Probabilistic Inference of Transcription Factor Binding from Multiple Data Sources

An important problem in molecular biology is to build a complete understanding of transcriptional regulatory processes in the cell. We have developed a flexible, probabilistic framework to predict TF binding from multiple data sources that differs from the standard hypothesis testing (scanning) methods in several ways. Our probabilistic modeling framework estimates the probability of binding and, thus, naturally reflects our degree of belief in binding. Probabilistic modeling also allows for easy and systematic integration of our binding predictions into other probabilistic modeling methods, such as expression-based gene network inference. The method answers the question of whether the whole analyzed promoter has a binding site, but can also be extended to estimate the binding probability at each nucleotide position. Further, we introduce an extension to model combinatorial regulation by several TFs. Most importantly, the proposed methods can make principled probabilistic inference from multiple evidence sources, such as, multiple statistical models (motifs) of the TFs, evolutionary conservation, regulatory potential, CpG islands, nucleosome positioning, DNase hypersensitive sites, ChIP-chip binding segments and other (prior) sequence-based biological knowledge. We developed both a likelihood and a Bayesian method, where the latter is implemented with a Markov chain Monte Carlo algorithm. Results on a carefully constructed test set from the mouse genome demonstrate that principled data fusion can significantly improve the performance of TF binding prediction methods. We also applied the probabilistic modeling framework to all promoters in the mouse genome and the results indicate a sparse connectivity between transcriptional regulators and their target promoters. To facilitate analysis of other sequences and additional data, we have developed an on-line web tool, ProbTF, which implements our probabilistic TF binding prediction method using multiple data sources. Test data set, a web tool, source codes and supplementary data are available at: http://www.probtf.org

Connexin channels and phospholipids: association and modulation

<p>Abstract</p> <p>Background</p> <p>For membrane proteins, lipids provide a structural framework and means to modulate function. Paired connexin hemichannels form the intercellular channels that compose gap junction plaques while unpaired hemichannels have regulated functions in non-junctional plasma membrane. The importance of interactions between connexin channels and phospholipids is poorly understood.</p> <p>Results</p> <p>Endogenous phospholipids most tightly associated with purified connexin26 or connexin32 hemichannels or with junctional plaques in cell membranes, those likely to have structural and/or modulatory effects, were identified by tandem electrospray ionization-mass spectrometry using class-specific interpretative methods. Phospholipids were characterized by headgroup class, charge, glycerol-alkyl chain linkage and by acyl chain length and saturation. The results indicate that specific endogenous phospholipids are uniquely associated with either connexin26 or connexin32 channels, and some phospholipids are associated with both. Functional effects of the major phospholipid classes on connexin channel activity were assessed by molecular permeability of hemichannels reconstituted into liposomes. Changes to phospholipid composition(s) of the liposome membrane altered the activity of connexin channels in a manner reflecting changes to the surface charge/potential of the membrane and, secondarily, to cholesterol content. Together, the data show that connexin26 and connexin32 channels have a preference for tight association with unique anionic phospholipids, and that these, independent of headgroup, have a positive effect on the activity of both connexin26 and connexin32 channels. Additionally, the data suggest that the likely in vivo phospholipid modulators of connexin channel structure-function that are connexin isoform-specific are found in the cytoplasmic leaflet. A modulatory role for phospholipids that promote negative curvature is also inferred.</p> <p>Conclusion</p> <p>This study is the first to identify (endogenous) phospholipids that tightly associate with connexin channels. The finding that specific phospholipids are associated with different connexin isoforms suggests connexin-specific regulatory and/or structural interactions with lipid membranes. The results are interpreted in light of connexin channel function and cell biology, as informed by current knowledge of lipid-protein interactions and membrane biophysics. The intimate involvement of distinct phospholipids with different connexins contributes to channel structure and/or function, as well as plaque integrity, and to modulation of connexin channels by lipophilic agents.</p