Bacterial sensitivity testing, also known as antimicrobial susceptibility testing (AST), is a vital process in clinical microbiology that determines the effectiveness of specific antimicrobial agents against bacterial pathogens isolated from clinical samples.
By identifying which antibiotics a bacterial isolate is sensitive or resistant to, AST guides clinicians in selecting appropriate antibiotic therapy, enhancing treatment outcomes, and controlling the spread of antimicrobial resistance.
Traditional phenotypic methods, though widely used, are time-consuming, leading to the empirical use of broad-spectrum antibiotics. Rapid genotypic identification techniques, such as DNA-based tests, offer faster and more precise results, significantly improving treatment accuracy and helping to prevent antibiotic misuse.
This approach is crucial for effective patient management and combating the growing threat of antibiotic resistance.
Testing for bacterial sensitivities, also known as antimicrobial susceptibility testing (AST), is used to determine the effectiveness of specific antimicrobial agents against bacterial pathogens isolated from clinical samples.
This process aids clinicians in selecting appropriate antibiotic therapy, enhancing treatment outcomes, and controlling the spread of resistance.
The primary purpose of AST is to identify which antibiotics a bacterial isolate is sensitive or resistant to, guiding clinical decisions for the most effective treatment regimens and monitoring resistance patterns in healthcare settings.
Accurate AST results are critical for diagnosing the causative agent and its resistance profile, leading to more targeted treatments and preventing misuse of antibiotics. Proper training and competence of laboratory personnel, as well as the availability of quality reagents and adherence to procedural standards, are crucial for reliable results.
Antimicrobial susceptibility testing (AST) is a critical procedure in clinical microbiology used to determine the sensitivity of bacterial pathogens to various antimicrobial agents, essential for guiding effective treatment and controlling antimicrobial resistance (AMR).
Traditional methods like broth microdilution and disk diffusion remain widely used, though time-consuming and labor-intensive.
Recent advancements, such as automated systems (e.g., VITEK 2, Phoenix), molecular-based techniques (e.g., PCR, DNA microarrays), and mass spectrometry (e.g., MALDI-TOF MS), offer faster and more detailed insights into resistance mechanisms but require extensive validation before widespread clinical implementation.
Despite the high costs and complexity, these modern methods hold promise for improving diagnostic accuracy and patient outcomes.
The rapid emergence of antibiotic resistance in microorganisms presents a significant public health challenge. Preventive strategies such as broad surveillance programs and educating healthcare professionals are essential to address this issue.
Understanding the biochemical mechanisms of antimicrobial resistance is crucial for developing new detection tools. Traditional phenotypic methods for determining bacterial susceptibility, like disc diffusion and MIC tests, are slow, often leading to the empirical use of broad-spectrum antibiotics, exacerbating resistance.
Rapid genotypic identification of bacteria and their resistance genes offers a promising solution.
DNA-based tests can identify pathogens within an hour, significantly improving treatment accuracy and reducing antibiotic misuse.
These tests detect specific resistance genes directly from clinical specimens, allowing clinicians to tailor antibiotic therapy more precisely and avoid broad-spectrum antibiotics unless necessary.
This approach not only improves patient outcomes but also helps control the spread of resistance.
Currently, DNA-based methods are primarily used for identifying hard-to-culture bacteria like Mycobacterium tuberculosis, but their application can be expanded to common bacterial pathogens.
The simultaneous detection of bacteria and their resistance genes would enable more targeted and effective treatments. For example, detecting the mecA gene in Staphylococcus aureus can guide the use of vancomycin only when necessary, conserving its effectiveness.
A study exploring real-time PCR for rapid detection of antibiotic resistance genes in clinical samples targeted the 16S rRNA and rpoB genes.
Researchers determined bacterial growth kinetics and antibiotic susceptibilities, finding the method to be rapid (2 hours for Gram-negative bacteria, 4 hours for Gram-positive bacteria, and 5 days for mycobacteria), sensitive, and consistent with traditional macrodilution broth assays.
This approach suggests that molecular detection could significantly speed up antibiotic susceptibility testing, improving treatment decisions and managing resistance more effectively.
Some companies incorporate testing for antibiotic resistance genes as part of a comprehensive microbiome assessment when opportunistic or pathogenic organisms are discovered. [7.]
Additionally, a study analyzed fecal samples from healthy young adult Japanese to detect antibiotic resistance genes using PCR with specific primers. [5.]
Over 50% of the subjects carried genes conferring resistance to macrolides (ermB, ermF, ermX, mefA/E), tetracyclines (tetW, tetQ, tetO, tetX), β-lactam antibiotics (blaTEM), and streptomycin (aadE). [5.]
This indicates that these resistance genes are widespread among the intestinal bacteria of young adult Japanese.
The study highlights the potential of PCR for rapid detection of antibiotic resistance genes, offering valuable insights for managing and preventing the spread of antibiotic-resistant bacteria.
Bacterial sensitivity testing may require one of many sample types, as the sample type is determined by where the infection is believed to be. Sample types include blood, urine, stool, cerebrospinal fluid, sputum, throat or genital swabs, or culturing of various other body fluids including those from the eyes, ears, lungs, joints, or others.
A bacterial sensitivity test is often done as part of a bacterial culture; this dual testing determines not only which organism is present, but also the appropriate therapy to address it.
Genetic testing for antibiotic resistance genes may be done as the primary bacterial sensitivity test.
Bacterial sensitivity testing is important in guiding antibiotic therapy.
This approach not only improves patient outcomes but also helps combat the growing threat of antimicrobial resistance.
By identifying which antibiotics are effective against specific bacterial strains, clinicians can prescribe targeted treatments, reducing the use of broad-spectrum antibiotics and reducing the likelihood of antimicrobial resistance, a major threat to public health.
For instance, in cases of urinary tract infections caused by E. coli, sensitivity testing can quickly determine the most appropriate antibiotic, ensuring effective treatment and minimizing the risk of complications.
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[1.] Bayot ML, Bragg BN. Antimicrobial Susceptibility Testing. [Updated 2024 May 27]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. Available from: https://www.ncbi.nlm.nih.gov/books/NBK539714/
[2.] Bergeron MG, Ouellette M. Preventing antibiotic resistance through rapid genotypic identification of bacteria and of their antibiotic resistance genes in the clinical microbiology laboratory. J Clin Microbiol. 1998 Aug;36(8):2169-72. doi: 10.1128/JCM.36.8.2169-2172.1998. PMID: 9665984; PMCID: PMC104995.
[3.] Gajic I, Kabic J, Kekic D, Jovicevic M, Milenkovic M, Mitic Culafic D, Trudic A, Ranin L, Opavski N. Antimicrobial Susceptibility Testing: A Comprehensive Review of Currently Used Methods. Antibiotics (Basel). 2022 Mar 23;11(4):427. doi: 10.3390/antibiotics11040427. PMID: 35453179; PMCID: PMC9024665.
[4.] Niazi-Ali S, Bircher J. Broad spectrum antibiotic stewardship by quality improvement methods. Int J Risk Saf Med. 2022;33(S1):S35-S40. doi: 10.3233/JRS-227021. PMID: 35871365; PMCID: PMC9844069.
[5.] Ohashi Y, Fujisawa T. Detection of antibiotic resistance genes in the feces of young adult Japanese. Biosci Microbiota Food Health. 2017;36(4):151-154. doi: 10.12938/bmfh.17-004. Epub 2017 Aug 3. PMID: 29038771; PMCID: PMC5633530.
[6.] Rolain JM. Real-time PCR for universal antibiotic susceptibility testing. Journal of Antimicrobial Chemotherapy. 2004;54(2):538-541. doi:https://doi.org/10.1093/jac/dkh324
[7.] Rupa Health. GI-MAP + Zonulin Sample Report.pdf. Google Docs. https://drive.google.com/file/d/13LXmPBhXV2Y9paOeE5id2OM2X0V5gJ56/view