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Sagawa, S.

Publications and source records attributed to Sagawa, S..

2 recordsLinked to original sources

Structural mechanism for Bruton’s tyrosine kinase activation at the cell membrane

Brutons tyrosine kinase (Btk) is critical for B-cell proliferation and activation, and the development of Btk inhibitors is a vigorously pursued strategy for the treatment of various B-cell malignancies. A detailed mechanistic understanding of Btk activation has, however, been lacking. Here, inspired by a previous suggestion that Btk activation might depend on dimerization of its lipid-binding PH-TH module on the cell membrane, we performed long-timescale molecular dynamics simulations of membrane-bound PH-TH modules and observed that they dimerized into a single predominant conformation. We found that the phospholipid PIP3 stabilized the dimer allosterically by binding at multiple sites, and that the effects of PH-TH mutations on dimer stability were consistent with their known effects on Btk activity. Taken together, our simulation results strongly suggest that PIP3-mediated dimerization of Btk at the cell membrane is a critical step in Btk activation.

biophysics

Validating Regulatory Predictions from Diverse Bacteria with Mutant Fitness Data

Although transcriptional regulation is fundamental to understanding bacterial physiology, the targets of most bacterial transcription factors are not known. Comparative genomics has been used to identify likely targets of some of these transcription factors, but these predictions typically lack experimental support. Here, we used mutant fitness data, which measures the importance of each gene for a bacteriums growth across many conditions, to validate regulatory predictions from RegPrecise, a curated collection of comparative genomics predictions. Because characterized transcription factors often have correlated fitness with one of their targets (either positively or negatively), correlated fitness patterns provide support for the comparative genomics predictions. At a false discovery rate of 3%, we identified significant cofitness for at least one target of 158 TFs in 107 ortholog groups and from 24 bacteria. Thus, high-throughput genetics can be used to identify a high-confidence subset of the sequence-based regulatory predictions.

microbiology