Identifying the causal agent and its antimicrobial susceptibility is crucial for the management of infectious diseases. With antimicrobial resistance increasing at alarming rates and becoming a worldwide threat, achieving rapid microbial identification allows to promptly direct the antimicrobial therapy, reducing the use of broad-range antimicrobials.
Traditionally, the gold standard in the microbiology laboratory relies on the growth of the microorganism, implying a delay between sample collection and the identification of the pathogen and its susceptibility pattern, which can be increased when dealing with slow-growing or fastidious microorganisms.
The automation of the microbiology laboratory can be complex, given the great diversity of samples to be analyzed and the inherent characteristics of different microorganisms. However, several technologies are currently routinely in use, allowing to achieve a faster identification. The introduction of the MALDI-TOF to identify microorganisms revolutionized the clinical microbiology laboratory, and it has been widely implemented, routinely identifying microorganisms from colony or samples such as urine or blood culture. Molecular methods, multiplexed or not, have been widely used in the clinical laboratory for decades. However, although their strength is their high sensitivity, they must deal with contaminations or sample interferences, among other drawbacks.
Although the pathogen’s identification would certainly guide antimicrobial therapy, antimicrobial susceptibility testing (or predicting it from genomic information) is required. Some rapid tests for the detection of specific resistance genes such as mecA from Staphylococcus aureus are widely used, but for genes located on plasmids, high allele diversity, or gene regulation, such as in the case of ß-lactamases or ß-lactams/ ß-lactamases inhibitors in Gram-negatives, detection of the AMR markers is more challenging. Therefore, new, more rapid, and reliable detection methods for antimicrobial resistance are still needed.
In the last few years, traditional or real-time PCR, next-generation sequencing, arrays, or biosensors-based methods have advanced in sensitivity, ease of use or format, and availability for routine use in the clinical laboratory.
This Research Topic welcomes manuscripts describing new approaches for identifying bacteria and fungi and/or their antimicrobial resistance that can potentially be implemented in a clinical laboratory in all acceptable formats, including Original Research articles, Methods articles, and Reviews.
Identifying the causal agent and its antimicrobial susceptibility is crucial for the management of infectious diseases. With antimicrobial resistance increasing at alarming rates and becoming a worldwide threat, achieving rapid microbial identification allows to promptly direct the antimicrobial therapy, reducing the use of broad-range antimicrobials.
Traditionally, the gold standard in the microbiology laboratory relies on the growth of the microorganism, implying a delay between sample collection and the identification of the pathogen and its susceptibility pattern, which can be increased when dealing with slow-growing or fastidious microorganisms.
The automation of the microbiology laboratory can be complex, given the great diversity of samples to be analyzed and the inherent characteristics of different microorganisms. However, several technologies are currently routinely in use, allowing to achieve a faster identification. The introduction of the MALDI-TOF to identify microorganisms revolutionized the clinical microbiology laboratory, and it has been widely implemented, routinely identifying microorganisms from colony or samples such as urine or blood culture. Molecular methods, multiplexed or not, have been widely used in the clinical laboratory for decades. However, although their strength is their high sensitivity, they must deal with contaminations or sample interferences, among other drawbacks.
Although the pathogen’s identification would certainly guide antimicrobial therapy, antimicrobial susceptibility testing (or predicting it from genomic information) is required. Some rapid tests for the detection of specific resistance genes such as mecA from Staphylococcus aureus are widely used, but for genes located on plasmids, high allele diversity, or gene regulation, such as in the case of ß-lactamases or ß-lactams/ ß-lactamases inhibitors in Gram-negatives, detection of the AMR markers is more challenging. Therefore, new, more rapid, and reliable detection methods for antimicrobial resistance are still needed.
In the last few years, traditional or real-time PCR, next-generation sequencing, arrays, or biosensors-based methods have advanced in sensitivity, ease of use or format, and availability for routine use in the clinical laboratory.
This Research Topic welcomes manuscripts describing new approaches for identifying bacteria and fungi and/or their antimicrobial resistance that can potentially be implemented in a clinical laboratory in all acceptable formats, including Original Research articles, Methods articles, and Reviews.
