Beta Cell Gene Bank FAQs

What is the Beta Cell Gene Expression Bank? Top

The Beta Cell Gene Expression Bank is a web accessible database that holds annotations for beta cell genes expertly curated. Functional annotations of genes expressed in beta cells are also included.

The ultimate goal of the Beta Cell Gene Expression Bank is to store, annotate and compare information obtained on genes expressed in primary and tumoral rodent beta-cells, and in human islets, expressed either under basal condition or following exposure to agents that contribute to beta-cell dysfunction and death in type 1 diabetes mellitus, such as cytokines, double stranded RNA or viral infection. We hope that the cumulative information, freely accessible to the scientific community, will save an enormous amount of time for scientists studying global beta-cell gene expression in models of diabetes mellitus or islet transplantation.
The initial data included in the Bank were generated from microarray analysis of the expression of cytokine-, dsRNA-, viral-induced genes in FACS-purified rat pancreatic beta-cells and INS-1E insulin-producing cells. Later we added microarray data obtained in human islets exposed to cytokines or diabetogenic viruses. We have already detected 4,600 probesets (3,700 genes) consistently expressed in rat beta-cells and INS-1 cells and around 6,400 probesets (4,800 genes) expressed in human islets. These findings are reproducible (less than 20% variation between assays, and >90% confirmation by RT-PCR) and correlate well with protein expression.

The "Beta Cell Gene Expression Bank" was originally developed as a collaboration between the Laboratory of Experimental Medicine, ULB, Belgium (Coordinator Dr. D.L. Eizirik) and the JDRF Center for Bioinformatics, ISB, Seattle (Coordinator Dr. N. Goodman). It is since 2010 run at the Université Libre de Bruxelles (ULB), as a collaboration between the Laboratory of Experimental Medicine, ULB, Belgium (Dr. D.L. Eizirik) and the Machine Learning Group, Computer Science Department - Département d'Informatique, Faculty of Science, ULB (Dr. Gianluca Bontempi and Catharina Olsen).

The Beta Cell Gene Expression Bank was started with support from the JDRF, the European Union 6th Frame Program - Project TONECA and by an educational and unrestricted donations by Eli Lilly Forschung Hamburg and by the EFSD/Pfizer Resource Award 2006. It is since October 2010 supported by a grant from the Communauté Française de Belgique -- Actions de Recherche Concertées (ARC) to Drs Eizirik and Bontempi.

Who is creating the Beta Cell Gene Expression Bank? Top

The Beta Cell Gene Expression Bank was initiated as the result of a collaboration between the Laboratory of Experimental Medicine, Université Libre de Bruxelles, and the JDRF Center for Bioinformatics at the Institute for Systems Biology, with support from the JDRF. The scientists initially involved in microarray analysis and gene annotations at the Laboratory of Experimental Medicine were Daisy Flamez, Burak Kutlu, Alessandra Cardozo, Fernanda Ortis, Martine Darville, Joanne Rasschaert, and Decio L. Eizirik (Coordinator). The scientists involved in software development and site design at the JDRF center for Bioinformatics at the Institute for Systems Biology are Erin Helton, Chris Cavnor, David Burdick, Victor Cassen, Sarah Killcoyne and Dr. N. Goodman (Coordinator). The Beta Cell Gene Expression Bank is since July 2010 run at the Université Libre de Bruxelles (ULB), as a collaboration between the Laboratory of Experimental Medicine, ULB, Belgium (Dr. D.L. Eizirik) and the Machine Learning Group, Computer Science Department - Département d'Informatique, Faculty of Science, ULB (Dr. Gianluca Bontempi and Catharina Olsen).

How do I cite the Beta Cell Gene Expression Bank? Top

Please include a reference to the Beta Cell Gene Expression Bank if you use it in your work and/or publication: "Beta Cell Gene Expression Bank; http://betacellgenebank.ulb.ac.be"

How will the Beta Cell Gene Expression Bank progress? Top

The information contained in the Beta Cell Gene Expression Bank is presented in two formats:

The "Annotated Data Set":
This Data Set contains filtered information on gene expression (using the criteria described above) and manual annotation on gene function and key references. The Annotated Data Set presently contains 835 genes. For an example, see iNOS.

The "Fast Track Data Set":
We are also posting non-filtered and non-annotated information in the "Fast Track Data Set". This "Fast Track Data Set" will allow scientists to check: a. whether genes of interest, and not yet annotated, are expressed in rat beta cells or in human islets; b. whether mRNA expression is affected by cytokines or dsRNA. This information set presently contains probesets scored as "present" by the Affymetrix software in purified rat beta cells, rat INS-1E cells and human islets. The information provided is based on microarrays performed using the rat U34A Affymetrix chip and the human HG-U133A Affymetrix chip. Genes are included in the list when they were considered as "present" in at least half of arrays under control condition, or half arrays following exposure to cytokines or dsRNA.
Beta Cell specific pathways: We are currently working on the generation of several pathways which will be freely consultable on our website. Along with the posting of these pathways on the web, we will annotate all genes present in the pathways. It will be possible to move directly from a specific gene depicted in the pathway to its respective annotation.

Relevant Publications:

Cardozo AK, Kruhøffer M, Leeman R, Orntoft T, Eizirik DL. Identification of novel cytokine-induced genes in pancreatic beta-cells by high-density oligonucleotide arrays. (2001) Diabetes. 50:909-20 PMID: 11334433
Cardozo AK, Heimberg H, Heremans Y, Leeman R, Kutlu B, Kruhoffer M, Orntoft T, Eizirik DL. A comprehensive analysis of cytokine-induced and nuclear factor-kappa B-dependent genes in primary rat pancreatic beta-cells. (2001) J Biol Chem. 276:48879-86. PMID: 11687580
Rasschaert J, Liu D, Kutlu B, Cardozo AK, Kruhøffer M, ØRntoft TF, Eizirik DL. Global profiling of double stranded RNA- and IFN-gamma-induced genes in rat pancreatic beta cells. (2003) Diabetologia. 46:1641-57 PMID: 14600816
Rasschaert J, Ladriere L, Urbain M, Dogusan Z, Katabua B, Sato S, Akira S, Gysemans C, Mathieu C, Eizirik DL. Toll-like receptor 3 and STAT-1 contribute to double-stranded RNA+ interferon-gamma-induced apoptosis in primary pancreatic beta-cells. (2005) J Biol Chem. 280:33984-91. PMID: 16027122
Kutlu B, Cardozo AK, Darville MI, Kruhoffer M, Magnusson N, ORntoft T, Eizirik DL. Discovery of Gene Networks Regulating Cytokine-Induced Dysfunction and Apoptosis in Insulin-Producing INS-1 Cells. (2003) Diabetes. 52:2701-19 PMID: 14578289
Ylipaasto P, Kutlu B, Rasilainen S, Rasschaert J, Salmela K, Teerijoki H, Korsgren O, Lahesmaa R, Hovi T, Eizirik DL, Otonkoski T, Roivainen M. Global profiling of coxsackievirus- and cytokine-induced gene expression in human pancreatic islets. (2005) Diabetologia. 48:1510-22. PMID: 15991020

How is mean expression level defined? Top

The Affymetrix probe arrays contains thousands of probesets, including both full-length sequences and EST clusters. Each probeset contains between 11 to 20 probe pairs. A probe pair contains an oligonucleotide complementary to the sequence of the gene (perfect match) and an oligonucleotide that contains homomeric (base transversion) mismatch at the central 13th base position of the oligomer (mismatch). The oligonucleotides are 25 bases in length. Mean expression levels or average difference (AvDiff as defined by Affymetrix software GeneChip 3.0 software) is based on the difference between perfect match and mismatch probe pairs.

How is fold change defined? Top

Fold change (FC) indicates the relative change in expression levels between the experimental and baseline (control) targets. FC is a positive number when the expression level in the experiment increases and a negative number when the expression level in the experiment decreases

How is a fold-change defined for a gene with mean expression level below detection limit? Top

If the noise of the baseline array is greater than the AvDiff of the transcript, fold change is calculated over the noise and FC is an approximation.

What are the criteria for choosing the probes, shown in the experimental results? Top

Affymetrix chips contain one or more probesets per gene. We selected the probesets which have a detectable mean expression level in our arrays. Some of the microarray data were reconfirmed by quantitative RT-PCR (rate of confirmation > 90%). Genes were arbitrarily defined as up-regulated with ≥ +2.5 fold change or down-regulated with ≤ -2.5 fold change by the different treatment compared to the control group. Future data will include statistical analysis.

Where does the homology data come from? Top

The homology data comes from a variety of sources, including Affymetrix and Unigene. The Institute for Systems Biology is currently working on a project to collect manually curated homology data, and this will be included when it is available.

How can I comment on the Beta Cell Gene Expression Bank? Top We would love to receive feedback and comments on the Beta Cell Gene Expression Bank. Please don't hesitate to contact us at deizirik@ulb.ac.be