Our understanding of region-specific microbial function within the gut is limited due to reliance on stool. Using a recently developed capsule device, we exploit regional sampling from the human intestines to develop models for interrogating small intestine (SI) microbiota composition and function. In vitro culturing of human intestinal contents produced stable, representative communities that robustly colonize the SI of germ-free mice. During mouse colonization, the combination of SI and stool microbes altered gut microbiota composition, functional capacity, and response to diet, resulting in increased diversity and reproducibility of SI colonization relative to stool microbes alone. Using a diverse strain library representative of the human SI microbiota, we constructed defined communities with taxa that largely exhibited the expected regional preferences. Response to a fiber-deficient diet was region-specific and reflected strain-specific fiber-processing and host mucus-degrading capabilities, suggesting that dietary fiber is critical for maintaining SI microbiota homeostasis. These tools should advance mechanistic modeling of the human SI microbiota and its role in disease and dietary responses.

The spatiotemporal structure of the human microbiome1,2, proteome3 and metabolome4,5 reflects and determines regional intestinal physiology and may have implications for disease6. Yet, little is known about the distribution of microorganisms, their environment and their biochemical activity in the gut because of reliance on stool samples and limited access to only some regions of the gut using endoscopy in fasting or sedated individuals7. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion. Collection of 240 intestinal samples from 15 healthy individuals using the device and subsequent multi-omics analyses identified significant differences between bacteria, phages, host proteins and metabolites in the intestines versus stool. Certain microbial taxa were differentially enriched and prophage induction was more prevalent in the intestines than in stool. The host proteome and bile acid profiles varied along the intestines and were highly distinct from those of stool. Correlations between gradients in bile acid concentrations and microbial abundance predicted species that altered the bile acid pool through deconjugation. Furthermore, microbially conjugated bile acid concentrations exhibited amino acid-dependent trends that were not apparent in stool. Overall, non-invasive, longitudinal profiling of microorganisms, proteins and bile acids along the intestinal tract under physiological conditions can help elucidate the roles of the gut microbiome and metabolome in human physiology and disease.

Most processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome 1 and microbial transformations. Here we probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy male and female participants. For this, we use a non-invasive, ingestible sampling device to collect and analyse 274 intestinal samples and 60 corresponding stool homogenates by combining five mass spectrometry assays 2,3 and 16S rRNA sequencing. We identify 1,909 metabolites, including sulfonolipids and fatty acid esters of hydroxy fatty acids (FAHFA) lipids. We observe that stool and intestinal metabolomes differ dramatically. Food metabolites display trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites account for the largest inter-individual differences. Notably, two individuals who had taken antibiotics within 6 months before sampling show large variation in levels of bioactive FAHFAs and sulfonolipids and other microbially related metabolites. From inter-individual variation, we identify Blautia species as a candidate to be involved in FAHFA metabolism. In conclusion, non-invasive, in vivo sampling of the human small intestine and ascending colon under physiological conditions reveals links between diet, host and microbial metabolism.

Abstract Most utilization of human diets occurs in the small intestine, which remains largely unstudied. Here, we used a novel non-invasive, ingestible sampling device to probe the spatiotemporal variation of upper intestinal luminal contents during routine daily digestion in 15 healthy subjects. We analyzed 274 intestinal samples and 60 corresponding stool homogenates by combining five metabolomics assays and 16S rRNA sequencing. We identified 1,909 metabolites, including sulfonolipids and novel bile acids. Stool and intestinal metabolomes differed dramatically. Food metabolites displayed known differences and trends in dietary biomarkers, unexpected increases in dicarboxylic acids along the intestinal tract, and a positive association between luminal keto acids and fruit intake. Diet-derived and microbially linked metabolites accounted for the largest inter-subject differences. Interestingly, subjects exhibited large variation in levels of bioactive fatty acid esters of hydroxy fatty acids (FAHFAs) and sulfonolipids. Two subjects who had taken antibiotics within 6 months prior to sampling showed markedly different patterns in these and other microbially related metabolites; from this variation, we identified Blautia species as most likely to be involved in FAHFA metabolism. Thus, in vivo sampling of the human small intestine under physiologic conditions can reveal links between diet, host and microbial metabolism.

We used cDNA microarrays to explore the variation in expression of approximately 8,000 unique genes among the 60 cell lines used in the National Cancer Institute's screen for anti-cancer drugs. Classification of the cell lines based solely on the observed patterns of gene expression revealed a correspondence to the ostensible origins of the tumours from which the cell lines were derived. The consistent relationship between the gene expression patterns and the tissue of origin allowed us to recognize outliers whose previous classification appeared incorrect. Specific features of the gene expression patterns appeared to be related to physiological properties of the cell lines, such as their doubling time in culture, drug metabolism or the interferon response. Comparison of gene expression patterns in the cell lines to those observed in normal breast tissue or in breast tumour specimens revealed features of the expression patterns in the tumours that had recognizable counterparts in specific cell lines, reflecting the tumour, stromal and inflammatory components of the tumour tissue. These results provided a novel molecular characterization of this important group of human cell lines and their relationships to tumours in vivo.

cDNA microarrays and a clustering algorithm were used to identify patterns of gene expression in human mammary epithelial cells growing in culture and in primary human breast tumors. Clusters of coexpressed genes identified through manipulations of mammary epithelial cells in vitro also showed consistent patterns of variation in expression among breast tumor samples. By using immunohistochemistry with antibodies against proteins encoded by a particular gene in a cluster, the identity of the cell type within the tumor specimen that contributed the observed gene expression pattern could be determined. Clusters of genes with coherent expression patterns in cultured cells and in the breast tumors samples could be related to specific features of biological variation among the samples. Two such clusters were found to have patterns that correlated with variation in cell proliferation rates and with activation of the IFN-regulated signal transduction pathway, respectively. Clusters of genes expressed by stromal cells and lymphocytes in the breast tumors also were identified in this analysis. These results support the feasibility and usefulness of this systematic approach to studying variation in gene expression patterns in human cancers as a means to dissect and classify solid tumors.

The temporal program of gene expression during a model physiological response of human cells, the response of fibroblasts to serum, was explored with a complementary DNA microarray representing about 8600 different human genes. Genes could be clustered into groups on the basis of their temporal patterns of expression in this program. Many features of the transcriptional program appeared to be related to the physiology of wound repair, suggesting that fibroblasts play a larger and richer role in this complex multicellular response than had previously been appreciated.

Gene Expression Micro-arrays, GEMs, measure the expression levels of thousands of genes simultaneously. GEMs utilize microscopic cDNA elements on a glass surface, low-volume hybridizations of total cDNA, and two-color fluorescence detection. This seminar will present data from GEMs containing thousands of human genes and discuss the use of this technology in genomic research.

cDNA microarray technology is used to profile complex diseases and discover novel disease-related genes, In inflammatory disease such as rheumatoid arthritis, expression patterns of diverse cell types contribute to the pathology, We have monitored gene expression in this disease state with a microarray of selected human genes of probable significance in inflammation as well as with genes expressed in peripheral human blood cells, Messenger RNA from cultured macrophages, chondrocyte cell lines, primary chondrocytes, and synoviocytes provided expression profiles for the selected cytokines, chemokines, DNA binding proteins, and matrix-degrading metalloproteinases, Comparisons between tissue samples of rheumatoid arthritis and inflammatory bowel disease verified the involvement of many genes and revealed novel participation of the cytokine interleukin 3, chemokine Gro alpha and the metalloproteinase matrix metallo-elastase in both diseases, From the peripheral blood library, tissue inhibitor of metalloproteinase 1, ferritin light chain, and manganese superoxide dismutase genes were identified as expressed differentially in rheumatoid arthritis compared with inflammatory bowel disease, These results successfully demonstrate the use of the cDNA microarray system as a general approach for dissecting human diseases.

Detecting and determining the relative abundance of diverse individual sequences in complex DNA samples is a recurring experimental challenge in analyzing genomes. We describe a general experimental approach to this problem, using microscopic arrays of DNA fragments on glass substrates for differential hybridization analysis of fluorescently labeled DNA samples. To test the system, 864 physically mapped lambda clones of yeast genomic DNA, together representing >75% of the yeast genome, were arranged into 1.8-cm x 1.8-cm arrays, each containing a total of 1744 elements. The microarrays were characterized by simultaneous hybridization of two different sets of isolated yeast chromosomes labeled with two different fluorophores. A laser fluorescent scanner was used to detect the hybridization signals from the two fluorophores. The results demonstrate the utility of DNA microarrays in the analysis of complex DNA samples. This system should find numerous applications in genome-wide genetic mapping, physical mapping, and gene expression studies.