Improved mouse models of the small intestine microbiota using region-specific sampling from humans.

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. culturing of human intestinal contents produced stable, representative communities that robustly colonize the SI of germ-free mice.

Profiling the human intestinal environment under physiological conditions.

The spatiotemporal structure of the human microbiome, proteome and metabolome reflects and determines regional intestinal physiology and may have implications for disease. 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 individuals. To address these deficiencies, we developed an ingestible device that collects samples from multiple regions of the human intestinal tract during normal digestion.

Human metabolome variation along the upper intestinal tract.

Most processing of the human diet occurs in the small intestine. Metabolites in the small intestine originate from host secretions, plus the ingested exposome 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.

Metabolomics analysis of time-series human small intestine lumen samples collected .

The human small intestine remains an elusive organ to study due to the difficulty of retrieving samples in a non-invasive manner. Stool samples as a surrogate do not reflect events in the upper gut intestinal tract. As proof of concept, this study investigates time-series samples collected from the upper gastrointestinal tract of a single healthy subject.

Systematic variation in gene expression patterns in human cancer cell lines.

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.

Distinctive gene expression patterns in human mammary epithelial cells and breast cancers.

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.

The transcriptional program in the response of human fibroblasts to serum.

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: a new tool for genomic research.

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.

Discovery and analysis of inflammatory disease-related genes using cDNA microarrays.

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.

Parallel human genome analysis: microarray-based expression monitoring of 1000 genes.

Microarrays containing 1046 human cDNAs of unknown sequence were printed on glass with high-speed robotics. These 1.0-cm2 DNA "chips" were used to quantitatively monitor differential expression of the cognate human genes using a highly sensitive two-color hybridization assay.

A DNA microarray system for analyzing complex DNA samples using two-color fluorescent probe hybridization.

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.

Quantitative monitoring of gene expression patterns with a complementary DNA microarray.

A high-capacity system was developed to monitor the expression of many genes in parallel. Microarrays prepared by high-speed robotic printing of complementary DNAs on glass were used for quantitative expression measurements of the corresponding genes. Because of the small format and high density of the arrays, hybridization volumes of 2 microliters could be used that enabled detection of rare transcripts in probe mixtures derived from 2 micrograms of total cellular messenger RNA.