Lactiplantibacillus plantarum 299v supplementation modulates ß-cell ER stress and antioxidative defense pathways and prevents type 1 diabetes in gluten-free BioBreeding rats.

The increasing incidence of Type 1 diabetes has coincided with the emergence of the low-fiber, high-gluten Western diet and other environmental factors linked to dysbiosis. Since Lactiplantibacillus plantarum 299 v (Lp299v) supplementation improves gut barrier function and reduces systemic inflammation, we studied its effects in spontaneously diabetic DRlyp/lyp rats provided a normal cereal diet (ND) or a gluten-free hydrolyzed casein diet (HCD). All rats provided ND developed diabetes (62.5±7.7 days); combining ND with Lp299v did not improve survival. Diabetes was delayed by HCD (72.2±9.4 days, p = .01) and further delayed by HCD+Lp299v (84.9±14.3 days, p < .001). HCD+Lp299v pups exhibited increased plasma propionate and butyrate levels, which correlated with enriched fecal Bifidobacteriaceae and Clostridiales taxa. Islet transcriptomic and histologic analyses at 40-days of age revealed that rats fed HCD expressed an autophagy profile, while those provided HCD+Lp299v expressed ER-associated protein degradation (ERAD) and antioxidative defense pathways, including Nrf2. Exposing insulinoma cells to propionate and butyrate promoted the antioxidative defense response but did not recapitulate the HCD+Lp299v islet ERAD transcriptomic profile. Here, both diet and microbiota influenced diabetes susceptibility. Moreover, Lp299v supplement modulated antioxidative defense and ER stress responses in ß-cells, potentially offering a new therapeutic direction to thwart diabetes progression and preserve insulin secretion.

Lactobacillus plantarum 299v probiotic supplementation in men with stable coronary artery disease suppresses systemic inflammation.

Recent trials demonstrate that systemic anti-inflammatory therapy reduces cardiovascular events in coronary artery disease (CAD) patients. We recently demonstrated Lactobacillus plantarum 299v (Lp299v) supplementation improved vascular endothelial function in men with stable CAD. Whether this favorable effect is in part due to anti-inflammatory action remains unknown. Testing this hypothesis, we exposed plasma obtained before and after Lp299v supplementation from these subjects to a healthy donor's PBMCs and measured differences in the PBMC transciptome, performed gene ontological analyses, and compared Lp299v-induced transcriptome changes with changes in vascular function. Daily alcohol users (DAUs) (n = 4) had a significantly different response to Lp299v and were separated from the main analyses. Non-DAUs- (n = 15) showed improved brachial flow-mediated dilation (FMD) and reduced circulating IL-8, IL-12, and leptin. 997 genes were significantly changed. I.I.com decreased (1.01 ± 0.74 vs. 0.22 ± 0.51; P < 0.0001), indicating strong anti-inflammatory effects. Pathway analyses revealed downregulation of IL-1ß, interferon-stimulated pathways, and toll-like receptor signaling, and an increase in regulator T-cell (Treg) activity. Reductions in GBP1, JAK2, and TRAIL expression correlated with improved FMD. In non-DAU men with stable CAD, post-Lp299v supplementation plasma induced anti-inflammatory transcriptome changes in human PBMCs that could benefit CAD patients. Future studies should delineate changes in circulating metabolites responsible for these effects.

Cross-species global and subset gene expression profiling identifies genes involved in prostate cancer response to selenium.

BACKGROUND: Gene expression technologies have the ability to generate vast amounts of data, yet there often resides only limited resources for subsequent validation studies. This necessitates the ability to perform sorting and prioritization of the output data. Previously described methodologies have used functional pathways or transcriptional regulatory grouping to sort genes for further study. In this paper we demonstrate a comparative genomics based method to leverage data from animal models to prioritize genes for validation. This approach allows one to develop a disease-based focus for the prioritization of gene data, a process that is essential for systems that lack significant functional pathway data yet have defined animal models. This method is made possible through the use of highly controlled spotted cDNA slide production and the use of comparative bioinformatics databases without the use of cross-species slide hybridizations. RESULTS: Using gene expression profiling we have demonstrated a similar whole transcriptome gene expression patterns in prostate cancer cells from human and rat prostate cancer cell lines both at baseline expression levels and after treatment with physiologic concentrations of the proposed chemopreventive agent Selenium. Using both the human PC3 and rat PAII prostate cancer cell lines have gone on to identify a subset of one hundred and fifty-four genes that demonstrate a similar level of differential expression to Selenium treatment in both species. Further analysis and data mining for two genes, the Insulin like Growth Factor Binding protein 3, and Retinoic X Receptor alpha, demonstrates an association with prostate cancer, functional pathway links, and protein-protein interactions that make these genes prime candidates for explaining the mechanism of Selenium's chemopreventive effect in prostate cancer. These genes are subsequently validated by western blots showing Selenium based induction and using tissue microarrays to demonstrate a significant association between downregulated protein expression and tumorigenesis, a process that is the reverse of what is seen in the presence of Selenium. CONCLUSIONS: Thus the outlined process demonstrates similar baseline and selenium induced gene expression profiles between rat and human prostate cancers, and provides a method for identifying testable functional pathways for the action of Selenium's chemopreventive properties in prostate cancer.

B.E.A.R. GeneInfo: a tool for identifying gene-related biomedical publications through user modifiable queries.

BACKGROUND: Once specific genes are identified through high throughput genomics technologies there is a need to sort the final gene list to a manageable size for validation studies. The triaging and sorting of genes often relies on the use of supplemental information related to gene structure, metabolic pathways, and chromosomal location. Yet in disease states where the genes may not have identifiable structural elements, poorly defined metabolic pathways, or limited chromosomal data, flexible systems for obtaining additional data are necessary. In these situations having a tool for searching the biomedical literature using the list of identified genes while simultaneously defining additional search terms would be useful. RESULTS: We have built a tool, BEAR GeneInfo, that allows flexible searches based on the investigators knowledge of the biological process, thus allowing for data mining that is specific to the scientist's strengths and interests. This tool allows a user to upload a series of GenBank accession numbers, Unigene Ids, Locuslink Ids, or gene names. BEAR GeneInfo takes these IDs and identifies the associated gene names, and uses the lists of gene names to query PubMed. The investigator can add additional modifying search terms to the query. The subsequent output provides a list of publications, along with the associated reference hyperlinks, for reviewing the identified articles for relevance and interest. An example of the use of this tool in the study of human prostate cancer cells treated with Selenium is presented. CONCLUSIONS: This tool can be used to further define a list of genes that have been identified through genomic or genetic studies. Through the use of targeted searches with additional search terms the investigator can limit the list to genes that match their specific research interests or needs. The tool is freely available on the web at http://prostategenomics.org1, and the authors will provide scripts and database components if requested mdatta@mcw.edu