Applications of comparative genomics in the surveillance of bacterial resistance

Autores

DOI:

https://doi.org/10.56183/iberojhr.v5i1.763

Palavras-chave:

Comparative genomics, Bacterial resistance, Bioinformatics, Epidemiological surveillance.

Resumo

In recent decades, bacterial resistance to antibiotics has become one of the greatest challenges to global public health, as it could cause 10 million deaths annually by 2050 if effective control measures are not implemented immediately. In this context, there is a need for accurate, rapid tools to monitor, understand, and combat the problem. Its application in surveillance has revolutionized the way bacterial resistance is monitored through the analysis of whole genome sequences. A systematic review was conducted to provide a detailed analysis based on the available scientific evidence. The search was conducted in recognized databases such as Scielo , PubMed, Scopus, and Google Scholar, focusing on scientific articles published in English, Portuguese, and Spanish. Comparative studies analyzing genomics were included. The articles were critically appraised to extract relevant data on the applications of comparative genomics in bacterial resistance surveillance. The data obtained were analyzed using an evidence matrix. Finally, it is important to note that their integration into health systems strengthens outbreak response capacity and helps create clearer and more useful rules for proper antibiotic use. Furthermore, their combination with bioinformatics tools and global genomic databases has enabled the development of collaborative international data surveillance networks, which are essential for responding to health problems.

Biografia do Autor

Carlos Fabian Argotti Zumbana, Universidad Técnica de Ambato, Ecuador

Docente de la Universidad Técnica de Ambato, Ecuador.

 

Rodrigo Daniel Argotti Zumbana, Universidad Técnica de Ambato, Ecuador

Docente de la Universidad Técnica de Ambato, Ecuador.

 

Grace Pamela López Pérez, Universidad Técnica de Ambato, Ecuador

Docente de la Universidad Técnica de Ambato, Equador.

 

Nathaly Michelle Sánchez Guarnizo, Lic. en Laboratorio Clínico e Histopatológico, Equador

Lic. en Laboratorio Clínico e Histopatológico. MSc. En Criminalística y Ciencias Forenses, Equador.

 

María Salome Argotti Zumbana, Medica General, Ecuador

Medica General, Ecuador.

 

Referências

Baker, KS, Jauneikaite , E., Hopkins, KL, Lo, SW, Sánchez- Busó , L., Getino , M., Howden , BP, Holt, KE, Musila , LA, Hendriksen, RS, Amoako , DG, Aanensen , DM, Okeke , IN, Egyir , B., Nunn , JG, Midega , JT, Feasey , NA, Peacock , SJ, & SEDRIC Genomics Surveillance Working Group . (2023). Genomics for public health and international surveillance of antimicrobial resistance. The Lancet. Microbe, 4(12), e1047–e1055. https://doi.org/10.1016/S2666-5247(23)00283-5

Baker, KS, Jauneikaite , E., Nunn, JG, Midega, JT, Atun, R., Holt, KE, Walia, K., Howden, BP, Tate, H., Okeke, IN, Carattoli , A., Hsu, LY, Hopkins, KL, Muloi , DM, Wheeler, NE, Aanensen, DM, Mason, LCE, Rodgus , J., Hendriksen, RS, … SEDRIC Genomics Surveillance Working Group. (2023). Evidence review and recommendations for the implementation of genomics for antimicrobial resistance surveillance: reports from an international expert group. The Lancet. Microbe , 4(12), e1035–e1039. https://doi.org/10.1016/S2666-5247(23)00281-1

Bradley, P., Gordon, NC, Walker, TM, Dunn, L., Heys , S., Huang, B., Earle , S., Pankhurst , LJ, Anson , L., de Cesare, M., Piazza, P., Votintseva , AA, Golubchik , T., Wilson, DJ, Wyllie , D.H., Diel , R., Niemann, S., Feuerriegel , S., Kohl, T.A., … Iqbal, Z. (2015). Rapid antibiotic-resistance predictions from genome sequence data for Staphylococcus aureus and Mycobacterium tuberculosis. Nature Communications , 6, 10063. https://doi.org/10.1038/ncomms10063

Calero-Cáceres, W., Ortuño-Gutiérrez, N., Sunyoto , T., Gomes- Dias , C.-A., Bastidas-Caldes, C., Ra https://doi.org/10.26633/RPSP.2023.8 Mírez , MS, & Harries , AD (2023). Whole-genome sequencing for surveillance of antimicrobial resistance in Ecuador: present and future implications. Pan American Journal of Public Health [Pan American Journal of Public Health ], 47, e8.

Cedeño, V., Reyes, V., Parra, C. L., Machuca, J., Pérez, L., Llanos, R., & Toala , A. (2020). Medical Microbiology. Mawil.us. https://mawil.us/wp-content/uploads/2020/03/microbiologia-medica.pdf

De Araújo Neto, PP, Silva, CR, Dos Santos, RRL, De Paiva, AGC, Ximenes , J. da C., Guimarães, DVF da S., Castro, LM de B., Moreira, THG, Carvalho, RRN, & Barros, FT (2023). BACTERIAL RESISTANCE CONSECUTIVE TO THE INDISCRIMINATE USE OF ANTIBIOTICS: INTEGRATIVE REVIEW. Arquivos de Ciências da Saúde da UNIPAR, 27(5), 3320–3330. https://doi.org/10.25110/arqsaude.v27i5.2023-076

Fernández Rodríguez, RE (2021). Antibiotic resistance: the role of humans, animals, and the environment. Salud Uninorte, 36(1), 298–324. https://doi.org/10.14482/sun.36.1.615

Garza-Ramos, U., Silva-Sánchez, J., & Martínez-Romero, E. (2019). Genetics and genomics focused on the study of bacterial resistance. Public Health of Mexico , 51, 439– 446. https://www.scielo.org.mx/scielo.php?script=sci_arttext&pid=S0036-36342009000900009

Hernández, M., Quijada, NM, Rodríguez-Lázaro, D., & Eiros , JM (2020). Application of massive sequencing and bioinformatics to clinical microbiological diagnosis. Argentine Journal of Microbiology , 52(2), 150–161. https://doi.org/10.1016/j.ram.2019.06.003

Jauneikaite , E., Baker, KS, Nunn, JG, Midega, JT, Hsu, LY, Singh, SR, Halpin, AL, Hopkins, KL, Price, JR, Srikantiah , P., Egyir , B., Okeke, IN, Holt, KE, Peacock, SJ, Feasey , NA, & SEDRIC Genomics Surveillance Working Group. (2023). Genomics for antimicrobial resistance surveillance to support infection prevention and control in health-care facilities. The Lancet. Microbe, 4(12), e1040–e1046. https://doi.org/10.1016/S2666-5247(23)00282-3

Landman, F., Jamin, C., de Haan, A., Witteveen, S., Bos, J., van der Heide, HGJ, Schouls , LM, Hendrickx, APA, & Dutch CPE/MRSA surveillance study group. (2024). Genomic surveillance of multidrug-resistant organisms based on long-read sequencing. Genome Medicine, 16(1), 137. https://doi.org/10.1186/s13073-024-01412-6

Lin, E.Y., Adamson, P.C., & Klausner, J.D. (2022). Applying molecular algorithms to predict decreased susceptibility to ceftriaxone from a report of strains of Neisseria gonorrhoeae in Amsterdam, the Netherlands. The Journal of Antimicrobial Chemotherapy , 77(2), 534–536. https://doi.org/10.1093/jac/dkab389

Lirola -Andreu, L., Ángel, F. Á.-J., Marta, AF-M., Reinoso-Espín, Á., & Martínez-Martínez, S. (2022). Bacterial resistance. Generalities, carbapenemases and current events: a narrative review . Ugr.es. https://digibug.ugr.es/bitstream/handle/10481/75043/ES%20-%20Resistencias.pdf?sequence=1&isAllowed=y

Murray C., Shunji K., Sharara F., Swetchinski L., Aguila G. (2022). Global burden of bacterial antimicrobial resistance in 2019: a systematic analysis. Lancet, 399(10325), 629–655. https://doi.org/10.1016/S0140-6736(21)02724-0

Naghavi M., Vollset S., Wool E., Han C., Chung E., Altay U., Smith G., Araki D., Alzoubi K., Amos B. (2024). Global burden of bacterial antimicrobial resistance 1990-2021: a systematic analysis with forecasts to 2050. Lancet, 404(10459), 1199–1226. https://doi.org/10.1016/S0140-6736(24)01867-1

Neca , CSM, Marques, A. Â., Oliveira Júnior, CL de, Silva, MES, Costa, ME, & Rodrigues , SA (2022). Or use of bacteriophages as a solution na antibiotic resistance and its applications na industry : uma literature review . Research, Society and Development, 11(9), e56011932098. https://doi.org/10.33448/rsd-v11i9.32098

Olsen, N.S., & Riber, L. (2025). Metagenomics as a transformative tool for antibiotic resistance surveillance: Highlighting the impact of mobile genetic elements with a focus on the complex role of phages. Antibiotics ( Basel , Switzerland ), 14(3). https://doi.org/10.3390/antibiotics14030296

Rubio, S., Pacheco-Orozco, R. A., Gómez, A. M., Perdomo, S., & García-Robles, R. (2020). Next-generation sequencing (NGS) of DNA: present and future in clinical practice. Universitas Médica, 61(2), 49–63 . https://doi.org/10.11144/javeriana.umed61-2.sngs

Sherry, NL, Lee, JYH, Giulieri , SG, Connor, CH, Horan, K., Lacey, JA, Lane, CR, Carter, GP, Seemann, T., Egli, A., Stinear , TP, & Howden, BP (2025). Genomics for antimicrobial resistance-progress and future directions. Antimicrobial Agents and Chemotherapy, 69(5), e0108224. https://doi.org/10.1128/aac.01082-24

Su, M., Satola , S.W., & Read , T.D. (2019). Genome-based prediction of bacterial antibiotic resistance. Journal of Clinical Microbiology , 57(3). https://doi.org/10.1128/JCM.01405-18

Vallejo-Espín, D., Galarza-Mayorga, J., Lalaleo , L., & Calero-Cáceres, W. (2025). Beyond clinical genomics: addressing critical gaps in One Health AMR surveillance. Frontiers in Microbiology, 16, 1596720. https://doi.org/10.3389/fmicb.2025.1596720

Zhang, R., & Zhang, C.-T. (2019). The impact of comparative genomics on infectious disease research. Microbes and Infection, 8(6), 1613–1622. https://doi.org/10.1016/j.micinf.2005.11.019

Zhen, X., Lundborg, C.S., Sun, X., Hu, X., & Dong, H. (2019). Economic burden of antibiotic resistance in ESKAPE organisms: a systematic review. Antimicrobial Resistance and Infection Control, 8(1), 137. https://doi.org/10.1186/s13756-019-0590-7

Zumbado Morales, R., Barquero Montero, A., & Hidalgo Mora, O. (2022). Antibiotic resistance: A bibliographic review. Journal of Science and Health Integrating Knowledge, 6(3), 145–153. https://doi.org/10.34192/cienciaysalud.v6i3.500

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Publicado

2025-06-15

Como Citar

Argotti Zumbana, C. F., Argotti Zumbana, R. D., López Pérez, G. P., Sánchez Guarnizo, N. M., & Argotti Zumbana, M. S. (2025). Applications of comparative genomics in the surveillance of bacterial resistance. Ibero-American Journal of Health Science Research, 5(1), 451–457. https://doi.org/10.56183/iberojhr.v5i1.763