Bioconductor: open software development for computational biology and bioinformatics

The Bioconductor project is an initiative for the collaborative creation of extensible software for computational biology and bioinformatics. The goals of the project include: fostering collaborative development and widespread use of innovative software, reducing barriers to entry into interdisciplinary scientific research, and promoting the achievement of remote reproducibility of research results. We describe details of our aims and methods, identify current challenges, compare Bioconductor to other open bioinformatics projects, and provide working examples.

GW572016 (Lapatinib) is a tyrosine kinase inhibitor in clinical development for cancer that is a potent dual inhibitor of epidermal growth factor receptor (EGFR, ErbB-1) and ErbB-2. We determined the crystal structure of EGFR bound to GW572016. The compound is bound to an inactive-like conformation of EGFR that is very different from the activelike structure bound by the selective EGFR inhibitor OSI-774 (Tarceva) described previously. Surprisingly, we found that GW572016 has a very slow off-rate from the purified intracellular domains of EGFR and ErbB-2 compared with OSI-774 and another EGFR selective inhibitor, ZD-1839 (Iressa). Treatment of tumor cells with these inhibitors results in down-regulation of receptor tyrosine phosphorylation. We evaluated the duration of the drug effect after washing away free compound and found that the rate of recovery of receptor phosphorylation in the tumor cells reflected the inhibitor off-rate from the purified intracellular domain. The slow off-rate of GW572016 correlates with a prolonged down-regulation of receptor tyrosine phosphorylation in tumor cells. The differences in the off-rates of these drugs and the ability of GW572016 to inhibit ErbB-2 can be explained by the enzyme-inhibitor structures.

Background: Recent advances in automation technologies have enabled the use of flow cytometry for high throughput screening, generating large complex data sets often in clinical trials or drug discovery settings. However, data management and data analysis methods have not advanced sufficiently far from the initial small-scale studies to support modeling in the presence of multiple covariates.

The lipid second messenger ceramide regulates several biochemical events that occur during aging. In addition, its level is highly elevated in the amyloid-burdened brains of Alzheimer's disease patients. Here, we analyzed the impact of aberrant ceramide levels on amyloid ␤-peptide (A␤) generation by using a cell-permeable analog of ceramide, C6-ceramide, and several biochemical inhibitors of the sphingomyelin/glycosphingolipid biosynthetic pathway. We found that C6-ceramide increased the biogenesis of A␤ by affecting ␤-but not ␥-cleavage of the amyloid precursor protein. Similarly to C6-ceramide, increased levels of endogenous ceramide induced by neutral sphingomyelinase treatment also promoted the biogenesis of A␤. Conversely, fumonisin B1, which inhibits the biosynthesis of endogenous ceramide, reduced A␤ production. Exogenous C6-ceramide restored both intracellular ceramide levels and A␤ generation in fumonisin B1-treated cells. These events were specific for amyloid precursor protein and were not associated with apoptotic cell death. Pulse-chase and time-course degradation experiments showed that ceramide post-translationally stabilizes the ␤-secretase BACE1. Taken together, these data indicate that the lipid second messenger ceramide, which is elevated in the brains of Alzheimer's disease patients, increases the half-life of BACE1 and thereby promotes A␤ biogenesis.Alzheimer's disease (AD) 1 affects ϳ15 million individuals worldwide. The prevalence of the disease doubles every 5 years after age 65 and approaches 50% by age 85. Because of the ongoing increase in life expectancy, the number of people affected by this disease is rapidly increasing. The major risk factor for late-onset AD is aging (1). The molecular events that mediate the effect of aging on AD are the subjects of intensive study.The main pathogenic event that occurs in all forms of AD is the abnormal accumulation of amyloid ␤-peptide (A␤) into senile (or amyloid) plaques (2). A␤ is a 39 -43-amino acid peptide proteolytically derived from the amyloid precursor protein (APP). APP is first cleaved by ␤-site APP-cleaving enzyme 1 (BACE1) at the N terminus of A␤ (␤-cleavage), producing a C-terminal fragment (␤-APP-CTF) of ϳ12 kDa, and subsequently in the transmembrane domain (␥-cleavage) by a presenilin-harboring protease complex. The two major sites of ␥-cleavage are located at positions 40 and 42 of A␤, generating A␤ 40 and A␤ 42 , respectively.The membrane lipid ceramide is the backbone of all complex sphingolipids and acts as a second messenger in many biological events. In addition, it regulates several biochemical and genetic events that occur during aging/senescence, including inhibition of phospholipase D and c-Fos-dependent signaling pathways, retinoblastoma protein dephosphorylation, arrest of the serum/growth factor-mediated activation of protein kinase C, and arrest of DNA synthesis (3, 4). Endogenous ceramide can be generated by either de novo synthesis or hydrolysis of sphingomyelin (SM) at the cell surface, the latter being the most ...

Algorithms for performing feature extraction and normalization on high-density oligonucleotide gene expression arrays, have not been fully explored, and the impact these algorithms have on the downstream analysis is not well understood. Advances in such low-level analysis methods are essential to increase the sensitivity and speci®city of detecting whether genes are present and/or differentially expressed. We have developed and implemented a number of algorithms for the analysis of expression array data in a software application, the DNA-Chip Analyzer (dChip). In this report, we describe the algorithms for feature extraction and normalization, and present validation data and comparison results with some of the algorithms currently in use.