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Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance
Author(s) -
Mihir Kekre,
Stefany Alejandra Arévalo,
María Fernanda Valencia,
Marietta L Lagrada,
Polle Krystle V Macaranas,
Geetha Nagaraj,
Anderson O. Oaikhena,
Agnettah M Olorosa,
David M. Aanensen,
Khalil Abudahab,
Monica Abrudan,
Silvia Argimón,
Harry Harste,
Dawn Muddyman,
Ben Taylor,
Anthony Underwood,
Nicole E. Wheeler,
Sophia David,
Pilar Donado-Godoy,
Johan Fabian Bernal,
Alejandra Arévalo,
Erik C D Osma Castro,
Ravikumar Kadahalli Lingegowda,
Varun Shamanna,
Vandana Govindan,
Akshata Prabhu,
D Sravani,
M R Shincy,
Steffimole Rose,
K N Ravishankar,
Iruka N. Okeke,
Ayorinde O. Afolayan,
Jolaade J Ajiboye,
Erkison Ewomazino Odih,
Celia Carlos,
June M Gayeta,
Elmer M Herrera,
Ali Molloy,
John Stelling,
Carolin Vegvari
Publication year - 2021
Publication title -
clinical infectious diseases
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.44
H-Index - 336
eISSN - 1537-6591
pISSN - 1058-4838
DOI - 10.1093/cid/ciab796
Subject(s) - standardization , whole genome sequencing , epidemiological surveillance , antibiotic resistance , scalability , global health , medicine , data science , genome , computational biology , computer science , epidemiology , biology , public health , genetics , database , nursing , antibiotics , gene , operating system
Antimicrobial resistance (AMR) is considered a global threat, and novel drug discovery needs to be complemented with systematic and standardized epidemiological surveillance. Surveillance data are currently generated using phenotypic characterization. However, due to poor scalability, this approach does little for true epidemiological investigations. There is a strong case for whole-genome sequencing (WGS) to enhance the phenotypic data. To establish global AMR surveillance using WGS, we developed a laboratory implementation approach that we applied within the NIHR Global Health Research Unit (GHRU) on Genomic Surveillance of Antimicrobial Resistance. In this paper, we outline the laboratory implementation at 4 units: Colombia, India, Nigeria, and the Philippines. The journey to embedding WGS capacity was split into 4 phases: Assessment, Assembly, Optimization, and Reassessment. We show that on-boarding WGS capabilities can greatly enhance the real-time processing power within regional and national AMR surveillance initiatives, despite the high initial investment in laboratory infrastructure and maintenance. Countries looking to introduce WGS as a surveillance tool could begin by sequencing select Global Antimicrobial Resistance Surveillance System (GLASS) priority pathogens that can demonstrate the standardization and impact genome sequencing has in tackling AMR.

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