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Oróstica KY, Mohr SB, Dehning J, Bauer S, Medina-Ortiz D, Iftekhar EN, Mujica K, Covarrubias PC, Ulloa S, Castillo AE, Daza-Sánchez A, Verdugo RA, Fernández J, Olivera-Nappa Á, Priesemann V, Contreras S. Early mutational signatures and transmissibility of SARS-CoV-2 Gamma and Lambda variants in Chile. Sci Rep 2024; 14:16000. [PMID: 38987406 PMCID: PMC11237036 DOI: 10.1038/s41598-024-66885-2] [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: 10/24/2023] [Accepted: 07/05/2024] [Indexed: 07/12/2024] Open
Abstract
Genomic surveillance (GS) programmes were crucial in identifying and quantifying the mutating patterns of SARS-CoV-2 during the COVID-19 pandemic. In this work, we develop a Bayesian framework to quantify the relative transmissibility of different variants tailored for regions with limited GS. We use it to study the relative transmissibility of SARS-CoV-2 variants in Chile. Among the 3443 SARS-CoV-2 genomes collected between January and June 2021, where sampling was designed to be representative, the Gamma (P.1), Lambda (C.37), Alpha (B.1.1.7), B.1.1.348, and B.1.1 lineages were predominant. We found that Lambda and Gamma variants' reproduction numbers were 5% (95% CI: [1%, 14%]) and 16% (95% CI: [11%, 21%]) larger than Alpha's, respectively. Besides, we observed a systematic mutation enrichment in the Spike gene for all circulating variants, which strongly correlated with variants' transmissibility during the studied period (r = 0.93, p-value = 0.025). We also characterised the mutational signatures of local samples and their evolution over time and with the progress of vaccination, comparing them with those of samples collected in other regions worldwide. Altogether, our work provides a reliable method for quantifying variant transmissibility under subsampling and emphasises the importance of continuous genomic surveillance.
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Affiliation(s)
| | - Sebastian B Mohr
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Jonas Dehning
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Simon Bauer
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
| | - David Medina-Ortiz
- Departamento de Ingeniería en Computación, Universidad de Magallanes, Punta Arenas, Chile
| | - Emil N Iftekhar
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Karen Mujica
- Sub Department of Molecular Genetics, Institute of Public Health of Chile (ISP), Santiago, Chile
| | - Paulo C Covarrubias
- Sub Department of Molecular Genetics, Institute of Public Health of Chile (ISP), Santiago, Chile
| | - Soledad Ulloa
- Sub Department of Molecular Genetics, Institute of Public Health of Chile (ISP), Santiago, Chile
| | - Andrés E Castillo
- Sub Department of Molecular Genetics, Institute of Public Health of Chile (ISP), Santiago, Chile
| | | | - Ricardo A Verdugo
- Facultad de Medicina, Universidad de Talca, Talca, Chile
- Departamento de Oncología Básico-Clínica, Facultad de Medicina, Universidad de Chile, Santiago, Chile
| | - Jorge Fernández
- Sub Department of Molecular Genetics, Institute of Public Health of Chile (ISP), Santiago, Chile
| | - Álvaro Olivera-Nappa
- Centre for Biotechnology and Bioengineering, Universidad de Chile, Santiago, Chile
- Department of Chemical Engineering, Biotechnology and Materials, Universidad de Chile, Santiago, Chile
| | - Viola Priesemann
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany
| | - Seba Contreras
- Max Planck Institute for Dynamics and Self-Organization, Göttingen, Germany.
- Institute for the Dynamics of Complex Systems, University of Göttingen, Göttingen, Germany.
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Sarmiento Varón L, González-Puelma J, Medina-Ortiz D, Aldridge J, Alvarez-Saravia D, Uribe-Paredes R, Navarrete MA. The role of machine learning in health policies during the COVID-19 pandemic and in long COVID management. Front Public Health 2023; 11:1140353. [PMID: 37113165 PMCID: PMC10126380 DOI: 10.3389/fpubh.2023.1140353] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2023] [Accepted: 03/20/2023] [Indexed: 04/29/2023] Open
Abstract
The ongoing COVID-19 pandemic is arguably one of the most challenging health crises in modern times. The development of effective strategies to control the spread of SARS-CoV-2 were major goals for governments and policy makers. Mathematical modeling and machine learning emerged as potent tools to guide and optimize the different control measures. This review briefly summarizes the SARS-CoV-2 pandemic evolution during the first 3 years. It details the main public health challenges focusing on the contribution of mathematical modeling to design and guide government action plans and spread mitigation interventions of SARS-CoV-2. Next describes the application of machine learning methods in a series of study cases, including COVID-19 clinical diagnosis, the analysis of epidemiological variables, and drug discovery by protein engineering techniques. Lastly, it explores the use of machine learning tools for investigating long COVID, by identifying patterns and relationships of symptoms, predicting risk indicators, and enabling early evaluation of COVID-19 sequelae.
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Affiliation(s)
| | - Jorge González-Puelma
- Centro Asistencial Docente y de Investigación, Universidad de Magallanes, Punta Arenas, Chile
- Escuela de Medicina, Universidad de Magallanes, Punta Arenas, Chile
| | - David Medina-Ortiz
- Departamento de Ingeniería en Computación, Facultad de Ingeniería, Universidad de Magallanes, Punta Arenas, Chile
| | - Jacqueline Aldridge
- Departamento de Ingeniería en Computación, Facultad de Ingeniería, Universidad de Magallanes, Punta Arenas, Chile
| | - Diego Alvarez-Saravia
- Centro Asistencial Docente y de Investigación, Universidad de Magallanes, Punta Arenas, Chile
- Escuela de Medicina, Universidad de Magallanes, Punta Arenas, Chile
| | - Roberto Uribe-Paredes
- Departamento de Ingeniería en Computación, Facultad de Ingeniería, Universidad de Magallanes, Punta Arenas, Chile
| | - Marcelo A. Navarrete
- Centro Asistencial Docente y de Investigación, Universidad de Magallanes, Punta Arenas, Chile
- Escuela de Medicina, Universidad de Magallanes, Punta Arenas, Chile
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3
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Special Issue “Viral and Host Factors Driving the Emergence and the Evolution of the SARS-CoV-2 and Other Coronaviruses”. Viruses 2022; 14:v14081705. [PMID: 36016327 PMCID: PMC9413748 DOI: 10.3390/v14081705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2022] [Accepted: 07/27/2022] [Indexed: 12/04/2022] Open
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4
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Acevedo ML, Gaete-Argel A, Alonso-Palomares L, de Oca MM, Bustamante A, Gaggero A, Paredes F, Cortes CP, Pantano S, Martínez-Valdebenito C, Angulo J, Le Corre N, Ferrés M, Navarrete MA, Valiente-Echeverría F, Soto-Rifo R. Differential neutralizing antibody responses elicited by CoronaVac and BNT162b2 against SARS-CoV-2 Lambda in Chile. Nat Microbiol 2022; 7:524-529. [PMID: 35365787 DOI: 10.1038/s41564-022-01092-1] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Accepted: 02/23/2022] [Indexed: 01/21/2023]
Abstract
SARS-CoV-2 variant Lambda was dominant in several South American countries, including Chile. To ascertain the efficacy of local vaccination efforts, we used pseudotyped viruses to characterize the neutralization capacity of antibodies elicited by CoronaVac (n = 53) and BNT162b2 (n = 56) in healthcare workers from Clínica Santa María and the Faculty of Medicine at Universidad de Chile, as well as in convalescent plasma from individuals infected during the first wave visiting the Hospital Clínico at Pontificia Universidad Católica (n = 30). We observed that BNT162b2 elicits higher neutralizing antibody titres than CoronaVac, with differences ranging from 7.4-fold for the ancestral spike (Wuhan-Hu-1) to 8.2-fold for the Lambda spike and 13-fold for the Delta spike. Compared with the ancestral virus, neutralization against D614G, Alpha, Gamma, Lambda and Delta variants was reduced by between 0.93- and 4.22-fold for CoronaVac, 1.04- and 2.38-fold for BNT162b2, and 1.26- and 2.67-fold for convalescent plasma. Comparative analyses among the spike structures of the different variants suggest that mutations in the spike protein from the Lambda variant, including the 246-252 deletion in an antigenic supersite at the N-terminal domain loop and L452Q/F490S within the receptor-binding domain, may account for immune escape. Interestingly, analyses using pseudotyped and whole viruses showed increased entry rates into HEK293T-ACE2 cells, but reduced replication rates in Vero-E6 cells for the Lambda variant when compared with the Alpha, Gamma and Delta variants. Our data show that inactivated virus and messenger RNA vaccines elicit different levels of neutralizing antibodies with different potency to neutralize SARS-CoV-2 variants, including the variant of interest Lambda.
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Affiliation(s)
- Mónica L Acevedo
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile.,Millennium Institute on Immunology and Immunotherapy, Santiago, Chile
| | - Aracelly Gaete-Argel
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile
| | - Luis Alonso-Palomares
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile
| | | | - Andrés Bustamante
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile
| | - Aldo Gaggero
- Laboratorio de Virología Ambiental, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile
| | - Fabio Paredes
- Departamento de Epidemiología, Ministerio de Salud de Chile, Santiago, Chile
| | - Claudia P Cortes
- Millennium Institute on Immunology and Immunotherapy, Santiago, Chile.,Clínica Santa María, Santiago, Chile.,Departamento de Medicina Centro, Universidad de Chile, Santiago, Chile
| | - Sergio Pantano
- Biomolecular Simulations Group, Instituto Pasteur de Montevideo, Montevideo, Uruguay
| | - Constanza Martínez-Valdebenito
- Departamento de Enfermedades Infecciosas e Inmunología Pediátricas, División de Pediatría, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.,Laboratorio de Infectología y Virología Molecular, Laboratorio de Bioseguridad Nivel 3, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Jenniffer Angulo
- Departamento de Enfermedades Infecciosas e Inmunología Pediátricas, División de Pediatría, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.,Laboratorio de Infectología y Virología Molecular, Laboratorio de Bioseguridad Nivel 3, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Nicole Le Corre
- Departamento de Enfermedades Infecciosas e Inmunología Pediátricas, División de Pediatría, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.,Laboratorio de Infectología y Virología Molecular, Laboratorio de Bioseguridad Nivel 3, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Marcela Ferrés
- Departamento de Enfermedades Infecciosas e Inmunología Pediátricas, División de Pediatría, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile.,Laboratorio de Infectología y Virología Molecular, Laboratorio de Bioseguridad Nivel 3, Escuela de Medicina, Pontificia Universidad Católica de Chile, Santiago, Chile
| | | | - Fernando Valiente-Echeverría
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile. .,Millennium Institute on Immunology and Immunotherapy, Santiago, Chile.
| | - Ricardo Soto-Rifo
- Laboratorio de Virología Molecular y Celular, Programa de Virología, Instituto de Ciencias Biomédicas, Universidad de Chile, Santiago, Chile. .,Millennium Institute on Immunology and Immunotherapy, Santiago, Chile.
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Zimerman RA, Ferrareze PAG, Cadegiani FA, Wambier CG, Fonseca DDN, de Souza AR, Goren A, Rotta LN, Ren Z, Thompson CE. Comparative Genomics and Characterization of SARS-CoV-2 P.1 (Gamma) Variant of Concern From Amazonas, Brazil. Front Med (Lausanne) 2022; 9:806611. [PMID: 35242782 PMCID: PMC8885995 DOI: 10.3389/fmed.2022.806611] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/01/2021] [Accepted: 01/12/2022] [Indexed: 11/23/2022] Open
Abstract
BACKGROUND P.1 lineage (Gamma) was first described in the State of Amazonas, northern Brazil, in the end of 2020, and has emerged as a very important variant of concern (VOC) of SARS-CoV-2 worldwide. P.1 has been linked to increased infectivity, higher mortality, and immune evasion, leading to reinfections and potentially reduced efficacy of vaccines and neutralizing antibodies. METHODS The samples of 276 patients from the State of Amazonas were sent to a central referral laboratory for sequencing by gold standard techniques, through Illumina MiSeq platform. Both global and regional phylogenetic analyses of the successfully sequenced genomes were conducted through maximum likelihood method. Multiple alignments were obtained including previously obtained unique human SARS-CoV-2 sequences. The evolutionary histories of spike and non-structural proteins from ORF1a of northern genomes were described and their molecular evolution was analyzed for detection of positive (FUBAR, FEL, and MEME) and negative (FEL and SLAC) selective pressures. To further evaluate the possible pathways of evolution leading to the emergence of P.1, we performed specific analysis for copy-choice recombination events. A global phylogenomic analysis with subsampled P.1 and B.1.1.28 genomes was applied to evaluate the relationship among samples. RESULTS Forty-four samples from the State of Amazonas were successfully sequenced and confirmed as P.1 (Gamma) lineage. In addition to previously described P.1 characteristic mutations, we find evidence of continuous diversification of SARS-CoV-2, as rare and previously unseen P.1 mutations were detected in spike and non-structural protein from ORF1a. No evidence of recombination was found. Several sites were demonstrated to be under positive and negative selection, with various mutations identified mostly in P.1 lineage. According to the Pango assignment, phylogenomic analyses indicate all samples as belonging to the P.1 lineage. CONCLUSION P.1 has shown continuous evolution after its emergence. The lack of clear evidence for recombination and the positive selection demonstrated for several sites suggest that this lineage emergence resulted mainly from strong evolutionary forces and progressive accumulation of a favorable signature set of mutations.
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Affiliation(s)
| | | | | | - Carlos Gustavo Wambier
- Department of Dermatology, Warren Alpert Medical School of Brown University, Providence, RI, United States
| | | | | | - Andy Goren
- Applied Biology, Inc., Irvine, CA, United States
| | - Liane Nanci Rotta
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
| | - Zhihua Ren
- Suzhou Kintor Pharmaceutical, Inc., Suzhou, China
| | - Claudia Elizabeth Thompson
- Graduate Program in Health Sciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
- Department of Pharmacosciences, Universidade Federal de Ciências da Saúde de Porto Alegre, Porto Alegre, Brazil
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6
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Buratto D, Saxena A, Ji Q, Yang G, Pantano S, Zonta F. Rapid Assessment of Binding Affinity of SARS-COV-2 Spike Protein to the Human Angiotensin-Converting Enzyme 2 Receptor and to Neutralizing Biomolecules Based on Computer Simulations. Front Immunol 2021; 12:730099. [PMID: 34858396 PMCID: PMC8632240 DOI: 10.3389/fimmu.2021.730099] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/24/2021] [Accepted: 10/25/2021] [Indexed: 12/17/2022] Open
Abstract
SARS-CoV-2 infects humans and causes Coronavirus disease 2019 (COVID-19). The S1 domain of the spike glycoprotein of SARS-CoV-2 binds to human angiotensin-converting enzyme 2 (hACE2) via its receptor-binding domain, while the S2 domain facilitates fusion between the virus and the host cell membrane for entry. The spike glycoprotein of circulating SARS-CoV-2 genomes is a mutation hotspot. Some mutations may affect the binding affinity for hACE2, while others may modulate S-glycoprotein expression, or they could result in a virus that can escape from antibodies generated by infection with the original variant or by vaccination. Since a large number of variants are emerging, it is of vital importance to be able to rapidly assess their characteristics: while changes of binding affinity alone do not always cause direct advantages for the virus, they still can provide important insights on where the evolutionary pressure is directed. Here, we propose a simple and cost-effective computational protocol based on Molecular Dynamics simulations to rapidly screen the ability of mutated spike protein to bind to the hACE2 receptor and selected neutralizing biomolecules. Our results show that it is possible to achieve rapid and reliable predictions of binding affinities. A similar approach can be used to perform preliminary screenings of the potential effects of S-RBD mutations, helping to prioritize the more time-consuming and expensive experimental work.
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Affiliation(s)
- Damiano Buratto
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Abhishek Saxena
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Qun Ji
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Guang Yang
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
| | - Sergio Pantano
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
- Institut Pasteur de Montevideo, Montevideo, Uruguay
| | - Francesco Zonta
- Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China
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