Artificial intelligence (AI) is a promising tool that can improve the field of microbiology in many ways by providing new ways to explore and understand the diversity and complexity of microorganisms with higher accuracy, speed, and efficiency than ever before. It will be helpful in improving microbiological techniques and their interaction with the environment, discovering new insights and knowledge about microorganisms and their roles in health, disease, and ecology. 

Microbiologists can discover new insights and applications from the vast amount of data generated using AI. In this opinion piece, I will explore some of the exciting applications of AI in microbiology and how they can benefit human health and the environment.

One of the most common applications of AI in microbiology is image analysis. Microscopes enhanced with AI have the potential to aid microbiologists’ examination of organisms and use the collected data for identification and differentiation, improving diagnosis or root cause analysis. Last year, a multinational team developed a new AI tool that can evaluate the image performance of environmental microorganisms for denoising, segmentation, feature extraction, classification and object detection.

The second application of AI in microbiology is studying the interaction between microbes and the surrounding environment by creating models to predict the behavior and response of microbial communities to various environmental factors. McElhinney’s team, in 2022, pointed to the importance of interfacing between AI and molecular microbial ecology for significantly advancing environmental monitoring and management practices through managing large multidimensional environmental omics data.

Another AI application in microbiology is genome sequencing analysis, which determines the order of nucleotides in a DNA molecule. However, AI can help to facilitate and improve genome sequencing analysis by automating tasks such as assembly, annotation, comparison, and visualization of genomic data. AI can also help to discover novel genes, pathways, and functions from genomic data using machine learning techniques. In 2022, Chen Li introduced the importance of AI in forensic microbiology by using AI for the identification, typing, and phylogenetic analysis of microorganisms, as well as for studying their evolution, diversity, function, and interaction with hosts and environments. In the same year, the researcher at Jiangsu JITRI Sioux Technologies Co, Yu, with his team, improved an automated method for diatom detection and taxonomy to provide quick supportive evidence in diagnosis of drowning victims.

The American company Becton, Dickinson and Company (BD), scored FDA clearance for AI software that can interpret bacterial growth. This software will result in meaningful workflows with minimal human interaction, improving microbiology laboratory efficiency. Also, it will allow medical laboratory technicians and scientists to spend more time on higher-value analysis. The software can analyze single and group specimens. Nikos Pavlidis, general manager for diagnostics at BD, said, “The pandemic created significant and ongoing labor challenges in laboratories, and reading plates is a labor-intense, potentially error-prone process in microbiology.”

AI is shaping the future of microbiology by providing new tools and techniques for studying microorganisms at different levels of complexity and resolution, raising the speed, accuracy, reliability, and reproducibility of results. Also, AI will be helpful in uncovering new knowledge and opportunities from microbiological data by enabling deeper analysis, interpretation, and integration of information. Moreover, AI will improve the microbiology field by advancing our understanding of microbial life and its impact on human health and the environment. As a microbiologist, I think AI will be a valuable ally for microbiologists who want to advance their field and contribute to society

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