Articles by Venkatramanan Krishnamani in JoVE
Informatic Analysis of Sequence Data from Batch Yeast 2-Hybrid Screens Venkatramanan Krishnamani1, Tabitha A. Peterson1, Robert C. Piper1, Mark A. Stamnes1 1Molecular Physiology and Biophysics, University of Iowa Deep sequencing of yeast populations selected for positive yeast 2-hybrid interactions potentially yields a wealth of information about interacting partner proteins. Here, we describe the operation of specific bioinformatics tools and customized updated software to analyze sequence data from such screens.
Other articles by Venkatramanan Krishnamani on PubMed
The Dimerization Equilibrium of a ClC Cl(-)/H(+) Antiporter in Lipid Bilayers ELife. | Pubmed ID: 27484630 Interactions between membrane protein interfaces in lipid bilayers play an important role in membrane protein folding but quantification of the strength of these interactions has been challenging. Studying dimerization of ClC-type transporters offers a new approach to the problem, as individual subunits adopt a stable and functionally verifiable fold that constrains the system to two states - monomer or dimer. Here, we use single-molecule photobleaching analysis to measure the probability of ClC-ec1 subunit capture into liposomes during extrusion of large, multilamellar membranes. The capture statistics describe a monomer to dimer transition that is dependent on the subunit/lipid mole fraction density and follows an equilibrium dimerization isotherm. This allows for the measurement of the free energy of ClC-ec1 dimerization in lipid bilayers, revealing that it is one of the strongest membrane protein complexes measured so far, and introduces it as new type of dimerization model to investigate the physical forces that drive membrane protein association in membranes.
DEEPN As an Approach for Batch Processing of Yeast 2-Hybrid Interactions Cell Reports. | Pubmed ID: 27681439 We adapted the yeast 2-hybrid assay to simultaneously uncover multiple transient protein interactions within a single screen by using a strategy termed DEEPN (dynamic enrichment for evaluation of protein networks). This approach incorporates high-throughput DNA sequencing and computation to follow competition among a plasmid population encoding interacting partners. To demonstrate the capacity of DEEPN, we identify a wide range of ubiquitin-binding proteins, including interactors that we verify biochemically. To demonstrate the specificity of DEEPN, we show that DEEPN allows simultaneous comparison of candidate interactors across multiple bait proteins, allowing differential interactions to be identified. This feature was used to identify interactors that distinguish between GTP- and GDP-bound conformations of Rab5.
Cellular Encoding of Cy Dyes for Single-molecule Imaging ELife. | Pubmed ID: 27938668 A general method is described for the site-specific genetic encoding of cyanine dyes as non-canonical amino acids (Cy-ncAAs) into proteins. The approach relies on an improved technique for nonsense suppression with in vitro misacylated orthogonal tRNA. The data show that Cy-ncAAs (based on Cy3 and Cy5) are tolerated by the eukaryotic ribosome in cell-free and whole-cell environments and can be incorporated into soluble and membrane proteins. In the context of the oocyte expression system, this technique yields ion channels with encoded Cy-ncAAs that are trafficked to the plasma membrane where they display robust function and distinct fluorescent signals as detected by TIRF microscopy. This is the first demonstration of an encoded cyanine dye as a ncAA in a eukaryotic expression system and opens the door for the analysis of proteins with single-molecule resolution in a cellular environment.