TIBS: a web database to browse gene expression in irritable bowel syndrome.

Irritable bowel syndrome (IBS) is a chronic functional gastrointestinal disorder. Its symptoms include chronic abdominal pain, bloating gas, diarrhea and constipation. Many IBS patients also have psychological symptoms like depression or anxiety. These unpleasant symptoms significantly lower patients׳ quality of life. The prevalence of IBS in Europe and North America is about 10-15% of the population, which makes IBS a disorder with a high social cost. The pathophysiology of IBS is considered to be multifactorial and the exact cause of the disease remains poorly understood. Recently, a genome-wide expression microarray technique has been applied to investigate the possible mechanisms of IBS. However, a user-friendly database that allows scientists without bioinformatics background to query gene expression levels in these data sets and compare gene expression patterns across different tissues has not yet been established. Therefore, we have integrated four public expression microarray data (320 samples) from the Gene Expression Omnibus (GEO) and ArrayExpress databases into an online database called Transcriptome of Irritable Bowel Syndrome (TIBS). The gene expression change in IBS patients compared to healthy volunteers or UC patients in jejunum, sigmoid colon, rectum, and descending colon can be queried by gene symbols. Users can compare gene expression levels of IBS patients across these tissues. Sex difference of gene expression in IBS patients was also shown in the database. The current version of TIBS database contains 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 plus 2.0 platform. TIBS will be an invaluable resource for a better understanding of the pathogenesis of IBS at the molecular level and for drug development. The TIBS database is available online at http://www.chengfeng.info/tibs_database.html.

SEGEL: A Web Server for Visualization of Smoking Effects on Human Lung Gene Expression.

Cigarette smoking is a major cause of death worldwide resulting in over six million deaths per year. Cigarette smoke contains complex mixtures of chemicals that are harmful to nearly all organs of the human body, especially the lungs. Cigarette smoking is considered the major risk factor for many lung diseases, particularly chronic obstructive pulmonary diseases (COPD) and lung cancer. However, the underlying molecular mechanisms of smoking-induced lung injury associated with these lung diseases still remain largely unknown. Expression microarray techniques have been widely applied to detect the effects of smoking on gene expression in different human cells in the lungs. These projects have provided a lot of useful information for researchers to understand the potential molecular mechanism(s) of smoke-induced pathogenesis. However, a user-friendly web server that would allow scientists to fast query these data sets and compare the smoking effects on gene expression across different cells had not yet been established. For that reason, we have integrated eight public expression microarray data sets from trachea epithelial cells, large airway epithelial cells, small airway epithelial cells, and alveolar macrophage into an online web server called SEGEL (Smoking Effects on Gene Expression of Lung). Users can query gene expression patterns across these cells from smokers and nonsmokers by gene symbols, and find the effects of smoking on the gene expression of lungs from this web server. Sex difference in response to smoking is also shown. The relationship between the gene expression and cigarette smoking consumption were calculated and are shown in the server. The current version of SEGEL web server contains 42,400 annotated gene probe sets represented on the Affymetrix Human Genome U133 Plus 2.0 platform. SEGEL will be an invaluable resource for researchers interested in the effects of smoking on gene expression in the lungs. The server also provides useful information for drug development against smoking-related diseases. The SEGEL web server is available online at http://www.chengfeng.info/smoking_database.html.