Recent studies investigating the human microbiome have identified particular bacterial species that correlate with the presence of colorectal cancer. To evaluate the role of qualitatively different but naturally occurring gut microbiota and the relationship with colorectal cancer development, genetically identical embryos from the Polyposis in Rat Colon (Pirc) rat model of colorectal cancer were transferred into recipients of three different genetic backgrounds (F344/NHsd, LEW/SsNHsd, and Crl:SD). Tumor development in the pups was tracked longitudinally via colonoscopy, and end-stage tumor burden was determined. To confirm vertical transmission and identify associations between the gut microbiota and disease phenotype, the fecal microbiota was characterized in recipient dams 24 hours pre-partum, and in Pirc rat offspring prior to and during disease progression. Our data show that the gut microbiota varies between rat strains, with LEW/SsNHsd having a greater relative abundance of the bacteria Prevotella copri. The mature gut microbiota of pups resembled the profile of their dams, indicating that the dam is the primary determinant of the developing microbiota. Both male and female F344-Pirc rats harboring the Lewis microbiota had decreased tumor burden relative to genetically identical rats harboring F344 or SD microbiota. Significant negative correlations were detected between tumor burden and the relative abundance of specific taxa from samples taken at weaning and shortly thereafter, prior to observable adenoma development. Notably, this naturally occurring variation in the gut microbiota is associated with a significant difference in severity of colorectal cancer, and the abundance of certain taxa is associated with decreased tumor burden.

Using next-generation, transcriptome-wide RNA sequencing (RNA-Seq) technology we assessed the effects of exercise training on transcriptional profiles in skeletal muscle arterioles isolated from the soleus and gastrocnemius muscles of Otsuka Long Evans Tokushima Fatty (OLETF) rats that underwent an endurance exercise training program (EX; n = 13), interval sprint training program (SPRINT; n = 14), or remained sedentary (Sed; n = 12). We hypothesized that the greatest effects of exercise would be in the gastrocnemius arterioles. Results show that EX caused the largest number of changes in gene expression in the soleus and white gastrocnemius 2a arterioles with little to no changes in the feed arteries. In contrast, SPRINT caused substantial changes in gene expression in the feed arteries. IPA canonical pathway analysis revealed 18 pathways with significant changes in gene expression when analyzed across vessels and revealed that EX induces increased expression of the following genes in all arterioles examined: Shc1, desert hedgehog protein (Dhh), adenylate cyclase 4 (Adcy4), G protein binding protein, alpha (Gnat1), and Bcl2l1 and decreased expression of ubiquitin D (Ubd) and cAMP response element modulator (Crem). EX increased expression of endothelin converting enzyme (Ece1), Hsp90b, Fkbp5, and Cdcl4b in four of five arterioles. SPRINT had effects on expression of Crem, Dhh, Bcl2l1, and Ubd that were similar to EX. SPRINT also increased expression of Nfkbia, Hspa5, Tubb 2a and Tubb 2b, and Fkbp5 in all five arterioles and increased expression of Gnat1 in all but the soleus second-order arterioles. Many contractile and/or structural protein genes were increased by SPRINT in the gastrocnemius feed artery, but the same genes exhibited decreased expression in red gastrocnemius arterioles. We conclude that training-induced changes in arteriolar gene expression patterns differ by muscle fiber type composition and along the arteriolar tree.

Endometriosis is a complex and common gynecological disorder yet a poorly understood disease affecting about 176 million women worldwide and causing significant impact on their quality of life and economic burden. Neither a definitive clinical symptom nor a minimally invasive diagnostic method is available, thus leading to an average of 4 to 11 years of diagnostic latency. Discovery of relevant biological patterns from microarray expression or next generation sequencing (NGS) data has been advanced over the last several decades by applying various machine learning tools. We performed machine learning analysis using 38 RNA-seq and 80 enrichment-based DNA methylation (MBD-seq) datasets. We experimented how well various supervised machine learning methods such as decision tree, partial least squares discriminant analysis (PLSDA), support vector machine, and random forest perform in classifying endometriosis from the control samples trained on both transcriptomics and methylomics data. The assessment was done from two different perspectives for improving classification performances: a) implication of three different normalization techniques and b) implication of differential analysis using the generalized linear model (GLM). Several candidate biomarker genes were identified by multiple machine learning experiments including NOTCH3, SNAPC2, B4GALNT1, SMAP2, DDB2, GTF3C5, and PTOV1 from the transcriptomics data analysis and TRPM6, RASSF2, TNIP2, RP3-522J7.6, FGD3, and MFSD14B from the methylomics data analysis. We concluded that an appropriate machine learning diagnostic pipeline for endometriosis should use TMM normalization for transcriptomics data, and quantile or voom normalization for methylomics data, GLM for feature space reduction and classification performance maximization.

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We employed next-generation, transcriptome-wide RNA sequencing (RNA-Seq) technology to assess the effects of two different exercise training protocols on transcriptional profiles in diaphragm second-order arterioles (D2a) and in the diaphragm feed artery (DFA) from Otsuka Long Evans Tokushima Fatty (OLETF) rats. Arterioles were isolated from the diaphragm of OLETF rats that underwent an endurance exercise training program (EX; n = 13), interval sprint training program (SPRINT; n = 14), or remained sedentary (Sed; n = 12). Our hypothesis was that exercise training would have similar effects on gene expression in the diaphragm and soleus muscle arterioles because diaphragm blood flow increases during exercise to a similar extent as in soleus. Results reveal that several canonical pathways that were significantly altered by exercise in limb skeletal muscles were not among the pathways significantly changed in the diaphragm arterioles including actin cytoskeleton signaling, role of NFAT in regulation of immune response, protein kinase A signaling, and protein ubiquitination pathway. EX training altered the expression of a smaller number of genes than did SPRINT in the DFA but induced a larger number of genes with altered expression in the D2a than did SPRINT. In fact, FDR differential expression analysis (FDR, 10%) indicated that only two genes exhibited altered expression in D2a of SPRINT rats. Very few of the genes that exhibited altered expression in the DFA or D2a were also altered in limb muscle arterioles. Finally, results indicate that the 2a arterioles of soleus muscle (S2a) from endurance-trained animals and the DFA of SPRINT animals exhibited the largest number of genes with altered expression.