Stool pattern is associated with not only the prevalence of tumorigenic bacteria isolated from fecal matter but also plasma and fecal fatty acids in healthy Japanese adults.

BACKGROUND: Colibactin-producing Escherichia coli containing polyketide synthase (pks+ E. coli) has been shown to be involved in colorectal cancer (CRC) development through gut microbiota analysis in animal models. Stool status has been associated with potentially adverse gut microbiome profiles from fecal analysis in adults. We examined the association between stool patterns and the prevalence of pks+ E. coli isolated from microbiota in fecal samples of 224 healthy Japanese individuals. RESULTS: Stool patterns were determined through factorial analysis using a previously validated questionnaire that included stool frequency, volume, color, shape, and odor. Factor scores were classified into tertiles. The prevalence of pks+ E. coli was determined by using specific primers for pks+ E. coli in fecal samples. Plasma and fecal fatty acids were measured via gas chromatography-mass spectrometry. The prevalence of pks+ E. coli was 26.8%. Three stool patterns identified by factorial analysis accounted for 70.1% of all patterns seen (factor 1: lower frequency, darker color, and harder shape; factor 2: higher volume and softer shape; and factor 3: darker color and stronger odor). Multivariable-adjusted odds ratios (95% confidence intervals) of the prevalence of pks+ E. coli for the highest versus the lowest third of the factor 1 score was 3.16 (1.38 to 7.24; P for trend = 0.006). This stool pattern exhibited a significant positive correlation with fecal isobutyrate, isovalerate, valerate, and hexanoate but showed a significant negative correlation with plasma eicosenoic acid and α-linoleic acid, as well as fecal propionate and succinate. No other stool patterns were significant. CONCLUSIONS: These results suggest that stool patterns may be useful in the evaluation of the presence of tumorigenic bacteria and fecal fatty acids through self-monitoring of stool status without the requirement for specialist technology or skill. Furthermore, it may provide valuable insight about effective strategies for the early discovery of CRC.