Introduction:

Automation has become a cornerstone in various clinical laboratory disciplines, but its implementation in clinical microbiology has been challenging due to complex specimen collection, diverse containers, and cost considerations. However, recent technological advancements and centralized laboratory models have led to the development and adoption of microbiology laboratory automation (MLA) systems. These systems streamline workflows, optimize incubation conditions, enhance sample tracking, and reduce errors and injuries. This article explores the current state of MLA and highlights emerging developments that are shaping the future of clinical microbiology.


Automated Specimen Processing:

MLA systems automate the inoculation of liquid-based specimens onto culture media, enabling precise specimen tracking and reducing variability and cross-contamination risks. Non-liquid specimens are semi-automated, requiring manual inoculation before being processed further. Automated systems can also prepare slides for Gram staining, reducing variability and improving efficiency in specimen processing.


Incubation and Monitoring:

MLA systems transport culture plates to incubators with controlled atmospheric conditions, providing stable environments for bacterial growth. High-resolution digital imaging allows users to monitor cultures and obtain images at specific incubation times. This continuous monitoring optimizes incubation conditions, enhances bacterial growth, and minimizes contamination risks.


Plate Reading:

MLA software enables laboratory staff to interpret digital images of culture plates and identify colonies that require further analysis. Some systems incorporate artificial intelligence (AI) algorithms for automated plate evaluation, detecting specific organisms and segregating different growth types. AI-assisted plate reading enhances efficiency and accuracy in the identification of pathogens.


Organism Identification and Antimicrobial Susceptibility:

Matrix-assisted laser desorption ionization – time-of-flight mass spectrometry (MALDI-TOF MS) has revolutionized organism identification. Automated systems for sample preparation coupled with MALDI-TOF MS enable rapid and accurate identification of bacteria and fungi. Automated instruments are also available for antimicrobial susceptibility testing (AST), reducing manual preparation steps and improving efficiency.


Future Directions:

Advances in machine learning and AI hold promise for further developments in clinical microbiology. Automated Gram stain interpretation and expanded applications of AI for diverse specimen types are anticipated. Additionally, applying guidelines for automated disk-diffusion AST processes may offer reliable and timely results.


Conclusion:

Despite challenges, the rapid expansion of MLA systems in clinical microbiology laboratories is revolutionizing workflows, improving efficiency, and enhancing patient care. Standardized processes, reproducible results, traceability, and reduced errors contribute to higher-quality microbiological testing. While initial costs must be considered, the long-term benefits in terms of efficiency and economic advantages are significant. Understanding the current state of automation and potential future developments is crucial for laboratories to remain at the forefront of innovation in clinical microbiology.


Cc: Do Young Kim, MD (former medical microbiology fellow at NorthShore University Health System and the University of Chicago)