Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults.
Project description:Human saliva microbiota is phylogenetically divergent among host individuals yet their roles in health and disease are poorly appreciated. We employed a microbial functional gene microarray, HuMiChip 1.0, to reconstruct the global functional profiles of human saliva microbiota from ten healthy and ten caries-active adults. Saliva microbiota in the pilot population featured a vast diversity of functional genes. No significant distinction in gene number or diversity indices was observed between healthy and caries-active microbiota. However, co-presence network analysis of functional genes revealed that caries-active microbiota was more divergent in non-core genes than healthy microbiota, despite both groups exhibited a similar degree of conservation at their respective core genes. Furthermore, functional gene structure of saliva microbiota could potentially distinguish caries-active patients from healthy hosts. Microbial functions such as Diaminopimelate epimerase, Prephenate dehydrogenase, Pyruvate-formate lyase and N-acetylmuramoyl-L-alanine amidase were significantly linked to caries. Therefore, saliva microbiota carried disease-associated functional signatures, which could be potentially exploited for caries diagnosis. The DMFT INDEX (Decayed, Missing, Filled [DMF] teeth index used in dental epidemiology) values are provided for each sample
Project description:We profiled transcriptome and accessible chromatin landscapes in intestinal epithelial cells (IECs) from mice reared in the presence or absence of microbiota. We show that regional differences in gene transcription along the intestinal tract were accompanied by major alterations in chromatin organization. Surprisingly, we discovered that microbiota modify host gene transcription in IECs without significantly impacting the accessible chromatin landscape. Instead, microbiota regulation of host gene transcription might be achieved by differential expression of specific TFs and enrichment of their binding sites in nucleosome depleted CRRs near target genes. Our results suggest that the chromatin landscape in IECs is pre-programmed by the host in a region-specific manner to permit responses to microbiota through binding of open CRRs by specific TFs. mRNA and accessible chromatin (DNase-seq) profiles from colonic and ileal IECs were compared between conventionally-raised (CR), germ-free (GF), and conventionalized (CV) C57BL/6 mice.
Project description:The effect of oral microbiota on the intestinal microbiota has garnered growing attention as a mechanism linking periodontal diseases to systemic diseases. However, the salivary microbiota is diverse and comprises numerous bacteria with a largely similar composition in healthy individuals and periodontitis patients. Thus, the systemic effects of small differences in the oral microbiota are unclear. In this study, we explored how health-associated and periodontitis-associated salivary microbiota differently colonized the intestine and their subsequent systemic effects by analyzing the hepatic gene expression and serum metabolomic profiles. The salivary microbiota was collected from a healthy individual and a periodontitis patient and gavaged into C57BL/6NJcl[GF] mice. Samples were collected five weeks after administration. Gut microbial communities were analyzed by 16S ribosomal RNA gene sequencing. Hepatic gene expression profiles were analyzed using a DNA microarray and quantitative polymerase chain reaction. Serum metabolites were analyzed by capillary electrophoresis time-of-flight mass spectrometry. The gut microbial composition at the genus level was significantly different between periodontitis-associated microbiota-administered (PAO) and health-associated oral microbiota-administered (HAO) mice. The hepatic gene expression profile demonstrated a distinct pattern between the two groups, with higher expression of Neat1, Mt1, Mt2, and Spindlin1, which are involved in lipid and glucose metabolism. Disease-associated metabolites such as 2-hydroxyisobutyric acid and hydroxybenzoic acid were elevated in PAO mice. These metabolites were significantly correlated with Bifidobacterium, Atomobium, Campylobacter, and Haemophilus, which are characteristic taxa in PAO mice. Conversely, health-associated oral microbiota were associated with higher levels of beneficial serum metabolites in HAO mice. The multi-omics approach used in this study revealed that periodontitis-associated oral microbiota is associated with the induction of disease phenotype when they colonized the gut of germ-free mice.
Project description:We then performed gene expression profiling analysis using data obtained from RNA-seq of 16 different cybrid lines at normoxia and hypoxia conditions. The goal was to compare the impact of mitochondrial haplogroup (European vs Non-European) on gene expression in the above conditions.
Project description:The incidence and mortality rates of prostate cancer are significantly higher in African-American men when compared to European-American men. We tested the hypothesis that differences in tumor biology contribute to this survival health disparity. Using microarray technology, we obtained gene expression profiles of primary prostate tumors resected from 33 African-American and 36 European-American patients. These tumors were matched on clinical parameters. We also evaluated 18 non-tumor prostate tissues from 7 African-American and 11 European-American patients. The resulting datasets were analyzed for expression differences on the gene and pathway level comparing African-American with European-American patients. Our analysis revealed a significant number of genes, e.g., 162 transcripts at a false-discovery rate less than 5%, to be differently expressed between African-American and European-American patients. Using a disease association analysis, we identified a common relationship of these transcripts with autoimmunity and inflammation. These findings were corroborated on the pathway level with numerous differently expressed genes clustering in immune response, stress response, cytokine signaling, and chemotaxis pathways. Furthermore, a two-gene tumor signature was identified that accurately differentiated between African-American and European-American patients. This finding was confirmed in a blinded analysis of a second sample set. In conclusion, the gene expression profiles of prostate tumors indicate prominent differences in tumor immunobiology between African-American and European-American men. The profiles portray the existence of a distinct tumor microenvironment in these two patient groups. Keywords: Microdissected tissue analysis