Artificial Intelligence and mNGS in Pathogenic Microorganism Research.

Pathogenic microorganisms refer to any microorganisms causing human or animal diseases, including viruses, parasites, bacteria, fungi, Rickettsia, Mycoplasma, Chlamydia, etc. They can be transferred from one host to another by air, body fluids, food, water, etc., causing public panic and economic losses. Rapid and accurate identification of pathogenic microorganisms is crucial to the development of strategies for the management of infections. Increasing evidence shows that artificial intelligence has tremendous potential for risk assessment, identification of disease outbreaks, disease diagnosis, prognosis prediction, and the delivery of patient care. Metagenomic next-generation sequencing (mNGS) overcomes the problems of conventional diagnostic assays and has been identified as a promising tool for unbiased pathogen identification and precision medicine.

Pathogenic microorganisms remain a great threat to human health and socioeconomic development and have been accepted as a major global public health concern. Management of pathogenic microorganism infections depends on rapid and precise identification of pathogens. Currently, the conventional culture method remains the gold standard for the identification of pathogenic microorganisms, which is time-consuming and fails in species identification. Immunological diagnostics are commonly used in clinical practices but suffer from a problem of low sensitivity, while PCR assay suffers from problems of high likelihood of pollution and low specificity. Metagenomic next-generation sequencing (mNGS) is a strong tool in precision medicine, which provides a rapid, precise tool for the identification of clinically unknown pathogenic microorganisms. Artificial intelligence is a breakthrough in human society and has been widely applied in modern medicine, including pathogen detection, disease diagnosis, subclassification, prediction of prognosis, and monitoring response to therapy. This Research Topic aims to summarize the latest findings on pathogenic microorganism research as revealed by artificial intelligence and mNGS, which may provide insights into future containment of pathogenic microorganism infections in clinical practices.

Role of mNGS for identification of pathogenic microorganisms
• mNGS for precise detection of rare cases infected with pathogenic microorganisms
• Artificial intelligence in assisting detection of pathogenic microorganisms
• Artificial intelligence in the prediction of the spread of pathogenic microorganisms
• Artificial intelligence for monitoring the response of pathogenic microorganisms to treatment
• Artificial intelligence in vaccine/drug development for pathogenic microorganisms
• Artificial intelligence for prediction of prognosis among patients with pathogenic microorganism infection