BackgroundDiet-induced obesity (DIO) is a significant health concern which has been linked to structural and functional changes in the gut microbiota. Exercise (Ex) is effective in preventing obesity, but whether Ex alters the gut microbiota during development with high fat (HF) feeding is unknown.ObjectiveDetermine the effects of voluntary Ex on the gastrointestinal microbiota in LF-fed mice and in HF-DIO.MethodsMale C57BL/6 littermates (5 weeks) were distributed equally into 4 groups: low fat (LF) sedentary (Sed) LF/Sed, LF/Ex, HF/Sed and HF/Ex. Mice were individually housed and LF/Ex and HF/Ex cages were equipped with a wheel and odometer to record Ex. Fecal samples were collected at baseline, 6 weeks and 12 weeks and used for bacterial DNA isolation. DNA was subjected both to quantitative PCR using primers specific to the 16S rRNA encoding genes for Bacteroidetes and Firmicutes and to sequencing for lower taxonomic identification using the Illumina MiSeq platform. Data were analyzed using a one or two-way ANOVA or Pearson correlation.ResultsHF diet resulted in significantly greater body weight and adiposity as well as decreased glucose tolerance that were prevented by voluntary Ex (p<0.05). Visualization of Unifrac distance data with principal coordinates analysis indicated clustering by both diet and Ex at week 12. Sequencing demonstrated Ex-induced changes in the percentage of major bacterial phyla at 12 weeks. A correlation between total Ex distance and the ΔCt Bacteroidetes: ΔCt Firmicutes ratio from qPCR demonstrated a significant inverse correlation (r2 = 0.35, p = 0.043).ConclusionEx induces a unique shift in the gut microbiota that is different from dietary effects. Microbiota changes may play a role in Ex prevention of HF-DIO.

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Highlights d Disease-associated DNMT3A mutations disrupt deposition of neuronal DNA methylation d Heterozygous DNMT3A mutant mice show disease-relevant growth and behavior phenotypes d Heterozygous DNMT3A mutation globally reduces non-CG DNA methylation in the brain d RNA and epigenomic changes in DNMT3A mutants overlap MeCP2 disorder and autism models

21Local translation in neuronal processes is key to the alteration of synaptic strength that contributes 22

Alzheimer Disease (AD) is the most common form of dementia. This neurodegenerative disorder is associated with neuronal death and gliosis specifically in the cerebral cortex. AD has a substantial but heterogeneous genetic component, presenting both Mendelian and complex genetic architectures. We previously reported different cellular proportions between brains exhibiting different AD genetic architecture, that we identified using bulk RNA-seq from homogenized parietal lobes and deconvolution methods. We sought investigate AD brain changes at single cell resolution. To do so, we generated unsorted single-nuclei RNA-sequence from brain tissue to leverage tissue donated from a carrier of a Mendelian genetic mutation and two family members who suffer from AD, but do not have the same mutation. We evaluated alternative alignment approaches to maximize the titer of reads, genes and cells with high quality. In addition, we employed distinct clustering strategies to determine the best approach to identify cell clusters that reveal neuronal and glial cell types and avoid artifacts such as sample and batch effects. We propose an approach that reduces biases to cluster cells and enables further analyses. We identified distinct types of neurons, both excitatory and inhibitory, and glial cells, including astrocytes, oligodendrocytes, and microglia among others. In particular, we identified a reduced proportion of excitatory neurons for the Mendelian mutation carrier, but similar distribution for the inhibitory neurons. Furthermore, we investigated whether single-nuclei RNAseq from human brains recapitulate the expression profile of Disease Associated Microglia (DAM) discovered in mice models. We determine that when analyzing human single-nuclei data it is critical to control for biases introduced by donor specific expression profiles. In conclusion, we propose a collection of best practices to generate a highly-detailed molecular cell atlas of highly informative frozen tissue stored in brain banks. Importantly, we have developed a new web application to make this unique single-nuclei molecular atlas publicly available. Keywordsbulk RNAseq, Single Nuclei RNAseq, Alzheimer's disease, Web-based brain molecular atlas application