Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos

ilustraciones, diagramas

Autores:
Carabali Mosquera, Oscar Eduardo
Tipo de recurso:
Fecha de publicación:
2023
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/84272
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/84272
https://repositorio.unal.edu.co/
Palabra clave:
570 - Biología::576 - Genética y evolución
Klebsiella pneumoniae
Pseudomonas aeruginosa
Taxa
Secuencia de ADN
DNA sequences
Secuenciación completa del genoma
Klebsiella pneumoniae
Pseudomonas aeruginosa
Tipificación molecular bacteriana
Herramientas Bioinformáticas
Benchmarking
Whole genome sequencing
Klebsiella pneumoniae
Pseudomonas aeruginosa
Bacterial molecular typing
Bioinformatics tools
Benchmarking
Rights
openAccess
License
Atribución-NoComercial-SinDerivadas 4.0 Internacional
id UNACIONAL2_cac7c73236c51e25a7a10f3b97b67806
oai_identifier_str oai:repositorio.unal.edu.co:unal/84272
network_acronym_str UNACIONAL2
network_name_str Universidad Nacional de Colombia
repository_id_str
dc.title.spa.fl_str_mv Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
dc.title.translated.eng.fl_str_mv Evaluation of Bioinformatic tools useful in the typing of Klebsiella pneumoniae and Pseudomonas aeruginosa from whole genome sequencing data
title Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
spellingShingle Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
570 - Biología::576 - Genética y evolución
Klebsiella pneumoniae
Pseudomonas aeruginosa
Taxa
Secuencia de ADN
DNA sequences
Secuenciación completa del genoma
Klebsiella pneumoniae
Pseudomonas aeruginosa
Tipificación molecular bacteriana
Herramientas Bioinformáticas
Benchmarking
Whole genome sequencing
Klebsiella pneumoniae
Pseudomonas aeruginosa
Bacterial molecular typing
Bioinformatics tools
Benchmarking
title_short Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
title_full Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
title_fullStr Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
title_full_unstemmed Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
title_sort Evaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completos
dc.creator.fl_str_mv Carabali Mosquera, Oscar Eduardo
dc.contributor.advisor.none.fl_str_mv Barreto Hernández, Emiliano
dc.contributor.author.none.fl_str_mv Carabali Mosquera, Oscar Eduardo
dc.contributor.researchgroup.spa.fl_str_mv Bioinformática
dc.subject.ddc.spa.fl_str_mv 570 - Biología::576 - Genética y evolución
topic 570 - Biología::576 - Genética y evolución
Klebsiella pneumoniae
Pseudomonas aeruginosa
Taxa
Secuencia de ADN
DNA sequences
Secuenciación completa del genoma
Klebsiella pneumoniae
Pseudomonas aeruginosa
Tipificación molecular bacteriana
Herramientas Bioinformáticas
Benchmarking
Whole genome sequencing
Klebsiella pneumoniae
Pseudomonas aeruginosa
Bacterial molecular typing
Bioinformatics tools
Benchmarking
dc.subject.agrovoc.none.fl_str_mv Klebsiella pneumoniae
Pseudomonas aeruginosa
dc.subject.agrovoc.spa.fl_str_mv Taxa
Secuencia de ADN
dc.subject.agrovoc.eng.fl_str_mv DNA sequences
dc.subject.proposal.spa.fl_str_mv Secuenciación completa del genoma
Klebsiella pneumoniae
Pseudomonas aeruginosa
Tipificación molecular bacteriana
Herramientas Bioinformáticas
Benchmarking
Whole genome sequencing
dc.subject.proposal.eng.fl_str_mv Klebsiella pneumoniae
Pseudomonas aeruginosa
Bacterial molecular typing
Bioinformatics tools
Benchmarking
description ilustraciones, diagramas
publishDate 2023
dc.date.accessioned.none.fl_str_mv 2023-07-26T12:54:22Z
dc.date.available.none.fl_str_mv 2023-07-26T12:54:22Z
dc.date.issued.none.fl_str_mv 2023-06-15
dc.type.spa.fl_str_mv Trabajo de grado - Maestría
dc.type.driver.spa.fl_str_mv info:eu-repo/semantics/masterThesis
dc.type.version.spa.fl_str_mv info:eu-repo/semantics/acceptedVersion
dc.type.content.spa.fl_str_mv Text
dc.type.redcol.spa.fl_str_mv http://purl.org/redcol/resource_type/TM
status_str acceptedVersion
dc.identifier.uri.none.fl_str_mv https://repositorio.unal.edu.co/handle/unal/84272
dc.identifier.instname.spa.fl_str_mv Universidad Nacional de Colombia
dc.identifier.reponame.spa.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
dc.identifier.repourl.spa.fl_str_mv https://repositorio.unal.edu.co/
url https://repositorio.unal.edu.co/handle/unal/84272
https://repositorio.unal.edu.co/
identifier_str_mv Universidad Nacional de Colombia
Repositorio Institucional Universidad Nacional de Colombia
dc.language.iso.spa.fl_str_mv spa
language spa
dc.relation.references.spa.fl_str_mv Alikhan, N. F., Zhou, Z., Sergeant, M. J., & Achtman, M. (2018). A genomic overview of the population structure of Salmonella. In PLoS Genetics (Vol. 14, Issue 4, p. e1007261). Public Library of Science. https://doi.org/10.1371/journal.pgen.1007261
Allard, M. W. (2016). The future of whole-genome sequencing for public health and the clinic. In Journal of Clinical Microbiology (Vol. 54, Issue 8, pp. 1946–1948). American Society for Microbiology. https://doi.org/10.1128/JCM.01082-16
Altmann, A., Weber, P., Bader, D., Preuß, M., Binder, E. B., & Müller-Myhsok, B. (2012). A beginners guide to SNP calling from high-Throughput DNA-sequencing data. In Human Genetics (Vol. 131, Issue 10, pp. 1541–1554). Springer. https://doi.org/10.1007/s00439-012-1213-z
Anani, H., Zgheib, R., Hasni, I., Raoult, D., & Fournier, P. E. (2020). Interest of bacterial pangenome analyses in clinical microbiology. Microbial Pathogenesis, 149. https://doi.org/10.1016/j.micpath.2020.104275
Basset, P., & Blanc, D. S. (2014). Fast and simple epidemiological typing of Pseudomonas aeruginosa using the double-locus sequence typing (DLST) method. European Journal of Clinical Microbiology and Infectious Diseases, 33(6), 927–932. https://doi.org/10.1007/s10096-013-2028-0
Bathke, J., & Lühken, G. (2021). OVarFlow: a resource optimized GATK 4 based Open source Variant calling workFlow. BMC Bioinformatics, 22(1). https://doi.org/10.1186/S12859-021-04317-Y
Bayliss, S. C., Thorpe, H. A., Coyle, N. M., Sheppard, S. K., & Feil, E. J. (2019). PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria. GigaScience, 8(10), 1–9. https://doi.org/10.1093/GIGASCIENCE/GIZ119
Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2017). GenBank. Nucleic Acids Research, 45(D1), D37–D42. https://doi.org/10.1093/nar/gkw1070
Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Ostell, J., Pruitt, K. D., & Sayers, E. W. (2018). GenBank. Nucleic Acids Research, 46(D1), D41–D47. https://doi.org/10.1093/nar/gkx1094
Blanc, D. S., Magalhães, B., Koenig, I., Senn, L., & Grandbastien, B. (2020). Comparison of Whole Genome (wg-) and Core Genome (cg-) MLST (BioNumericsTM) Versus SNP Variant Calling for Epidemiological Investigation of Pseudomonas aeruginosa. Frontiers in Microbiology, 11, 1729. https://doi.org/10.3389/fmicb.2020.01729
Bogaerts, B., Winand, R., Fu, Q., Van Braekel, J., Ceyssens, P.-J., Mattheus, W., Bertrand, S., De Keersmaecker, S. C. J., Roosens, N. H. C., & Vanneste, K. (2019). Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept. Frontiers in Microbiology, 10(MAR), 362. https://doi.org/10.3389/fmicb.2019.00362
Botes, J., Williamson, G., Sinickas, V., & Gürtler, V. (2003). Genomic typing of Pseudomonas aeruginosa isolates by comparison of Riboprinting and PFGE: correlation of experimental results with those predicted from the complete genome sequence of isolate PAO1. Journal of Microbiological Methods, 55(1), 231–240. https://doi.org/10.1016/s0167-7012(03)00156-8
Bou, G., Fernández-Olmos, A., García, C., Sáez-Nieto, J. A., & Valdezate, S. (2011). Métodos de identificación bacteriana en el laboratorio de microbiología. Enfermedades Infecciosas y Microbiología Clínica, 29(8), 601–608. https://doi.org/10.1016/J.EIMC.2011.03.012
Brilhante, M., Gobeli Brawand, S., Endimiani, A., Rohrbach, H., Kittl, S., Willi, B., Schuller, S., & Perreten, V. (2021). Two high-risk clones of carbapenemase-producing Klebsiella pneumoniae that cause infections in pets and are present in the environment of a veterinary referral hospital. Journal of Antimicrobial Chemotherapy, 76(5), 1140–1149. https://doi.org/10.1093/JAC/DKAB028
Buchka, S., Hapfelmeier, A., Gardner, P. P., Wilson, R., & Boulesteix, A. L. (2021). On the optimistic performance evaluation of newly introduced bioinformatic methods. Genome Biology, 22(1). https://doi.org/10.1186/S13059-021-02365-4
Bush, S. J. (2021). Generalizable characteristics of false-positive bacterial variant calls. Microbial Genomics, 7(8). https://doi.org/10.1099/MGEN.0.000615
Bush, S. J., Foster, D., Eyre, D. W., Clark, E. L., de Maio, N., Shaw, L. P., Stoesser, N., Peto, T. E. A., Crook, D. W., & Walker, A. S. (2020). Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism–calling pipelines. GigaScience, 9(2), 1–21. https://doi.org/10.1093/GIGASCIENCE/GIAA007
Carattoli, A., Zankari, E., Garciá-Fernández, A., Larsen, M. V., Lund, O., Villa, L., Aarestrup, F. M., & Hasman, H. (2014). In Silico detection and typing of plasmids using plasmidfinder and plasmid multilocus sequence typing. Antimicrobial Agents and Chemotherapy, 58(7), 3895–3903. https://doi.org/10.1128/AAC.02412-14
Chang, C. H., Chang, Y. C., Underwood, A., Chiou, C. S., & Kao, C. Y. (2007). VNTRDB: A bacterial variable number tandem repeat locus database. Nucleic Acids Research, 35(SUPPL. 1). https://doi.org/10.1093/nar/gkl872
Chen, Y., Gonzalez-Escalona, N., Hammack, T. S., Allard, M. W., Strain, E. A., & Brown, E. W. (2016). Core genome multilocus sequence typing for identification of globally distributed clonal groups and differentiation of outbreak strains of Listeria monocytogenes. Applied and Environmental Microbiology, 82(20), 6258–6272. https://doi.org/10.1128/AEM.01532-16
Clarke, T. H., Brinkac, L. M., Inman, J. M., Sutton, G., & Fouts, D. E. (2018). PanACEA: A bioinformatics tool for the exploration and visualization of bacterial pan-chromosomes. BMC Bioinformatics, 19(1), 246. https://doi.org/10.1186/s12859-018-2250-y
Coll, F., Gouliouris, T., Bruchmann, S., Phelan, J., Raven, K. E., Clark, T. G., Parkhill, J., & Peacock, S. J. (2022). PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies. Communications Biology, 5(1). https://doi.org/10.1038/S42003-022-03194-2
Coll, F., Raven, K. E., Knight, G. M., Blane, B., Harrison, E. M., Leek, D., Enoch, D. A., Brown, N. M., Parkhill, J., & Peacock, S. J. (2020). Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: a genomic epidemiology analysis. The Lancet Microbe, 1(8), e328–e335. https://doi.org/10.1016/S2666-5247(20)30149-X
Dalsass, M., Bodini, M., Lambert, C., Mortier, M. C., Romanelli, M., Medini, D., Muzzi, A., & Brozzi, A. (2019). STRAIN: An R package for multi-locus sequence typing from whole genome sequencing data. BMC Bioinformatics, 20(Suppl 9). https://doi.org/10.1186/s12859-019-2887-1
Das, D., Baruah, R., Sarma Roy, A., Singh, A. K., Deka Boruah, H. P., Kalita, J., & Bora, T. C. (2015). Complete genome sequence analysis of Pseudomonas aeruginosa N002 reveals its genetic adaptation for crude oil degradation. Genomics, 105(3), 182–190. https://doi.org/10.1016/j.ygeno.2014.12.006
De Rosa, F. G., Corcione, S., Pagani, N., & Di Perri, G. (2015). From ESKAPE to ESCAPE, From KPC to CCC. Clinical Infectious Diseases, 60(8), 1289–1290. https://doi.org/10.1093/CID/CIU1170
Deneke, C., Uelze, L., Brendebach, H., Tausch, S. H., & Malorny, B. (2021). Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST. Frontiers in Microbiology, 12, 874. https://doi.org/10.3389/fmicb.2021.649517
Escalona, M., Rocha, S., & Posada, D. (2016). A comparison of tools for the simulation of genomic next-generation sequencing data. In Nature Reviews Genetics (Vol. 17, Issue 8, pp. 459–469). Nature Publishing Group. https://doi.org/10.1038/nrg.2016.57
Ettorchi -Tardy, A., Levif, M., & Michel, P. (2012). Benchmarking: A method for continuous quality improvement in health. Healthcare Policy, 7(4). https://doi.org/10.12927/hcpol.2012.22872
Feijao, P., Yao, H. T., Fornika, D., Gardy, J., Hsiao, W., Chauve, C., & Chindelevitch, L. (2018). MentaLiST - A fast MLST caller for large MLST schemes. Microbial Genomics, 4(2), e000146. https://doi.org/10.1099/mgen.0.000146
Fouts, D. E., Brinkac, L., Beck, E., Inman, J., & Sutton, G. (2012). PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species. Nucleic Acids Research, 40(22). https://doi.org/10.1093/NAR/GKS757
Francisco, A. P., Bugalho, M., Ramirez, M., & Carriço, J. A. (2009). Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach. BMC Bioinformatics, 10(1), 1–15. https://doi.org/10.1186/1471-2105-10-152/FIGURES/5
Francisco, A. P., Vaz, C., Monteiro, P. T., Melo-Cristino, J., Ramirez, M., & Carriço, J. A. (2012). PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods. BMC Bioinformatics, 13(1), 87. https://doi.org/10.1186/1471-2105-13-87
Friedman, S., Gauthier, L., Farjoun, Y., & Banks, E. (2020). Lean and deep models for more accurate filtering of SNP and INDEL variant calls. Bioinformatics (Oxford, England), 36(7), 2060–2067. https://doi.org/10.1093/BIOINFORMATICS/BTZ901
Gardner, S. N., & Hall, B. G. (2013). When whole-genome alignments just won’t work: KSNP v2 software for alignment-free SNP discovery and phylogenetics of hundreds of microbial genomes. PLoS ONE, 8(12). https://doi.org/10.1371/journal.pone.0081760
Gardner, S. N., Slezak, T., & Hall, B. G. (2015). kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics (Oxford, England), 31(17), 2877–2878. https://doi.org/10.1093/BIOINFORMATICS/BTV271
Guigon, G., Cheval, J., Cahuzac, R., & Brisse, S. (2008). MLVA-NET--a standardised web database for bacterial genotyping and surveillance. Euro Surveillance : Bulletin Européen Sur Les Maladies Transmissibles = European Communicable Disease Bulletin, 13(19), 18863. https://doi.org/10.2807/ese.13.19.18863-en
Guimarães, L. C., Florczak-Wyspianska, J., Jesus, L. B. de, Viana, M. V. C., Silva, A., Ramos, R. T. J., Soares, S. de C., & Soares, S. de C. (2015). Inside the Pan-genome - Methods and Software Overview. Current Genomics, 16(4), 245. https://doi.org/10.2174/1389202916666150423002311
Gupta, A., Jordan, I. K., & Rishishwar, L. (2017). stringMLST: a fast k-mer based tool for multilocus sequence typing. Bioinformatics, 33(1), 119–121. https://doi.org/10.1093/BIOINFORMATICS/BTW586
Gupta, A. K. (1996). Classification. Springer Geology, 69–87. https://doi.org/10.1007/978-81-322-2083-1_3
Hall, B. G. (2014). SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments. PLoS ONE, 9(2), 90490. https://doi.org/10.1371/journal.pone.0090490
Hallgren, M. B., Overballe-Petersen, S., Lund, O., Hasman, H., & Clausen, P. T. L. C. (2021). MINTyper: an outbreak-detection method for accurate and rapid SNP typing of clonal clusters with noisy long reads. Biology Methods and Protocols, 6(1). https://doi.org/10.1093/BIOMETHODS/BPAB008
Henry, V. J., Bandrowski, A. E., Pepin, A. S., Gonzalez, B. J., & Desfeux, A. (2014). OMICtools: an informative directory for multi-omic data analysis. Database: The Journal of Biological Databases and Curation, 2014. https://doi.org/10.1093/DATABASE/BAU069
INS. (2018). INFORME DE RESULTADOS DE LA VIGILANCIA POR LABORATORIO DE RESISTENCIA ANTIMICROBIANA EN INFECCIONES ASOCIADAS A LA ATENCIÓN EN SALUD.
Jolley, K. A., Bliss, C. M., Bennett, J. S., Bratcher, H. B., Brehony, C., Colles, F. M., Wimalarathna, H., Harrison, O. B., Sheppard, S. K., Cody, A. J., & Maiden, M. C. J. (2012). Ribosomal multilocus sequence typing: Universal characterization of bacteria from domain to strain. Microbiology, 158(4), 1005–1015. https://doi.org/10.1099/mic.0.055459-0
Jolley, K. A., Chan, M. S., & Maiden, M. C. J. (2004). mlstdbNet - Distributed multi-locus sequence typing (MLST) databases. BMC Bioinformatics, 5(1), 86. https://doi.org/10.1186/1471-2105-5-86
Jolley, K. A., & Maiden, M. C. J. (2014). Using MLST to study bacterial variation: Prospects in the genomic era. Future Microbiology, 9(5), 623–630. https://doi.org/10.2217/fmb.14.24
Jonas, D., Spitzmüller, B., Daschner, F. D., Verhoef, J., & Brisse, S. (2004). Discrimination of Klebsiella pneumoniae and Klebsiella oxytoca phylogenetic groups and other Klebsiella species by use of amplified fragment length polymorphism. Research in Microbiology, 155(1), 17–23.
Kimura, B. (2018). Will the emergence of core genome MLST end the role of in silico MLST? In Food Microbiology (Vol. 75, pp. 28–36). Academic Press. https://doi.org/10.1016/j.fm.2017.09.003
Kingry, L. C., Rowe, L. A., Respicio-Kingry, L. B., Beard, C. B., Schriefer, M. E., & Petersen, J. M. (2016). Whole genome multilocus sequence typing as an epidemiologic tool for Yersinia pestis. Diagnostic Microbiology and Infectious Disease, 84(4), 275–280. https://doi.org/10.1016/j.diagmicrobio.2015.12.003
Kozyreva, V. K., Truong, C. L., Greninger, A. L., Crandall, J., Mukhopadhyay, R., & Chaturvedi, V. (2017). Validation and implementation of clinical laboratory improvements act-compliant whole-genome sequencing in the public health microbiology laboratory. Journal of Clinical Microbiology, 55(8), 2502–2520. https://doi.org/10.1128/JCM.00361-17
Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution, 35(6), 1547. https://doi.org/10.1093/MOLBEV/MSY096
Kwong, J. C., Mccallum, N., Sintchenko, V., & Howden, B. P. (2015). Whole genome sequencing in clinical and public health microbiology. Pathology, 47(3), 199–210. https://doi.org/10.1097/PAT.0000000000000235
Labbé, G., Kruczkiewicz, P., Robertson, J., Mabon, P., Schonfeld, J., Kein, D., Rankin, M. A., Gopez, M., Hole, D., Son, D., Knox, N., Laing, C. R., Bessonov, K., Taboada, E. N., Yoshida, C., Ziebell, K., Nichani, A., Johnson, R. P., Van Domselaar, G., & Nash, J. H. E. (2021). Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel. Microbial Genomics, 7(9), 651. https://doi.org/10.1099/MGEN.0.000651
Larsen, M. V., Cosentino, S., Lukjancenko, O., Saputra, D., Rasmussen, S., Hasman, H., Sicheritz-Pontén, T., Aarestrup, F. M., Ussery, D. W., & Lund, O. (2014). Benchmarking of methods for genomic taxonomy. Journal of Clinical Microbiology, 52(5), 1529–1539. https://doi.org/10.1128/JCM.02981-13
Letunic, I., & Bork, P. (2019). Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Research, 47(W1), W256. https://doi.org/10.1093/NAR/GKZ239
Li, F., Wang, Y., Li, C., Marquez-Lago, T. T., Leier, A., Rawlings, N. D., Haffari, G., Revote, J., Akutsu, T., Chou, K. C., Purcell, A. W., Pike, R. N., Webb, G. I., Ian Smith, A., Lithgow, T., Daly, R. J., Whisstock, J. C., & Song, J. (2019). Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods. Briefings in Bioinformatics, 20(6), 2150. https://doi.org/10.1093/BIB/BBY077
Li, H. (2011). A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics, 27(21), 2987–2993. https://doi.org/10.1093/bioinformatics/btr509
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., & Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics (Oxford, England), 25(16), 2078–2079
Li, W., Raoult, D., & Fournier, P. E. (2009). Bacterial strain typing in the genomic era. In FEMS Microbiology Reviews (Vol. 33, Issue 5, pp. 892–916). Oxford Academic. https://doi.org/10.1111/j.1574-6976.2009.00182.x
Lindgreen, S., Adair, K. L., & Gardner, P. P. (2016). An evaluation of the accuracy and speed of metagenome analysis tools. Scientific Reports, 6. https://doi.org/10.1038/SREP19233
Liu, J., Li, L., Peters, B. M., Li, B., Chen, D., Xu, Z., & Shirtliff, M. E. (2018). Complete genomic analysis of multidrug-resistance Pseudomonas aeruginosa Guangzhou-Pae617, the host of megaplasmid pBM413. Microbial Pathogenesis, 117, 265–269. https://doi.org/10.1016/j.micpath.2018.02.049
Liu, Y. Y., Chiou, C. S., & Chen, C. C. (2016). PGAdb-builder: A web service tool for creating pan-genome allele database for molecular fine typing. Scientific Reports, 6. https://doi.org/10.1038/srep36213
Liu, Y. Y., Lin, J. W., & Chen, C. C. (2019). Cano-wgMLST_BacCompare: A bacterial genome analysis platform for epidemiological investigation and comparative genomic analysis. In Frontiers in Microbiology (Vol. 10, Issue JULY). Frontiers Media S.A. https://doi.org/10.3389/fmicb.2019.01687
Luis, J. (2012). Hipótesis, Método & Diseño de Investigación. In Daena: International Journal of Good Conscience (Vol. 7, Issue 2).
Lüth, S., Deneke, C., Kleta, S., & Dahouk, S. Al. (2021). Translatability of wgs typing results can simplify data exchange for surveillance and control of listeria monocytogenes. Microbial Genomics, 7(1), 1–12.
Magalhães, B., Valot, B., Abdelbary, M. M. H., Prod’hom, G., Greub, G., Senn, L., & Blanc, D. S. (2020). Combining Standard Molecular Typing and Whole Genome Sequencing to Investigate Pseudomonas aeruginosa Epidemiology in Intensive Care Units. Frontiers in Public Health, 8. https://doi.org/10.3389/fpubh.2020.00003
Maiden, M. C. J., Rensburg, M. J. J. van, Bray, J. E., Earle, S. G., Ford, S. A., Jolley, K. A., & McCarthy, N. D. (2013). MLST revisited: the gene-by-gene approach to bacterial genomics. Nature Reviews. Microbiology, 11(10), 728. https://doi.org/10.1038/NRMICRO3093
Maiden, M. C. J., Van Rensburg, M. J. J., Bray, J. E., Earle, S. G., Ford, S. A., Jolley, K. A., & McCarthy, N. D. (2013). MLST revisited: The gene-by-gene approach to bacterial genomics. In Nature Reviews Microbiology (Vol. 11, Issue 10, pp. 728–736). https://doi.org/10.1038/nrmicro3093
Mamede, R., Vila-Cerqueira, P., Silva, M., Carriço, J. A., & Ramirez, M. (2021). Chewie Nomenclature Server (chewie-NS): a deployable nomenclature server for easy sharing of core and whole genome MLST schemas. Nucleic Acids Research, 49(D1), D660–D666. https://doi.org/10.1093/NAR/GKAA889
Mangul, S., Martin, L. S., Hill, B. L., Lam, A. K. M., Distler, M. G., Zelikovsky, A., Eskin, E., & Flint, J. (2019). Systematic benchmarking of omics computational tools. In Nature Communications (Vol. 10, Issue 1, pp. 1–11). Nature Publishing Group. https://doi.org/10.1038/s41467-019-09406-4
Marcos-Zambrano, L. J., Escribano, P., Bouza, E., & Guinea, J. (2014). Use of molecular typing tools for the study of hospital outbreaks of candidemia. Revista Iberoamericana de Micologia, 31(2), 97–103. https://doi.org/10.1016/j.riam.2013.06.003
Martin, J., Phan, H. T. T., Findlay, J., Stoesser, N., Pankhurst, L., Navickaite, I., De Maio, N., Eyre, D. W., Toogood, G., Orsi, N. M., Kirby, A., Young, N., Turton, J. F., Hill, R. L. R., Hopkins, K. L., Woodford, N., Peto, T. E. A., Walker, A. S., Crook, D. W., & Wilcox, M. H. (2017). Covert dissemination of carbapenemase-producing Klebsiella pneumoniae (KPC) in a successfully controlled outbreak: long- and short-read whole-genome sequencing demonstrate multiple genetic modes of transmission. The Journal of Antimicrobial Chemotherapy, 72(11), 3025–3034. https://doi.org/10.1093/jac/dkx264
Martínez-Carranza, E., García-Reyes, S., González-Valdez, A., & Soberón-Chávez, G. (2020). Tracking the genome of four Pseudomonas aeruginosa isolates that have a defective Las quorum-sensing system, but are still virulent. Access Microbiology, 2(7). https://doi.org/10.1099/acmi.0.000132
Merchán, M. A., Caicedo, M. I. T., & Torres, A. K. D. (2017). Técnicas de Biología Molecular en el desarrollo de la investigación. Revisión de la literatura. Revista Habanera de Ciencias Medicas, 16(5), 796–807
Michael Dunne, W., Pouseele, H., Monecke, S., Ehricht, R., & van Belkum, A. (2018). Epidemiology of transmissible diseases: Array hybridization and next generation sequencing as universal nucleic acid-mediated typing tools. Infection, Genetics and Evolution, 63, 332–345. https://doi.org/10.1016/j.meegid.2017.09.019
Mirande, C., Bizine, I., Giannetti, A., Picot, N., & van Belkum, A. (2018). Epidemiological aspects of healthcare-associated infections and microbial genomics. European Journal of Clinical Microbiology and Infectious Diseases, 37(5), 823–831. https://doi.org/10.1007/S10096-017-3170-X/TABLES/4
Miro, E., Rossen, J. W. A., Chlebowicz, M. A., Harmsen, D., Brisse, S., Passet, V., Navarro, F., Friedrich, A. W., & García-Cobos, S. (2020). Core/Whole Genome Multilocus Sequence Typing and Core Genome SNP-Based Typing of OXA-48-Producing Klebsiella pneumoniae Clinical Isolates From Spain. Frontiers in Microbiology, 10. https://doi.org/10.3389/fmicb.2019.02961
Misra, B. B., Langefeld, C., Olivier, M., & Cox, L. A. (2019). Integrated omics: Tools, advances and future approaches. In Journal of Molecular Endocrinology (Vol. 62, Issue 1, pp. R21–R45). BioScientifica Ltd. https://doi.org/10.1530/JME-18-0055
Moradigaravand, D., Martin, V., Peacock, S. J., & Parkhill, J. (2017). Evolution and epidemiology of multidrug-resistant Klebsiella pneumoniae in the United Kingdom and Ireland. MBio, 8(1). https://doi.org/10.1128/mBio.01976-16
Nadon, C. A., Trees, E., Ng, L. K., Møller Nielsen, E., Reimer, A., Maxwell, N., Kubota, K. A., & Gerner-Smidt, P. (2013). Development and application of MLVA methods as a tool for inter-laboratory surveillance. Eurosurveillance, 18(35), 20565. https://doi.org/10.2807/1560-7917.ES2013.18.35.20565
Neoh, H. min, Tan, X. E., Sapri, H. F., & Tan, T. L. (2019). Pulsed-field gel electrophoresis (PFGE): A review of the “gold standard” for bacteria typing and current alternatives. In Infection, Genetics and Evolution (Vol. 74). Elsevier B.V. https://doi.org/10.1016/j.meegid.2019.103935
Neoh, H. min, Tan, X. E., Sapri, H. F., & Tan, T. L. (2019). Pulsed-field gel electrophoresis (PFGE): A review of the “gold standard” for bacteria typing and current alternatives. In Infection, Genetics and Evolution (Vol. 74). Elsevier B.V. https://doi.org/10.1016/j.meegid.2019.103935
Nguyen, K. T., Bonasera, R., Benson, G., Hernandez-Morales, A. C., Gill, J. J., & Liu, M. (2019). Complete Genome Sequence of Klebsiella pneumoniae Myophage May. Microbiology Resource Announcements, 8(19). https://doi.org/10.1128/MRA.00252-19
Noller, A. C., McEllistrem, M. C., Pacheco, A. G. F., Boxrud, D. J., & Harrison, L. H. (2003). Multilocus Variable-Number Tandem Repeat Analysis Distinguishes Outbreak and Sporadic Escherichia coli O157:H7 Isolates. Journal of Clinical Microbiology, 41(12), 5389–5397. https://doi.org/10.1128/JCM.41.12.5389-5397.2003
Page, A. J., Cummins, C. A., Hunt, M., Wong, V. K., Reuter, S., Holden, M. T. G., Fookes, M., Falush, D., Keane, J. A., & Parkhill, J. (2015). Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics, 31(22), 3691–3693. https://doi.org/10.1093/bioinformatics/btv421
Papić, B., Diricks, M., & Kušar, D. (2021). Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme. Frontiers in Veterinary Science, 8, 582677. https://doi.org/10.3389/fvets.2021.582677
Payne, M., Kaur, S., Wang, Q., Hennessy, D., Luo, L., Octavia, S., Tanaka, M. M., Sintchenko, V., & Lan, R. (2020). Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens. Euro Surveillance : Bulletin Europeen Sur Les Maladies Transmissibles = European Communicable Disease Bulletin, 25(20). https://doi.org/10.2807/1560-7917.ES.2020.25.20.1900519
Peix, A., Ramírez-Bahena, M. H., & Velázquez, E. (2009). Historical evolution and current status of the taxonomy of genus Pseudomonas. Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases, 9(6), 1132–1147. https://doi.org/10.1016/J.MEEGID.2009.08.001
Peix, A., Ramírez-Bahena, M. H., & Velázquez, E. (2018). The current status on the taxonomy of Pseudomonas revisited: An update. Infection, Genetics and Evolution, 57, 106–116. https://doi.org/10.1016/j.meegid.2017.10.026
Perrin, A., & Rocha, E. P. C. (2021). PanACoTA: a modular tool for massive microbial comparative genomics. NAR Genomics and Bioinformatics, 3(1), lqaa106. https://doi.org/10.1093/nargab/lqaa106
Platt, S., Pichon, B., George, R., & Green, J. (2006). RESEARCH NOTE A bioinformatics pipeline for high-throughput microbial multilocus sequence typing (MLST) analyses. https://doi.org/10.1111/j.1469-0691.2006.01541.x
Riley, L. W. (2018). Laboratory Methods in Molecular Epidemiology: Bacterial Infections. Microbiology Spectrum, 6(6). https://doi.org/10.1128/MICROBIOLSPEC.AME-0004-2018
Robinson, M. D., & Vitek, O. (2019). Benchmarking comes of age. Genome Biology, 20(1). https://doi.org/10.1186/S13059-019-1846-5
Rouli, L., Merhej, V., Fournier, P. E., & Raoult, D. (2015). The bacterial pangenome as a new tool for analysing pathogenic bacteria. New Microbes and New Infections, 7, 72–85. https://doi.org/10.1016/j.nmni.2015.06.005
Royer, G., Fourreau, F., Boulanger, B., Mercier-Darty, M., Ducellier, D., Cizeau, F., Potron, A., Podglajen, I., Mongardon, N., & Decousser, J. W. (2020). outbreak. Journal of Hospital Infection, 104(1), 33–39. https://doi.org/10.1016/j.jhin.2019.07.014
Ruppé, E., Olearo, F., Pires, D., Baud, D., Renzi, G., Cherkaoui, A., Goldenberger, D., Huttner, A., François, P., Harbarth, S., & Schrenzel, J. (2017). Clonal or not clonal? Investigating hospital outbreaks of KPC-producing Klebsiella pneumoniae with whole-genome sequencing. Clinical Microbiology and Infection, 23(7), 470–475. https://doi.org/10.1016/j.cmi.2017.01.015
Saharman, Y. R., Pelegrin, A. C., Karuniawati, A., Sedono, R., Aditianingsih, D., Goessens, W. H. F., Klaassen, C. H. W., van Belkum, A., Mirande, C., Verbrugh, H. A., & Severin, J. A. (2019). Epidemiology and characterisation of carbapenem-non-susceptible Pseudomonas aeruginosa in a large intensive care unit in Jakarta, Indonesia. International Journal of Antimicrobial Agents, 54(5), 655–660. https://doi.org/10.1016/j.ijantimicag.2019.08.003
Sahl, J. W., Lemmer, D., Travis, J., Schupp, J. M., Gillece, J. D., Aziz, M., Driebe, E. M., Drees, K. P., Hicks, N. D., Williamson, C. H. D., Hepp, C. M., Smith, D. E., Roe, C., Engelthaler, D. M., Wagner, D. M., & Keim, P. (2016). NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats. Microbial Genomics, 2(8), e000074. https://doi.org/10.1099/mgen.0.000074
Salipante, S. J., SenGupta, D. J., Cummings, L. A., Land, T. A., Hoogestraat, D. R., & Cookson, B. T. (2015). Application of whole-genome sequencing for bacterial strain typing in molecular epidemiology. Journal of Clinical Microbiology, 53(4), 1072–1079. https://doi.org/10.1128/JCM.03385-14
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., Bremges, A., Fritz, A., Garrido-Oter, R., Jørgensen, T. S., Shapiro, N., Blood, P. D., Gurevich, A., Bai, Y., Turaev, D., … McHardy, A. C. (2017). Critical Assessment of Metagenome Interpretation - A benchmark of metagenomics software. Nature Methods, 14(11), 1063–1071. https://doi.org/10.1038/nmeth.4458
Seth-Smith, H. M. B., Bonfiglio, F., Cuénod, A., Reist, J., Egli, A., & Wüthrich, D. (2019). Evaluation of Rapid Library Preparation Protocols for Whole Genome Sequencing Based Outbreak Investigation. Frontiers in Public Health, 7(AUG), 241. https://doi.org/10.3389/fpubh.2019.00241
Singh, M., Malik, M. A., Singh, D. K., Doimari, S., Bhavna, & Sharma, R. (2020). Multilocus variable number tandem repeat analysis (MLVA)-typing of Brucella abortus isolates of India reveals limited genetic diversity. Tropical Animal Health and Production, 52(3), 1187–1194. https://doi.org/10.1007/s11250-019-02110-x
Sitto, F., & Battistuzzi, F. U. (2020). Estimating Pangenomes with Roary. Molecular Biology and Evolution, 37(3), 933–939. https://doi.org/10.1093/MOLBEV/MSZ284
Tadee, P., Tadee, P., Hitchings, M. D., Pascoe, B., Sheppard, S. K., & Patchanee, P. (2018). High Resolution Whole Genome Multilocus Sequence Typing (wgMLST) Schemes for Salmonella enterica Weltevreden Epidemiologic Investigations. Biotechnol. Lett, 46(2), 162–170. https://doi.org/10.4014/mbl.1802.02008
Tenover, F. C., Arbeit, R. D., Goering, R. V., Mickelsen, P. A., Murray, B. E., Persing, D. H., & Swaminathan, B. (1995). Interpreting chromosomal DNA restriction patterns produced by pulsed- field gel electrophoresis: Criteria for bacterial strain typing. In Journal of Clinical Microbiology (Vol. 33, Issue 9, pp. 2233–2239). American Society for Microbiology. https://doi.org/10.1128/jcm.33.9.2233-2239.1995
Timme, R. E., Rand, H., Shumway, M., Trees, E. K., Simmons, M., Agarwala, R., Davis, S., Tillman, G. E., Defibaugh-Chavez, S., Carleton, H. A., Klimke, W. A., & Katz, L. S. (2017). Benchmark datasets for phylogenomic pipeline validation, applications for foodborne pathogen surveillance. PeerJ, 2017(10). https://doi.org/10.7717/peerj.3893
Tissot, F., Blanc, D. S., Basset, P., Zanetti, G., Berger, M. M., Que, Y. A., Eggimann, P., & Senn, L. (2016). New genotyping method discovers sustained nosocomial Pseudomonas aeruginosa outbreak in an intensive care burn unit. Journal of Hospital Infection, 94(1), 2–7. https://doi.org/10.1016/j.jhin.2016.05.011
Treangen, T. J., Ondov, B. D., Koren, S., & Phillippy, A. M. (2014). The harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15(11), 1–15. https://doi.org/10.1186/S13059-014-0524-X/TABLES/4
Tsai, M. H., Liu, Y. Y., & Soo, V. W. (2017). PathoBacTyper: A web server for pathogenic bacteria identification and molecular genotyping. Frontiers in Microbiology, 8(AUG), 1474. https://doi.org/10.3389/fmicb.2017.01474
Uelze, L., Grützke, J., Borowiak, M., Hammerl, J. A., Juraschek, K., Deneke, C., Tausch, S. H., & Malorny, B. (2020). Typing methods based on whole genome sequencing data. One Health Outlook, 2(1), 1–19. https://doi.org/10.1186/s42522-020-0010-1
van Beek, J., Räisänen, K., Broas, M., Kauranen, J., Kähkölä, A., Laine, J., Mustonen, E., Nurkkala, T., Puhto, T., Sinkkonen, J., Torvinen, S., Vornanen, T., Vuento, R., Jalava, J., & Lyytikäinen, O. (2019). Tracing local and regional clusters of carbapenemase-producing Klebsiella pneumoniae ST512 with whole genome sequencing, Finland, 2013 to 2018. Eurosurveillance, 24(38). https://doi.org/10.2807/1560-7917.ES.2019.24.38.1800522
Van Belkum, A., Struelens, M., De Visser, A., Verbrugh, H., & Tibayrenc, M. (2001). Role of Genomic Typing in Taxonomy, Evolutionary Genetics, and Microbial Epidemiology. Clinical Microbiology Reviews, 14(3), 547. https://doi.org/10.1128/CMR.14.3.547-560.2001
van Dorp, L., Wang, Q., Shaw, L. P., Acman, M., Brynildsrud, O. B., Eldholm, V., Wang, R., Gao, H., Yin, Y., Chen, H., Ding, C., Farrer, R. A., Didelot, X., Balloux, F., & Wang, H. (2019). Rapid phenotypic evolution in multidrug-resistant Klebsiella pneumoniae hospital outbreak strains. Microbial Genomics, 5(4), 1–11. https://doi.org/10.1099/mgen.0.000263
Vaz, C., Francisco, A. P., Silva, M., Jolley, K. A., Bray, J. E., Pouseele, H., Rothganger, J., Ramirez, M., & Carriço, J. A. (2014). TypOn: the microbial typing ontology. Journal of Biomedical Semantics, 5(1), 43. https://doi.org/10.1186/2041-1480-5-43
Vernikos, G. S. (2020). A Review of Pangenome Tools and Recent Studies. The Pangenome: Diversity, Dynamics and Evolution of Genomes, 89–112. https://doi.org/10.1007/978-3-030-38281-0_4
Wang, G., Zhao, G., Chao, X., Xie, L., & Wang, H. (2020). The Characteristic of Virulence, Biofilm and Antibiotic Resistance of Klebsiella pneumoniae. International Journal of Environmental Research and Public Health, 17(17), 1–17. https://doi.org/10.3390/IJERPH17176278
Weber, L. M., Saelens, W., Cannoodt, R., Soneson, C., Hapfelmeier, A., Gardner, P. P., Boulesteix, A. L., Saeys, Y., & Robinson, M. D. (2019). Essential guidelines for computational method benchmarking. In Genome Biology (Vol. 20, Issue 1, pp. 1–12). BioMed Central Ltd. https://doi.org/10.1186/s13059-019-1738-8
Wingett, S. W., & Andrews, S. (2018). FastQ Screen: A tool for multi-genome mapping and quality control. F1000Research, 7, 1338
Yoshimura, D., Kajitani, R., Gotoh, Y., Katahira, K., Okuno, M., Ogura, Y., Hayashi, T., & Itoh, T. (2019). Evaluation of SNP calling methods for closely related bacterial isolates and a novel high-accuracy pipeline: BactSNP. Microbial Genomics, 5(5). https://doi.org/10.1099/mgen.0.000261
Youenou, B., Brothier, E., & Nazaret, S. (2014). Diversity among strains of Pseudomonas aeruginosa from manure and soil, evaluated by multiple locus variable number tandem repeat analysis and antibiotic resistance profiles. Research in Microbiology, 165(1), 2–13. https://doi.org/10.1016/j.resmic.2013.10.004
Zheng, S. (2017). Bogaerts Contexts and details matter. In Genome Biology (Vol. 18, Issue 1, p. 129). BioMed Central Ltd. https://doi.org/10.1186/s13059-017-1258-3
Zhi, X. Y., Zhao, W., Li, W. J., & Zhao, G. P. (2011). Prokaryotic systematics in the genomics era. Antonie van Leeuwenhoek 2011 101:1, 101(1), 21–34. https://doi.org/10.1007/S10482-011-9667-X
Zhou, G. H., Gotou, M., Kajiyama, T., & Kambara, H. (2005). Multiplex SNP typing by bioluminometric assay coupled with terminator incorporation (BATI). Nucleic Acids Research, 33(15), 1–11. https://doi.org/10.1093/nar/gni132
Zhou, K., Lokate, M., Deurenberg, R. H., Tepper, M., Arends, J. P., Raangs, E. G. C., Lo-Ten-Foe, J., Grundmann, H., Rossen, J. W. A., & Friedrich, A. W. (2016). Whole genome sequencing for the molecular characterization of carbapenem-resistant Klebsiella pneumoniae strains isolated at the Italian ASST Fatebenefratelli Sacco Hospital, 2012-2014Use of whole-genome sequencing to trace, control and characterize the r. Scientific Reports, 6, 20840. https://doi.org/10.1038/srep20840
Zhou, Z., Alikhan, N. F., Sergeant, M. J., Luhmann, N., Vaz, C., Francisco, A. P., Carriço, J. A., & Achtman, M. (2018). GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Research, 28(9), 1395–1404. https://doi.org/10.1101/GR.232397.117
Inouye, M., Dashnow, H., Raven, L. A., Schultz, M. B., Pope, B. J., Tomita, T., Zobel, J., & Holt, K. E. (2014). SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Medicine, 6(11), 90. https://doi.org/10.1186/s13073-014-0090-6
Pérez-Losada, M., Arenas, M., & Castro-Nallar, E. (2018). Microbial sequence typing in the genomic era. Infection, Genetics and Evolution, 63, 346–359. https://doi.org/10.1016/j.meegid.2017.09.022
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_abf2
dc.rights.license.spa.fl_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional
dc.rights.uri.spa.fl_str_mv http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.accessrights.spa.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv Atribución-NoComercial-SinDerivadas 4.0 Internacional
http://creativecommons.org/licenses/by-nc-nd/4.0/
http://purl.org/coar/access_right/c_abf2
eu_rights_str_mv openAccess
dc.format.extent.spa.fl_str_mv xx, 77 páginas
dc.format.mimetype.spa.fl_str_mv application/pdf
dc.publisher.spa.fl_str_mv Universidad Nacional de Colombia
dc.publisher.program.spa.fl_str_mv Bogotá - Ingeniería - Maestría en Bioinformática
dc.publisher.faculty.spa.fl_str_mv Facultad de Ingeniería
dc.publisher.place.spa.fl_str_mv Bogotá, Colombia
dc.publisher.branch.spa.fl_str_mv Universidad Nacional de Colombia - Sede Bogotá
institution Universidad Nacional de Colombia
bitstream.url.fl_str_mv https://repositorio.unal.edu.co/bitstream/unal/84272/1/license.txt
https://repositorio.unal.edu.co/bitstream/unal/84272/2/16843909.2023.pdf
https://repositorio.unal.edu.co/bitstream/unal/84272/3/16843909.2023.pdf.jpg
bitstream.checksum.fl_str_mv eb34b1cf90b7e1103fc9dfd26be24b4a
2e8067c417feae48f399357d68a0c1bf
9d67d56faaece55b809c99993e0d189c
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
MD5
repository.name.fl_str_mv Repositorio Institucional Universidad Nacional de Colombia
repository.mail.fl_str_mv repositorio_nal@unal.edu.co
_version_ 1814089985627783168
spelling Atribución-NoComercial-SinDerivadas 4.0 Internacionalhttp://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccesshttp://purl.org/coar/access_right/c_abf2Barreto Hernández, Emilianob7a2cae2c08b5d6a549e173576c6c82dCarabali Mosquera, Oscar Eduardoc2631a483d68ccbb092c28a7e6d09420Bioinformática2023-07-26T12:54:22Z2023-07-26T12:54:22Z2023-06-15https://repositorio.unal.edu.co/handle/unal/84272Universidad Nacional de ColombiaRepositorio Institucional Universidad Nacional de Colombiahttps://repositorio.unal.edu.co/ilustraciones, diagramasLa Secuencia del Genoma Completo se obtiene mediante las tecnologías de secuenciación, especialmente las de próxima generación (NGS). Gracias a su alto poder discriminatorio, simplicidad, precisión, velocidad y flexibilidad, la aplicación de la Secuenciación de Genoma Completo (WGS) se ha convertido en una herramienta que aporta el nivel más alto hasta el momento de discriminación de cepas bacterianas para la investigación de brotes, permitiendo identificar estructura y composición de genes, variantes genéticas y reordenamientos del genoma entre otros (Kwong et al., 2015). Por tal motivo, esta herramienta es de gran utilidad para la investigación epidemiológica ya que proporciona información más detallada y precisa para la toma oportuna de medidas de control derivado de la identificación, tipificación, dinámica de transmisión, procedencia de infección y posibles patrones de propagación de brotes con bacterias como Klebsiella pneumoniae y Pseudomonas aeruginosa causantes de Infecciones Asociadas a la Atención en Salud (IAAS), esto dado que estas bacterias poseen un alto grado de adaptabilidad fisiológica y elevados niveles de resistencia frente a numerosos agentes antimicrobianos, por lo que son patógenos con una elevada incidencia de morbilidad y mortalidad (Saharman et al., 2019)(Moradigaravand et al., 2017). Dentro del uso más frecuente de los datos de Secuenciación de Genoma Completo (WGS) se encuentra la tipificación molecular bacteriana. Por la cual, se han desarrollado varios métodos que se basan principalmente en análisis derivados de Ribosomal Multilocus Sequence Typing (rMLST), Core genome multilocus sequence typing (cgMLST), Whole genome multi locus sequence typing (wgMLST), core genome single nucleotide polymorphism (cgSNP), whole-genome single nucleotide polymorphism (wgSNP) y pangenome (Coll et al., 2020)(Anani et al., 2020). Estos métodos pueden variar en su resolución e idoneidad dependiendo de las especies. Sin embargo, debido al variado número de herramientas bioinformáticas útiles para tipificar y a la falta de consenso de evaluación comparativa de las herramientas los investigadores se pueden enfrentan con dificultades en la elección de herramientas indicada para sus actividades. Es por ello, que se hace necesario realizar una evaluación del desempeño de las herramientas útiles para tipificar, con el fin de informar al usuario sobre las mejores herramientas bioinformáticas disponibles actualmente que brinden información precisa y relevante. (Texto tomado de la fuente)Whole Genome Sequence is obtained by sequencing technologies, especially nextgeneration sequencing (NGS). Due to its high discriminatory power, simplicity, precision, speed, and flexibility, the application of Whole Genome Sequencing (WGS) has become a tool that provides the highest level of discrimination of bacterial strains for outbreak investigation to date, allowing to identify both, structure and composition of genes, genetic variants, and rearrangements of the genome among others (Kwong et al., 2015). For this reason, this tool is highly useful for epidemiological research since it provides more detailed and precise information for the timely taking of control measures derived from the identification, classification, transmission dynamics, the origin of infection, and possible patterns of spread of outbreaks with bacteria such as Klebsiella pneumoniae and Pseudomonas aeruginosa that cause Health Care Associated Infections (IAAS), these bacteria have a high degree of physiological adaptability and high levels of resistance against numerous antimicrobial agents, which constitutes them as a pathological with a high incidence of morbidity and mortality (Saharman et al., 2019) (Moradigaravand et al., 2017). One of the most frequent uses of data from Whole Genome Sequencing (WGS) is bacterial molecular typing. Consecuently, several methods have been developed are uptoday mainly based on analyzes derived from Ribosomal Multilocus Sequence Typing (rMLST), Core genome Multilocus Sequence Typing (cgMLST), Whole genome multilocus sequence typing (wgMLST), core genome Single Nucleotide Polymorphism ( cgSNP), whole-genome single nucleotide polymorphism (wgSNP) and pangenome (Coll et al., 2020) (Anani et al., 2020). These methods vary in their resolution and suitability depending on the species. However, due to the varied number of helpful bioinformatics tools for typing, and the lack of consensus benchmarking tools, researchers may face difficulties in choosing the right tools for their activities. For this reason, it is necessary to perform an evaluation of the performance of the tools for typing, to inform the user about the best bioinformatics tools currently available that provide accurate and relevant information.MaestríaMagíster en BioinformáticaBioinformática funcional y estructuralxx, 77 páginasapplication/pdfspaUniversidad Nacional de ColombiaBogotá - Ingeniería - Maestría en BioinformáticaFacultad de IngenieríaBogotá, ColombiaUniversidad Nacional de Colombia - Sede Bogotá570 - Biología::576 - Genética y evoluciónKlebsiella pneumoniaePseudomonas aeruginosaTaxaSecuencia de ADNDNA sequencesSecuenciación completa del genomaKlebsiella pneumoniaePseudomonas aeruginosaTipificación molecular bacterianaHerramientas BioinformáticasBenchmarkingWhole genome sequencingKlebsiella pneumoniaePseudomonas aeruginosaBacterial molecular typingBioinformatics toolsBenchmarkingEvaluación de herramientas bioinformáticas útiles en la tipificación de Klebsiella pneumoniae y Pseudomonas aeruginosa a partir de datos de secuenciación de genomas completosEvaluation of Bioinformatic tools useful in the typing of Klebsiella pneumoniae and Pseudomonas aeruginosa from whole genome sequencing dataTrabajo de grado - Maestríainfo:eu-repo/semantics/masterThesisinfo:eu-repo/semantics/acceptedVersionTexthttp://purl.org/redcol/resource_type/TMAlikhan, N. F., Zhou, Z., Sergeant, M. J., & Achtman, M. (2018). A genomic overview of the population structure of Salmonella. In PLoS Genetics (Vol. 14, Issue 4, p. e1007261). Public Library of Science. https://doi.org/10.1371/journal.pgen.1007261Allard, M. W. (2016). The future of whole-genome sequencing for public health and the clinic. In Journal of Clinical Microbiology (Vol. 54, Issue 8, pp. 1946–1948). American Society for Microbiology. https://doi.org/10.1128/JCM.01082-16Altmann, A., Weber, P., Bader, D., Preuß, M., Binder, E. B., & Müller-Myhsok, B. (2012). A beginners guide to SNP calling from high-Throughput DNA-sequencing data. In Human Genetics (Vol. 131, Issue 10, pp. 1541–1554). Springer. https://doi.org/10.1007/s00439-012-1213-zAnani, H., Zgheib, R., Hasni, I., Raoult, D., & Fournier, P. E. (2020). Interest of bacterial pangenome analyses in clinical microbiology. Microbial Pathogenesis, 149. https://doi.org/10.1016/j.micpath.2020.104275Basset, P., & Blanc, D. S. (2014). Fast and simple epidemiological typing of Pseudomonas aeruginosa using the double-locus sequence typing (DLST) method. European Journal of Clinical Microbiology and Infectious Diseases, 33(6), 927–932. https://doi.org/10.1007/s10096-013-2028-0Bathke, J., & Lühken, G. (2021). OVarFlow: a resource optimized GATK 4 based Open source Variant calling workFlow. BMC Bioinformatics, 22(1). https://doi.org/10.1186/S12859-021-04317-YBayliss, S. C., Thorpe, H. A., Coyle, N. M., Sheppard, S. K., & Feil, E. J. (2019). PIRATE: A fast and scalable pangenomics toolbox for clustering diverged orthologues in bacteria. GigaScience, 8(10), 1–9. https://doi.org/10.1093/GIGASCIENCE/GIZ119Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2017). GenBank. Nucleic Acids Research, 45(D1), D37–D42. https://doi.org/10.1093/nar/gkw1070Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Ostell, J., Pruitt, K. D., & Sayers, E. W. (2018). GenBank. Nucleic Acids Research, 46(D1), D41–D47. https://doi.org/10.1093/nar/gkx1094Blanc, D. S., Magalhães, B., Koenig, I., Senn, L., & Grandbastien, B. (2020). Comparison of Whole Genome (wg-) and Core Genome (cg-) MLST (BioNumericsTM) Versus SNP Variant Calling for Epidemiological Investigation of Pseudomonas aeruginosa. Frontiers in Microbiology, 11, 1729. https://doi.org/10.3389/fmicb.2020.01729Bogaerts, B., Winand, R., Fu, Q., Van Braekel, J., Ceyssens, P.-J., Mattheus, W., Bertrand, S., De Keersmaecker, S. C. J., Roosens, N. H. C., & Vanneste, K. (2019). Validation of a Bioinformatics Workflow for Routine Analysis of Whole-Genome Sequencing Data and Related Challenges for Pathogen Typing in a European National Reference Center: Neisseria meningitidis as a Proof-of-Concept. Frontiers in Microbiology, 10(MAR), 362. https://doi.org/10.3389/fmicb.2019.00362Botes, J., Williamson, G., Sinickas, V., & Gürtler, V. (2003). Genomic typing of Pseudomonas aeruginosa isolates by comparison of Riboprinting and PFGE: correlation of experimental results with those predicted from the complete genome sequence of isolate PAO1. Journal of Microbiological Methods, 55(1), 231–240. https://doi.org/10.1016/s0167-7012(03)00156-8Bou, G., Fernández-Olmos, A., García, C., Sáez-Nieto, J. A., & Valdezate, S. (2011). Métodos de identificación bacteriana en el laboratorio de microbiología. Enfermedades Infecciosas y Microbiología Clínica, 29(8), 601–608. https://doi.org/10.1016/J.EIMC.2011.03.012Brilhante, M., Gobeli Brawand, S., Endimiani, A., Rohrbach, H., Kittl, S., Willi, B., Schuller, S., & Perreten, V. (2021). Two high-risk clones of carbapenemase-producing Klebsiella pneumoniae that cause infections in pets and are present in the environment of a veterinary referral hospital. Journal of Antimicrobial Chemotherapy, 76(5), 1140–1149. https://doi.org/10.1093/JAC/DKAB028Buchka, S., Hapfelmeier, A., Gardner, P. P., Wilson, R., & Boulesteix, A. L. (2021). On the optimistic performance evaluation of newly introduced bioinformatic methods. Genome Biology, 22(1). https://doi.org/10.1186/S13059-021-02365-4Bush, S. J. (2021). Generalizable characteristics of false-positive bacterial variant calls. Microbial Genomics, 7(8). https://doi.org/10.1099/MGEN.0.000615Bush, S. J., Foster, D., Eyre, D. W., Clark, E. L., de Maio, N., Shaw, L. P., Stoesser, N., Peto, T. E. A., Crook, D. W., & Walker, A. S. (2020). Genomic diversity affects the accuracy of bacterial single-nucleotide polymorphism–calling pipelines. GigaScience, 9(2), 1–21. https://doi.org/10.1093/GIGASCIENCE/GIAA007Carattoli, A., Zankari, E., Garciá-Fernández, A., Larsen, M. V., Lund, O., Villa, L., Aarestrup, F. M., & Hasman, H. (2014). In Silico detection and typing of plasmids using plasmidfinder and plasmid multilocus sequence typing. Antimicrobial Agents and Chemotherapy, 58(7), 3895–3903. https://doi.org/10.1128/AAC.02412-14Chang, C. H., Chang, Y. C., Underwood, A., Chiou, C. S., & Kao, C. Y. (2007). VNTRDB: A bacterial variable number tandem repeat locus database. Nucleic Acids Research, 35(SUPPL. 1). https://doi.org/10.1093/nar/gkl872Chen, Y., Gonzalez-Escalona, N., Hammack, T. S., Allard, M. W., Strain, E. A., & Brown, E. W. (2016). Core genome multilocus sequence typing for identification of globally distributed clonal groups and differentiation of outbreak strains of Listeria monocytogenes. Applied and Environmental Microbiology, 82(20), 6258–6272. https://doi.org/10.1128/AEM.01532-16Clarke, T. H., Brinkac, L. M., Inman, J. M., Sutton, G., & Fouts, D. E. (2018). PanACEA: A bioinformatics tool for the exploration and visualization of bacterial pan-chromosomes. BMC Bioinformatics, 19(1), 246. https://doi.org/10.1186/s12859-018-2250-yColl, F., Gouliouris, T., Bruchmann, S., Phelan, J., Raven, K. E., Clark, T. G., Parkhill, J., & Peacock, S. J. (2022). PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies. Communications Biology, 5(1). https://doi.org/10.1038/S42003-022-03194-2Coll, F., Raven, K. E., Knight, G. M., Blane, B., Harrison, E. M., Leek, D., Enoch, D. A., Brown, N. M., Parkhill, J., & Peacock, S. J. (2020). Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: a genomic epidemiology analysis. The Lancet Microbe, 1(8), e328–e335. https://doi.org/10.1016/S2666-5247(20)30149-XDalsass, M., Bodini, M., Lambert, C., Mortier, M. C., Romanelli, M., Medini, D., Muzzi, A., & Brozzi, A. (2019). STRAIN: An R package for multi-locus sequence typing from whole genome sequencing data. BMC Bioinformatics, 20(Suppl 9). https://doi.org/10.1186/s12859-019-2887-1Das, D., Baruah, R., Sarma Roy, A., Singh, A. K., Deka Boruah, H. P., Kalita, J., & Bora, T. C. (2015). Complete genome sequence analysis of Pseudomonas aeruginosa N002 reveals its genetic adaptation for crude oil degradation. Genomics, 105(3), 182–190. https://doi.org/10.1016/j.ygeno.2014.12.006De Rosa, F. G., Corcione, S., Pagani, N., & Di Perri, G. (2015). From ESKAPE to ESCAPE, From KPC to CCC. Clinical Infectious Diseases, 60(8), 1289–1290. https://doi.org/10.1093/CID/CIU1170Deneke, C., Uelze, L., Brendebach, H., Tausch, S. H., & Malorny, B. (2021). Decentralized Investigation of Bacterial Outbreaks Based on Hashed cgMLST. Frontiers in Microbiology, 12, 874. https://doi.org/10.3389/fmicb.2021.649517Escalona, M., Rocha, S., & Posada, D. (2016). A comparison of tools for the simulation of genomic next-generation sequencing data. In Nature Reviews Genetics (Vol. 17, Issue 8, pp. 459–469). Nature Publishing Group. https://doi.org/10.1038/nrg.2016.57Ettorchi -Tardy, A., Levif, M., & Michel, P. (2012). Benchmarking: A method for continuous quality improvement in health. Healthcare Policy, 7(4). https://doi.org/10.12927/hcpol.2012.22872Feijao, P., Yao, H. T., Fornika, D., Gardy, J., Hsiao, W., Chauve, C., & Chindelevitch, L. (2018). MentaLiST - A fast MLST caller for large MLST schemes. Microbial Genomics, 4(2), e000146. https://doi.org/10.1099/mgen.0.000146Fouts, D. E., Brinkac, L., Beck, E., Inman, J., & Sutton, G. (2012). PanOCT: automated clustering of orthologs using conserved gene neighborhood for pan-genomic analysis of bacterial strains and closely related species. Nucleic Acids Research, 40(22). https://doi.org/10.1093/NAR/GKS757Francisco, A. P., Bugalho, M., Ramirez, M., & Carriço, J. A. (2009). Global optimal eBURST analysis of multilocus typing data using a graphic matroid approach. BMC Bioinformatics, 10(1), 1–15. https://doi.org/10.1186/1471-2105-10-152/FIGURES/5Francisco, A. P., Vaz, C., Monteiro, P. T., Melo-Cristino, J., Ramirez, M., & Carriço, J. A. (2012). PHYLOViZ: phylogenetic inference and data visualization for sequence based typing methods. BMC Bioinformatics, 13(1), 87. https://doi.org/10.1186/1471-2105-13-87Friedman, S., Gauthier, L., Farjoun, Y., & Banks, E. (2020). Lean and deep models for more accurate filtering of SNP and INDEL variant calls. Bioinformatics (Oxford, England), 36(7), 2060–2067. https://doi.org/10.1093/BIOINFORMATICS/BTZ901Gardner, S. N., & Hall, B. G. (2013). When whole-genome alignments just won’t work: KSNP v2 software for alignment-free SNP discovery and phylogenetics of hundreds of microbial genomes. PLoS ONE, 8(12). https://doi.org/10.1371/journal.pone.0081760Gardner, S. N., Slezak, T., & Hall, B. G. (2015). kSNP3.0: SNP detection and phylogenetic analysis of genomes without genome alignment or reference genome. Bioinformatics (Oxford, England), 31(17), 2877–2878. https://doi.org/10.1093/BIOINFORMATICS/BTV271Guigon, G., Cheval, J., Cahuzac, R., & Brisse, S. (2008). MLVA-NET--a standardised web database for bacterial genotyping and surveillance. Euro Surveillance : Bulletin Européen Sur Les Maladies Transmissibles = European Communicable Disease Bulletin, 13(19), 18863. https://doi.org/10.2807/ese.13.19.18863-enGuimarães, L. C., Florczak-Wyspianska, J., Jesus, L. B. de, Viana, M. V. C., Silva, A., Ramos, R. T. J., Soares, S. de C., & Soares, S. de C. (2015). Inside the Pan-genome - Methods and Software Overview. Current Genomics, 16(4), 245. https://doi.org/10.2174/1389202916666150423002311Gupta, A., Jordan, I. K., & Rishishwar, L. (2017). stringMLST: a fast k-mer based tool for multilocus sequence typing. Bioinformatics, 33(1), 119–121. https://doi.org/10.1093/BIOINFORMATICS/BTW586Gupta, A. K. (1996). Classification. Springer Geology, 69–87. https://doi.org/10.1007/978-81-322-2083-1_3Hall, B. G. (2014). SNP-associations and phenotype predictions from hundreds of microbial genomes without genome alignments. PLoS ONE, 9(2), 90490. https://doi.org/10.1371/journal.pone.0090490Hallgren, M. B., Overballe-Petersen, S., Lund, O., Hasman, H., & Clausen, P. T. L. C. (2021). MINTyper: an outbreak-detection method for accurate and rapid SNP typing of clonal clusters with noisy long reads. Biology Methods and Protocols, 6(1). https://doi.org/10.1093/BIOMETHODS/BPAB008Henry, V. J., Bandrowski, A. E., Pepin, A. S., Gonzalez, B. J., & Desfeux, A. (2014). OMICtools: an informative directory for multi-omic data analysis. Database: The Journal of Biological Databases and Curation, 2014. https://doi.org/10.1093/DATABASE/BAU069INS. (2018). INFORME DE RESULTADOS DE LA VIGILANCIA POR LABORATORIO DE RESISTENCIA ANTIMICROBIANA EN INFECCIONES ASOCIADAS A LA ATENCIÓN EN SALUD.Jolley, K. A., Bliss, C. M., Bennett, J. S., Bratcher, H. B., Brehony, C., Colles, F. M., Wimalarathna, H., Harrison, O. B., Sheppard, S. K., Cody, A. J., & Maiden, M. C. J. (2012). Ribosomal multilocus sequence typing: Universal characterization of bacteria from domain to strain. Microbiology, 158(4), 1005–1015. https://doi.org/10.1099/mic.0.055459-0Jolley, K. A., Chan, M. S., & Maiden, M. C. J. (2004). mlstdbNet - Distributed multi-locus sequence typing (MLST) databases. BMC Bioinformatics, 5(1), 86. https://doi.org/10.1186/1471-2105-5-86Jolley, K. A., & Maiden, M. C. J. (2014). Using MLST to study bacterial variation: Prospects in the genomic era. Future Microbiology, 9(5), 623–630. https://doi.org/10.2217/fmb.14.24Jonas, D., Spitzmüller, B., Daschner, F. D., Verhoef, J., & Brisse, S. (2004). Discrimination of Klebsiella pneumoniae and Klebsiella oxytoca phylogenetic groups and other Klebsiella species by use of amplified fragment length polymorphism. Research in Microbiology, 155(1), 17–23.Kimura, B. (2018). Will the emergence of core genome MLST end the role of in silico MLST? In Food Microbiology (Vol. 75, pp. 28–36). Academic Press. https://doi.org/10.1016/j.fm.2017.09.003Kingry, L. C., Rowe, L. A., Respicio-Kingry, L. B., Beard, C. B., Schriefer, M. E., & Petersen, J. M. (2016). Whole genome multilocus sequence typing as an epidemiologic tool for Yersinia pestis. Diagnostic Microbiology and Infectious Disease, 84(4), 275–280. https://doi.org/10.1016/j.diagmicrobio.2015.12.003Kozyreva, V. K., Truong, C. L., Greninger, A. L., Crandall, J., Mukhopadhyay, R., & Chaturvedi, V. (2017). Validation and implementation of clinical laboratory improvements act-compliant whole-genome sequencing in the public health microbiology laboratory. Journal of Clinical Microbiology, 55(8), 2502–2520. https://doi.org/10.1128/JCM.00361-17Kumar, S., Stecher, G., Li, M., Knyaz, C., & Tamura, K. (2018). MEGA X: Molecular Evolutionary Genetics Analysis across Computing Platforms. Molecular Biology and Evolution, 35(6), 1547. https://doi.org/10.1093/MOLBEV/MSY096Kwong, J. C., Mccallum, N., Sintchenko, V., & Howden, B. P. (2015). Whole genome sequencing in clinical and public health microbiology. Pathology, 47(3), 199–210. https://doi.org/10.1097/PAT.0000000000000235Labbé, G., Kruczkiewicz, P., Robertson, J., Mabon, P., Schonfeld, J., Kein, D., Rankin, M. A., Gopez, M., Hole, D., Son, D., Knox, N., Laing, C. R., Bessonov, K., Taboada, E. N., Yoshida, C., Ziebell, K., Nichani, A., Johnson, R. P., Van Domselaar, G., & Nash, J. H. E. (2021). Rapid and accurate SNP genotyping of clonal bacterial pathogens with BioHansel. Microbial Genomics, 7(9), 651. https://doi.org/10.1099/MGEN.0.000651Larsen, M. V., Cosentino, S., Lukjancenko, O., Saputra, D., Rasmussen, S., Hasman, H., Sicheritz-Pontén, T., Aarestrup, F. M., Ussery, D. W., & Lund, O. (2014). Benchmarking of methods for genomic taxonomy. Journal of Clinical Microbiology, 52(5), 1529–1539. https://doi.org/10.1128/JCM.02981-13Letunic, I., & Bork, P. (2019). Interactive Tree Of Life (iTOL) v4: recent updates and new developments. Nucleic Acids Research, 47(W1), W256. https://doi.org/10.1093/NAR/GKZ239Li, F., Wang, Y., Li, C., Marquez-Lago, T. T., Leier, A., Rawlings, N. D., Haffari, G., Revote, J., Akutsu, T., Chou, K. C., Purcell, A. W., Pike, R. N., Webb, G. I., Ian Smith, A., Lithgow, T., Daly, R. J., Whisstock, J. C., & Song, J. (2019). Twenty years of bioinformatics research for protease-specific substrate and cleavage site prediction: a comprehensive revisit and benchmarking of existing methods. Briefings in Bioinformatics, 20(6), 2150. https://doi.org/10.1093/BIB/BBY077Li, H. (2011). A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics, 27(21), 2987–2993. https://doi.org/10.1093/bioinformatics/btr509Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., & Durbin, R. (2009). The Sequence Alignment/Map format and SAMtools. Bioinformatics (Oxford, England), 25(16), 2078–2079Li, W., Raoult, D., & Fournier, P. E. (2009). Bacterial strain typing in the genomic era. In FEMS Microbiology Reviews (Vol. 33, Issue 5, pp. 892–916). Oxford Academic. https://doi.org/10.1111/j.1574-6976.2009.00182.xLindgreen, S., Adair, K. L., & Gardner, P. P. (2016). An evaluation of the accuracy and speed of metagenome analysis tools. Scientific Reports, 6. https://doi.org/10.1038/SREP19233Liu, J., Li, L., Peters, B. M., Li, B., Chen, D., Xu, Z., & Shirtliff, M. E. (2018). Complete genomic analysis of multidrug-resistance Pseudomonas aeruginosa Guangzhou-Pae617, the host of megaplasmid pBM413. Microbial Pathogenesis, 117, 265–269. https://doi.org/10.1016/j.micpath.2018.02.049Liu, Y. Y., Chiou, C. S., & Chen, C. C. (2016). PGAdb-builder: A web service tool for creating pan-genome allele database for molecular fine typing. Scientific Reports, 6. https://doi.org/10.1038/srep36213Liu, Y. Y., Lin, J. W., & Chen, C. C. (2019). Cano-wgMLST_BacCompare: A bacterial genome analysis platform for epidemiological investigation and comparative genomic analysis. In Frontiers in Microbiology (Vol. 10, Issue JULY). Frontiers Media S.A. https://doi.org/10.3389/fmicb.2019.01687Luis, J. (2012). Hipótesis, Método & Diseño de Investigación. In Daena: International Journal of Good Conscience (Vol. 7, Issue 2).Lüth, S., Deneke, C., Kleta, S., & Dahouk, S. Al. (2021). Translatability of wgs typing results can simplify data exchange for surveillance and control of listeria monocytogenes. Microbial Genomics, 7(1), 1–12.Magalhães, B., Valot, B., Abdelbary, M. M. H., Prod’hom, G., Greub, G., Senn, L., & Blanc, D. S. (2020). Combining Standard Molecular Typing and Whole Genome Sequencing to Investigate Pseudomonas aeruginosa Epidemiology in Intensive Care Units. Frontiers in Public Health, 8. https://doi.org/10.3389/fpubh.2020.00003Maiden, M. C. J., Rensburg, M. J. J. van, Bray, J. E., Earle, S. G., Ford, S. A., Jolley, K. A., & McCarthy, N. D. (2013). MLST revisited: the gene-by-gene approach to bacterial genomics. Nature Reviews. Microbiology, 11(10), 728. https://doi.org/10.1038/NRMICRO3093Maiden, M. C. J., Van Rensburg, M. J. J., Bray, J. E., Earle, S. G., Ford, S. A., Jolley, K. A., & McCarthy, N. D. (2013). MLST revisited: The gene-by-gene approach to bacterial genomics. In Nature Reviews Microbiology (Vol. 11, Issue 10, pp. 728–736). https://doi.org/10.1038/nrmicro3093Mamede, R., Vila-Cerqueira, P., Silva, M., Carriço, J. A., & Ramirez, M. (2021). Chewie Nomenclature Server (chewie-NS): a deployable nomenclature server for easy sharing of core and whole genome MLST schemas. Nucleic Acids Research, 49(D1), D660–D666. https://doi.org/10.1093/NAR/GKAA889Mangul, S., Martin, L. S., Hill, B. L., Lam, A. K. M., Distler, M. G., Zelikovsky, A., Eskin, E., & Flint, J. (2019). Systematic benchmarking of omics computational tools. In Nature Communications (Vol. 10, Issue 1, pp. 1–11). Nature Publishing Group. https://doi.org/10.1038/s41467-019-09406-4Marcos-Zambrano, L. J., Escribano, P., Bouza, E., & Guinea, J. (2014). Use of molecular typing tools for the study of hospital outbreaks of candidemia. Revista Iberoamericana de Micologia, 31(2), 97–103. https://doi.org/10.1016/j.riam.2013.06.003Martin, J., Phan, H. T. T., Findlay, J., Stoesser, N., Pankhurst, L., Navickaite, I., De Maio, N., Eyre, D. W., Toogood, G., Orsi, N. M., Kirby, A., Young, N., Turton, J. F., Hill, R. L. R., Hopkins, K. L., Woodford, N., Peto, T. E. A., Walker, A. S., Crook, D. W., & Wilcox, M. H. (2017). Covert dissemination of carbapenemase-producing Klebsiella pneumoniae (KPC) in a successfully controlled outbreak: long- and short-read whole-genome sequencing demonstrate multiple genetic modes of transmission. The Journal of Antimicrobial Chemotherapy, 72(11), 3025–3034. https://doi.org/10.1093/jac/dkx264Martínez-Carranza, E., García-Reyes, S., González-Valdez, A., & Soberón-Chávez, G. (2020). Tracking the genome of four Pseudomonas aeruginosa isolates that have a defective Las quorum-sensing system, but are still virulent. Access Microbiology, 2(7). https://doi.org/10.1099/acmi.0.000132Merchán, M. A., Caicedo, M. I. T., & Torres, A. K. D. (2017). Técnicas de Biología Molecular en el desarrollo de la investigación. Revisión de la literatura. Revista Habanera de Ciencias Medicas, 16(5), 796–807Michael Dunne, W., Pouseele, H., Monecke, S., Ehricht, R., & van Belkum, A. (2018). Epidemiology of transmissible diseases: Array hybridization and next generation sequencing as universal nucleic acid-mediated typing tools. Infection, Genetics and Evolution, 63, 332–345. https://doi.org/10.1016/j.meegid.2017.09.019Mirande, C., Bizine, I., Giannetti, A., Picot, N., & van Belkum, A. (2018). Epidemiological aspects of healthcare-associated infections and microbial genomics. European Journal of Clinical Microbiology and Infectious Diseases, 37(5), 823–831. https://doi.org/10.1007/S10096-017-3170-X/TABLES/4Miro, E., Rossen, J. W. A., Chlebowicz, M. A., Harmsen, D., Brisse, S., Passet, V., Navarro, F., Friedrich, A. W., & García-Cobos, S. (2020). Core/Whole Genome Multilocus Sequence Typing and Core Genome SNP-Based Typing of OXA-48-Producing Klebsiella pneumoniae Clinical Isolates From Spain. Frontiers in Microbiology, 10. https://doi.org/10.3389/fmicb.2019.02961Misra, B. B., Langefeld, C., Olivier, M., & Cox, L. A. (2019). Integrated omics: Tools, advances and future approaches. In Journal of Molecular Endocrinology (Vol. 62, Issue 1, pp. R21–R45). BioScientifica Ltd. https://doi.org/10.1530/JME-18-0055Moradigaravand, D., Martin, V., Peacock, S. J., & Parkhill, J. (2017). Evolution and epidemiology of multidrug-resistant Klebsiella pneumoniae in the United Kingdom and Ireland. MBio, 8(1). https://doi.org/10.1128/mBio.01976-16Nadon, C. A., Trees, E., Ng, L. K., Møller Nielsen, E., Reimer, A., Maxwell, N., Kubota, K. A., & Gerner-Smidt, P. (2013). Development and application of MLVA methods as a tool for inter-laboratory surveillance. Eurosurveillance, 18(35), 20565. https://doi.org/10.2807/1560-7917.ES2013.18.35.20565Neoh, H. min, Tan, X. E., Sapri, H. F., & Tan, T. L. (2019). Pulsed-field gel electrophoresis (PFGE): A review of the “gold standard” for bacteria typing and current alternatives. In Infection, Genetics and Evolution (Vol. 74). Elsevier B.V. https://doi.org/10.1016/j.meegid.2019.103935Neoh, H. min, Tan, X. E., Sapri, H. F., & Tan, T. L. (2019). Pulsed-field gel electrophoresis (PFGE): A review of the “gold standard” for bacteria typing and current alternatives. In Infection, Genetics and Evolution (Vol. 74). Elsevier B.V. https://doi.org/10.1016/j.meegid.2019.103935Nguyen, K. T., Bonasera, R., Benson, G., Hernandez-Morales, A. C., Gill, J. J., & Liu, M. (2019). Complete Genome Sequence of Klebsiella pneumoniae Myophage May. Microbiology Resource Announcements, 8(19). https://doi.org/10.1128/MRA.00252-19Noller, A. C., McEllistrem, M. C., Pacheco, A. G. F., Boxrud, D. J., & Harrison, L. H. (2003). Multilocus Variable-Number Tandem Repeat Analysis Distinguishes Outbreak and Sporadic Escherichia coli O157:H7 Isolates. Journal of Clinical Microbiology, 41(12), 5389–5397. https://doi.org/10.1128/JCM.41.12.5389-5397.2003Page, A. J., Cummins, C. A., Hunt, M., Wong, V. K., Reuter, S., Holden, M. T. G., Fookes, M., Falush, D., Keane, J. A., & Parkhill, J. (2015). Roary: rapid large-scale prokaryote pan genome analysis. Bioinformatics, 31(22), 3691–3693. https://doi.org/10.1093/bioinformatics/btv421Papić, B., Diricks, M., & Kušar, D. (2021). Analysis of the Global Population Structure of Paenibacillus larvae and Outbreak Investigation of American Foulbrood Using a Stable wgMLST Scheme. Frontiers in Veterinary Science, 8, 582677. https://doi.org/10.3389/fvets.2021.582677Payne, M., Kaur, S., Wang, Q., Hennessy, D., Luo, L., Octavia, S., Tanaka, M. M., Sintchenko, V., & Lan, R. (2020). Multilevel genome typing: genomics-guided scalable resolution typing of microbial pathogens. Euro Surveillance : Bulletin Europeen Sur Les Maladies Transmissibles = European Communicable Disease Bulletin, 25(20). https://doi.org/10.2807/1560-7917.ES.2020.25.20.1900519Peix, A., Ramírez-Bahena, M. H., & Velázquez, E. (2009). Historical evolution and current status of the taxonomy of genus Pseudomonas. Infection, Genetics and Evolution : Journal of Molecular Epidemiology and Evolutionary Genetics in Infectious Diseases, 9(6), 1132–1147. https://doi.org/10.1016/J.MEEGID.2009.08.001Peix, A., Ramírez-Bahena, M. H., & Velázquez, E. (2018). The current status on the taxonomy of Pseudomonas revisited: An update. Infection, Genetics and Evolution, 57, 106–116. https://doi.org/10.1016/j.meegid.2017.10.026Perrin, A., & Rocha, E. P. C. (2021). PanACoTA: a modular tool for massive microbial comparative genomics. NAR Genomics and Bioinformatics, 3(1), lqaa106. https://doi.org/10.1093/nargab/lqaa106Platt, S., Pichon, B., George, R., & Green, J. (2006). RESEARCH NOTE A bioinformatics pipeline for high-throughput microbial multilocus sequence typing (MLST) analyses. https://doi.org/10.1111/j.1469-0691.2006.01541.xRiley, L. W. (2018). Laboratory Methods in Molecular Epidemiology: Bacterial Infections. Microbiology Spectrum, 6(6). https://doi.org/10.1128/MICROBIOLSPEC.AME-0004-2018Robinson, M. D., & Vitek, O. (2019). Benchmarking comes of age. Genome Biology, 20(1). https://doi.org/10.1186/S13059-019-1846-5Rouli, L., Merhej, V., Fournier, P. E., & Raoult, D. (2015). The bacterial pangenome as a new tool for analysing pathogenic bacteria. New Microbes and New Infections, 7, 72–85. https://doi.org/10.1016/j.nmni.2015.06.005Royer, G., Fourreau, F., Boulanger, B., Mercier-Darty, M., Ducellier, D., Cizeau, F., Potron, A., Podglajen, I., Mongardon, N., & Decousser, J. W. (2020). outbreak. Journal of Hospital Infection, 104(1), 33–39. https://doi.org/10.1016/j.jhin.2019.07.014Ruppé, E., Olearo, F., Pires, D., Baud, D., Renzi, G., Cherkaoui, A., Goldenberger, D., Huttner, A., François, P., Harbarth, S., & Schrenzel, J. (2017). Clonal or not clonal? Investigating hospital outbreaks of KPC-producing Klebsiella pneumoniae with whole-genome sequencing. Clinical Microbiology and Infection, 23(7), 470–475. https://doi.org/10.1016/j.cmi.2017.01.015Saharman, Y. R., Pelegrin, A. C., Karuniawati, A., Sedono, R., Aditianingsih, D., Goessens, W. H. F., Klaassen, C. H. W., van Belkum, A., Mirande, C., Verbrugh, H. A., & Severin, J. A. (2019). Epidemiology and characterisation of carbapenem-non-susceptible Pseudomonas aeruginosa in a large intensive care unit in Jakarta, Indonesia. International Journal of Antimicrobial Agents, 54(5), 655–660. https://doi.org/10.1016/j.ijantimicag.2019.08.003Sahl, J. W., Lemmer, D., Travis, J., Schupp, J. M., Gillece, J. D., Aziz, M., Driebe, E. M., Drees, K. P., Hicks, N. D., Williamson, C. H. D., Hepp, C. M., Smith, D. E., Roe, C., Engelthaler, D. M., Wagner, D. M., & Keim, P. (2016). NASP: an accurate, rapid method for the identification of SNPs in WGS datasets that supports flexible input and output formats. Microbial Genomics, 2(8), e000074. https://doi.org/10.1099/mgen.0.000074Salipante, S. J., SenGupta, D. J., Cummings, L. A., Land, T. A., Hoogestraat, D. R., & Cookson, B. T. (2015). Application of whole-genome sequencing for bacterial strain typing in molecular epidemiology. Journal of Clinical Microbiology, 53(4), 1072–1079. https://doi.org/10.1128/JCM.03385-14Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., Bremges, A., Fritz, A., Garrido-Oter, R., Jørgensen, T. S., Shapiro, N., Blood, P. D., Gurevich, A., Bai, Y., Turaev, D., … McHardy, A. C. (2017). Critical Assessment of Metagenome Interpretation - A benchmark of metagenomics software. Nature Methods, 14(11), 1063–1071. https://doi.org/10.1038/nmeth.4458Seth-Smith, H. M. B., Bonfiglio, F., Cuénod, A., Reist, J., Egli, A., & Wüthrich, D. (2019). Evaluation of Rapid Library Preparation Protocols for Whole Genome Sequencing Based Outbreak Investigation. Frontiers in Public Health, 7(AUG), 241. https://doi.org/10.3389/fpubh.2019.00241Singh, M., Malik, M. A., Singh, D. K., Doimari, S., Bhavna, & Sharma, R. (2020). Multilocus variable number tandem repeat analysis (MLVA)-typing of Brucella abortus isolates of India reveals limited genetic diversity. Tropical Animal Health and Production, 52(3), 1187–1194. https://doi.org/10.1007/s11250-019-02110-xSitto, F., & Battistuzzi, F. U. (2020). Estimating Pangenomes with Roary. Molecular Biology and Evolution, 37(3), 933–939. https://doi.org/10.1093/MOLBEV/MSZ284Tadee, P., Tadee, P., Hitchings, M. D., Pascoe, B., Sheppard, S. K., & Patchanee, P. (2018). High Resolution Whole Genome Multilocus Sequence Typing (wgMLST) Schemes for Salmonella enterica Weltevreden Epidemiologic Investigations. Biotechnol. Lett, 46(2), 162–170. https://doi.org/10.4014/mbl.1802.02008Tenover, F. C., Arbeit, R. D., Goering, R. V., Mickelsen, P. A., Murray, B. E., Persing, D. H., & Swaminathan, B. (1995). Interpreting chromosomal DNA restriction patterns produced by pulsed- field gel electrophoresis: Criteria for bacterial strain typing. In Journal of Clinical Microbiology (Vol. 33, Issue 9, pp. 2233–2239). American Society for Microbiology. https://doi.org/10.1128/jcm.33.9.2233-2239.1995Timme, R. E., Rand, H., Shumway, M., Trees, E. K., Simmons, M., Agarwala, R., Davis, S., Tillman, G. E., Defibaugh-Chavez, S., Carleton, H. A., Klimke, W. A., & Katz, L. S. (2017). Benchmark datasets for phylogenomic pipeline validation, applications for foodborne pathogen surveillance. PeerJ, 2017(10). https://doi.org/10.7717/peerj.3893Tissot, F., Blanc, D. S., Basset, P., Zanetti, G., Berger, M. M., Que, Y. A., Eggimann, P., & Senn, L. (2016). New genotyping method discovers sustained nosocomial Pseudomonas aeruginosa outbreak in an intensive care burn unit. Journal of Hospital Infection, 94(1), 2–7. https://doi.org/10.1016/j.jhin.2016.05.011Treangen, T. J., Ondov, B. D., Koren, S., & Phillippy, A. M. (2014). The harvest suite for rapid core-genome alignment and visualization of thousands of intraspecific microbial genomes. Genome Biology, 15(11), 1–15. https://doi.org/10.1186/S13059-014-0524-X/TABLES/4Tsai, M. H., Liu, Y. Y., & Soo, V. W. (2017). PathoBacTyper: A web server for pathogenic bacteria identification and molecular genotyping. Frontiers in Microbiology, 8(AUG), 1474. https://doi.org/10.3389/fmicb.2017.01474Uelze, L., Grützke, J., Borowiak, M., Hammerl, J. A., Juraschek, K., Deneke, C., Tausch, S. H., & Malorny, B. (2020). Typing methods based on whole genome sequencing data. One Health Outlook, 2(1), 1–19. https://doi.org/10.1186/s42522-020-0010-1van Beek, J., Räisänen, K., Broas, M., Kauranen, J., Kähkölä, A., Laine, J., Mustonen, E., Nurkkala, T., Puhto, T., Sinkkonen, J., Torvinen, S., Vornanen, T., Vuento, R., Jalava, J., & Lyytikäinen, O. (2019). Tracing local and regional clusters of carbapenemase-producing Klebsiella pneumoniae ST512 with whole genome sequencing, Finland, 2013 to 2018. Eurosurveillance, 24(38). https://doi.org/10.2807/1560-7917.ES.2019.24.38.1800522Van Belkum, A., Struelens, M., De Visser, A., Verbrugh, H., & Tibayrenc, M. (2001). Role of Genomic Typing in Taxonomy, Evolutionary Genetics, and Microbial Epidemiology. Clinical Microbiology Reviews, 14(3), 547. https://doi.org/10.1128/CMR.14.3.547-560.2001van Dorp, L., Wang, Q., Shaw, L. P., Acman, M., Brynildsrud, O. B., Eldholm, V., Wang, R., Gao, H., Yin, Y., Chen, H., Ding, C., Farrer, R. A., Didelot, X., Balloux, F., & Wang, H. (2019). Rapid phenotypic evolution in multidrug-resistant Klebsiella pneumoniae hospital outbreak strains. Microbial Genomics, 5(4), 1–11. https://doi.org/10.1099/mgen.0.000263Vaz, C., Francisco, A. P., Silva, M., Jolley, K. A., Bray, J. E., Pouseele, H., Rothganger, J., Ramirez, M., & Carriço, J. A. (2014). TypOn: the microbial typing ontology. Journal of Biomedical Semantics, 5(1), 43. https://doi.org/10.1186/2041-1480-5-43Vernikos, G. S. (2020). A Review of Pangenome Tools and Recent Studies. The Pangenome: Diversity, Dynamics and Evolution of Genomes, 89–112. https://doi.org/10.1007/978-3-030-38281-0_4Wang, G., Zhao, G., Chao, X., Xie, L., & Wang, H. (2020). The Characteristic of Virulence, Biofilm and Antibiotic Resistance of Klebsiella pneumoniae. International Journal of Environmental Research and Public Health, 17(17), 1–17. https://doi.org/10.3390/IJERPH17176278Weber, L. M., Saelens, W., Cannoodt, R., Soneson, C., Hapfelmeier, A., Gardner, P. P., Boulesteix, A. L., Saeys, Y., & Robinson, M. D. (2019). Essential guidelines for computational method benchmarking. In Genome Biology (Vol. 20, Issue 1, pp. 1–12). BioMed Central Ltd. https://doi.org/10.1186/s13059-019-1738-8Wingett, S. W., & Andrews, S. (2018). FastQ Screen: A tool for multi-genome mapping and quality control. F1000Research, 7, 1338Yoshimura, D., Kajitani, R., Gotoh, Y., Katahira, K., Okuno, M., Ogura, Y., Hayashi, T., & Itoh, T. (2019). Evaluation of SNP calling methods for closely related bacterial isolates and a novel high-accuracy pipeline: BactSNP. Microbial Genomics, 5(5). https://doi.org/10.1099/mgen.0.000261Youenou, B., Brothier, E., & Nazaret, S. (2014). Diversity among strains of Pseudomonas aeruginosa from manure and soil, evaluated by multiple locus variable number tandem repeat analysis and antibiotic resistance profiles. Research in Microbiology, 165(1), 2–13. https://doi.org/10.1016/j.resmic.2013.10.004Zheng, S. (2017). Bogaerts Contexts and details matter. In Genome Biology (Vol. 18, Issue 1, p. 129). BioMed Central Ltd. https://doi.org/10.1186/s13059-017-1258-3Zhi, X. Y., Zhao, W., Li, W. J., & Zhao, G. P. (2011). Prokaryotic systematics in the genomics era. Antonie van Leeuwenhoek 2011 101:1, 101(1), 21–34. https://doi.org/10.1007/S10482-011-9667-XZhou, G. H., Gotou, M., Kajiyama, T., & Kambara, H. (2005). Multiplex SNP typing by bioluminometric assay coupled with terminator incorporation (BATI). Nucleic Acids Research, 33(15), 1–11. https://doi.org/10.1093/nar/gni132Zhou, K., Lokate, M., Deurenberg, R. H., Tepper, M., Arends, J. P., Raangs, E. G. C., Lo-Ten-Foe, J., Grundmann, H., Rossen, J. W. A., & Friedrich, A. W. (2016). Whole genome sequencing for the molecular characterization of carbapenem-resistant Klebsiella pneumoniae strains isolated at the Italian ASST Fatebenefratelli Sacco Hospital, 2012-2014Use of whole-genome sequencing to trace, control and characterize the r. Scientific Reports, 6, 20840. https://doi.org/10.1038/srep20840Zhou, Z., Alikhan, N. F., Sergeant, M. J., Luhmann, N., Vaz, C., Francisco, A. P., Carriço, J. A., & Achtman, M. (2018). GrapeTree: visualization of core genomic relationships among 100,000 bacterial pathogens. Genome Research, 28(9), 1395–1404. https://doi.org/10.1101/GR.232397.117Inouye, M., Dashnow, H., Raven, L. A., Schultz, M. B., Pope, B. J., Tomita, T., Zobel, J., & Holt, K. E. (2014). SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Medicine, 6(11), 90. https://doi.org/10.1186/s13073-014-0090-6Pérez-Losada, M., Arenas, M., & Castro-Nallar, E. (2018). Microbial sequence typing in the genomic era. Infection, Genetics and Evolution, 63, 346–359. https://doi.org/10.1016/j.meegid.2017.09.022LICENSElicense.txtlicense.txttext/plain; charset=utf-85879https://repositorio.unal.edu.co/bitstream/unal/84272/1/license.txteb34b1cf90b7e1103fc9dfd26be24b4aMD51ORIGINAL16843909.2023.pdf16843909.2023.pdfTesis de Maestría en Bioinformáticaapplication/pdf2038863https://repositorio.unal.edu.co/bitstream/unal/84272/2/16843909.2023.pdf2e8067c417feae48f399357d68a0c1bfMD52THUMBNAIL16843909.2023.pdf.jpg16843909.2023.pdf.jpgGenerated Thumbnailimage/jpeg5277https://repositorio.unal.edu.co/bitstream/unal/84272/3/16843909.2023.pdf.jpg9d67d56faaece55b809c99993e0d189cMD53unal/84272oai:repositorio.unal.edu.co:unal/842722024-08-12 01:58:51.977Repositorio Institucional Universidad Nacional de Colombiarepositorio_nal@unal.edu.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