Automated isolation methods have recently been developed for use in microbiology, which has redefined how microbial species are isolated and analyzed.
These methods leverage robotics, advanced instrumentation, and software to automate processes traditionally performed manually, such as streaking, plating, and liquid handling. Automating microorganism isolation has the potential to improve efficiency, accuracy, and reproducibility.1
Image Credit: Stock-Asso/Shutterstock.com
Key Concepts in Automated Isolation
What Are Automated Isolation Methods?
The name refers to the use of robotic systems and advanced technologies to isolate microbial species from complex sample. These methods minimize manual intervention by automating tasks such as streaking microorganisms onto agar plates, pipetting, and sample tracking. Examples include automated streaking systems, such as the COPAN WASP or BD Kiestra, which deliver consistent streak patterns for colony isolation.2
Why Automation is Important
Manual isolation methods, despite being used for decades by most, if not all, microbiologists, have their limitations. They are time-consuming, require skilled labor, and are susceptible to variability due to human error. These drawbacks are much more critical in high-throughput settings, such as clinical laboratories and industrial microbiology facilities.
Automation addresses these challenges by ensuring consistency, reducing hands-on time, and accommodating the growing demand for microbial analyses. High-throughput systems can process hundreds to thousands of samples daily, streamlining workflows and reducing turnaround times for critical results.3
Isolation Techniques in Microbiology
Applications of Automated Isolation in Microbiology
Clinical Diagnostics
In clinical microbiology, timely and accurate pathogen identification is crucial. Automated isolation methods significantly improve the efficiency of diagnostic practices.
For example, during the COVID-19 pandemic, automated platforms proved invaluable in managing the sudden surges in demand for diagnostic testing. These systems not only sped up sample processing but also reduced contamination risks, giving more reliable results.4
Research and Development
Automated isolation methods are becoming more commonly used in microbiology research and development, as they offer high throughput and increased testing specificity. In microbial genomics, these methods facilitate the precise isolation of target organisms for DNA extraction and sequencing.
Similarly, in biotechnology, automation aids in the discovery of novel enzymes and metabolites by allowing researchers to screen microbial libraries more quickly than with traditional methods.5
Industrial Microbiology
In industrial settings, automation is driving productivity and quality for operations at a much larger scale than research and development. These methods are currently being used in several industries:
- Fermentation Processes: Ensuring pure starter cultures and consistent production.
- Pharmaceutical Development: Supporting both the discovery of new microbial strains and the optimization of routinely used organisms for antibiotic and vaccine production.
- Food Microbiology: Enhancing the safety and quality of food products by rapidly isolating and identifying microorganisms that could cause spoilage.
For example, automated isolation systems are widely utilized in breweries to monitor yeast purity and maintain product consistency.6
Industrial Applications of Microbes and Viruses in Biotechnology
Advantages of Automated Isolation Methods
There are several notable advantages to using automated isolation methods:
- Increased Speed and Scalability: These methods offer the ability to process large sample volumes quickly, which is vital for high-demand laboratories.
- Enhanced Reproducibility: Automation eliminates the inconsistencies that inevitably come with the use of manual techniques.
- Precision in Microbial Identification: Integrated artificial intelligence (AI) analysis and imaging can significantly improve the accuracy in identifying key microbes.
- Reduced Contamination and Human Error: Fully sealed, automated processes minimize the risk of both operator errors and external contamination.
These benefits also offer financial savings and improved reliability in both clinical and industrial microbiology.7
Challenges and Future Directions
Challenges
Despite the benefits, automated isolation methods also have their challenges:
- High Initial Costs: The acquisition and maintenance of specialist equipment require significant investment, which reduces accessibility for smaller or resource-limited laboratories.
- Biological Limitations: Current automated technologies occasionally struggle to isolate rare or slow-growing microbe strains, requiring manual intervention.
- Skill Shortage: Operators require specialized training to manage and troubleshoot these advanced systems effectively.8
Future Directions
Advancements in AI has the potential to revolutionize the ways in which automated isolation is used. AI-powered systems can analyze potential microbial growth patterns with greater precision, offering more accurate insights that result in improved decision-making.9
Moreover, efforts to develop cost-effective automation solutions aim to improve the accessibility of this technology, particularly in organizations with limited resources. Modular systems and open-source software platforms are now being offered as viable options for small laboratories.10
Global Market Report: Laboratory Automation
Conclusion
Automated isolation methods have the potential to revolutionize numerous areas of microbiology - by addressing critical limitations of traditional, manual processes and enabling high-throughput analyses with greater precision and scalability.
While challenges such as cost and skill shortages remain, ongoing technological advancements and efforts to increase accessibility are paving the way for more widespread acceptance of automated isolation methods.
References
- Ledeboer, N.A., & Dallas, S.D. (2014). The automated clinical microbiology laboratory: fact or fantasy? J Clin Microbiol, 52(9):3140-6. DOI: 10.1128/JCM.00686-14.
- Riaz, A., et al. (2021). Total lab automation in microbiology: An overview of BD Kiestra InoqulA and Copan WASP. Open Access Research Journal of Biology and Pharmacy, 01(01):007-015. DOI: 10.53022/oarjbp.2021.1.1.0011
- Burckhardt, I. Laboratory Automation in Clinical Microbiology. (2018). Bioengineering (Basel), 5(4):102. DOI: 10.3390/bioengineering5040102.
- Jonguitud-Borrego, N., et al. (2022). High-throughput and automated screening for COVID-19. Front Med Technol, 4:969203. DOI: 10.3389/fmedt.2022.969203.
- Ayon, N.J. (2023). High-Throughput Screening of Natural Product and Synthetic Molecule Libraries for Antibacterial Drug Discovery. Metabolites, 13(5):625. DOI: 10.3390/metabo13050625.
- Du, Y-H., et al. (2022). Optimization and Scale-Up of Fermentation Processes Driven by Models. Bioengineering, 9(9):473. DOI: 10.3390/bioengineering9090473.
- Rienzo, M., et al. (2021). High-throughput screening for high-efficiency small-molecule biosynthesis. Metabolic Engineering, 63:102-125. DOI: 10.1016/j.ymben.2020.09.004.
- Kritikos, A. (2021). Current State of Laboratory Automation in Clinical Microbiology Laboratory. Clinical Chemistry, 68(1):99-114. DOI: 10.1093/clinchem/hvab242.
- Dharmani, K., et al. AI-driven microbial medicine development. Methods in Microbiology, 55:101-124. DOI: 10.1016/bs.mim.2024.05.008.
- Nsoh, B., et al. (2024). Internet of Things-Based Automated Solutions Utilizing Machine Learning for Smart and Real-Time Irrigation Management: A Review. Sensors, 24(23):7480. DOI: 10.3390/s24237480.
Further Reading