» Articles » PMID: 28093921

Microbial Genomics and Antimicrobial Susceptibility Testing

Overview
Specialty Molecular Biology
Date 2017 Jan 18
PMID 28093921
Citations 12
Authors
Affiliations
Soon will be listed here.
Abstract

Antimicrobial susceptibility testing is key in modern clinical microbiology. With pandemic emergence of (multi-)antibiotic resistance, methods to detect and quantify resistance of clinically important bacterial species are imperative. Historically, antimicrobial susceptibility testing (AST) was mostly performed using methods relying on bacterial growth. Such methods may be time-consuming and more rapid alternatives have been actively sought for. Areas covered: Among the new AST methods there are many that focus on detection of causal resistance genes and/or gene mutations. The approaches most used are based on nucleic acid amplification and, more recently, high-throughput (next generation) sequencing of amplified targets and complete microbial genomes. The authors provide a review of PCR-mediated and genomic AST methods used for human and veterinary pathogens and show where these approaches work well or may become difficult to interpret. Expert commentary: Microbial genome sequencing will play an important role in the field of AST, but there remain issues to be resolved. These include the development of user friendly data analysis, reducing the duration and cost of sequencing and comprehensiveness of the databases. In addition, clinical evaluation studies need to be performed involving real-life patients.

Citing Articles

A comparison of various feature extraction and machine learning methods for antimicrobial resistance prediction in .

Kaya D, Ulgen E, Kocagoz A, Sezerman O Front Antibiot. 2025; 2():1126468.

PMID: 39816648 PMC: 11731958. DOI: 10.3389/frabi.2023.1126468.


Comparison of commercial next-generation sequencing assays to conventional culture methods for bacterial identification and antimicrobial susceptibility of samples obtained from clinical cases of canine superficial bacterial folliculitis.

Smart K, Pieper J, Viall A, Noxon J, Berger D Vet Dermatol. 2024; 36(1):14-23.

PMID: 39323044 PMC: 11696477. DOI: 10.1111/vde.13299.


Rapid and Simple Morphological Assay for Determination of Susceptibility/Resistance to Combined Ciprofloxacin and Ampicillin, Independently, in .

Lopez I, Otero F, Fernandez M, Bou G, Gosalvez J, Fernandez J Antibiotics (Basel). 2024; 13(7).

PMID: 39061357 PMC: 11273673. DOI: 10.3390/antibiotics13070676.


Combining machine learning with high-content imaging to infer ciprofloxacin susceptibility in isolates of Salmonella Typhimurium.

Tran T, Sridhar S, Reece S, Lunguya O, Jacobs J, Van Puyvelde S Nat Commun. 2024; 15(1):5074.

PMID: 38871710 PMC: 11176356. DOI: 10.1038/s41467-024-49433-4.


Under-oil open microfluidic systems for rapid phenotypic antimicrobial susceptibility testing.

Li C, McCrone S, Warrick J, Andes D, Hite Z, Volk C Lab Chip. 2023; 23(8):2005-2015.

PMID: 36883560 PMC: 10581760. DOI: 10.1039/d3lc00066d.