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Abstract The microbiome in a specific human organ has been well-studied, but few reports have investigated the multi-organ microbiome as a whole. Here, we aim to analyse the intra-individual inter-organ and intra-organ microbiome in deceased humans. We collected 1608 samples from 53 sites of 7 surface organs (oral cavity, esophagus, stomach, small intestine, appendix, large intestine and skin; n = 33 subjects) and performed microbiome profiling, including 16S full-length sequencing. Microbial diversity varied dramatically among organs, and core microbial species co-existed in different intra-individual organs. We deciphered microbial changes across distinct intra-organ sites, and identified signature microbes, their functional traits, and interactions specific to each site. We revealed significant microbial heterogeneity between paired mucosa-lumen samples of stomach, small intestine, and large intestine. Finally, we established the landscape of inter-organ relationships of microbes along the digestive tract. Therefore, we generate a catalogue of bacterial composition, diversity, interaction, functional traits, and bacterial translocation in human at inter-organ and intra-organ levels.

Cancer is a leading cause of death worldwide. Around one-third of the total global cancer incidence and mortality are related to gastrointestinal (GI) cancers. Over the past few years, rapid developments have been made in patient-derived organoid (PDO) models for gastrointestinal cancers. By closely mimicking the molecular properties of their parent tumors in vitro, PDOs have emerged as powerful tools in personalized medicine and drug discovery. Here, we review the current literature on the application of PDOs of common gastrointestinal cancers in the optimization of drug treatment strategies in the clinic and their rising importance in pre-clinical drug development. We discuss the advantages and limitations of gastrointestinal cancer PDOs and outline the microfluidics-based strategies that improve the throughput of PDO models in order to extract the maximal benefits in the personalized medicine and drug discovery process.