Molecular mechanism for inhibition of twinfilin by phosphoinositides

Bsp1, a fungal CPI motif protein, regulates actin filament capping in endocytosis and cytokinesis

The capping of barbed filament ends is a fundamental mechanism for actin regulation. Capping protein controls filament growth and actin turnover in cells by binding to the barbed ends of the filaments with high affinity and slow off-rate. The interaction between capping protein and actin is regulated by capping protein interaction (CPI) motif proteins. We identified a novel CPI motif protein, Bsp1, which is involved in cytokinesis and endocytosis in budding yeast. We demonstrate that Bsp1 is an actin binding protein with a high affinity for capping protein via its CPI motif. In cells, Bsp1 regulates capping protein at endocytic sites and is a major recruiter of capping protein to the cytokinetic actin ring. Lastly, we define Bsp1-related proteins as a distinct fungi-specific CPI protein group. Our results suggest that Bsp1 promotes actin filament capping by the capping protein. This study establishes Bsp1 as a new capping protein regulator and promising candidate to regulate actin networks in fungi.

Multicomponent regulation of actin barbed end assembly by twinfilin, formin and capping protein

Cells control actin assembly by regulating reactions at actin filament barbed ends. Formins accelerate elongation, capping protein (CP) arrests growth and twinfilin promotes depolymerization at barbed ends. How these distinct activities get integrated within a shared cytoplasm is unclear. Using microfluidics-assisted TIRF microscopy, we find that formin, CP and twinfilin can simultaneously bind filament barbed ends. Three‑color, single-molecule experiments reveal that twinfilin cannot bind barbed ends occupied by formin unless CP is present. This trimeric complex is short-lived (~1 s), and results in dissociation of CP by twinfilin, promoting formin-based elongation. Thus, the depolymerase twinfilin acts as a pro-formin pro-polymerization factor when both CP and formin are present. While one twinfilin binding event is sufficient to displace CP from the barbed-end trimeric complex, ~31 twinfilin binding events are required to remove CP from a CP-capped barbed end. Our findings establish a paradigm where polymerases, depolymerases and cappers together tune actin assembly.

Multicomponent regulation of actin barbed end assembly by twinfilin, formin and capping protein

Living cells assemble their actin networks by regulating reactions at the barbed end of actin filaments. Formins accelerate elongation, capping protein (CP) arrests growth and twinfilin promotes depolymerization at barbed ends. How cells integrate these disparate activities within a shared cytoplasm to produce diverse actin networks, each with distinct morphologies and finely tuned assembly kinetics, is unclear. We used microfluidics-assisted TIRF microscopy to investigate how formin mDia1, CP and twinfilin influence the elongation of actin filament barbed ends. We discovered that the three proteins can simultaneously bind a barbed end in a multiprotein complex. Three-color single molecule experiments showed that twinfilin cannot bind actin filament ends occupied by formin mDia1 unless CP is present. The trimeric complex is short-lived (∼1s) and results in rapid dissociation of CP by twinfilin causing resumption of rapid formin- based elongation. Thus, the depolymerase twinfilin acts as a pro-formin factor that promotes polymerization when both CP and formin are present. While a single twinfilin binding event is sufficient to displace CP from the trimeric complex, it takes about 30 independent twinfilin binding events to remove capping protein from CP-bound barbed end. Our findings establish a new paradigm in which polymerases, depolymerases and cappers work in concert to tune cellular actin assembly.

Cofilin-Membrane Interactions: Electrostatic Effects in Phosphoinositide Lipid Binding

The actin cytoskeleton interacts with the cell membrane primarily through the indirect interactions of actin-binding proteins such as cofilin-1. The molecular mechanisms underlying the specific interactions of cofilin-1 with membrane lipids are still unclear. Here, we performed coarse-grain molecular dynamics simulations of cofilin-1 with complex lipid bilayers to analyze the specificity of protein-lipid interactions. We observed the maximal interactions with phosphoinositide (PIP) lipids, especially PIP₂ and PIP₃ lipids. A good match was observed between the residues predicted to interact and previous experimental studies. The clustering of PIP lipids around the membrane bound protein leads to an overall lipid demixing and gives rise to persistent membrane curvature. Further, through a series of control simulations, we observe that both electrostatics and geometry are critical for specificity of lipid binding. Our current study is a step towards understanding the physico-chemical basis of cofilin-PIP lipid interactions.

Actin capping protein regulates postsynaptic spine development through CPI-motif interactions

Dendritic spines are small actin-rich protrusions essential for the formation of functional circuits in the mammalian brain. During development, spines begin as dynamic filopodia-like protrusions that are then replaced by relatively stable spines containing an expanded head. Remodeling of the actin cytoskeleton plays a key role in the formation and modification of spine morphology, however many of the underlying regulatory mechanisms remain unclear. Capping protein (CP) is a major actin regulating protein that caps the barbed ends of actin filaments, and promotes the formation of dense branched actin networks. Knockdown of CP impairs the formation of mature spines, leading to an increase in the number of filopodia-like protrusions and defects in synaptic transmission. Here, we show that CP promotes the stabilization of dendritic protrusions, leading to the formation of stable mature spines. However, the localization and function of CP in dendritic spines requires interactions with proteins containing a capping protein interaction (CPI) motif. We found that the CPI motif-containing protein Twinfilin-1 (Twf1) also localizes to spines where it plays a role in CP spine enrichment. The knockdown of Twf1 leads to an increase in the density of filopodia-like protrusions and a decrease in the stability of dendritic protrusions, similar to CP knockdown. Finally, we show that CP directly interacts with Shank and regulates its spine accumulation. These results suggest that spatiotemporal regulation of CP in spines not only controls the actin dynamics underlying the formation of stable postsynaptic spine structures, but also plays an important role in the assembly of the postsynaptic apparatus underlying synaptic function.

Structural Insights into the Regulation of Actin Capping Protein by Twinfilin C-terminal Tail

Twinfilin is a conserved actin regulator that interacts with actin capping protein (CP) via C terminus residues (TWtail) that exhibits sequence similarity with the CP interaction (CPI) motif of CARMIL. Here we report the crystal structure of TWtail in complex with CP. Our structure showed that although TWtail and CARMIL CPI bind CP to an overlapping surface via their middle regions, they exhibit different CP-binding modes at both termini. Consequently, TWtail and CARMIL CPI restrict the CP in distinct conformations of open and closed forms, respectively. Interestingly, V-1, which targets CP away from the TWtail binding site, also favors the open-form CP. Consistently, TWtail forms a stable ternary complex with CP and V-1, a striking contrast to CARMIL CPI, which rapidly dissociates V-1 from CP. Our results demonstrate that TWtail is a unique CP-binding motif that regulates CP in a manner distinct from CARMIL CPI.

Twinfilin uncaps filament barbed ends to promote turnover of lamellipodial actin networks

Coordinated polymerization of actin filaments provides force for cell migration, morphogenesis and endocytosis. Capping protein (CP) is a central regulator of actin dynamics in all eukaryotes. It binds to actin filament (F-actin) barbed ends with high affinity and slow dissociation kinetics to prevent filament polymerization and depolymerization. However, in cells, CP displays remarkably rapid dynamics within F-actin networks, but the underlying mechanism remains unclear. Here, we report that the conserved cytoskeletal regulator twinfilin is responsible for CP's rapid dynamics and specific localization in cells. Depletion of twinfilin led to stable association between CP and cellular F-actin arrays, as well as to its retrograde movement throughout leading-edge lamellipodia. These were accompanied by diminished F-actin turnover rates. In vitro single-filament imaging approaches revealed that twinfilin directly promotes dissociation of CP from filament barbed ends, while enabling subsequent filament depolymerization. These results uncover a bipartite mechanism that controls how actin cytoskeleton-mediated forces are generated in cells.

Predicting Genetic Variation Severity Using Machine Learning to Interpret Molecular Simulations

Distinct missense mutations in a specific gene have been associated with different diseases as well as differing severity of a disease. Current computational methods predict the potential pathogenicity of a missense variant but fail to differentiate between separate disease or severity phenotypes. We have developed a method to overcome this limitation by applying machine learning to features extracted from molecular dynamics simulations, creating a way to predict the effect of novel genetic variants in causing a disease, drug resistance, or another specific trait. As an example, we have applied this novel approach to variants in calmodulin associated with two distinct arrhythmias as well as two different neurodegenerative diseases caused by variants in amyloid-β peptide. The new method successfully predicts the specific disease caused by a gene variant and ranks its severity with more accuracy than existing methods. We call this method molecular dynamics phenotype prediction model.

Cytoskeletal Remodeling in Cancer

Simple Summary

Cell migration is an essential process from embryogenesis to cell death. This is tightly regulated by numerous proteins that help in proper functioning of the cell. In diseases like cancer, this process is deregulated and helps in the dissemination of tumor cells from the primary site to secondary sites initiating the process of metastasis. For metastasis to be efficient, cytoskeletal components like actin, myosin, and intermediate filaments and their associated proteins should co-ordinate in an orderly fashion leading to the formation of many cellular protrusions-like lamellipodia and filopodia and invadopodia. Knowledge of this process is the key to control metastasis of cancer cells that leads to death in 90% of the patients. The focus of this review is giving an overall understanding of these process, concentrating on the changes in protein association and regulation and how the tumor cells use it to their advantage. Since the expression of cytoskeletal proteins can be directly related to the degree of malignancy, knowledge about these proteins will provide powerful tools to improve both cancer prognosis and treatment.

Abstract

Successful metastasis depends on cell invasion, migration, host immune escape, extravasation, and angiogenesis. The process of cell invasion and migration relies on the dynamic changes taking place in the cytoskeletal components; actin, tubulin and intermediate filaments. This is possible due to the plasticity of the cytoskeleton and coordinated action of all the three, is crucial for the process of metastasis from the primary site. Changes in cellular architecture by internal clues will affect the cell functions leading to the formation of different protrusions like lamellipodia, filopodia, and invadopodia that help in cell migration eventually leading to metastasis, which is life threatening than the formation of neoplasms. Understanding the signaling mechanisms involved, will give a better insight of the changes during metastasis, which will eventually help targeting proteins for treatment resulting in reduced mortality and longer survival.

Proteomic analysis of male rat nucleus accumbens, dorsal hippocampus and amygdala on conditioned place aversion induced by morphine withdrawal

Addiction is characterized by compulsive drug seeking and taking behavior, which is thought to result from persistent neuroadaptations, encoded by changes of gene expression. We previously demonstrated that the changes in synaptic plasticity were required for the formation of aversive memories associated with morphine withdrawal. However, the proteins involved in synaptic plasticity and aversive memory formation have not been well explored. In the present study, we employed a two-dimensional gel electrophoresis (2-DE)-based proteomic technique to detect the changes of protein expression in the nucleus accumbens, amygdala and dorsal hippocampus of the rats that had developed conditioned morphine withdrawal. We found that twenty-three proteins were significantly altered in the amygdala and dorsal hippocampus after conditioned morphine withdrawal. These proteins can be classified into multiple categories, such as energy metabolism, signal transduction, synaptic transmission, cytoskeletal proteins, chaperones, and protein metabolism according to their biological functions. Eight proteins related to synaptic plasticity were further confirmed by western blot analysis. It is very likely that these identified proteins may contribute to conditioned morphine withdrawal-induced neural plasticity and aversive memory formation. Thus, our work will help understand the potential mechanism associated with generation of drug withdrawal memories.

Computational Modeling of Realistic Cell Membranes

Cell membranes contain a large variety of lipid types and are crowded with proteins, endowing them with the plasticity needed to fulfill their key roles in cell functioning. The compositional complexity of cellular membranes gives rise to a heterogeneous lateral organization, which is still poorly understood. Computational models, in particular molecular dynamics simulations and related techniques, have provided important insight into the organizational principles of cell membranes over the past decades. Now, we are witnessing a transition from simulations of simpler membrane models to multicomponent systems, culminating in realistic models of an increasing variety of cell types and organelles. Here, we review the state of the art in the field of realistic membrane simulations and discuss the current limitations and challenges ahead.

Multiscale Simulations of Biological Membranes: The Challenge To Understand Biological Phenomena in a Living Substance

Biological membranes are tricky to investigate. They are complex in terms of molecular composition and structure, functional over a wide range of time scales, and characterized by nonequilibrium conditions. Because of all of these features, simulations are a great technique to study biomembrane behavior. A significant part of the functional processes in biological membranes takes place at the molecular level; thus computer simulations are the method of choice to explore how their properties emerge from specific molecular features and how the interplay among the numerous molecules gives rise to function over spatial and time scales larger than the molecular ones. In this review, we focus on this broad theme. We discuss the current state-of-the-art of biomembrane simulations that, until now, have largely focused on a rather narrow picture of the complexity of the membranes. Given this, we also discuss the challenges that we should unravel in the foreseeable future. Numerous features such as the actin-cytoskeleton network, the glycocalyx network, and nonequilibrium transport under ATP-driven conditions have so far received very little attention; however, the potential of simulations to solve them would be exceptionally high. A major milestone for this research would be that one day we could say that computer simulations genuinely research biological membranes, not just lipid bilayers.