malik SMMR. Epidemiology of severe cases of influenza and other acute respiratory infections in the Eastern Mediterranean Region, July 2016 to June 2018. J Infect Public Health 2020; 13:423-429. [PMID: 31281105 PMCID: PMC7102678 DOI: 10.1016/j.jiph.2019.06.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2018] [Revised: 06/11/2019] [Accepted: 06/12/2019] [Indexed: 11/22/2022] Open
Abstract
BACKGROUND Influenza surveillance systems in the Eastern Mediterranean Region have been strengthened in the past few years and 16 of the 19 countries in the Region with functional influenza surveillance systems report their influenza data to the EMFLU Network. This study aimed to investigate the epidemiology of circulating influenza viruses, causing SARI, and reported to the EMFLU during July 2016 to June 2018. METHODS Data included in this study were collected by 15 countries of the Region from 110 SARI sentinel surveillance sites over two influenza seasons. RESULTS A total of 40,917 cases of SARI were included in the study. Most cases [20,551 (50.2%)] were less than 5years of age. Influenza virus was detected in 3995 patients, 2849 (11.8%) were influenza A and 1146 (4.8%) were influenza B. Influenza A(H1N1)pdm09 was the predominant circulating subtype with 1666 cases (58.5%). Other than influenza, respiratory syncytial virus was the most common respiratory infection circulating, with 277 cases (35.9%). CONCLUSION Influenza viruses cause a high number of severe respiratory infections in EMR. It is crucial for the countries to continue improving their influenza surveillance capacity in order detect any unusual influenza activity or new strain that may cause a pandemic.
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Affiliation(s)
- Mohamed Elhakim
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt.
| | - Mohammad Hafiz Rasooly
- Surveillance/National Influenza Coordinator, EHIS DG, Surveillance Department, Ministry of Public Health, Kabul, Afghanistan
| | - Manal Fahim
- Department of Epidemiology and Surveillance, Preventive Sector, Ministry of Health and Population, Cairo, Egypt
| | - Sami Sheikh Ali
- Data Analysis Division, Influenza Surveillance Focal Point, Communicable Diseases Directorate, Ministry of Health, Amman, Jordan
| | - Nadine Haddad
- Epidemiological Surveillance Program, Ministry of Public Health, Beirut, Lebanon
| | - Imad Cherkaoui
- Influenza Surveillance Focal Point, Directorate of Epidemiology, Ministry of Health, Rabat, Morocco
| | - Diaa Hjaija
- Palestinian Ministry of Health, Ramallah, occupied Palestinian territory
| | - Shazia Nadeem
- Public Health Department, Ministry of Public Health, Doha, Qatar
| | | | - Alanoud Aljifri
- Influenza Surveillance Focal Point, Adult Infectious Disease Consultant, Ministry of Health, Riyadh, Saudi Arabia
| | - Amgad Elkholy
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt
| | - Amal Barakat
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt
| | - Bhagawan Shrestha
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt
| | - Abdinasir Abubakar
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt
| | - Sk Md Mamunur R Malik
- Infectious Hazard Management Unit, Department of Health Emergencies, World Health Organization, Regional Office for the Eastern Mediterranean, Cairo, Egypt
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