Metaomics in Clinical Laboratory: Potential Driving Force for Innovative Disease Diagnosis

Abstract

Currently, more and more studies suggested that reductionism was lack of holistic and integrative view of biological processes, leading to limited understanding of complex systems like microbiota and the associated diseases. In fact, microbes are rarely present in individuals but normally live in complex multispecies communities. With the recent development of a variety of metaomics techniques, microbes could be dissected dynamically in both temporal and spatial scales. Therefore, in-depth understanding of human microbiome from different aspects such as genomes, transcriptomes, proteomes, and metabolomes could provide novel insights into their functional roles, which also holds the potential in making them diagnostic biomarkers in many human diseases, though there is still a huge gap to fill for the purpose. In this mini-review, we went through the frontlines of the metaomics techniques and explored their potential applications in clinical diagnoses of human diseases, e.g., infectious diseases, through which we concluded that novel diagnostic methods based on human microbiomes shall be achieved in the near future, while the limitations of these techniques such as standard procedures and computational challenges for rapid and accurate analysis of metaomics data in clinical settings were also examined.

Editorial: Untangle the broad connections and tight interactions between human microbiota and complex diseases through data-driven approaches

“…Although current technologies have already helped us identify many previously unexpected connections between the microbiota and diseases, such as cancer, autoinflammatory diseases, metabolic syndromes, digestive system diseases, cardiovascular diseases, and central nervous system disorders, the present level of knowledge is still limited (Zhang et al, 2015 ). It is rather difficult to analyze the existing meta-omics data in-depth due to the lack of competent algorithms and bioinformatics tools, which leads to a narrow understanding of the microbiome-disease association and severely limits the development of the association mechanisms (Wang et al, 2022 ). Therefore, more efforts should be applied to the microbiota-disease association analysis, especially to promote the application of microbial analysis in the clinical settings for the diagnosis, treatment, and prevention of complex human diseases.…”