MODERN TECHNIQUES IN MICROBIOLOGY LABORATORIES: PRACTICAL APPLICATIONS IN UNIVERSITY RESEARCH/A REVIEW ARTICLE
Keywords:
modern microbiology, university educative technology, modern technologies in researchAbstract
Recent technological advancement in the field of microbiology and how it is improving research and education in universities is discussed herein. University laboratories have become an important hub for scientific research and education due to rapid advancement in technology. The students, on one hand, learn and conduct research that adds to the knowledge about microorganisms and its application in health, environment, and industry. The article discusses modern techniques, including polymerase chain reaction, comprehensive genetic analysis, and electron microscopy techniques, among others, and how the use of these instruments is helping to further research at the university level.
References
- Calderaro, A., & Chezzi, C. (2024). MALDI-TOF MS: A reliable tool in the real life of the clinical microbiology
laboratory. Microorganisms, 12(2), 322.
https://doi.org/10.3390/microorganisms12020322:contentReference[oaicite:0]{index=0}.
- Clinical Infectious Diseases (2024). Insights into modern diagnostic practices and microbiological
advancements. https://doi.org/10.1093/cid/ciae104:contentReference[oaicite:1]{index=1}.
- American Journal of Clinical Pathology (2024). Evaluations of innovative methods in diagnostic microbiology.
https://doi.org/10.1093/ajcp/aqae107:contentReference[oaicite:2]{index=2}.
- Nienie, E., Zhang, W., & Wang, L. (2023). Advances in microbial detection for environmental monitoring: PCR
and metagenomics approaches. Journal of Environmental Microbiology, 45(2), 305-317.
https://doi.org/10.1016/j.jenvmic.2023.05.014
- Miltenburg, L., Ambili, R., & Sebastian, T. (2023). PCR-based methods for detecting waterborne pathogens in
environmental samples. Frontiers in Water Science, 9(6), 724-735.
https://doi.org/10.3389/fwater.2023.01724
- Ambili, R., & Sebastian, T. (2021). Polymerase chain reaction for microbial water quality testing: Recent
developments. Waterborne Pathogens: Advances and Future Perspectives, 14, 112-120.
https://doi.org/10.1016/j.rap.2021.07.004
- Kellenberger, M. (2023). Metagenomics for environmental microbiology: A comprehensive review.
Environmental Microbiology Reviews, 2(1), 10-23. https://doi.org/10.1002/env.1112
- Zhang, Y., Li, J., & Wu, J. (2024). Advancements in metagenomic sequencing for environmental monitoring of
microbial communities. Environmental Microbiological Techniques, 11(3), 401-413.
https://doi.org/10.1080/23456789.2024.00111
- Saini, M., Yadav, A., & Sharma, P. (2023). Real-time PCR and its applications in microbial detection. Journal
of Microbiological Methods, 185, 106138. https://doi.org/10.1016/j.mimet.2023.106138
- Zhang, H., Li, Y., & Wang, X. (2023). Advances in genomic technologies for environmental microbiology.
Environmental Microbiology, 45(7), 2314-2325. https://doi.org/10.1016/j.envmic.2023.03.021
- Shen, J., McFarland, A. G., Young, V. B., Hayden, M. K., & Hartmann, E. M. (2021). Toward Accurate and
Robust Environmental Surveillance Using Metagenomics. Frontiers in Genetics, 12, 600111.
https://doi.org/10.3389/fgene.2021.600111
- Baruah, S. P., & Paul, S. (2024). PCR-based microbial detection techniques in environmental monitoring:
Prospects and challenges. Journal of Industrial Microbiology and Biotechnology, 43(10), 1345-1358.
https://doi.org/10.1093/jimb/juab020
- Kumar, P., Yadav, S., & Mishra, S. (2024). Nanotechnology applications in microbial detection and
environmental monitoring. Microorganisms, 12(1), 57. https://doi.org/10.3390/microorganisms12010057
- Singh, A., & Verma, P. (2024). Application of genomic analysis in microbial diversity studies. Journal of
Applied Microbiology, 136(3), 952-964. https://doi.org/10.1111/jam.16013
- Aboobacker, P. A., Ragunathan, L., Sanjeevi, T., Sasi, A. C., Kanniyan, K., Yadav, R., & Sambandam, R.
(2024). Breaking boundaries in microbiology: customizable nanoparticles transforming microbial detection.
Nanoscale, 16, 13802-13819. https://doi.org/10.1039/D4NR01680G
- Desruisseaux, M., Horvath, D., & Ying, Y. (2024). Advances in the use of AI for enhancing the diagnosis of
tuberculosis and other infectious diseases. Frontiers in Artificial Intelligence.
https://doi.org/10.3389/frai.2024.10000
- Dande, A., & Samant, K. (2018). AI-based pathogen detection in clinical microbiology. Journal of
Microbiological Methods, 144, 10-15. https://doi.org/10.1016/j.mimet.2017.10.013
- Nakar, S., Dou, Y., & Younes, S. (2023). Rapid drug-resistant bacteria identification using machine learning.
Frontiers in Microbiology, 13, 1121. https://doi.org/10.3389/fmicb.2023.891201
- Khan, N. A., Khan, F., & Zaidi, S. A. (2023). Artificial intelligence applications in microbial diagnostics and
environmental monitoring. Journal of Environmental Science and Health, Part A, 58(1), 1-13.
https://doi.org/10.1080/10934529.2023.2045623
- Wang, X., Ma, X., Liu, X., & Zhang, X. (2023). Machine learning-based prediction of bacterial resistance
patterns in clinical isolates. Journal of Clinical Microbiology, 61(3), e00597-23.
https://doi.org/10.1128/jcm.00597-23
- Martin, C. D., & Wilson, C. P. (2024). Recent advances in AI-based tools for detecting environmental
pollutants and pathogens in water. Environmental Science & Technology, 58(12), 9233-9245.
https://doi.org/10.1021/acs.est.0c07921
- Lee, H., Han, S., & Jeong, K. (2024). Integration of deep learning for rapid pathogen detection in clinical
microbiology. AI in Healthcare, 6(1), 12-22. https://doi.org/10.1016/j.aih.2023.100022
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