Trends in Clinical Microbiology Diagnostic Methods

Diagnosis of microbial infections requires specimen collection, sample preparation, and analysis. New methods are emerging that allow for faster, more cost-effective, and more accurate microbial identification. Quicker diagnosis allows for fast treatment and prevents the overuse of antibiotics, which can lead to resistance.

Standard procedure for confirming an infectious disease requires specimen collection and test selection. Routine diagnostic tests include microscopic examination, culture and biochemical tests, serological tests including agglutination and ELISA, and genetic tests. More advanced diagnostic methods are emerging, focused on speed, accuracy, and cost effectiveness.

Matrix-Assisted Laser Desorption/Ionization Time-of-Flight Mass Spectrometry (MALDI-TOF-MS)

MALDI-TOF-MS has been approved by the FDA for microbial identification. The Clinical and Laboratory Standards Institute Guideline M58 published in 2017 provides information for sample preparation and analysis, result interpretation and reporting, and troubleshooting.

MALDI-TOF-MS is a nonfragmenting, or soft ionization, technique. The analyte is embedded in an acidic matrix material on a metal plate, and nitrogen laser excitation is used to catalyze the charge transfer from the matrix to the analyte for desorption. Ions are separated based on their m/z, and a mass analyzer is used for detection and creation of a spectral profile. Future directions for MALDI-TOF-MS include antimicrobial susceptibility testing, microbial virulence, and glycans.

Advantages	Limitations
It is suitable for high-throughput testing and may be completely automated. IVD-compliant systems are available. This technique does not require pre-analytic separation steps.	It necessitates microorganism culture to obtain whole-cell or extracted protein specimens with a minimum number of CFUs. It is not able to separate multiple spectra collected simultaneously, which may occur with polymicrobial cultures.

Next-Generation Sequencing (NGS)

The NGS workflow begins with pathogen culturing and isolation, followed by DNA extraction and library preparation. Images or signals are converted into base calls during primary analysis. Further data processing in secondary analysis includes trimming and filtering, and sequence reads are assigned to a reference sequence or assembled with de novo assembly. The identification of clinically significant findings in tertiary analysis is used to generate a final report.

Advantages	Limitations
NGS may be used for whole genome sequencing on bacterial isolates from a single patient or from multiple patients. It offers rapid bacterial identification and has the capacity to differentiate between clones. The technique is becoming increasingly automated, and the cost continues to decrease.	NGS generates complex data that necessitates interpretation by a clinical microbiologist to ensure the report is designed to help the physician select an appropriate treatment. Sensitivity and specificity of individual platforms cannot be compared directly.

Automated Polymerase Chain Reaction (PCR)

Multiplex PCR is especially useful for specimens from patients presenting with nonspecific symptoms, which may result from any number of different pathogens. A sample-to-result automated PCR system enables the addition of a clinical specimen directly to the device. The sample is treated with multiple reagents for nucleic acid extraction followed by amplification and detection of a target sequence. Platforms range in classification from high-complexity molecular assays to FDA-cleared moderate-complexity IVD tests.

Advantages	Limitations
Automating PCR limits specimen handling to reduce the risk of contamination. Automated multiplex instruments are suitable for rapid detection of a greater number of targets than detected by traditional PCR. Cost per test is reduced when multiple specimens are processed together.	Patient care decisions sometimes require rapid testing, and automated on-demand testing is more costly than batch testing.