Biology subjects

Zuckerman, D. M.

Publications and source records attributed to Zuckerman, D. M..

28 records · Page 2Linked to original sources

bioRxiv2020

Connexin 46 and connexin 50 gap junction channel open stability and unitary conductance are shaped by structural and dynamic features of their N-terminal domains

The connexins form intercellular communication channels, known as gap junctions (GJs), that facilitate diverse physiological roles in vertebrate species, ranging from electrical coupling and long-range chemical signaling, to coordinating development and nutrient exchange. GJs formed by different connexins are expressed throughout the body and harbor unique channel properties that have not been fully defined mechanistically. Recent structural studies have implicated the amino-terminal (NT) domain as contributing to isoform-specific functional differences that exist between the lens connexins, Cx50 and Cx46. To better understand the structural and functional differences in the two closely related, yet functionally distinct GJs, we constructed models corresponding to CryoEM-based structures of the wildtype Cx50 and Cx46 GJs, NT domain swapped chimeras (Cx46-50NT and Cx50-46NT), and point variants at the 9th residue (Cx46-R9N and Cx50-N9R) for comparative MD simulation and electrophysiology studies. All of these constructs formed functional GJ channels, except Cx46-50NT, which correlated with increased dynamical behavior (instability) of the NT domain observed by MD simulation. Single channel conductance (γj) also correlated well with free-energy landscapes predicted by MD, where γj of Cx46-R9N was increased from Cx46 and the γjs of Cx50-46NT and Cx50-N9R was decreased from Cx50, but to a surprisingly greater degree. Additionally, we observed significant effects on transjunctional voltage-dependent gating (Vj-gating) and open-state dwell times induced by the designed NT domain variants. Together, these studies indicate that the NT domains of Cx46 and Cx50 play an important role in defining channel properties related to open-state stability and single channel conductance.Competing Interest StatementThe authors have declared no competing interest.AbbreviationsGJgap junctionGjgap junctional coupling conductanceγjsingle gap junction channel conductanceIjmacroscopic transjunctional currentijsingle gap junction channel currentCx46sheep connexin 46Cx50sheep connexin 50Vjtransjunctional voltageMDmolecular dynamicsr.m.s.d.root mean square deviationr.m.s.f.root mean square fluctuationPMFpotential of mean forceView Full Text

biophysics↗

bioRxiv2020

Automated and statistically corrected identification of flexible multivalent IDP-bound assemblies in electron micrographs

Multivalent intrinsically disordered protein (IDP) complexes are prevalent in biology and control diverse cellular functions, including tuning levels of transcription, coordinating cell-signaling events, and regulating the assembly and disassembly of complex macromolecular architectures. These systems pose a significant challenge to structural investigation, due to the continuum dynamics imparted by the IDP and compositional heterogeneity resulting from characteristic low-affinity interactions. Traditional single-particle electron microscopy (EM) is a powerful tool for visualizing IDP complexes. However, the IDPs themselves are typically "invisible" by EM, undermining methods of image analysis and structural interpretation. To overcome these challenges, we developed a pipeline for automated analysis of common beads-on-a-string type of assemblies, composed of IDPs bound at multivalent sites to the ubiquitous ~20 kDa cross-linking hub protein LC8. This approach quantifies conformational and compositional heterogeneity on a single-particle basis, and statistically corrects spurious observations arising from random proximity of bound and unbound LC8. After careful validation of the methodology, the approach was applied to the nuclear pore IDP Nup159 and the transcription factor ASCIZ. The analysis unveiled significant compositional and conformational diversity in both systems that could not be obtained from traditional single particle EM class-averaging strategies, and shed new light on how these architectural properties contribute to their physiological roles in supramolecular assembly and transcriptional regulation. Ultimately, we expect that this approach may be adopted to many other intrinsically disordered systems that have evaded traditional methods of structural characterization. Significance StatementIntrinsically disordered proteins (IDPs) or protein regions (IDRs) represent >30% of the human proteome, but mechanistically remain some of the most poorly understood classes of proteins in biology. This dearth in understanding stems from these very same intrinsic and dynamic properties, which make them difficult targets for quantitative and structural characterization. Here, we present an automated approach for extracting quantitative descriptions of conformational and compositional heterogeneity present in a common beads-on-a-string type of multivalent IDP system from single-particle images in electron micrographs. This promising approach may be adopted to many other intrinsically disordered systems that have evaded traditional ensemble methods of characterization.

biophysics↗

bioRxiv2020

Connexin-46/50 in a dynamic lipid environment resolved by CryoEM at 1.9 A

Gap junctions establish direct pathways for connected cells and tissues to transfer metabolic and electrical messages1. The local lipid environment is known to affect the structure, stability and intercellular channel activity of gap junctions2-5; however, the molecular basis for these effects remains unknown. To gain insight toward how gap junctions interact with their local membrane environment, we used lipid nanodisc technology to incorporate native connexin-46/50 (Cx46/50) intercellular channels into a dual lipid membrane system, closely mimicking a native cell-to-cell junction. Structural characterization of Cx46/50 lipid-embedded channels by single particle CryoEM revealed a lipid-induced stabilization to the channel, resulting in a 3D reconstruction at 1.9 [A] resolution. Together with all-atom molecular dynamics (MD) simulations and 3D heterogeneity analysis of the ensemble CryoEM data, it is shown that Cx46/50 in turn imparts long-range stabilization to the dynamic local lipid environment that is specific to the extracellular lipid leaflet of the two opposed membranes. In addition, nearly 400 water molecules are resolved in the CryoEM map, localized throughout the intercellular permeation pathway and contributing to the channel architecture. These results illustrate how the aqueous-lipid environment is integrated with the architectural stability, structure and function of gap junction communication channels, and demonstrates the ability of CryoEM to effectively characterize dynamical protein-lipid interactions.

biophysics↗

bioRxiv2019

What is that molecular machine really doing? Automated exploration of alternative transporter mechanisms

Motivated by growing evidence for pathway heterogeneity and alternative functions of molecular machines, we demonstrate a computational approach for investigating two questions: (1) Are there multiple mechanisms (state-space pathways) by which a machine can perform a given function, such as cotransport across a membrane? (2) How can additional functionality, such as proofreading/error-correction, be built into machine function using standard biochemical processes? Answers to these questions will aid both the understanding of molecular-scale cell biology and the design of synthetic machines. Focusing on transport in this initial study, we sample a variety of mechanisms by employing Metropolis Markov chain Monte Carlo. Trial moves adjust transition rates among an automatically generated set of conformational and binding states while maintaining fidelity to thermodynamic principles and a user-supplied fitness/functionality goal. Each accepted move generates a new model. The simulations yield both single and mixed reaction pathways for cotransport in a simple environment with a single substrate along with a driving ion. In a "competitive" environment including an additional decoy substrate, several qualitatively distinct reaction pathways are found which are capable of extremely high discrimination coupled to a leak of the driving ion, akin to proofreading. The array of functional models would be difficult to find by intuition alone in the complex state-spaces of interest. Author summaryMolecular machines, which operate on the nanoscale, are proteins/complexes that perform remarkable tasks such as the selective absorption of nutrients into the cell by transporters. These complex machines are often described using a fairly simple set of states and transitions that may not account for the stochasticity and heterogeneity generally expected at the nanoscale at body temperature. New tools are needed to study the full array of possibilities. This study presents a novel in silico method to systematically generate testable molecular-machine kinetic models and explore alternative mechanisms, applied first to membrane transport proteins. Our initial results suggest these transport machines may contain mechanisms which detoxify the cell of an unwanted toxin, as well as significantly discriminate against the import of the toxin. This novel approach should aid the experimental study of key physiological processes such as renal glucose re-absorption, rational drug design, and potentially the development of synthetic machines.

biophysics↗

bioRxiv2019

Should virus capsids assemble perfectly? A simple equilibrium model for defects

Although published structural models of viral capsids generally exhibit a high degree of regularity or symmetry, structural defects might be expected because of the fluctuating environment in which capsids assemble and the requirement of some capsids for disassembly prior to genome delivery. Defective structures are observed in computer simulations, and are evident in single-particle cryoEM studies. Here, we quantify the conditions under which defects might be expected, using a statistical mechanics model allowing for ideal, defective, and vacant sites. The model displays a threshold in affinity parameters below which there is an appreciable population of defective capsids. Even when defective sites are not allowed, there is generally some population of vacancies. Analysis of single particles in cryoEM micrographs yields a confirmatory {gtrsim}15% of defective particles. Our findings suggest structural heterogeneity in virus capsids may be under-appreciated, and also points to a non-traditional strategy for assembly inhibition.

biophysics↗

bioRxiv2019

HER2 Cancer Protrusion Growth Signaling Regulated by Unhindered, Localized Filopodial Dynamics

Protrusions are plasma membrane extensions that are found in almost every cell in the human body. Cancer cell filopodial and lamellipodial protrusions play key roles in the integral processes of cell motility and signaling underlying tumor invasion and metastasis. HER2 (ErbB-2) is overexpressed in diverse types of tumors and regulates PI3K-pathway-mediated protrusion growth. It is known that HER2 resides at breast cancer cell protrusions, but how protrusion-based HER2 spatiotemporal dynamics shape cancer signaling is unclear. Here, we study how HER2 location and motion regulate protrusion signaling and growth using quantitative spatio-temporal molecular imaging approaches. Our data highlight morphologically-segregated features of filopodial and lamellipodial protrusions, in in vitro 2D breast cancer cells and in vivo intact breast tumor. Functional-segregation parallels morphological-segregation, as HER2 and its activated downstream pAKT-PI3K signaling remain spatially-localized at protrusions, provoking new protrusion growth proximal to sites of HER2 activation. HER2 in SKBR3 breast cancer cell filopodia exhibits fast, linearly-directed motion that is distinct from lamellipodia and non-protrusion subcellular regions ([~]3-4 times greater diffusion constant, rapid speeds of 2-3 um2/s). Surprisingly, filopodial HER2 motion is passive, requiring no active energy sources. Moreover, while HER2 motion in lamellipodia and non-protrusion regions show hindered diffusion typical of membrane proteins, HER2 diffuses freely within filopodia. We conclude that HER2 activation, propagation, and functional protrusion growth is a local process in which filopodia have evolved to exploit Brownian thermal fluctuations within a barrier-free nanostructure to transduce rapid signaling. These results support the importance of developing filopodia and other protrusion-targeted strategies for cancer.

cancer biology↗

bioRxiv2019

High-throughput single-particle tracking reveals nested membrane nanodomain organization that dictates Ras diffusion and trafficking

Membrane nanodomains have been implicated in Ras signaling, but what these domains are and how they interact with Ras remain obscure. Using high throughput single particle tracking with photoactivated localization microscopy and detailed trajectory analysis, here we show that distinct membrane domains dictate KRas diffusion and trafficking in U2OS cells. KRas exhibits an immobile state in domains [~]70 nm in size, each embedded in a larger domain ([~]200 nm) that confers intermediate mobility, while the rest of the membrane supports fast diffusion. Moreover, KRas is continuously removed from the membrane via the immobile state and replenished to the fast state, likely coupled to internalization and recycling. Importantly, both the diffusion and trafficking properties of KRas remain invariant over a broad range of protein expression levels. Our results reveal how membrane organization dictates KRas diffusion and trafficking and offer insight into how Ras signaling may be regulated through spatial mechanisms.

biophysics↗

bioRxiv2018

Computational estimation of ms-sec atomistic folding times

Despite the development of massively parallel computing hardware including inexpensive graphics processing units (GPUs), it has remained infeasible to simulate the folding of atomistic proteins at room temperature using conventional molecular dynamics (MD) beyond the s scale. Here we report the folding of atomistic, implicitly solvated protein systems with folding times {tau}f ranging from ~100 s to ~10s using the weighted ensemble (WE) strategy in combination with GPU computing. Starting from an initial structure or set of structures, WE organizes an ensemble of GPU-accelerated MD trajectory segments via intermittent pruning and replication events to generate statistically unbiased estimates of rate constants for rare events such as folding; no biasing forces are used. Although the variance among atomistic WE folding runs is significant, multiple independent runs are used to reduce and quantify statistical uncertainty. Three systems were examined: NTL9 at low solvent viscosity (yielding {tau}f ~ 5s), NTL9 at water-like viscosity ({tau}f ~ 40s), and Protein G at low viscosity ({tau}f ~ 10s). In all cases the folding time, uncertainty, and ensemble properties could be estimated from WE simulation; for protein G, this characterization required significantly less overall computing than would be required to observe a single folding event with conventional MD simulations. Our results suggest discrepancies with experimental folding times that should enable improvement of force fields and solvent models.

biophysics↗

bioRxiv2018

Middle-way flexible docking: Pose prediction using mixed-resolution Monte Carlo in estrogen receptor α

There is a vast gulf between the two primary strategies for simulating protein-ligand interactions. Docking methods significantly limit or eliminate protein flexibility to gain great speed at the price of uncontrolled inaccuracy, whereas fully flexible atomistic molecular dynamics simulations are expensive and often suffer from limited sampling. We have developed a flexible docking approach geared especially for highly flexible or poorly resolved targets based on mixed-resolution Monte Carlo (MRMC), which is intended to offer a balance among speed, protein flexibility, and sampling power. The binding region of the protein is treated with a standard atomistic force field, while the remainder of the protein is modeled at the residue level with a G[o] model that permits protein flexibility while saving computational cost. Implicit solvation is used. Here we assess three facets of the MRMC approach with implications for other docking studies: (i) the role of receptor flexibility in cross-docking pose prediction; (ii) the use of non-equilibrium candidate Monte Carlo (NCMC) and (iii) the use of pose-clustering in scoring. We examine 61 co-crystallized ligands of estrogen receptor , an important cancer target known for its flexibility. We also compare the performance of the MRMC approach with Autodock smina, a docking program. [1] Adding protein flexibility, not surprisingly, leads to significantly lower total energies and stronger interactions between protein and ligand, but notably we document the important role of backbone flexibility in the improvement. The improved backbone flexibility also leads to improved performance relative to smina. Somewhat unexpectedly, our implementation of NCMC leads to only modestly improved sampling of ligand poses. Overall, the addition of protein flexibility improves the performance of docking, as measured by energy-ranked poses, but we do not find significant improvements based on cluster information or the use of NCMC.

biophysics↗

bioRxiv2018

Stochastic Simulation to Visualize Gene Expression and Error Correction in Living Cells

Stochastic simulation can make the molecular processes of cellular control more vivid than the traditional differential-equation approach by generating typical system histories instead of just statistical measures such as the mean and variance of a population. Simple simulations are now easy for students to construct from scratch, that is, without recourse to black-box packages. In some cases, their results can also be compared directly to single-molecule experimental data. After introducing the stochastic simulation algorithm, this article gives two case studies, involving gene expression and error correction, respectively. Code samples and resulting animations showing results are given in the online supplement.

biophysics↗