Various molecular biological methods have been developed for sensitive analysis of the complex ecosystem of intestinal microflora. The fluorescence in situ hybridization (FISH) method is useful for spatial distribution of bacterial communities and has the advantage of being able to detect the bacteria while maintaining their morphological integrity, without nucleic acid extraction. The multi-color FISH method with a combination of several labeling oligo-nucleotide probes enables the analysis of spatial distributions of microbial populations in the intestines, and it is more suitable to analysis of the complex ecosystem of intestinal microflora than the conventional FISH method. We have developed a multi-color FISH method for the analysis of intestinal microflora, with which 7 different bacterial groups (species) can be analyzed at the same time. We have also established the appropriate hybridization conditions for probes with mucosal tissue specimens for the analysis of microflora on the surface of mucosa specimens by the multi-color FISH method. The bacterial populations in feces were found to be clearly different from that of the gut mucosa of patients with inflammatory bowel disease. FISH targeting functional bacterial genes will further deepen the understanding of the possible relationships of certain intestinal bacteria withseveral diseases.

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Next generation sequencer (NGS) has allowed the precise profiling of complex microbial communities in nature. This methodology has been introduced into research of gastrointestinal microbiota which is composed of 100 trillion cells of several hundred species. However, recent developments in NGS technology have obliged us to update the platform of microbiota analysis. In this study, we compared and validated the results obtained using 454 pyrosequencer (Roche), which has hitherto mainly been used for gut microbiota analysis, and a MiSeq (Illumina) which recently incorporated remarkable technological advances. We also validated the accuracy of taxonomic classification obtained from different variable regions of 16S ribosomal RNA genes. The V3-V4 region showed the best results for accuracy of taxonomic classification. In contrast, V6-V8 showed less bias for the bacterial composition of higher taxonomic levels, but all variable regions generated more or less bias for certain bacteria groups due to the universal primers used. Finally, UniFrac-PCoA data generated by different NGS data sets were compared using Procrustes analysis, and were shown to be robust regardless of variable regions and sequencers. Among a variety of NGSs, MiSeq is suitable for gut microbiota analysis in terms of running cost and operability, and can be more generally used for gastrointestinal tract microbial research.

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Metabologenomics which integrates metabolomics and metagenomics is the novel approach toward understanding the function of gut microbiota. The human gut is colonized by a wide variety of microorganisms, the commensal microbiota. They form a highly complex microbial community and shape the host mucosal immune system through host-microbial crosstalk at the mucosal interface, which plays a vital role as the boundary between gut microbiota and our body. Homeostatic balance of the gut ecosystem is maintained by the consequences of the interactions among microbes, gut epithelial cells and mucosal immune cells. It has been postulated that an imbalance in the gut ecosystem could be a risk factor for human disorders including not only gut-associated disorders such as inflammatory bowel diseases and colorectal cancer, but also systemic diseases such as metabolic syndrome and allergy. Therefore, in order to move toward a comprehensive understanding and regulation of the gut ecosystem, we need to consider the gut ecosystem as another organ consisting of prokaryotic and eukaryotic cells in our body. Recent metagenomic and metatranscriptomic approaches can reveal the individual gut microbiome gene map and the presumed functional pathways in the gut ecosystem; however, these approaches will probably be insufficient for the identification of the responsible molecule(s) in the complex gut ecosystem. Gut microbiota-derived metabolites are considered to be the responsible factor(s) most likely in facilitating host-microbial crosstalk due to the fact that prokaryotic and eukaryotic cells utilize intestinal metabolites in the same manner. In this review, I would like to introduce recent metabolome-based research on the function of gut microbiota, and to discuss the utility of metabologenomics in progress toward a comprehensive understanding of the gut ecosystem.

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