1
|
Sessions Z, Bobrowski T, Martin HJ, Beasley JMT, Kothari A, Phares T, Li M, Alves VM, Scotti MT, Moorman NJ, Baric R, Tropsha A, Muratov EN. Praemonitus praemunitus: can we forecast and prepare for future viral disease outbreaks? FEMS Microbiol Rev 2023; 47:fuad048. [PMID: 37596064 PMCID: PMC10532129 DOI: 10.1093/femsre/fuad048] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2023] [Revised: 07/04/2023] [Accepted: 08/17/2023] [Indexed: 08/20/2023] Open
Abstract
Understanding the origins of past and present viral epidemics is critical in preparing for future outbreaks. Many viruses, including SARS-CoV-2, have led to significant consequences not only due to their virulence, but also because we were unprepared for their emergence. We need to learn from large amounts of data accumulated from well-studied, past pandemics and employ modern informatics and therapeutic development technologies to forecast future pandemics and help minimize their potential impacts. While acknowledging the complexity and difficulties associated with establishing reliable outbreak predictions, herein we provide a perspective on the regions of the world that are most likely to be impacted by future outbreaks. We specifically focus on viruses with epidemic potential, namely SARS-CoV-2, MERS-CoV, DENV, ZIKV, MAYV, LASV, noroviruses, influenza, Nipah virus, hantaviruses, Oropouche virus, MARV, and Ebola virus, which all require attention from both the public and scientific community to avoid societal catastrophes like COVID-19. Based on our literature review, data analysis, and outbreak simulations, we posit that these future viral epidemics are unavoidable, but that their societal impacts can be minimized by strategic investment into basic virology research, epidemiological studies of neglected viral diseases, and antiviral drug discovery.
Collapse
Affiliation(s)
- Zoe Sessions
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Tesia Bobrowski
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Holli-Joi Martin
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Jon-Michael T Beasley
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Aneri Kothari
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Trevor Phares
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
- School of Chemistry, University of Louisville, 2320 S Brook St, Louisville, KY 40208, United States
| | - Michael Li
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Vinicius M Alves
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Marcus T Scotti
- Department of Pharmaceutical Sciences, Federal University of Paraiba, Campus I Lot. Cidade Universitaria, PB, 58051-900, Brazil
| | - Nathaniel J Moorman
- Department of Microbiology and Immunology, University of North Carolina, 116 Manning Drive, Chapel Hill, NC 27599, United States
| | - Ralph Baric
- Department of Epidemiology, University of North Carolina, 401 Pittsboro St, Chapel Hill, NC 27599, United States
| | - Alexander Tropsha
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| | - Eugene N Muratov
- Laboratory for Molecular Modeling, Division of Chemical Biology and Medicinal Chemistry, UNC Eshelman School of Pharmacy, University of North Carolina, 301 Pharmacy Ln, Chapel Hill, NC 27599, United States
| |
Collapse
|
2
|
Suzuki Y. Predicting Dominant Genotypes in Norovirus Seasons in Japan. Life (Basel) 2023; 13:1634. [PMID: 37629491 PMCID: PMC10455559 DOI: 10.3390/life13081634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 07/19/2023] [Accepted: 07/25/2023] [Indexed: 08/27/2023] Open
Abstract
Human noroviruses are an etiological agent of acute gastroenteritis. Since multiple genotypes co-circulate every season changing their proportions, it may be desirable to develop multivalent vaccines by formulating genotype composition of seed strains to match that of dominant strains. Here, performances of the models for predicting dominant genotypes, defined as the two most prevalent genotypes, were evaluated using observed genotype frequencies in Japan and genomic sequences for GI and GII strains. In the null model, genotype proportions in the target season were predicted to be the same as those in the immediately preceding season. In the fitness model, genotype proportions were predicted taking into account the acquisition of novel P-types through recombination and genotype-specific proliferation efficiency, as well as herd immunity to VP1 assuming the duration (d) of 0-10 years. The null model performed better in GII than in GI, apparently because dominant genotypes were more stable in the former than in the latter. Performance of the fitness model was similar to that of the null model irrespective of the assumed value of d. However, performance was improved when dominant genotypes were predicted as the union of those predicted with d = 0-10, suggesting that d may vary among individuals.
Collapse
Affiliation(s)
- Yoshiyuki Suzuki
- Graduate School of Science, Nagoya City University, 1 Yamanohata, Nagoya-shi, Aichi-ken 467-8501, Japan
| |
Collapse
|
5
|
Wang Y, Yue H, Tang C. Prevalence and complete genome of bovine norovirus with novel VP1 genotype in calves in China. Sci Rep 2019; 9:12023. [PMID: 31427703 PMCID: PMC6700072 DOI: 10.1038/s41598-019-48569-4] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/01/2019] [Accepted: 08/07/2019] [Indexed: 12/21/2022] Open
Abstract
Bovine norovirus (BNoV) is a diarrhea-causing pathogen of calves. In this study, 211 diarrheic fecal samples were collected from 25 farms across six provinces in China, between November 2017 and September 2018. 20.4% of the samples were detected as BNoV-positive by RT-PCR. Phylogenetic analyses based on RdRp, VP1, and VP2 fragments revealed these BNoV strains had unique evolutionary characteristics. The complete genome of strain Bo/BET-17/18/CH was successfully sequenced. It was 7321 nucleotides (nt) in length, shared 79.4-80.9% nt identity with all five BNoV genomes, clustered on a separate branch of the phylogenetic tree, suggesting that strain Bo/BET-17/18/CH could represent a novel BNoV strain. Two interesting characteristics were found in the genome: (i) the VP1 sequence differed greatly from known BNoV VP1 sequences; (ii) a recombination event is predicted within the ORF1-ORF2 overlap. Moreover 16.3% (7/43) of the BNoV were identified as the novel VP1 genotype, which were distributed on four farms across two provinces, indicating that the novel VP1 genotype strain has spread. To our knowledge, this is first description of the molecular and genomic characteristics of BNoV in China. These findings extend our understanding of the genetic evolution and epidemics of BNoV.
Collapse
Affiliation(s)
- Yuelin Wang
- College of Life Science and Technology, Southwest Minzu University, Chengdu, China
| | - Hua Yue
- College of Life Science and Technology, Southwest Minzu University, Chengdu, China. .,Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Chengdu, China.
| | - Cheng Tang
- College of Life Science and Technology, Southwest Minzu University, Chengdu, China. .,Key Laboratory of Qinghai-Tibetan Plateau Animal Genetic Resource Reservation and Utilization, Chengdu, China.
| |
Collapse
|