Integrating Scalable Genome Sequencing Into Microbiology Laboratories for Routine Antimicrobial Resistance Surveillance
Author:
Kekre Mihir12, Arevalo Stefany Alejandra3, Valencia María Fernanda3, Lagrada Marietta L4, Macaranas Polle Krystle V4, Nagaraj Geetha5, Oaikhena Anderson O6, Olorosa Agnettah M4, Aanensen David M12, Abudahab Khalil, Abrudan Monica, Argimón Silvia, Harste Harry, Muddyman Dawn, Taylor Ben, Underwood Anthony, Wheeler Nicole, David Sophia, Donado-Godoy Pilar, Fabian Bernal Johan, Arevalo Alejandra, Osma Castro Erik C D, Ravikumar K L, Shamanna Varun, Govindan Vandana, Prabhu Akshata, Sravani D, Shincy M R, Rose Steffimole, Ravishankar K N, Okeke Iruka N, Afolayan Ayorinde O, Ajiboye Jolaade J, Ewomazino Odih Erkison, Carlos Celia, Gayeta June M, Herrera Elmer M, Molloy Ali, Stelling John, Vegvari Carolin,
Affiliation:
1. Centre for Genomic Pathogen Surveillance, Big Data Institute, University of Oxford, Old Road Campus, Oxford, United Kingdom 2. Wellcome Genome Campus, Hinxton, United Kingdom 3. Colombian Integrated Program for Antimicrobial Resistance Surveillance—Coipars, CI Tibaitatá, Corporación Colombiana de Investigación Agropecuaria (AGROSAVIA), Tibaitatá–Mosquera, Cundinamarca, Colombia 4. Research Institute for Tropical Medicine, Muntinlupa, Philippines 5. Central Research Laboratory, Kempegowda Institute of Medical Sciences, Bengaluru, India 6. Department of Pharmaceutical Microbiology, University of Ibadan, Ibadan, Nigeria
Abstract
Abstract
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.
Publisher
Oxford University Press (OUP)
Subject
Infectious Diseases,Microbiology (medical)
Cited by
16 articles.
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