Editorial: Computational Predictions, Dynamic Tracking, and Evolutionary Analysis of Antibiotic Resistance Through the Mining of Microbial Genomes and Metagenomic Data

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

“…Metaomics is an innovative integration approach that is based on the in-depth analysis of human microbiomes, which has spurred a paradigm shift in understanding human health and detecting infectious diseases (Xu and Yang, 2021). Apparent advantages have been reported that makes these techniques with promising potentials in clinical diagnosis of bacterial infections, such as quantification of bacterial compositions, detection of unculturable bacterial pathogens, profiling of bacterial antibiotics-resistant genes, identification of virulence factors in large scale, and establishment of associations between bacteria and diseases, etc., all of which could be realized through metagenomic analysis (Wang et al, 2022). In addition, the dynamics of microbe-microbe interplays, host-microbe interactions, energy metabolism, and chemical cycling during bacterial infection could be elucidated through metatranscriptomic studies, which could not only improve the understanding of bacterial pathogenicity, but also facilitate biomarker discovery and development of microbial therapeutics (Zhang et al, 2021).…”

“…(Chiu and Miller, 2019;Shakya et al, 2019;Dias et al, 2020). In addition, for metabolomics, techniques with acceptable sensitivity are only just being developed, while computational analysis and integration of metaomics data are other challenges that hinder the potential application of metaomics techniques in clinical settings, though data management and comparative analysis system are actively explored at current stage (Chen et al, 2019;Wang et al, 2022). In this mini-review, we will not look into the technical details of metaomics approaches; in contrast, we endeavor to focus on the application potentials of metaomics techniques for their rapid and accurate diagnosis of bacterial pathogens and infections.…”