Intestinal M (microfold or membranous) cells are an enigmatic lineage of intestinal epithelial cells that initiate mucosal immune responses through the uptake and transcytosis of luminal antigens. Due to their rarity, the mechanisms of M-cell function and differentiation are poorly understood. To overcome this problem, experimental strategies to enrich for M-cells have been established. Transcriptome analyses have provided valuable insight, especially on the receptors for antigen uptake, and such studies have broadened our knowledge of M-cell function. In another line of investigation, we and others have begun to dissect the molecular pathways of M-cell differentiation. Among them, receptor activator of NF-κB ligand (RANKL) has been identified as an essential factor for M-cell differentiation. We have focused on the M-cell inducible activity of RANKL and have been able to observe temporal transitions during M-cell differentiation by using in vivo ectopic M-cell differentiation induced by exogenous RANKL treatment. We have found that the ets-family transcription factor Spi-B is essential for functional maturation of M cells. In the absence of Spi-B, the immune response to Salmonella Typhimurium is severely impaired, suggesting that M cells are important for maintaining intestinal homeostasis.
Research on intestinal bacteria began around the end of the 19th century. During the last 5 decades of the 20th century, research on the intestinal microbiota made rapid progress. At first, in my work, I first developed a method of comprehensive analysis of the intestinal microbiota, and then I established classification and identification methods for intestinal anaerobes. Using these methods I discovered a number of ecological rules governing the intestinal microbiota and the role of the intestinl microbiota in health and disease. Moreover, using germfree animals, it was proven that the intestinal microbiota has a role in carcinogenesis and aging in the host. Thus, a new interdisciplinary field, “intestinal bacteriology” was established.
Recent advances in intestinal microbiota research are the background for the appearance of functional foods. Lactic fermentation products are included in the functional foods and classified into 3 groups based on their mechanisms of action: probiotics, prebiotics and biogenics. Probiotics are viable microorganisms, such as lactobacilli and bifidobacteria, that beneficially affect the host by improving the intestinal bacterial balance. Prebiotics are nondigestible food ingredients, such as oligosaccharides and dietary fiber, that beneficially affect the host by selectively stimulating the growth or activities of beneficial intestinal bacteria in the colon and thus improve the health of the hosts. Biogenics are biologically active peptides, including immunopotentiators (biological response modifier: BRM), plant flavonoids, etc. They act directly or indirectly through modulation of intestinal microbiota on the health of the hosts. Thus, functional foods enhance bioregulation such as stresses, appetite and absorption; biodefence, such as immunity and suppression of allergies; prevent diseases, including diarrhea, constipation, cancer, cholesterolemia and diabetes; and suppress aging through immunostimulation as well as suppression of mutagenesis, carcinogenesis, oxidation processes, intestinal putrefaction, and cholesterolemia.
The application of data mining analyses (DM) is effective for the quantitative classification of human intestinal microbiota (HIM). However, there remain various technical problems that must be overcome. This paper deals with the number of nominal partitions (NP) of the target dataset, which is a major technical problem. We used here terminal restriction fragment length polymorphism data, which was obtained from the feces of 92 Japanese men. Data comprised operational taxonomic units (OTUs) and subject smoking and drinking habits, which were effectively classified by two NP (2-NP; Yes or No). Using the same OTU data, 3-NP and 5-NP were examined here and results were obtained, focusing on the accuracies of prediction, and the reliability of the selected OTUs by DM were compared to the former 2-NP. Restriction enzymes for PCR were further affected by the accuracy and were compared with 7 enzymes. There were subjects who possess HIM at the border zones of partitions, and the greater the number of partitions, the lower the obtained DM accuracy. The application of balance nodes boosted and duplicated the data, and was able to improve accuracy. More accurate and reliable DM operations are applicable to the classification of unknown subjects for identifying various characteristics, including disease.
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