2021, Number 2
<< Back Next >>
Revista Cubana de Información en Ciencias de la Salud (ACIMED) 2021; 32 (2)
Nextstrain: a tool to analyze the molecular epidemiology of SARSCoV- 2
Iglesias-Osores S, Alcántara-Mimbela M, Arce-Gil Z, Córdova-Rojas LM, López-López E, Rafael-Heredia A
Language: Spanish
References: 38
Page: 1-22
PDF size: 653.78 Kb.
ABSTRACT
Worldwide concern about the novel coronavirus (2019-nCoV) as a global threat
to public health is the reason for the exponential growth of phylogenetic
analyses. The purpose of this review was to describe the mode of operation and
advantages of the tool Nextstrain, as well as the sequencing of the SARS-CoV-2
virus worldwide. The interface of the Nextstrain page was used to show its
functions and data visualization modes. These were downloaded from the
website GISAID to show the number of SARS-CoV-2 sequencing processes
performed so far. Nextstrain is an open code project created by bioinformatics
biologists to make good use of the scientific and public health potential of data
about genomes of pathogens. Nextstrain consists in a set of tools operating with
unprocessed sequences (in FASTA format). Nextstrain performs a sequence
alignment of the input data into a multiple sequence alignment based on fast
Fourier transform. Its use is based on two software applications: Augur and
Auspice. Nextstrain is an efficient tool by which lay people may obtain
epidemiological data in a simple manner. It may be used in the public health
sector, since it shows real time data about epidemics and their geographic distribution. It may also be used to follow-up outbreaks, as is the case with
COVID-19.
REFERENCES
Benvenuto D, Giovanetti M, Ciccozzi A, Spoto S, Angeletti S, Ciccozzi M.The 2019-new coronavirus epidemic: Evidence for virus evolution. J Med Virol[Internet]. 2020 [acceso: 25/07/2020];92(4):455-9. Disponible en:https://onlinelibrary.wiley.com/doi/full/10.1002/jmv.25688
Fleming PL, Wortley PM, Karon JM, DeCock KM, Janssen RS. Tracking theHIV epidemic: Current issues, future challenges [Internet]. Am J Publ Health.2000 [acceso: 25/07/2020];90(7):1037-41. Disponible en:https://www.pmc/articles/PMC1446284/?report=abstract
Pastor-Satorras R, Castellano C, Van Mieghem P, Vespignani A. Epidemicprocesses in complex networks. Rev Mod Phys [Internet]. 2015 [acceso:25/07/2020];87(3):925. Disponible en:https://journals.aps.org/rmp/abstract/10.1103/RevModPhys.87.925
Keeling MJ, Eames KT. Networks and epidemic models. J Roy Soc Interface[Internet]. 2005 [acceso: 25/07/2020];2(4):295-307. Disponible en:https://royalsocietypublishing.org/doi/10.1098/rsif.2005.0051
Brockmann D. Digital epidemiology. Bundesgesundh Gesundheits Gesundh.2020;63(2):166-75.
Ladner JT, Grubaugh ND, Pybus OG, Andersen KG. Precision epidemiologyfor infectious disease control. Nat Med. 2019;25(2):206-11.
von Bubnoff A. Next-Generation Sequencing: The Race Is On. Cell Press.2008;132:721-3.
Sagulenko P, Puller V, Neher RA. TreeTime: Maximum-likelihoodphylodynamic analysis. Virus Evol. 2018;4(1):1.
Suchard MA, Lemey P, Baele G, Ayres DL, Drummond AJ, Rambaut A.Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10.Virus Evol [Internet]. 2018 [acceso: 25/07/2020];4(1). Disponible en:https://pubmed.ncbi.nlm.nih.gov/29942656/
Hadfield J, Megill C, Bell SM, Huddleston J, Potter B, Callender C, et al.Nextstrain: real-time tracking of pathogen evolution. Bioinformatics[Internet]. 2018 [acceso: 10/04/2020];34(23):4121-3. Disponible en:https://academic.oup.com/bioinformatics/article/34/23/4121/5001388
Hadfield J, Brito AF, Swetnam DM, Vogels CBF, Tokarz RE, Andersen KG,et al. Twenty years of West Nile virus spread and evolution in the Americasvisualized by Nextstrain [Internet]. PLoS Pathogens: Public Library of Science;2019 [acceso: 25/07/2020]. p. e1008042. Disponible en:https://doi.org/10.1371/journal.ppat.1008042
Pearson WR. Finding Protein and Nucleotide Similarities with FASTA. CurrProtoc Bioinform [Internet]. 2016 [acceso: 26/07/2020];53(1):391-925.Disponible en:https://onlinelibrary.wiley.com/doi/abs/10.1002/0471250953.bi0309s53
Katoh K, Standley DM. MAFFT Multiple Sequence Alignment Software:Improvements in Performance and Usability. Mol Biol Evol [Internet].2013;30(4):772-80. DOI: https://doi.org/10.1093/molbev/mst010
Lanave C, Preparata G, Sacone C, Serio G. A new method for calculatingevolutionary substitution rates. J Mol Evol [Internet]. 1984 [acceso:24/07/2020];20(1):86-93. Disponible en:https://link.springer.com/article/10.1007/BF02101990
To TH, Jung M, Lycett S, Gascuel O. Fast Dating Using Least-SquaresCriteria and Algorithms. Syst Biol [Internet]. 2015;65(1):82-97. DOI:https://doi.org/10.1093/sysbio/syv068
Junqueira DM, Wilkinson E, Vallari A, Deng X, Achari A, Yu G, et al. Newgenomes from the Congo Basin Expand History of CRF01_AE Origin and Dissemination. AIDS Res Hum Retrovir [Internet]. 2020 [acceso:24/07/2020];36(7):574-82. Disponible en:https://www.liebertpub.com/doi/10.1089/aid.2020.0031
Billion A, Ghai R, Chakraborty T, Hain T. Augur - a computational pipelinefor whole genome microbial surface protein prediction and classification.Bioinformatics [Internet]. 2006;22(22):2819-20. DOI:https://doi.org/10.1093/bioinformatics/btl466
Katoh K, Misawa K, Kuma K, Miyata T. MAFFT: a novel method for rapidmultiple sequence alignment based on fast Fourier transform. Nucleic AcidsRes [Internet]. 2002 [acceso: 25/07/2020];30(14):3059-66. Disponible en:https://pubmed.ncbi.nlm.nih.gov/12136088
Nguyen LT, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast andeffective stochastic algorithm for estimating maximum-likelihood phylogenies.Mol Biol Evol. 2015;32(1):268-74.
Perkel J. Democratic databases: Science on GitHub. Nature [Internet].2016 [acceso: 25/07/2020];538(7623):127-8. Disponible en:http://www.nature.com/news/democratic-databases-science-on-github-1.20719
Elbe S, Buckland-Merrett G. Data, disease and diplomacy: GISAID’sinnovative contribution to global health. Glob Challenges. 2017;1(1):33-46.
Seberg O, Petersen G. Assembling the Tree of Life [Internet]. OxfordUniversity Press; 2006 [acceso: 26/07/2020]. p. 33-46. Disponible en:https://books.google.com.pe/books/about/Assembling_the_Tree_of_Life.html?id=6lXTP0YU6_kC&redir_esc=y
Han AX, Parker E, Scholer F, Maurer-Stroh S, Russell CA. PhylogeneticClustering by Linear Integer Programming (PhyCLIP). Mol Biol Evol [Internet].2019;36(7):1580-95. DOI: https://doi.org/10.1093/molbev/msz053
Tang X, Wu C, Li X, Song Y, Yao X, Wu X, et al. On the origin andcontinuing evolution of SARS-CoV-2. Natl Sci Rev [Internet]. 2020;7(6):1012-23. DOI: https://doi.org/10.1093/nsr/nwaa036
Rambaut A, Holmes EC, O’Toole Á, Hill V, McCrone JT, Ruis C, et al. Adynamic nomenclature proposal for SARS-CoV-2 lineages to assist genomic epidemiology. Nat Microbiol [Internet]. 2020 [acceso: 25/07/2020];1-5.Disponible en:http://www.nature.com/articles/s41564-020-0770-5
Hodcroft EB, Hadfield J, Neher RA, Bedford T. Year-letter genetic cladenaming for SARS-CoV-2 on nextstrain.org [Internet]. Nextstrain. 2020 [acceso:25/07/2020]. Disponible en: https://nextstrain.org/blog/2020-06-02-SARSCoV2-clade-naming
Rife BD, Mavian C, Chen X, Ciccozzi M, Salemi M, Min J, et al.Phylodynamic applications in 21st century global infectious disease research.Glob Heal Res Policy. 2017;2(1):1-10.
Monteil V, Kwon H, Prado P, Hagelkrüys A, Wimmer RA, Stahl M, et al.Inhibition of SARS-CoV-2 Infections in Engineered Human Tissues UsingClinical-Grade Soluble Human ACE2. Cell. 2020;181(4):905-13.
Lee JM, Huddleston J, Doud MB, Hooper KA, Wu NC, Bedford T, et al.Deep mutational scanning of hemagglutinin helps predict evolutionary fates ofhuman H3N2 influenza variants. Proc Natl Acad Sci USA [Internet]. 2018[acceso: 26/07/2020];115(35):E8276-85. Disponible en:https://www.pnas.org/content/115/35/E8276
Yamayoshi S, Kawaoka Y. Current and future influenza vaccines. Nat Med[Internet]. 2019 [acceso: 12/04/2020];25(2):212-20. Disponible en:http://www.nature.com/articles/s41591-018-0340-z
Dolan PT, Whitfield ZJ, Andino R. Mechanisms and Concepts in RNA VirusPopulation Dynamics and Evolution. Annu Rev Virol [Internet]. 2018 [acceso:26/07/2020];5(1):69-92. Disponible en:https://www.annualreviews.org/doi/abs/10.1146/annurev-virology-101416-041718
van de Vossenberg BTLH, Visser M, Bruinsma M, Koenraadt HMS,Westenberg M, Botermans M. Real-time tracking of Tomato brown rugose fruitvirus (ToBRFV) outbreaks in the Netherlands using Nextstrain. bioRxiv[Internet]. 2020 [acceso: 26/07/2020];06(02):129395. Disponible en:http://biorxiv.org/content/early/2020/06/02/2020.06.02.129395.abstract
Vega-Fernández J, Iglesias-Osores S, Tullume-Vergara P. Use of abioinformatic tool for the molecular epidemiology of SARS-CoV-2. Univ MédPinar [Internet]. 2020 [acceso: 14/04/2020];16(3):3-5. Disponible en:http://revgaleno.sld.cu/index.php/ump/article/view/530
Wang JT, Lin YY, Chang SY, Yeh SH, Hu BH, Chen PJ, et al. The role ofphylogenetic analysis in clarifying the infection source of a COVID-19 patient.J Infect. 2020;81(1):147-78.
Fauver JR, Petrone ME, Hodcroft EB, Shioda K, Ehrlich HY, Watts AG, etal. Coast-to-Coast Spread of SARS-CoV-2 during the Early Epidemic in theUnited States. Cell. 2020;181(5):990-6.
Singer JB, Thomson EC, McLauchlan J, Hughes J, Gifford RJ. GLUE: Aflexible software system for virus sequence data. BMC Bioinformatics[Internet]. 2018 [acceso: 26/07/2020];19(1):1-18. Disponible en:https://link.springer.com/articles/10.1186/s12859-018-2459-9
Neher RA, Bedford T. Nextflu: real-time tracking of seasonal influenzavirus evolution in humans. Bioinformatics [Internet]. 2015;31(21):3546-8. DOI:https://doi.org/10.1093/bioinformatics/btv381
Iglesias-Osores S, Iglesias-Osores S, Tullume-Vergara PO, Acosta-Quiroz J,Saavedra-Camacho JL, Rafael-Heredia A. Epidemiología genómica del virusSARS-CoV-2 con una plataforma bioinformática. Univ Méd Pinar [Internet].2020 [acceso: 25/07/2020];16(3):e555. Disponible en:http://revgaleno.sld.cu/index.php/ump/article/view/555