Bacterial community and antimicrobial resistant genes profile in hospital wastewater among economic classes: A systematic review

• Main Author: Ishimura, Aiko B.
• Format: text
• Language: English
• Published: Animo Repository 2024
• Subjects: Anti-infective agents; Sewage—Microbiology; Bacterial communities; Microbiology
• Online Access: https://animorepository.dlsu.edu.ph/etdb_bio/81
• Institution: De La Salle University

Antimicrobial resistance (AMR) has been an increasing problem worldwide in recent years. Current surveillance programs lack data on AMR profiles from hospital wastewater, which can be detrimental as hospitals are hotspots of antibiotics and pathogenic bacteria. This literature review examined AMR profiles of different countries based on economic classes using PRISMA guidelines. A total of 243 papers from PubMed, Scopus, Proquest, EbscoHost, and Wiley were screened with 18 papers passing the screening process with over 14 countries being represented. Economic representation included upper middle (n=9), high income (n=8), lower middle (n=2), and low income countries (n=1). Among the studied countries, 29 phyla and 262 genera were present in wastewater. Some of reported phyla were: Pseudomonadota, Bacteroidota, Bacillota, Actinomycetota, and Campylobacterota; and genera: Acinetobacter, Aeromonas, Bacteroides, Pseudomonas, and Klebsiella being the most abundant. Conversely, 448 antimicrobial-resistant genes (ARGs) and 91 drug classes were present with sul1, msrE, tet(A), tet(C), and ErmB being the most abundant ARGs along with their associated drug classes which were sulfonamides, macrolides, and tetracyclines. Using WHO’s ranking of important antimicrobials, the top 15 drug classes present among the economic classes belong to highly important (n=16), critically important (n=33), and important (n=3), while others were not on the list (n=39). The results indicate how widespread antibiotic resistance is regardless of the country’s economic status. It is recommended to have more studies on the monitoring of AMR profiles in wastewater and possibly in other environmental sources using metagenomic analysis.