Figure 2.

Multi-omics microbiome-based diagnostic methods. Microbiome-based diagnostic models typically utilize three primary technologies derived from patient fecal samples: 1) 16s amplicon or metagenomic sequencing to determine microbial taxa, 2) Liquid chromatography-mass spectrometry (LC-MS) metabolomics/proteomics to identify microbially derived metabolites, and 3) High-performance liquid chromatography (HP-LC) profiling of amino stool amino acid profiles. A fourth and more recently proposed approach amplifies circulating microbial DNA from patient blood or plasma samples, followed by stringent computational filtering. In all methods, marker selection is conducted using machine learning models to identify discriminating markers correlating with tumor stage, and accuracy can be improved by integrating one or more of these datasets.