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Feng Y, Chen S, Wang A, Zhao Z, Chen C. Trends and impacts of SARS-CoV-2 genome sharing: a comparative analysis of China and the global community, 2020-2023. Front Public Health 2024; 12:1491623. [PMID: 39635220 PMCID: PMC11614776 DOI: 10.3389/fpubh.2024.1491623] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Accepted: 11/07/2024] [Indexed: 12/07/2024] Open
Abstract
Objective The global sharing of pathogen genome sequences has been significantly expedited by the COVID-19 pandemic. This study aims to elucidate the global landscape of SARS-CoV-2 genome sharing between 2020 and 2023 with a focus on quantity, timeliness, and quality. Specifically, the characteristics of China are examined. Methods SARS-CoV-2 genomes along with associated metadata were sourced from GISAID database. The genomes were analyzed to evaluate the quantity, timeliness, and quality across different countries/regions. The metadata characteristics of shared genomes in China in 2023 were examined and compared with the actual demographic data of China in 2023. Results From 2020 to 2023, European countries consistently maintained high levels of genomic data sharing in terms of quantity, timeliness, and quality. In 2023, China made remarkable improvements in sequence sharing, ranking among the top 3.89% globally for quantity, 22.78% for timeliness, and 17.78% for quality. The genome sharing in China in 2023 covered all provinces with Shanghai Municipality contributing the most genomes. Human samples accounted for 99.73% of the shared genomes and exhibited three distinct peaks in collection dates. Males constituted 52.06%, while females constituted 47.94%. Notably, there was an increase in individuals aged 65 and above within the GISAID database compared to China's overall population in 2023. Conclusion The global sharing of SARS-CoV-2 genomes in 2020-2023 exhibited disparities in terms of quantity, timeliness, and quality. However, China has made significant advancements since 2023 by achieving comprehensive coverage across provinces, timely dissemination of data, and widespread population monitoring. Strengthening data sharing capabilities in countries like China during the SARS-CoV-2 pandemic will play a crucial role in containing and responding to future pandemics caused by emerging pathogens.
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Affiliation(s)
| | | | | | | | - Cao Chen
- National Key Laboratory of Intelligent Tracking and Forecasting for Infectious Diseases, NHC Key Laboratory of Medical Virology and Viral Diseases, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention, Beijing, China
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2
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Chen O, Guan F, Zhan C, Li Y. From infected to recovered: the mediating role of sleep quality between self-compassion, social support and COVID-19 psychosomatic symptoms. BMC Public Health 2024; 24:3196. [PMID: 39558277 PMCID: PMC11571965 DOI: 10.1186/s12889-024-20657-9] [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: 01/31/2024] [Accepted: 11/07/2024] [Indexed: 11/20/2024] Open
Abstract
BACKGROUND Recent research has shown significant individual differences in COVID-19 psychosomatic symptoms. However, there has been a lack of studies investigating the influence of physical and psychological factors on these symptoms and their underlying mechanisms. This study aims to fill this gap by investigating the predictive role of self-compassion and social support on COVID-19 psychosomatic symptoms, as well as the potential mediating role of sleep quality. METHODS Data were collected from 636 participants infected with COVID-19 during the early post-pandemic reopening phase in China. The measurement tools used in the current study included the Self-Compassion Scale, the Perceived Social Support Scale, Self-Rating Scale of Sleep, and a COVID-19 Psychosomatic Symptom Diary. RESULTS A structural equation model revealed that: (1) social support directly predicts COVID-19 psychosomatic symptoms; (2) sleep quality fully mediates the relationship between self-compassion and COVID-19 psychosomatic symptoms; and (3) sleep quality partially mediates the relationship between social support and COVID-19 psychosomatic symptoms. CONCLUSIONS These findings not only confirm previous research but also provide new insights into the intricate interplay between psychological and physical factors and their influence on COVID-19 psychosomatic symptoms. The implications of these findings may inform the development of targeted rehabilitation programs in the post-pandemic era of the "new normal". CLINICAL TRIAL NUMBER Not applicable.
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Affiliation(s)
- Outong Chen
- Department of Psychology, Normal College & School of Teacher Education, Qingdao University, Qingdao, China
| | - Fang Guan
- School of Psychology, Third Military Medical University, Chongqing, China.
| | - Chengqing Zhan
- School of Psychology, Third Military Medical University, Chongqing, China
| | - Ying Li
- Fukang Hospital of Tibet University, Lhasa, China
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Mahase V, Sobitan A, Yao Q, Shi X, Qin H, Kidane D, Tang Q, Teng S. Impact of Missense Mutations on Spike Protein Stability and Binding Affinity in the Omicron Variant. Viruses 2024; 16:1150. [PMID: 39066312 PMCID: PMC11281596 DOI: 10.3390/v16071150] [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: 06/20/2024] [Revised: 07/04/2024] [Accepted: 07/10/2024] [Indexed: 07/28/2024] Open
Abstract
The global effort to combat the COVID-19 pandemic faces ongoing uncertainty with the emergence of Variants of Concern featuring numerous mutations on the Spike (S) protein. In particular, the Omicron Variant is distinguished by 32 mutations, including 10 within its receptor-binding domain (RBD). These mutations significantly impact viral infectivity and the efficacy of vaccines and antibodies currently in use for therapeutic purposes. In our study, we employed structure-based computational saturation mutagenesis approaches to predict the effects of Omicron missense mutations on RBD stability and binding affinity, comparing them to the original Wuhan-Hu-1 strain. Our results predict that mutations such as G431W and P507W induce the most substantial destabilizations in the Wuhan-Hu-1-S/Omicron-S RBD. Notably, we postulate that mutations in the Omicron-S exhibit a higher percentage of enhancing binding affinity compared to Wuhan-S. We found that the mutations at residue positions G447, Y449, F456, F486, and S496 led to significant changes in binding affinity. In summary, our findings may shed light on the widespread prevalence of Omicron mutations in human populations. The Omicron mutations that potentially enhance their affinity for human receptors may facilitate increased viral binding and internalization in infected cells, thereby enhancing infectivity. This informs the development of new neutralizing antibodies capable of targeting Omicron's immune-evading mutations, potentially aiding in the ongoing battle against the COVID-19 pandemic.
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Affiliation(s)
| | - Adebiyi Sobitan
- Department of Biology, Howard University, Washington, DC 20059, USA
| | - Qiaobin Yao
- Department of Biology, Howard University, Washington, DC 20059, USA
| | - Xinghua Shi
- Department of Computer & Information Sciences, Temple University, Philadelphia, PA 19122, USA
| | - Hong Qin
- Department of Computer Science and Engineering, University of Tennessee at Chattanooga, Chattanooga, TN 37403, USA
| | - Dawit Kidane
- Department of Physiology and Biophysics, Howard University College of Medicine, Washington, DC 20059, USA
| | - Qiyi Tang
- Department of Microbiology, Howard University College of Medicine, Washington, DC 20059, USA
| | - Shaolei Teng
- Department of Biology, Howard University, Washington, DC 20059, USA
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4
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Liu B, Liu H, Han P, Wang X, Wang C, Yan X, Lei W, Xu K, Zhou J, Qi J, Fan R, Wu G, Tian WX, Gao GF, Wang Q. Enhanced potency of an IgM-like nanobody targeting conserved epitope in SARS-CoV-2 spike N-terminal domain. Signal Transduct Target Ther 2024; 9:131. [PMID: 38740785 PMCID: PMC11091055 DOI: 10.1038/s41392-024-01847-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2023] [Revised: 03/25/2024] [Accepted: 04/26/2024] [Indexed: 05/16/2024] Open
Abstract
Almost all the neutralizing antibodies targeting the receptor-binding domain (RBD) of spike (S) protein show weakened or lost efficacy against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) emerged or emerging variants, such as Omicron and its sub-variants. This suggests that highly conserved epitopes are crucial for the development of neutralizing antibodies. Here, we present one nanobody, N235, displaying broad neutralization against the SARS-CoV-2 prototype and multiple variants, including the newly emerged Omicron and its sub-variants. Cryo-electron microscopy demonstrates N235 binds a novel, conserved, cryptic epitope in the N-terminal domain (NTD) of the S protein, which interferes with the RBD in the neighboring S protein. The neutralization mechanism interpreted via flow cytometry and Western blot shows that N235 appears to induce the S1 subunit shedding from the trimeric S complex. Furthermore, a nano-IgM construct (MN235), engineered by fusing N235 with the human IgM Fc region, displays prevention via inducing S1 shedding and cross-linking virus particles. Compared to N235, MN235 exhibits varied enhancement in neutralization against pseudotyped and authentic viruses in vitro. The intranasal administration of MN235 in low doses can effectively prevent the infection of Omicron sub-variant BA.1 and XBB in vivo, suggesting that it can be developed as a promising prophylactic antibody to cope with the ongoing and future infection.
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Affiliation(s)
- Bo Liu
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Honghui Liu
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Pu Han
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Xiaoyun Wang
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Chunmei Wang
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
- School of Life Sciences, Yunnan University, 650504, Kunming, Yunnan Province, China
| | - Xinxin Yan
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Wenwen Lei
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), 102206, Beijing, China
| | - Ke Xu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), 102206, Beijing, China
| | - Jianjie Zhou
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
| | - Jianxun Qi
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China
- Savaid Medical School, University of Chinese Academy of Sciences, 101408, Beijing, China
| | - Ruiwen Fan
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China
| | - Guizhen Wu
- NHC Key Laboratory of Biosafety, National Institute for Viral Disease Control and Prevention, Chinese Center for Disease Control and Prevention (China CDC), 102206, Beijing, China.
| | - Wen-Xia Tian
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China.
| | - George F Gao
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China.
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China.
| | - Qihui Wang
- College of Veterinary Medicine, Shanxi Agricultural University, 030801, Jinzhong, China.
- CAS Key Laboratory of Pathogen Microbiology and Immunology, Institute of Microbiology, Chinese Academy of Sciences (CAS), 100101, Beijing, China.
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Lu H, Zhang G, Mao J, Chen X, Zhan Y, Lin L, Zhang T, Tang Y, Lin F, Zhu F, Lin Y, Zeng Y, Zhang K, Yuan W, Liang Z, Sun R, Huo L, Hu P, Lin Y, Zhuang X, Wei Z, Chen X, Yan W, Yan X, Mu L, Lin Z, Tu X, Tan H, Huang F, Hu Z, Li H, Li G, Fu H, Yang Z, Chen X, Wang FS, Zhong N. Efficacy and safety of GST-HG171 in adult patients with mild to moderate COVID-19: a randomised, double-blind, placebo-controlled phase 2/3 trial. EClinicalMedicine 2024; 71:102582. [PMID: 38618202 PMCID: PMC11015484 DOI: 10.1016/j.eclinm.2024.102582] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2024] [Revised: 03/16/2024] [Accepted: 03/19/2024] [Indexed: 04/16/2024] Open
Abstract
Background GST-HG171 is a potent, broad-spectrum, orally bioavailable small-molecule 3C like protease inhibitor that has demonstrated greater potency and efficacy compared to Nirmatrelvir in pre-clinical studies. We aimed to evaluate the efficacy and safety of orally administered GST-HG171 plus Ritonavir in patients with coronavirus disease 2019 (COVID-19) infected with emerging XBB and non-XBB variants. Methods This randomised, double-blind, placebo-controlled phase 2/3 trial was conducted in 47 sites in China among adult patients with mild-to-moderate COVID-19 with symptoms onset ≤72 h. Eligible patients were randomised 1:1 to receive GST-HG171 (150 mg) plus Ritonavir (100 mg) or corresponding placebo tablets twice daily for 5 days, with stratification factors including the risk level of disease progression and vaccination status. The primary efficacy endpoint was time to sustained recovery of clinical symptoms within 28 days, defined as a score of 0 for 11 COVID-19-related target symptoms for 2 consecutive days, assessed in the modified intention-to-treat (mITT) population. This trial was registered at ClinicalTrials.gov (NCT05656443) and Chinese Clinical Trial Registry (ChiCTR2200067088). Findings Between Dec 19, 2022, and May 4, 2023, 1525 patients were screened. Among 1246 patients who underwent randomisation, most completed basic (21.2%) or booster (74.9%) COVID-19 immunization, and most had a low risk of disease progression at baseline. 610 of 617 who received GST-HG171 plus Ritonavir and 603 of 610 who received placebo were included in the mITT population. Patients who received GST-HG171 plus Ritonavir showed shortened median time to sustained recovery of clinical symptoms compared to the placebo group (13.0 days [95.45% confidence interval 12.0-15.0] vs. 15.0 days [14.0-15.0], P = 0.031). Consistent results were observed in both SARS-CoV-2 XBB (45.7%, 481/1053 of mITT population) and non-XBB variants (54.3%, 572/1053 of mITT population) subgroups. Incidence of adverse events was similar in the GST-HG171 plus Ritonavir (320/617, 51.9%) and placebo group (298/610, 48.9%). The most common adverse events in both placebo and treatment groups were hypertriglyceridaemia (10.0% vs. 14.7%). No deaths occurred. Interpretation Treatment with GST-HG171 plus Ritonavir has demonstrated benefits in symptom recovery and viral clearance among low-risk vaccinated adult patients with COVID-19, without apparent safety concerns. As most patients were treated within 2 days after symptom onset in our study, confirming the potential benefits of symptom recovery for patients with a longer duration between symptom onset and treatment initiation will require real-world studies. Funding Fujian Akeylink Biotechnology Co., Ltd.
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Affiliation(s)
- Hongzhou Lu
- The Third People's Hospital of Shenzhen, Shenzhen, China
- National Clinical Research Center for Infectious Diseases, Shenzhen, China
| | - George Zhang
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | - John Mao
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | | | - Yangqing Zhan
- The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Ling Lin
- Sanya Central Hospital (The Third People's Hospital of Hainan Province), Sanya, China
| | | | - Yanan Tang
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | - Feng Lin
- Hainan General Hospital, Haikou, China
| | | | - Yuanlong Lin
- The Third People's Hospital of Shenzhen, Shenzhen, China
| | - Yiming Zeng
- Fujian Medical University 2nd Affiliated Hospital, Fuzhou, China
| | - Kaiyu Zhang
- The First Hospital of Jilin University, Changchun, China
| | - Wenfang Yuan
- Shijiazhuang Fifth Hospital, Shijiazhuang, China
| | - Zhenyu Liang
- The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Ruilin Sun
- Guangdong Second Provincial General Hospital, Guangzhou, China
| | - Liya Huo
- Nanyang Central Hospital, Nanyang, China
| | - Peng Hu
- The Second Affiliated Hospital of Chongqing Medical University, Chongqing, China
| | - Yihua Lin
- The First Affiliated Hospital of Xiamen University, Xiamen, China
| | | | | | | | - Wenhao Yan
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | - Xiuping Yan
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | | | | | | | - Hongshan Tan
- Fujian Akeylink Biotechnology Co., Ltd., Shanghai, China
| | - Fuhu Huang
- Fujian Cosunter Pharmaceutical Co., Ltd., Fuzhou, China
| | - Zhiqiang Hu
- Fujian Cosunter Pharmaceutical Co., Ltd., Fuzhou, China
| | - Hongming Li
- Fujian Cosunter Pharmaceutical Co., Ltd., Fuzhou, China
| | - Guoping Li
- Fujian Cosunter Pharmaceutical Co., Ltd., Fuzhou, China
| | - Haijun Fu
- Shanghai Zenith Medical Research Co., Ltd., Shanghai, China
| | - Zifeng Yang
- The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
| | - Xinwen Chen
- Guangzhou National Laboratory, Guangdong Province, China
| | - Fu-Sheng Wang
- The Fifth Medical Center of Chinese PLA General Hospital, National Clinical Research Center for Infectious Diseases, Beijing, China
| | - Nanshan Zhong
- The First Affiliated Hospital of Guangzhou Medical University, State Key Laboratory of Respiratory Disease, National Clinical Research Center for Respiratory Disease, Guangzhou Institute of Respiratory Health, Guangzhou, China
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Emad R, Naga IS. Comparative genotyping of SARS-CoV-2 among Egyptian patients: near-full length genomic sequences versus selected spike and nucleocapsid regions. Med Microbiol Immunol 2023; 212:437-446. [PMID: 37789185 PMCID: PMC10618331 DOI: 10.1007/s00430-023-00783-8] [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: 07/10/2023] [Accepted: 09/19/2023] [Indexed: 10/05/2023]
Abstract
Several tools have been developed for severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) genotyping based on either whole genome or spike sequencing. We aimed to highlight the molecular epidemiological landscape of SARS-CoV-2 in Egypt since the start of the pandemic, to describe discrepancies between the 3 typing tools: Global Initiative on Sharing Avian Influenza Data (GISAID), Nextclade, and Phylogenetic Assignment of Named Global Outbreak Lineages (PANGOLIN) and to assess the fitness of spike and nucleocapsid regions for lineage assignment compared to the whole genome. A total of 3935 sequences isolated from Egypt (March 2020-2023) were retrieved from the GISAID database. A subset of data (n = 1212) with high coverage whole genome was used for tool discrimination and agreement analyses. Among 1212 sequences, the highest discriminatory power was 0.895 for PANGOLIN, followed by GISAID (0.872) and Nextclade (0.866). There was a statistically significant difference (p = 0.0418) between lineages assigned via spike (30%) and nucleocapsid (46%) compared to their whole genome-assigned lineages. The first 3 pandemic waves were dominated by B.1, followed by C.36 and then C.36.3, while the fourth to sixth waves were dominated by the B.1.617.2, BA, and BA.5.2 lineages, respectively. Current shift in lineage typing to recombinant forms. The 3 typing tools showed comparable discrimination among SARS-CoV-2 lineages. The nucleocapsid region could be used for lineage assignment.
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Affiliation(s)
- Rasha Emad
- Alexandria Main University Hospital, Alexandria, Egypt.
| | - Iman S Naga
- Department of Microbiology, Medical Research Institute, Alexandria University, Alexandria, Egypt
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7
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Dumm W, Barker M, Howard-Snyder W, DeWitt Iii WS, Matsen Iv FA. Representing and extending ensembles of parsimonious evolutionary histories with a directed acyclic graph. J Math Biol 2023; 87:75. [PMID: 37878119 PMCID: PMC10600060 DOI: 10.1007/s00285-023-02006-3] [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: 01/10/2023] [Revised: 09/12/2023] [Accepted: 09/26/2023] [Indexed: 10/26/2023]
Abstract
In many situations, it would be useful to know not just the best phylogenetic tree for a given data set, but the collection of high-quality trees. This goal is typically addressed using Bayesian techniques, however, current Bayesian methods do not scale to large data sets. Furthermore, for large data sets with relatively low signal one cannot even store every good tree individually, especially when the trees are required to be bifurcating. In this paper, we develop a novel object called the "history subpartition directed acyclic graph" (or "history sDAG" for short) that compactly represents an ensemble of trees with labels (e.g. ancestral sequences) mapped onto the internal nodes. The history sDAG can be built efficiently and can also be efficiently trimmed to only represent maximally parsimonious trees. We show that the history sDAG allows us to find many additional equally parsimonious trees, extending combinatorially beyond the ensemble used to construct it. We argue that this object could be useful as the "skeleton" of a more complete uncertainty quantification.
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Affiliation(s)
- Will Dumm
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Howard Hughes Medical Institute, Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - Mary Barker
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
- Howard Hughes Medical Institute, Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA
| | - William Howard-Snyder
- Paul G. Allen School of Computer Science and Engineering, University of Washington, Seattle, Washington, USA
| | - William S DeWitt Iii
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, California, USA
| | - Frederick A Matsen Iv
- Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
- Howard Hughes Medical Institute, Computational Biology Program, Fred Hutchinson Cancer Research Center, Seattle, Washington, USA.
- Department of Genome Sciences, University of Washington, Seattle, Washington, USA.
- Department of Statistics, University of Washington, Seattle, Washington, USA.
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8
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Ghedira K, Dallali H, Ardhaoui M, Bouslema Z, Hamdi Y, Feki Ben-Salah S, Chelbi H, Atri C, Chaouch M, Dekhil N, Rais A, Azouz S, Gharbi M, Guerfali F, Hkimi C, Kamoun S, Ksouri A, Moumni I, Ouragini H, Bsibes R, Afifi Z, Youssfi K, Ben Hassine H, Hadhri N, Mardassi H, Othman H, Khamessi O. PHINDaccess Hackathons for COVID-19 and Host-Pathogen Interaction: Lessons Learned and Recommendations for Low- and Middle-Income Countries. BIOMED RESEARCH INTERNATIONAL 2023; 2023:6638714. [PMID: 37854792 PMCID: PMC10581832 DOI: 10.1155/2023/6638714] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 04/15/2023] [Revised: 08/29/2023] [Accepted: 09/01/2023] [Indexed: 10/20/2023]
Abstract
Hackathons are collaborative events that bring together diverse groups to solve predefined challenges. The COVID-19 pandemic caused by SARS-CoV-2 has emphasized the need for portable and reproducible genomics analysis pipelines to study the genetic susceptibility of the human host and investigate human-SARS-CoV-2 protein interactions. To build and strengthen institutional capacities in OMICS data analysis applied to host-pathogen interaction (HPI), the PHINDaccess project organized two hackathons in 2020 and 2021. These hackathons are aimed at developing bioinformatics pipelines related to the SARS-CoV-2 viral genome, its phylodynamic transmission, and the identification of human genome host variants, with a focus on addressing global health challenges, particularly in low- and middle-income countries (LMIC). This paper outlines the preparation, proceedings, and lessons learned from these hackathons, including the challenges faced by participants and our recommendations based on our experience for organizing hackathons in LMIC and beyond.
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Affiliation(s)
- Kais Ghedira
- Laboratory of Bioinformatics, Biomathematics and Biostatistics LR20IPT09, Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Hamza Dallali
- Laboratory of Biomedical Genomics and Oncogenetics (LR20IPT05), Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Monia Ardhaoui
- Department of Human and Experimentally Anatomic Pathology, Laboratory of Molecular Epidemiology and Experimental Pathology, Institut Pasteur de Tunis, University of Tunis El Manar, Tunis, Tunisia
- Laboratory of Molecular Epidemiology and Experimental Pathology, Tunisia
| | - Zied Bouslema
- Laboratory for Rabies Diagnostics, Institute Pasteur of Tunis, Belvedere, Tunis 1002, Tunisia
- University of Tunis El Manar, Tunis, Tunisia
| | - Yosr Hamdi
- Laboratory of Biomedical Genomics and Oncogenetics (LR20IPT05), Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Salma Feki Ben-Salah
- Laboratory of Virus, Vector and Hosts (LR20IPT02), Institut Pasteur de Tunis, Université Tunis El Manar, Tunis 1068, Tunisia
| | - Hanen Chelbi
- Laboratory of Medical Parasitology, Biotechnology and Biomolecules, LR16IPT06, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis Belvédère 1002, Tunisia
| | - Chiraz Atri
- Laboratory of Transmission, Control and Immunobiology of Infections (LTCII), LR16IPT02, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis Belvédère 1002, Tunisia
| | - Melek Chaouch
- Laboratory of Bioinformatics, Biomathematics and Biostatistics LR20IPT09, Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Naira Dekhil
- Laboratory of Molecular Microbiology, Vaccinology, And Biotechnology Development, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis, Tunisia
| | - Afef Rais
- Laboratory of Transmission, Control and Immunobiology of Infections (LTCII), LR16IPT02, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis Belvédère 1002, Tunisia
| | - Saifeddine Azouz
- Genomics Platform, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis 1068, Tunisia
| | - Manel Gharbi
- Laboratory of Epidemiology and Veterinary Microbiology. Group of Bacteriology and Biotechnology Institut Pasteur of Tunisia, University of Tunis El Manar (UTM), Tunis 1002, Tunisia
| | - Fatma Guerfali
- Laboratory of Transmission, Control and Immunobiology of Infections (LTCII), LR16IPT02, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis Belvédère 1002, Tunisia
| | - Chaima Hkimi
- Laboratory of Bioinformatics, Biomathematics and Biostatistics LR20IPT09, Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Selim Kamoun
- Laboratory of Bioinformatics, Biomathematics and Biostatistics LR20IPT09, Pasteur Institute of Tunis, University of Tunis El Manar, Tunis 1002, Tunisia
| | - Ayoub Ksouri
- Laboratory of Venom, Toxins and Therapeutic Molecules, Institut Pasteur Tunis, University Tunis El Manar, Tunis, Tunisia
| | - Imen Moumni
- Laboratory of Molecular and Cellular Hematology, LR16IPT07, Pasteur Institute of Tunis, University of Tunis El Manar, Tunisia
| | - Houyem Ouragini
- Laboratory of Molecular and Cellular Hematology, LR16IPT07, Pasteur Institute of Tunis, University of Tunis El Manar, Tunisia
| | - Raghda Bsibes
- Grant Office, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Zeineb Afifi
- Grant Office, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Khouloud Youssfi
- Specialized Unit “Communication, Science and Society”, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Hichem Ben Hassine
- Specialized Unit “Communication, Science and Society”, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Najet Hadhri
- Grant Office, Institut Pasteur de Tunis, Tunis, Tunisia
| | - Helmi Mardassi
- Laboratory of Molecular Microbiology, Vaccinology, And Biotechnology Development, Institut Pasteur de Tunis, Université Tunis El Manar, Tunis, Tunisia
| | - Houcemeddine Othman
- Sydney Brenner Institute for Molecular Bioscience, Faculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
- Department of Genetics, Farhat Hached University Hospital, Sousse, Tunisia
- Laboratory of Cytogenetics, Molecular Genetics, and Reproductive Biology (LR03SP02), Farhat Hached University Hospital, Sousse, Tunisia
| | - Oussema Khamessi
- Laboratory of Venoms and Therapeutic Molecules LR11IPT08, Institut Pasteur de Tunis, University of Tunis El Manar, 13 Place Pasteur BP74Belvédère, Tunis Belvédère, Tunisia
- High Institute of Biotechnology of Sidi Thabet, University of Manouba, Ariana BP-66, Manouba 2010, Tunisia
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9
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Tai C, Li H, Zhang J. BCEDB: a linear B-cell epitopes database for SARS-CoV-2. Database (Oxford) 2023; 2023:baad065. [PMID: 37776561 PMCID: PMC10541793 DOI: 10.1093/database/baad065] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 08/17/2023] [Accepted: 09/13/2023] [Indexed: 10/02/2023]
Abstract
The 2019 Novel Coronavirus (SARS-CoV-2) has infected millions of people worldwide and caused millions of deaths. The virus has gone numerous mutations to replicate faster, which can overwhelm the immune system of the host. Linear B-cell epitopes are becoming promising in prevention of various deadly infectious diseases, breaking the general idea of their low immunogenicity and partial protection. However, there is still no public repository to host the linear B-cell epitopes for facilitating the development vaccines against SARS-CoV-2. Therefore, we developed BCEDB, a linear B-cell epitopes database specifically designed for hosting, exploring and visualizing linear B-cell epitopes and their features. The database provides a comprehensive repository of computationally predicted linear B-cell epitopes from Spike protein; a systematic annotation of epitopes including sequence, antigenicity score, genomic locations of epitopes, mutations in different virus lineages, mutation sites on the 3D structure of Spike protein and a genome browser to visualize them in an interactive manner. It represents a valuable resource for peptide-based vaccine development. Database URL: http://www.oncoimmunobank.cn/bcedbindex.
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Affiliation(s)
- Chengzheng Tai
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
| | - Hongjun Li
- Department of Radiology, Beijing YouAn Hospital, Capital Medical University, No. 8 Youan Gate Outer Xitou Alley, Beijing 100069, China
| | - Jing Zhang
- Key Laboratory for Biomechanics and Mechanobiology of Ministry of Education, Beijing Advanced Innovation Centre for Biomedical Engineering, School of Engineering Medicine & School of Biological Science and Medical Engineering, Beihang University, No. 37 Xueyuan Road, Haidian District, Beijing 100191, China
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10
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Li X, Yan H, Wong G, Ouyang W, Cui J. Identifying featured indels associated with SARS-CoV-2 fitness. Microbiol Spectr 2023; 11:e0226923. [PMID: 37698427 PMCID: PMC10580940 DOI: 10.1128/spectrum.02269-23] [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: 06/01/2023] [Accepted: 07/14/2023] [Indexed: 09/13/2023] Open
Abstract
As an RNA virus, severe acute respiratory coronavirus 2 (SARS-CoV-2) is known for frequent substitution mutations, and substitutions in important genome regions are often associated with viral fitness. However, whether indel mutations are related to viral fitness is generally ignored. Here we developed a computational methodology to investigate indels linked to fitness occurring in over 9 million SARS-CoV-2 genomes. Remarkably, by analyzing 31,642,404 deletion records and 1,981,308 insertion records, our pipeline identified 26,765 deletion types and 21,054 insertion types and discovered 65 indel types with a significant association with Pango lineages. We proposed the concept of featured indels representing the population of specific Pango lineages and variants as substitution mutations and termed these 65 indels as featured indels. The selective pressure of all indel types is assessed using the Bayesian model to explore the importance of indels. Our results exhibited higher selective pressure of indels like substitution mutations, which are important for assessing viral fitness and consistent with previous studies in vitro. Evaluation of the growth rate of each viral lineage indicated that indels play key roles in SARS-CoV-2 evolution and deserve more attention as substitution mutations. IMPORTANCE The fitness of indels in pathogen genome evolution has rarely been studied. We developed a computational methodology to investigate the severe acute respiratory coronavirus 2 genomes and analyze over 33 million records of indels systematically, ultimately proposing the concept of featured indels that can represent specific Pango lineages and identifying 65 featured indels. Machine learning model based on Bayesian inference and viral lineage growth rate evaluation suggests that these featured indels exhibit selection pressure comparable to replacement mutations. In conclusion, indels are not negligible for evaluating viral fitness.
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Affiliation(s)
- Xiang Li
- CAS Key Laboratory of Molecular Virology & Immunology, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
- AI for Science, Shanghai Artificial Intelligence Laboratory, Shanghai, China
- University of Chinese Academy of Sciences, Beijing, China
| | - Hongliang Yan
- AI for Science, Shanghai Artificial Intelligence Laboratory, Shanghai, China
| | - Gary Wong
- CAS Key Laboratory of Molecular Virology & Immunology, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
| | - Wanli Ouyang
- AI for Science, Shanghai Artificial Intelligence Laboratory, Shanghai, China
| | - Jie Cui
- CAS Key Laboratory of Molecular Virology & Immunology, Shanghai Institute of Immunity and Infection, Chinese Academy of Sciences, Shanghai, China
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11
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Ren H, Ling Y, Cao R, Wang Z, Li Y, Huang T. Early warning of emerging infectious diseases based on multimodal data. BIOSAFETY AND HEALTH 2023; 5:S2590-0536(23)00074-5. [PMID: 37362865 PMCID: PMC10245235 DOI: 10.1016/j.bsheal.2023.05.006] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2023] [Revised: 05/18/2023] [Accepted: 05/31/2023] [Indexed: 06/28/2023] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic has dramatically increased the awareness of emerging infectious diseases. The advancement of multiomics analysis technology has resulted in the development of several databases containing virus information. Several scientists have integrated existing data on viruses to construct phylogenetic trees and predict virus mutation and transmission in different ways, providing prospective technical support for epidemic prevention and control. This review summarized the databases of known emerging infectious viruses and techniques focusing on virus variant forecasting and early warning. It focuses on the multi-dimensional information integration and database construction of emerging infectious viruses, virus mutation spectrum construction and variant forecast model, analysis of the affinity between mutation antigen and the receptor, propagation model of virus dynamic evolution, and monitoring and early warning for variants. As people have suffered from COVID-19 and repeated flu outbreaks, we focused on the research results of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and influenza viruses. This review comprehensively viewed the latest virus research and provided a reference for future virus prevention and control research.
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Affiliation(s)
- Haotian Ren
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yunchao Ling
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ruifang Cao
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Zhen Wang
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
| | - Yixue Li
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
- School of Life Science, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou 310024 China
- Guangzhou Laboratory, Guangzhou 510005, China
- School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
- Collaborative Innovation Center for Genetics and Development, Fudan University, Shanghai 200433, China
| | - Tao Huang
- Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, University of Chinese Academy of Sciences, Chinese Academy of Sciences, Shanghai 200031, China
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12
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Guo H, Yang Y, Zhao T, Lu Y, Gao Y, Li T, Xiao H, Chu X, Zheng L, Li W, Cheng H, Huang H, Liu Y, Lou Y, Nguyen HC, Wu C, Chen Y, Yang H, Ji X. Mechanism of a rabbit monoclonal antibody broadly neutralizing SARS-CoV-2 variants. Commun Biol 2023; 6:364. [PMID: 37012333 PMCID: PMC10069731 DOI: 10.1038/s42003-023-04759-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2022] [Accepted: 03/24/2023] [Indexed: 04/05/2023] Open
Abstract
Due to the continuous evolution of SARS-CoV-2, the Omicron variant has emerged and exhibits severe immune evasion. The high number of mutations at key antigenic sites on the spike protein has made a large number of existing antibodies and vaccines ineffective against this variant. Therefore, it is urgent to develop efficient broad-spectrum neutralizing therapeutic drugs. Here we characterize a rabbit monoclonal antibody (RmAb) 1H1 with broad-spectrum neutralizing potency against Omicron sublineages including BA.1, BA.1.1, BA.2, BA.2.12.1, BA.2.75, BA.3 and BA.4/5. Cryo-electron microscopy (cryo-EM) structure determination of the BA.1 spike-1H1 Fab complexes shows that 1H1 targets a highly conserved region of RBD and avoids most of the circulating Omicron mutations, explaining its broad-spectrum neutralization potency. Our findings indicate 1H1 as a promising RmAb model for designing broad-spectrum neutralizing antibodies and shed light on the development of therapeutic agents as well as effective vaccines against newly emerging variants in the future.
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Affiliation(s)
- Hangtian Guo
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Yixuan Yang
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Tiantian Zhao
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210008, China
| | - Yuchi Lu
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
| | - Yan Gao
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
| | - Tinghan Li
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Hang Xiao
- Yurogen Biosystem LLC, Wuhan, Hubei, 430075, China
| | - Xiaoyu Chu
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Le Zheng
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China
| | - Wanting Li
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Xuzhou Medical University, Nanjing, Jiangsu, 210008, China
| | - Hao Cheng
- Yurogen Biosystem LLC, Wuhan, Hubei, 430075, China
| | - Haibin Huang
- Yurogen Biosystem LLC, Wuhan, Hubei, 430075, China
| | - Yang Liu
- Yurogen Biosystem LLC, Wuhan, Hubei, 430075, China
| | - Yang Lou
- Yurogen Biosystem LLC, Wuhan, Hubei, 430075, China
| | - Henry C Nguyen
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
| | - Chao Wu
- Department of Infectious Diseases, Nanjing Drum Tower Hospital Clinical College of Nanjing University of Chinese Medicine, Nanjing, Jiangsu, 210008, China
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, 210008, China
| | - Yuxin Chen
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, 210008, China.
| | - Haitao Yang
- Shanghai Institute for Advanced Immunochemical Studies and School of Life Science and Technology, ShanghaiTech University, Shanghai, 201210, China
- Shanghai Clinical Research and Trial Center, Shanghai, 201210, China
| | - Xiaoyun Ji
- The State Key Laboratory of Pharmaceutical Biotechnology, School of Life Sciences, Nanjing University, Nanjing, Jiangsu, 210023, China.
- Institute of Viruses and Infectious Diseases, Nanjing University, Nanjing, Jiangsu, 210008, China.
- Department of Laboratory Medicine, Nanjing Drum Tower Hospital, Nanjing University Medical School, Nanjing, Jiangsu, 210008, China.
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13
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Jian X, Zhang Y, Zhao J, Zhao Z, Lu M, Xie L. CoV2-TCR: A web server for screening TCR CDR3 from TCR immune repertoire of COVID-19 patients and their recognized SARS-CoV-2 epitopes. Comput Struct Biotechnol J 2023; 21:1362-1371. [PMID: 36741787 PMCID: PMC9882952 DOI: 10.1016/j.csbj.2023.01.038] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2022] [Revised: 01/08/2023] [Accepted: 01/26/2023] [Indexed: 01/30/2023] Open
Abstract
Although multiple vaccines have been developed and widely administered, several severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants have been reported to evade immune responses and spread diffusely. Here, 108 RNA-seq files from coronavirus disease 2019 (COVID-19) patients and healthy donors (HD) were downloaded to extract their TCR immune repertoire by MiXCR. Those extracted TCR repertoire were compared and it was found that disease progression was related negatively with diversity and positively with clonality. Specifically, greater proportions of high-abundance clonotypes were observed in active and severe COVID-19 samples, probably resulting from strong stimulation of SARS-CoV-2 epitopes and a continued immune response in host. To investigate the specific recognition between TCR CDR3 and SARS-CoV-2 epitopes, we constructed an accurate classifier CoV2-TCR with an AUC of 0.967 in an independent dataset, which outperformed several similar tools. Based on this model, we observed a huge range in the number of those TCR CDR3 recognizing those different peptides, including 28 MHC-I epitopes from SARS-CoV-2 and 22 immunogenic peptides from SARS-CoV-2 variants. Interestingly, their proportions of high-abundance, low-abundance and rare clonotypes were close for each peptide. To expand the potential application of this model, we established the webserver, CoV2-TCR, in which users can obtain those recognizing CDR3 sequences from the TCR repertoire of COVID-19 patients based on the 9-mer peptides containing mutation site(s) on the four main proteins of SARS-CoV-2 variants. Overall, this study provides preliminary screening for candidate antigen epitopes and the TCR CDR3 that recognizes them, and should be helpful for vaccine design on SARS-CoV-2 variants.
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Affiliation(s)
- Xingxing Jian
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China,Corresponding author.
| | - Yu Zhang
- Shanghai-MOST Key Laboratory of Health and Disease Genomics (Chinese National Human Genome Center at Shanghai), Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China,School of Medical Instrument and Food Engineering, University of Shanghai for Science and Technology, Shanghai, China
| | - Jingjing Zhao
- Shanghai-MOST Key Laboratory of Health and Disease Genomics (Chinese National Human Genome Center at Shanghai), Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China,College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Zhuoming Zhao
- Shanghai-MOST Key Laboratory of Health and Disease Genomics (Chinese National Human Genome Center at Shanghai), Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China,College of Food Science and Technology, Shanghai Ocean University, Shanghai, China
| | - Manman Lu
- Shanghai-MOST Key Laboratory of Health and Disease Genomics (Chinese National Human Genome Center at Shanghai), Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China
| | - Lu Xie
- Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China,Shanghai-MOST Key Laboratory of Health and Disease Genomics (Chinese National Human Genome Center at Shanghai), Institute of Genome and Bioinformatics, Shanghai Institute for Biomedical and Pharmaceutical Technologies, Shanghai, China,Corresponding author at: Bioinformatics Center & National Clinical Research Centre for Geriatric Disorders & Department of Geriatrics, Xiangya Hospital, Central South University, Changsha, Hunan, China.
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14
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Alemrajabi M, Macias Calix K, Assis R. Epistasis-Driven Evolution of the SARS-CoV-2 Secondary Structure. J Mol Evol 2022; 90:429-437. [PMID: 36178491 PMCID: PMC9523185 DOI: 10.1007/s00239-022-10073-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/11/2022] [Accepted: 09/02/2022] [Indexed: 11/25/2022]
Abstract
Epistasis is an evolutionary phenomenon whereby the fitness effect of a mutation depends on the genetic background in which it arises. A key source of epistasis in an RNA molecule is its secondary structure, which contains functionally important topological motifs held together by hydrogen bonds between Watson–Crick (WC) base pairs. Here we study epistasis in the secondary structure of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) by examining properties of derived alleles arising from substitution mutations at ancestral WC base-paired and unpaired (UP) sites in 15 conserved topological motifs across the genome. We uncover fewer derived alleles and lower derived allele frequencies at WC than at UP sites, supporting the hypothesis that modifications to the secondary structure are often deleterious. At WC sites, we also find lower derived allele frequencies for mutations that abolish base pairing than for those that yield G·U “wobbles,” illustrating that weak base pairing can partially preserve the integrity of the secondary structure. Last, we show that WC sites under the strongest epistatic constraint reside in a three-stemmed pseudoknot motif that plays an essential role in programmed ribosomal frameshifting, whereas those under the weakest epistatic constraint are located in 3’ UTR motifs that regulate viral replication and pathogenicity. Our findings demonstrate the importance of epistasis in the evolution of the SARS-CoV-2 secondary structure, as well as highlight putative structural and functional targets of different forms of natural selection.
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Affiliation(s)
- Mahsa Alemrajabi
- Department of Physics, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Ksenia Macias Calix
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA
| | - Raquel Assis
- Department of Electrical Engineering and Computer Science, Florida Atlantic University, Boca Raton, FL, 33431, USA.
- Institute for Human Health and Disease Intervention, Florida Atlantic University, Boca Raton, FL, 33431, USA.
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15
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COVID-19 Whole-Genome Resequencing with Redundant Tiling PCR and Subtract-Based Amplicon Normalization Successfully Characterized SARS-CoV-2 Variants in Clinical Specimens. Interdiscip Perspect Infect Dis 2022; 2022:2109641. [PMID: 36212105 PMCID: PMC9534710 DOI: 10.1155/2022/2109641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Accepted: 08/20/2022] [Indexed: 11/17/2022] Open
Abstract
With an increasing number of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) sequences gathered worldwide, we recognize that deletion mutants and nucleotide substitutions that may affect whole-genome sequencing are accumulating. Here, we propose an additional strategy for tiling PCR for whole-genome resequencing, which can make the pipeline robust for mutations at the primer annealing site by a redundant amplicon scheme. We further demonstrated that subtracting overrepresented amplicons from the multiplex PCR products reduced the bias of the next-generation sequencing (NGS) library, resulting in decreasing required sequencing reads per sample. We applied this sequencing strategy to clinical specimens collected in Bangladesh. More than 80% out of the 304 samples were successfully sequenced. Less than 5% were ambiguous nucleotides, and several known variants were detected. With the additional strategies presented here, we believe that whole-genome resequencing of SARS-CoV-2 from clinical samples can be optimized.
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16
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Yu D, Zhu J, Yang J, Pan YH, Mu H, Cao R, Tang B, Duan G, Hao ZQ, Dai L, Zhao GP, Zhang YP, Zhao W, Zhang G, Li H, Zhang G, Li H. Global cold-chain related SARS-CoV-2 transmission identified by pandemic-scale phylogenomics. Zool Res 2022; 43:871-874. [PMID: 36031769 PMCID: PMC9486523 DOI: 10.24272/j.issn.2095-8137.2022.238] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/15/2022] Open
Affiliation(s)
- Dalang Yu
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Junwei Zhu
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Jianing Yang
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Yi-Hsuan Pan
- Key Laboratory of Brain Functional Genomics of Ministry of Education, School of Life Science, East China Normal University, Shanghai 200062, China
| | - Hailong Mu
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China
| | - Ruifang Cao
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China
| | - Bixia Tang
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China
| | - Guangya Duan
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Zi-Qian Hao
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,University of Chinese Academy of Sciences, Beijing 100049, China
| | - Long Dai
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,Shanghai Southgene Technology Co. Ltd, Shanghai 201203, China
| | - Guo-Ping Zhao
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China,School of Life and Health Sciences, Hangzhou Institute for Advanced Study, University of Chinese Academy of Sciences, Hangzhou, Zhejiang 310024, China
| | - Ya-Ping Zhang
- State Key Laboratory of Genetic Resources and Evolution, Yunnan Laboratory of Molecular Biology of Domestic Animals, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan 650223, China
| | - Wenming Zhao
- National Genomics Data Center, Beijing Institute of Genomics, Chinese Academy of Sciences and China National Center for Bioinformation, Beijing 100101, China,University of Chinese Academy of Sciences, Beijing 100049, China,E-mail:
| | - Guoqing Zhang
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,University of Chinese Academy of Sciences, Beijing 100049, China,
| | - Haipeng Li
- National Genomics Data Center & Bio-Med Big Data Center, CAS Key Laboratory of Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai 200031, China,University of Chinese Academy of Sciences, Beijing 100049, China,
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17
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Cheng Y, Peng X. In silico study on the effects of disulfide bonds in ORF8 of SARS-CoV-2. Phys Chem Chem Phys 2022; 24:16876-16883. [DOI: 10.1039/d2cp01724e] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Abstract
The COVID-19 epidemic, caused by virus SARS-CoV-2, has been a pandemic and threatening everyone's health in the past two years. In SARS-CoV-2, ORF8 is one of the most important accessory...
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