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De Maio N, Walker CR, Turakhia Y, Lanfear R, Corbett-Detig R, Goldman N. Mutation Rates and Selection on Synonymous Mutations in SARS-CoV-2. Genome Biol Evol 2021; 13:evab087. [PMID: 33895815 PMCID: PMC8135539 DOI: 10.1093/gbe/evab087] [Citation(s) in RCA: 64] [Impact Index Per Article: 21.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 04/19/2021] [Indexed: 12/23/2022] Open
Abstract
The COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G →U and C →U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e., they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. Although previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite.
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Affiliation(s)
- Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
| | - Conor R Walker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
- Department of Genetics, University of Cambridge, United Kingdom
| | - Yatish Turakhia
- Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA
- Genomics Institute, University of California, Santa Cruz, California, USA
| | - Robert Lanfear
- Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT, Australia
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz, California, USA
- Genomics Institute, University of California, Santa Cruz, California, USA
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridgeshire, United Kingdom
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52
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Chan WM, Ip JD, Chu AWH, Tse H, Tam AR, Li X, Kwan MYW, Yau YS, Leung WS, Chik TSH, To WK, Ng ACK, Yip CCY, Poon RWS, Chan KH, Wong SCY, Choi GKY, Lung DC, Cheng VCC, Hung IFN, Yuen KY, To KKW. Phylogenomic analysis of COVID-19 summer and winter outbreaks in Hong Kong: An observational study. THE LANCET REGIONAL HEALTH. WESTERN PACIFIC 2021; 10:100130. [PMID: 33778795 PMCID: PMC7985010 DOI: 10.1016/j.lanwpc.2021.100130] [Citation(s) in RCA: 23] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 03/01/2021] [Accepted: 03/02/2021] [Indexed: 01/04/2023]
Abstract
BACKGROUND Viral genomic surveillance is vital for understanding the transmission of COVID-19. In Hong Kong, breakthrough outbreaks have occurred in July (third wave) and November (fourth wave) 2020. We used whole viral genome analysis to study the characteristics of these waves. METHODS We analyzed 509 SARS-CoV-2 genomes collected from Hong Kong patients between 22nd January and 29th November, 2020. Phylogenetic and phylodynamic analyses were performed, and were interpreted with epidemiological information. FINDINGS During the third and fourth waves, diverse SARS-CoV-2 genomes were identified among imported infections. Conversely, local infections were dominated by a single lineage during each wave, with 96.6% (259/268) in the third wave and 100% (73/73) in the fourth wave belonging to B.1.1.63 and B.1.36.27 lineages, respectively. While B.1.1.63 lineage was imported 2 weeks before the beginning of the third wave, B.1.36.27 lineage has circulated in Hong Kong for 2 months prior to the fourth wave. During the fourth wave, 50.7% (37/73) of local infections in November was identical to the viral genome from an imported case in September. Within B.1.1.63 or B.1.36.27 lineage in our cohort, the most common non-synonymous mutations occurred at the helicase (nsp13) gene. INTERPRETATION Although stringent measures have prevented most imported cases from spreading in Hong Kong, a single lineage with low-level local transmission in October and early November was responsible for the fourth wave. A superspreading event or lower temperature in November may have facilitated the spread of the B.1.36.27 lineage.
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Affiliation(s)
- Wan-Mui Chan
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Jonathan Daniel Ip
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Allen Wing-Ho Chu
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Herman Tse
- Department of Pathology, Hong Kong Children's Hospital, Kowloon, Hong Kong Special Administrative Region, China
| | - Anthony Raymond Tam
- Department of Medicine, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Xin Li
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Mike Yat-Wah Kwan
- Department of Paediatrics and Adolescent Medicine, Princess Margaret Hospital, Hong Kong Special Administrative Region, China
| | - Yat-Sun Yau
- Department of Paediatrics, Queen Elizabeth Hospital, Kowloon, Hong Kong Special Administrative Region, China
| | - Wai-Shing Leung
- Department of Medicine and Geriatrics, Princess Margaret Hospital, Hong Kong Special Administrative Region, China
| | - Thomas Shiu-Hong Chik
- Department of Medicine and Geriatrics, Princess Margaret Hospital, Hong Kong Special Administrative Region, China
| | - Wing-Kin To
- Department of Pathology, Princess Margaret Hospital, Hong Kong Special Administrative Region, China
| | - Anthony Chin-Ki Ng
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Cyril Chik-Yan Yip
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Rosana Wing-Shan Poon
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Kwok-Hung Chan
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Sally Cheuk-Ying Wong
- Department of Pathology, Hong Kong Children's Hospital, Kowloon, Hong Kong Special Administrative Region, China
| | - Garnet Kwan-Yue Choi
- Department of Pathology, Hong Kong Children's Hospital, Kowloon, Hong Kong Special Administrative Region, China
- Department of Pathology, Queen Elizabeth Hospital, Kowloon, Hong Kong Special Administrative Region, China
| | - David Christopher Lung
- Department of Pathology, Hong Kong Children's Hospital, Kowloon, Hong Kong Special Administrative Region, China
- Department of Pathology, Queen Elizabeth Hospital, Kowloon, Hong Kong Special Administrative Region, China
| | - Vincent Chi-Chung Cheng
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Ivan Fan-Ngai Hung
- Department of Medicine, Queen Mary Hospital, Hong Kong Special Administrative Region, China
- Department of Medicine, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
| | - Kwok-Yung Yuen
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
| | - Kelvin Kai-Wang To
- State Key Laboratory for Emerging Infectious Diseases, Carol Yu Centre for Infection, Department of Microbiology, Li Ka Shing Faculty of Medicine, The University of Hong Kong, Pokfulam, Hong Kong Special Administrative Region, China
- Department of Microbiology, Queen Mary Hospital, Hong Kong Special Administrative Region, China
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53
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Wang M, Withers JB, Ricchiuto P, Voitalov I, McAnally M, Sanchez HN, Saleh A, Akmaev VR, Ghiassian SD. A systems-based method to repurpose marketed therapeutics for antiviral use: a SARS-CoV-2 case study. Life Sci Alliance 2021; 4:e202000904. [PMID: 33593923 PMCID: PMC7893815 DOI: 10.26508/lsa.202000904] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2020] [Revised: 02/04/2021] [Accepted: 02/05/2021] [Indexed: 01/02/2023] Open
Abstract
This study describes two complementary methods that use network-based and sequence similarity tools to identify drug repurposing opportunities predicted to modulate viral proteins. This approach could be rapidly adapted to new and emerging viruses. The first method built and studied a virus-host-physical interaction network; a three-layer multimodal network of drug target proteins, human protein-protein interactions, and viral-host protein-protein interactions. The second method evaluated sequence similarity between viral proteins and other proteins, visualized by constructing a virus-host-similarity interaction network. Methods were validated on the human immunodeficiency virus, hepatitis B, hepatitis C, and human papillomavirus, then deployed on SARS-CoV-2. Comparison of virus-host-physical interaction predictions to known antiviral drugs had AUCs of 0.69, 0.59, 0.78, and 0.67, respectively, reflecting that the scores are predictive of effective drugs. For SARS-CoV-2, 569 candidate drugs were predicted, of which 37 had been included in clinical trials for SARS-CoV-2 (AUC = 0.75, P-value 3.21 × 10-3). As further validation, top-ranked candidate antiviral drugs were analyzed for binding to protein targets in silico; binding scores generated by BindScope indicated a 70% success rate.
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Affiliation(s)
| | | | | | | | | | | | - Alif Saleh
- Scipher Medicine Corporation, Waltham, MA, USA
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54
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Thornlow B, Hinrichs AS, Jain M, Dhillon N, La S, Kapp JD, Anigbogu I, Cassatt-Johnstone M, McBroome J, Haeussler M, Turakhia Y, Chang T, Olsen HE, Sanford J, Stone M, Vaske O, Bjork I, Akeson M, Shapiro B, Haussler D, Kilpatrick AM, Corbett-Detig R. A new SARS-CoV-2 lineage that shares mutations with known Variants of Concern is rejected by automated sequence repository quality control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.04.05.438352. [PMID: 33851162 PMCID: PMC8043452 DOI: 10.1101/2021.04.05.438352] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
We report a SARS-CoV-2 lineage that shares N501Y, P681H, and other mutations with known variants of concern, such as B.1.1.7. This lineage, which we refer to as B.1.x (COG-UK sometimes references similar samples as B.1.324.1), is present in at least 20 states across the USA and in at least six countries. However, a large deletion causes the sequence to be automatically rejected from repositories, suggesting that the frequency of this new lineage is underestimated using public data. Recent dynamics based on 339 samples obtained in Santa Cruz County, CA, USA suggest that B.1.x may be increasing in frequency at a rate similar to that of B.1.1.7 in Southern California. At present the functional differences between this variant B.1.x and other circulating SARS-CoV-2 variants are unknown, and further studies on secondary attack rates, viral loads, immune evasion and/or disease severity are needed to determine if it poses a public health concern. Nonetheless, given what is known from well-studied circulating variants of concern, it seems unlikely that the lineage could pose larger concerns for human health than many already globally distributed lineages. Our work highlights a need for rapid turnaround time from sequence generation to submission and improved sequence quality control that removes submission bias. We identify promising paths toward this goal.
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Affiliation(s)
- Bryan Thornlow
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
| | | | - Miten Jain
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
| | - Namrita Dhillon
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
| | - Scott La
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
| | - Joshua D. Kapp
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz
| | - Ikenna Anigbogu
- Department of Biomolecular Engineering, University of California, Santa Cruz
| | | | - Jakob McBroome
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
| | | | - Yatish Turakhia
- Genomics Institute, University of California, Santa Cruz
- Howard Hughes Medical Institute, University of California, Santa Cruz
| | - Terren Chang
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
| | - Hugh E Olsen
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
| | - Jeremy Sanford
- Genomics Institute, University of California, Santa Cruz
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
- Department of Molecular Cellular and Developmental Biology, University of California, Santa Cruz
| | - Michael Stone
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
- Department of Chemistry and Biochemistry, University of California, Santa Cruz
| | - Olena Vaske
- Genomics Institute, University of California, Santa Cruz
- Molecular Diagnostics Laboratory, University of California, Santa Cruz
- Department of Molecular Cellular and Developmental Biology, University of California, Santa Cruz
| | - Isabel Bjork
- Genomics Institute, University of California, Santa Cruz
| | - Mark Akeson
- Department of Biomolecular Engineering, University of California, Santa Cruz
| | - Beth Shapiro
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz
- Howard Hughes Medical Institute, University of California, Santa Cruz
| | - David Haussler
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
- Howard Hughes Medical Institute, University of California, Santa Cruz
| | - A. Marm Kilpatrick
- Department of Ecology and Evolutionary Biology, University of California, Santa Cruz
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California, Santa Cruz
- Genomics Institute, University of California, Santa Cruz
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55
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Ahsan MA, Liu Y, Feng C, Zhou Y, Ma G, Bai Y, Chen M. Bioinformatics resources facilitate understanding and harnessing clinical research of SARS-CoV-2. Brief Bioinform 2021; 22:714-725. [PMID: 33432321 PMCID: PMC7929412 DOI: 10.1093/bib/bbaa416] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2020] [Revised: 11/18/2020] [Accepted: 12/19/2020] [Indexed: 12/17/2022] Open
Abstract
The coronavirus disease 2019 (COVID-19) pandemic, caused by the coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has created an unprecedented threat to public health. The pandemic has been sweeping the globe, impacting more than 200 countries, with more outbreaks still lurking on the horizon. At the time of the writing, no approved drugs or vaccines are available to treat COVID-19 patients, prompting an urgent need to decipher mechanisms underlying the pathogenesis and develop curative treatments. To fight COVID-19, researchers around the world have provided specific tools and molecular information for SARS-CoV-2. These pieces of information can be integrated to aid computational investigations and facilitate clinical research. This paper reviews current knowledge, the current status of drug development and various resources for key steps toward effective treatment of COVID-19, including the phylogenetic characteristics, genomic conservation and interaction data. The final goal of this paper is to provide information that may be utilized in bioinformatics approaches and aid target prioritization and drug repurposing. Several SARS-CoV-2-related tools/databases were reviewed, and a web-portal named OverCOVID (http://bis.zju.edu.cn/overcovid/) is constructed to provide a detailed interpretation of SARS-CoV-2 basics and share a collection of resources that may contribute to therapeutic advances. These information could improve researchers' understanding of SARS-CoV-2 and help to accelerate the development of new antiviral treatments.
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Affiliation(s)
- Md Asif Ahsan
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Yongjing Liu
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Cong Feng
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Yincong Zhou
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Guangyuan Ma
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
| | - Youhuang Bai
- Department of Bioinformatics, Fujian Agriculture and Forestry University, Fuzhou, 350002, China
| | - Ming Chen
- Department of Bioinformatics, College of Life Sciences; The First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou 310058, China
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56
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Chrisman BS, Paskov K, Stockham N, Tabatabaei K, Jung JY, Washington P, Varma M, Sun MW, Maleki S, Wall DP. Indels in SARS-CoV-2 occur at template-switching hotspots. BioData Min 2021; 14:20. [PMID: 33743803 PMCID: PMC7980745 DOI: 10.1186/s13040-021-00251-0] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Accepted: 02/23/2021] [Indexed: 11/10/2022] Open
Abstract
The evolutionary dynamics of SARS-CoV-2 have been carefully monitored since the COVID-19 pandemic began in December 2019. However, analysis has focused primarily on single nucleotide polymorphisms and largely ignored the role of insertions and deletions (indels) as well as recombination in SARS-CoV-2 evolution. Using sequences from the GISAID database, we catalogue over 100 insertions and deletions in the SARS-CoV-2 consensus sequences. We hypothesize that these indels are artifacts of recombination events between SARS-CoV-2 replicates whereby RNA-dependent RNA polymerase (RdRp) re-associates with a homologous template at a different loci ("imperfect homologous recombination"). We provide several independent pieces of evidence that suggest this. (1) The indels from the GISAID consensus sequences are clustered at specific regions of the genome. (2) These regions are also enriched for 5' and 3' breakpoints in the transcription regulatory site (TRS) independent transcriptome, presumably sites of RNA-dependent RNA polymerase (RdRp) template-switching. (3) Within raw reads, these indel hotspots have cases of both high intra-host heterogeneity and intra-host homogeneity, suggesting that these indels are both consequences of de novo recombination events within a host and artifacts of previous recombination. We briefly analyze the indels in the context of RNA secondary structure, noting that indels preferentially occur in "arms" and loop structures of the predicted folded RNA, suggesting that secondary structure may be a mechanism for TRS-independent template-switching in SARS-CoV-2 or other coronaviruses. These insights into the relationship between structural variation and recombination in SARS-CoV-2 can improve our reconstructions of the SARS-CoV-2 evolutionary history as well as our understanding of the process of RdRp template-switching in RNA viruses.
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Affiliation(s)
| | - Kelley Paskov
- Department of Biomedical Data Science, Stanford University, Stanford, USA
| | - Nate Stockham
- Department of Neuroscience, Stanford University, Stanford, USA
| | - Kevin Tabatabaei
- Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | - Jae-Yoon Jung
- Department of Biomedical Data Science, Stanford University, Stanford, USA
| | - Peter Washington
- Department of Bioengineering, Stanford University, Stanford, USA
| | - Maya Varma
- Department of Computer Science, Stanford University, Stanford, USA
| | - Min Woo Sun
- Department of Biomedical Data Science, Stanford University, Stanford, USA
| | - Sepideh Maleki
- Department of Computer Science, University of Texas Austin, Austin, USA
| | - Dennis P Wall
- Department of Biomedical Data Science, Stanford University, Stanford, USA.
- Department of Pediatrics (Systems Medicine), Stanford University, Stanford, USA.
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Bousali M, Dimadi A, Kostaki EG, Tsiodras S, Nikolopoulos GK, Sgouras DN, Magiorkinis G, Papatheodoridis G, Pogka V, Lourida G, Argyraki A, Angelakis E, Sourvinos G, Beloukas A, Paraskevis D, Karamitros T. SARS-CoV-2 Molecular Transmission Clusters and Containment Measures in Ten European Regions during the First Pandemic Wave. Life (Basel) 2021; 11:life11030219. [PMID: 33803490 PMCID: PMC8001481 DOI: 10.3390/life11030219] [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: 01/18/2021] [Revised: 02/12/2021] [Accepted: 03/03/2021] [Indexed: 12/23/2022] Open
Abstract
Background: The spatiotemporal profiling of molecular transmission clusters (MTCs) using viral genomic data can effectively identify transmission networks in order to inform public health actions targeting SARS-CoV-2 spread. Methods: We used whole genome SARS-CoV-2 sequences derived from ten European regions belonging to eight countries to perform phylogenetic and phylodynamic analysis. We developed dedicated bioinformatics pipelines to identify regional MTCs and to assess demographic factors potentially associated with their formation. Results: The total number and the scale of MTCs varied from small household clusters identified in all regions, to a super-spreading event found in Uusimaa-FI. Specific age groups were more likely to belong to MTCs in different regions. The clustered sequences referring to the age groups 50–100 years old (y.o.) were increased in all regions two weeks after the establishment of the lockdown, while those referring to the age group 0–19 y.o. decreased only in those regions where schools’ closure was combined with a lockdown. Conclusions: The spatiotemporal profiling of the SARS-CoV-2 MTCs can be a useful tool to monitor the effectiveness of the interventions and to reveal cryptic transmissions that have not been identified through contact tracing.
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Affiliation(s)
- Maria Bousali
- Bioinformatics and Applied Genomics Unit, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (M.B.); (A.D.); (V.P.)
| | - Aristea Dimadi
- Bioinformatics and Applied Genomics Unit, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (M.B.); (A.D.); (V.P.)
| | - Evangelia-Georgia Kostaki
- Department of Hygiene Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 15772 Athens, Greece; (E.-G.K.); (G.M.)
| | - Sotirios Tsiodras
- 4th Department of Internal Medicine & Infectious Diseases, School of Medicine, National and Kapodistrian University of Athens, 15772 Athens, Greece;
| | | | - Dionyssios N. Sgouras
- Laboratory of Medical Microbiology, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (D.N.S.); (E.A.)
| | - Gkikas Magiorkinis
- Department of Hygiene Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 15772 Athens, Greece; (E.-G.K.); (G.M.)
| | - George Papatheodoridis
- Department of Gastroenterology, Medical School of National and Kapodistrian University of Athens, “Laiko” General Hospital of Athens, 11527 Athens, Greece;
| | - Vasiliki Pogka
- Bioinformatics and Applied Genomics Unit, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (M.B.); (A.D.); (V.P.)
- Laboratory of Medical Microbiology, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (D.N.S.); (E.A.)
| | - Giota Lourida
- Infectious Diseases Clinic A, Sotiria Chest Diseases Hospital, 11527 Athens, Greece; (G.L.); (A.A.)
| | - Aikaterini Argyraki
- Infectious Diseases Clinic A, Sotiria Chest Diseases Hospital, 11527 Athens, Greece; (G.L.); (A.A.)
| | - Emmanouil Angelakis
- Laboratory of Medical Microbiology, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (D.N.S.); (E.A.)
- IRD, APHM, VITROME, IHU-Mediterranean Infections, Aix Marseille University, 13005 Marseille, France
| | - George Sourvinos
- Laboratory of Clinical Virology, School of Medicine, University of Crete, 71500 Heraklion, Greece;
| | - Apostolos Beloukas
- Department of Biomedical Sciences, University of West Attica, 12243 Athens, Greece
- Institute of Infection and Global Health, University of Liverpool, Liverpool L69 7BE, UK
- Correspondence: (A.B.); (D.P.); (T.K.); Tel.: +30-210-5385697 (A.B.); +30-210-7462114 (D.P.); +30-210-6478871 (T.K.)
| | - Dimitrios Paraskevis
- Department of Hygiene Epidemiology and Medical Statistics, School of Medicine, National and Kapodistrian University of Athens, 15772 Athens, Greece; (E.-G.K.); (G.M.)
- Correspondence: (A.B.); (D.P.); (T.K.); Tel.: +30-210-5385697 (A.B.); +30-210-7462114 (D.P.); +30-210-6478871 (T.K.)
| | - Timokratis Karamitros
- Bioinformatics and Applied Genomics Unit, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (M.B.); (A.D.); (V.P.)
- Laboratory of Medical Microbiology, Department of Microbiology, Hellenic Pasteur Institute, 11521 Athens, Greece; (D.N.S.); (E.A.)
- Correspondence: (A.B.); (D.P.); (T.K.); Tel.: +30-210-5385697 (A.B.); +30-210-7462114 (D.P.); +30-210-6478871 (T.K.)
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Yoshimoto FK. A Biochemical Perspective of the Nonstructural Proteins (NSPs) and the Spike Protein of SARS CoV-2. Protein J 2021; 40:260-295. [PMID: 33629236 PMCID: PMC7904240 DOI: 10.1007/s10930-021-09967-8] [Citation(s) in RCA: 16] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 01/30/2021] [Indexed: 01/18/2023]
Abstract
The global pandemic that shut down the world in 2020 was caused by the virus, SARS CoV-2. The chemistry of the various nonstructural proteins (NSP3, NSP5, NSP12, NSP13, NSP14, NSP15, NSP16) of SARS CoV-2 is discussed. Secondly, a recent major focus of this pandemic is the variant strains of SARS CoV-2 that are increasingly occurring and more transmissible. One strain, called “D614G”, possesses a glycine (G) instead of an aspartate (D) at position 614 of the spike protein. Additionally, other emerging strains called “501Y.V1” and “501Y.V2” have several differences in the receptor binding domain of the spike protein (N501Y) as well as other locations. These structural changes may enhance the interaction between the spike protein and the ACE2 receptor of the host, increasing infectivity. The global pandemic caused by SARS CoV-2 is a rapidly evolving situation, emphasizing the importance of continuing the efforts to interrogate and understand this virus.
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Affiliation(s)
- Francis K Yoshimoto
- The University of Texas at San Antonio (UTSA), Department of Chemistry, San Antonio, TX, 78249-0698, USA.
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Chen AT, Altschuler K, Zhan SH, Chan YA, Deverman BE. COVID-19 CG enables SARS-CoV-2 mutation and lineage tracking by locations and dates of interest. eLife 2021; 10:e63409. [PMID: 33620031 PMCID: PMC7901870 DOI: 10.7554/elife.63409] [Citation(s) in RCA: 69] [Impact Index Per Article: 23.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 01/22/2021] [Indexed: 12/24/2022] Open
Abstract
COVID-19 CG (covidcg.org) is an open resource for tracking SARS-CoV-2 single-nucleotide variations (SNVs), lineages, and clades using the virus genomes on the GISAID database while filtering by location, date, gene, and mutation of interest. COVID-19 CG provides significant time, labor, and cost-saving utility to projects on SARS-CoV-2 transmission, evolution, diagnostics, therapeutics, vaccines, and intervention tracking. Here, we describe case studies in which users can interrogate (1) SNVs in the SARS-CoV-2 spike receptor binding domain (RBD) across different geographical regions to inform the design and testing of therapeutics, (2) SNVs that may impact the sensitivity of commonly used diagnostic primers, and (3) the emergence of a dominant lineage harboring an S477N RBD mutation in Australia in 2020. To accelerate COVID-19 efforts, COVID-19 CG will be upgraded with new features for users to rapidly pinpoint mutations as the virus evolves throughout the pandemic and in response to therapeutic and public health interventions.
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Affiliation(s)
- Albert Tian Chen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and HarvardCambridgeUnited States
| | | | - Shing Hei Zhan
- Department of Zoology & Biodiversity Research Centre, the University of British ColumbiaVancouverCanada
- Fusion Genomics CorporationBurnabyCanada
| | - Yujia Alina Chan
- Stanley Center for Psychiatric Research, Broad Institute of MIT and HarvardCambridgeUnited States
| | - Benjamin E Deverman
- Stanley Center for Psychiatric Research, Broad Institute of MIT and HarvardCambridgeUnited States
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Fiocchi A, Jensen-Jarolim E. SARS-COV-2, can you be over it? World Allergy Organ J 2021; 14:100514. [PMID: 33552379 PMCID: PMC7846213 DOI: 10.1016/j.waojou.2021.100514] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2020] [Revised: 01/18/2021] [Accepted: 01/19/2021] [Indexed: 12/16/2022] Open
Abstract
OBJECTIVES Uncertainty has surrounded the duration of immunity against SARS CoV-2. This concerns both the duration of vaccine immunity and the duration of natural immunity. We aim to critically review the information available today, and draw practical conclusions. METHODS This is a narrative review of the recently published information on the topic, compared with the knowledge we already have of the behavior of various viral infectious agents. RESULTS It is too early to have any meaningful information on the duration of vaccine immunity against SARS CoV-2. For those who already had the infeciton, the rate of reinfection is very low. Most reinfections are due to laboratory errors, to incomplete cure of the primary infection, to the supervening immunodeficiency of the host, or to pre-existing immunodeficiency made evident by the SARS CoV-2 infection. The available studies on the immunology of the infection converge in indicating that it generates a robust and persistent immunity. This behavior does not differ from that of respiratory viruses known to date: in naturally occurring viral respiratory infections, reinfections are exceptional. CONCLUSIONS AND IMPLICATIONS The civil community awaits suggestions from scientists not only to protect susceptible people, but to be able to safely resume activities made uncertain by the pandemic. From the information we have to-date, we suggest that, in principle, patients who have already overcome the infection should not be prioritized to the SARS CoV-2 vaccine. Instead, they could be provided with an immunological passport that allows them to resume a normal social life.
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Affiliation(s)
- Alessandro Fiocchi
- Allergy Unit, Bambino Gesù Children's Hospital, IRCCS, Piazza Sant'Onofrio 4, 00165, Rome, Italy
| | - Erika Jensen-Jarolim
- The Interuniversity Messerli Research Institute of the University of Veterinary Medicine Vienna, Medical University Vienna and University Vienna, Vienna, Austria
- Institute of Pathophysiology and Allergy Research, Center of Pathophysiology, Infectivology and Immunology, Medical University of Vienna, Vienna, Austria
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De Maio N, Walker CR, Turakhia Y, Lanfear R, Corbett-Detig R, Goldman N. Mutation rates and selection on synonymous mutations in SARS-CoV-2. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2021:2021.01.14.426705. [PMID: 33469589 PMCID: PMC7814826 DOI: 10.1101/2021.01.14.426705] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
The COVID-19 pandemic has seen an unprecedented response from the sequencing community. Leveraging the sequence data from more than 140,000 SARS-CoV-2 genomes, we study mutation rates and selective pressures affecting the virus. Understanding the processes and effects of mutation and selection has profound implications for the study of viral evolution, for vaccine design, and for the tracking of viral spread. We highlight and address some common genome sequence analysis pitfalls that can lead to inaccurate inference of mutation rates and selection, such as ignoring skews in the genetic code, not accounting for recurrent mutations, and assuming evolutionary equilibrium. We find that two particular mutation rates, G→U and C→U, are similarly elevated and considerably higher than all other mutation rates, causing the majority of mutations in the SARS-CoV-2 genome, and are possibly the result of APOBEC and ROS activity. These mutations also tend to occur many times at the same genome positions along the global SARS-CoV-2 phylogeny (i.e., they are very homoplasic). We observe an effect of genomic context on mutation rates, but the effect of the context is overall limited. While previous studies have suggested selection acting to decrease U content at synonymous sites, we bring forward evidence suggesting the opposite.
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Affiliation(s)
- Nicola De Maio
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Conor R Walker
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
| | - Yatish Turakhia
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Robert Lanfear
- Department of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, ACT 2601, Australia
| | - Russell Corbett-Detig
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA 95064, USA
| | - Nick Goldman
- European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Genome Campus, Hinxton, Cambridgeshire, CB10 1SD, UK
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