Correction to: A statistical framework for analyzing deep mutational scanning data.

CORRECTION: After publication of our article [1] it was brought to our attention that a line of code was missing from our program to combine the within-replicate variance and between-replicate variance. This led to an overestimation of the standard errors calculated using the Enrich2 random-effects model.

A statistical framework for analyzing deep mutational scanning data.

Deep mutational scanning is a widely used method for multiplex measurement of functional consequences of protein variants. We developed a new deep mutational scanning statistical model that generates error estimates for each measurement, capturing both sampling error and consistency between replicates. We apply our model to one novel and five published datasets comprising 243,732 variants and demonstrate its superiority in removing noisy variants and conducting hypothesis testing. Simulations show our model applies to scans based on cell growth or binding and handles common experimental errors. We implemented our model in Enrich2, software that can empower researchers analyzing deep mutational scanning data.

Microarray analysis of Akt PH domain binding employing synthetic biotinylated analogs of all seven phosphoinositide headgroup isomers.

Signaling lipids control many of the most important biological pathways, typically by recruiting cognate protein binding targets to cell surfaces, thereby regulating both their function and subcellular localization. A critical family of signaling lipids is that of the phosphatidylinositol polyphosphates (PIP(n)s), which is composed of seven isomers that vary based on phosphorylation pattern. A key protein that is activated upon PIP(n) binding is Akt, which then plays important roles in regulating the cell cycle, and is thus aberrant in disease. Characterization of protein-PIP(n) binding interactions is hindered by the complexity of the membrane environment and of the PIP(n) structures. Herein, we describe two rapid assays of use for characterizing protein-PIP(n) binding interactions. First, a microplate-based binding assay was devised to characterize the binding of effectors to immobilized synthetic PIP(n) headgroup-biotin conjugates corresponding to all seven isomers. The assay was implemented for simultaneous analysis of Akt-PH domain, indicating PI(3,4,5)P(3) and PI(3,4)P(2) as the primary ligands. In addition, density-dependant studies indicated that the amount of ligand immobilized on the surface affected the amplitude of protein binding, but not the affinity, for Akt-PH. Since the PIP(n) ligand motifs used in this analysis lack the membrane environment and glycerolipid backbone, yet still exhibit high-affinity protein binding, these results narrow down the structural requirements for Akt recognition. Additionally, binding detection was also achieved through microarray analysis via the robotic pin printing of ligands onto glass slides in a miniaturized format. Here, fluorescence-based detection provided sensitive detection of binding using minimal amounts of materials. Due to their high-throughput and versatile attributes, these assays provide invaluable tools for probing and perturbing protein-membrane binding interactions.

Phosphatidylinositol 3,4,5-trisphosphate activity probes for the labeling and proteomic characterization of protein binding partners.

Phosphatidylinositol polyphosphate lipids, such as phosphatidylinositol 3,4,5-trisphosphate [PI(3,4,5)P3], regulate critical biological processes, many of which are aberrant in disease. These lipids often act as site-specific ligands in interactions that enforce membrane association of protein binding partners. Herein, we describe the development of bifunctional activity probes corresponding to the headgroup of PI(3,4,5)P3 that are effective for identifying and characterizing protein binding partners from complex samples, namely cancer cell extracts. These probes contain both a photoaffinity tag for covalent labeling of target proteins and a secondary handle for subsequent detection or manipulation of labeled proteins. Probes bearing different secondary tags were exploited, either by direct attachment of a fluorescent dye for optical detection or by using an alkyne that can be derivatized after protein labeling via click chemistry. First, we describe the design and modular synthetic strategy used to generate multiple probes with different reporter tags of use for characterizing probe-labeled proteins. Next, we report initial labeling studies using purified protein, the PH domain of Akt, in which probes were found to label this target, as judged by in-gel detection. Furthermore, protein labeling was abrogated by controls including competition with an unlabeled PI(3,4,5)P3 headgroup analogue as well as through protein denaturation, indicating specific labeling. In addition, probes featuring linkers of different lengths between the PI(3,4,5)P3 headgroup and photoaffinity tag led to variations in protein labeling, indicating that a shorter linker was more effective in this case. Finally, proteomic labeling studies were performed using cell extracts; labeled proteins were observed by in-gel detection and characterized using postlabeling with biotin, affinity chromatography, and identification via tandem mass spectrometry. These studies yielded a total of 265 proteins, including both known and novel candidate PI(3,4,5)P3-binding proteins.

Phosphatidylserine binding is essential for plasma membrane recruitment and signaling function of 3-phosphoinositide-dependent kinase-1.

3-Phosphoinositide-dependent kinase-1 (PDK1) is a ubiquitously expressed serine/threonine kinase that functions downstream of phosphoinositide 3-kinase. Although binding of 3'-phosphoinositides, phosphatidylinositol 3,4,5-trisphosphate and phosphatidylinositol 3,4-bisphosphate, to the pleckstrin homology (PH) domain of PDK1 is known to be essential for its interaction with and activation of downstream kinases, the mechanism by which PDK1 is recruited to the plasma membrane remains controversial. Our surface plasmon resonance analysis of the PDK1 PH domain and selected mutants shows that the PH domain specifically binds phosphatidylserine using a site that is separate from the canonical phosphoinositide-binding site. Further cell studies show that this specific phosphatidylserine binding is important for the plasma membrane localization and signaling function of PDK1.