APOE genotype influences the gut microbiome structure and function in humans and mice: relevance for Alzheimer's disease pathophysiology.

Apolipoprotein E (APOE) genotype is the strongest prevalent genetic risk factor for Alzheimer's disease (AD). Numerous studies have provided insights into the pathologic mechanisms. However, a comprehensive understanding of the impact of APOE genotype on microflora speciation and metabolism is completely lacking. In this study, we investigated the association between APOE genotype and the gut microbiome composition in human and APOE-targeted replacement (TR) transgenic mice. Fecal microbiota amplicon sequencing from matched individuals with different APOE genotypes revealed no significant differences in overall microbiota diversity in group-aggregated human APOE genotypes. However, several bacterial taxa showed significantly different relative abundance between APOE genotypes. Notably, we detected an association of Prevotellaceae and Ruminococcaceae and several butyrate-producing genera abundances with APOE genotypes. These findings were confirmed by comparing the gut microbiota of APOE-TR mice. Furthermore, metabolomic analysis of murine fecal water detected significant differences in microbe-associated amino acids and short-chain fatty acids between APOE genotypes. Together, these findings indicate that APOE genotype is associated with specific gut microbiome profiles in both humans and APOE-TR mice. This suggests that the gut microbiome is worth further investigation as a potential target to mitigate the deleterious impact of the APOE4 allele on cognitive decline and the prevention of AD.-Tran, T. T. T., Corsini, S., Kellingray, L., Hegarty, C., Le Gall, G., Narbad, A., Müller, M., Tejera, N., O'Toole, P. W., Minihane, A.-M., Vauzour, D. APOE genotype influences the gut microbiome structure and function in humans and mice: relevance for Alzheimer's disease pathophysiology.

Gut and Whole-Body Microbiota of the Honey Bee Separate Thriving and Non-thriving Hives.

The recent worldwide decline of honey bee colonies is a major ecological problem which also threatens pollinated crop production. Several interacting stressors such as environmental pressures and pathogens are suspected. Recently, the gut microbiota has emerged as a critical factor affecting bee health and fitness. We profiled the bacterial communities associated with the gut and whole body of worker bees to assess whether non-thriving colonies could be separated from thriving hives based on their microbial signature. The microbiota of thriving colonies was characterised by higher diversity and higher relative abundance of bacterial taxa involved in sugar degradation that were previously associated with healthy bees (e.g. Commensalibacter sp. and Bartonella apis). In contrast, the microbiota of non-thriving bees was depleted in health-associated species (e.g. Lactobacillus apis), and bacterial taxa associated with disease states (e.g. Gilliamella apicola) and pollen degradation (e.g. G. apicola and Bifidobacterium asteroides) were present in higher abundance compared to thriving colonies. Gut and whole-body microbiota shared a similar dominant core but their comparison showed differences in composition and relative abundance. More differences in taxon relative abundance between gut and whole body were observed in non-thriving bees, suggesting that microbiota associated with other bee organs might also be different. Thus, microbiota profiling could be used as a diagnostic tool in beekeeping practices to predict hive health and guide hive management.

The effect of central corneal thickness on estimates of the anterior chamber depth.

BACKGROUND: The slitlamp can be used to estimate the anterior chamber depth (ACD). The length of a slit object is increased until the corneal and iris/lens images appear to just touch. Multiplying the just-touching-slit-length (JTSL) by a conversion factor gives an estimate of the ACD as measured by ultrasonography. The purpose of this study was to determine if central corneal thickness (CCT) affects the accuracy of this technique. METHODS: The ACD of 50 subjects was measured by A-scan ultrasonography and estimated by the slitlamp technique. CCT was measured by ultrasonic pachometry. The refractive error was determined subjectively. RESULTS: The average ultrasonographic ACD for all subjects was 3.32 +/- 0.65 mm. The average JTSL was 2.46 +/- 0.38 mm. The conversion ratio between the ultrasonographic ACD and the average JTSL was 1.35. The predicted ACD using the regression equation of JTSL on the ultrasound anterior chamber depth (USACD) was 3.32 +/- 0.54 mm. The corresponding value using the regression equation of JTSL and CCT on USACD was exactly the same, that is, 3.32 +/- 0.54 mm. CONCLUSION: Incorporation of CCT into a regression equation does not improve the accuracy of the Smith technique.