Biophysical Journal

The plasma membrane is a laterally heterogeneous environment in which lipid organization plays a central role in regulating protein function. In model systems, this heterogeneity is often described in terms of coexisting liquid-ordered (Lo) and liquid-disordered (Ld) phases, commonly associated with the lipid raft concept. Despite extensive experimental and computational efforts, the molecular determinants governing protein partitioning between these domains remain poorly understood, largely due to the limited number of systems studied. Here, we address this challenge using a high-throughput computational approach, systematically analyzing the partitioning behavior of almost 5,000 helical transmembrane peptides in phase-separating lipid membranes. Across all simulations, we find that none of the peptides exhibit a clear preference for the Lo phase, while the vast majority partition into the Ld phase. This observation is consistent with experimental results in simplified membrane systems and suggests that commonly used ternary lipid mixtures may not fully capture the physicochemical environment governing protein sorting in biological membranes. In addition, we identify a subset of peptides that preferentially localize at the Lo/Ld interface. These interfacial peptides display distinct sequence characteristics, indicating that boundary localization is governed by specific combinations of residue composition and spatial arrangement rather than a single dominant feature. Overall, our results reveal that transmembrane helix partitioning in model membranes is dominated by a preference for disordered environments, with interfacial localization emerging as a distinct and potentially functional behavior.

Although organelles are often studied one at a time, whole-cell imaging studies show that organelles take up a large part of the cell volume such that they are crowded together. Here we use whole cell soft X-ray tomography imaging to investigate how such crowding affects organelle size scaling, position, and shape, focusing on the nucleus and vacuole of budding yeast. We find that as the vacuole becomes larger, the nucleus loses its normal scaling relation with respect to cell volume, becomes displaced from its normal position near the cell center, and becomes progressively deformed from a sphere into a pancake shape. Using a whole-cell integrated modeling framework, we find that these changes are statistically correlated and give rise to distinct modes in cell organization space. Using a simplified mechanical model for two initially spherical compartments contained inside a confined intracellular space, we are able to recapitulate the effects seen in the experimental data, indicating that these observations are consistent with a purely mechanical interaction. Taken together, our work indicates that, in addition to the well-known protein-based organelle-organelle interactions, physical steric packing of organelles inside a limited cellular volume also plays a large role in the inter-organelle relationships and the overall geometry of the cell.

A major challenge in neuroscience is to predict how currents in nanodomains affect voltage and ionic concentrations. Cable and Rall theory provide analytic current-voltage relations by neglecting concentration gradients, and the impact of concentration gradients is usually studied numerically with the Poisson-Nernst-Planck (PNP) model. A precise quantitative understanding of the combined dynamics remains limited because analytic current-voltage-concentration relations are missing. In this work we derive such relations using a novel approach based on cross-diffusion equations. For narrow cylindrical domains, we derive time-dependent and steady-state expressions that explicitly show how currents affect voltage and ionic concentrations. We find that the influx of only one ion can significantly change the concentrations of all the other ions even if no channels for these ions are present. After a current injection we compute a biphasic voltage transient where the small-time asymptotic corresponds to the steady-state solution of the cable equation. We show that the accuracy of cable theory prediction for the voltage depends on how the current is distributed among the various ions. Finally, we develop an iterative method to accurately compute steady-state profiles for voltage and concentrations using first-order results by subdividing a cylinder into small segments.

Following ER Ca2+ depletion, Ca2+ release-activated Ca2+ (CRAC) channels are activated by STIM1 at ER-plasma membrane junctions. The restricted localization and low conductance of the CRAC channel (<40 fS) precludes single-channel recordings, limiting studies of CRAC channel gating. Here we describe an optical approach to characterize the gating of HaloTag-fused Orai1 channels labeled with JF646-BAPTA, a Ca2+-sensitive fluorescent dye. While Ca2+ influx through single channels generates fluorescence fluctuations, identifying true gating events is complicated by stochastic transitions of JF646-BAPTA to a non-fluorescent state. To overcome this, we combine TIRF microscopy with whole-cell voltage clamp to control the driving force for Ca2+ entry. We show the open channel intensity at -100 mV reflects Ca2+ saturation of the dyes on each channel, while the closed-channel intensity is defined by the fluorescence at +30 mV, where influx is absent. True gating events can be identified from transitions between the open- and closed-channel levels, distinguishing them from transitions to a non-fluorescent state. We describe the gating behavior of CRAC channels activated by STIM1 after store depletion. Dwell time distributions indicate at least two open and closed states with durations of 0.1 to several seconds, with most channels having an open probability of [&ge;]0.7. We also detect silent channels that colocalize with STIM1 but show no activity over tens of seconds, a population that would be undetectable by whole-cell electrophysiology alone. This method offers an approach to explore CRAC channel gating mechanisms and may be applicable to other Ca2+- permeable channels not amenable to patch-clamp techniques.

Actin-bundle organization is essential for vascular smooth muscle cell mechanics and is implicated in actin-related diseases. However, it remains unclear how cell stretching affects intracellular actin bundles when actin polymerization is impaired. Here, we performed live imaging of Latrunculin A-treated A7r5 vascular smooth muscle cells in a stretch chamber. GFP--actinin imaging showed that Latrunculin A reduced actin-bundle coverage while periodicity was maintained. Subsequent mechanical stretch disrupted both actin-bundle coverage and periodicity. We constructed a stochastic filament bundle model in which actin filament length, actin crosslinking protein dynamics, external stretch, and myosin-driven contractile shortening determine bundle connectivity. The model generated non-spanning, collapse, and persistent states based on spanning connectivity before and after stretch, shaped by filament length and applied strain. A reduced model further showed that these states are governed by a balance between connectivity formation and stretch-induced loss. Together, our results suggest that reduced actin polymerization destabilizes intracellular actin-bundle organization under mechanical stretch, providing a mechanism linking actin polymerization defects to mechanical fragility in vascular smooth muscle cells.

Genomic organization within the nucleus is crucial for gene regulation and cell health, as disruptions in this organization are linked to genetic disorders and cancers. Recent studies suggest that molecular-scale organization of chromatin near the nuclear periphery (lamina-associated domains, LADs) affects gene regulation, providing transciptional supression, but the biophysical mechanisms of supression behind remain unclear. LADs are large heterochromatic regions near the nuclear lamina, where transcriptional factors and RNA polymerase are scarce, implying a nonspecific filtering property. Here, we investigate the steric filtering capabilities of LADs by performing coarse-grained polymer simulations. Our results show that LAD thickness can be affected by the interaction between chromatin and nuclear periphery as well as chromatin self-compaction. Regardless, the LAD layer acts as a size-selective steric partitioning environment for protein particles limiting their access to nuclear periphery. Notably, increasing bulk protein levels enhances protein access linearly. These results align with experimental observations and suggest that LADs could control the presence of transcription machinery on the periphery of the nucleus, providing a polymer-physical mechanism for gene regulation in nuclei.

GFAP is a type III intermediate filament primarily found within astrocytes and is known to maintain proper cell structure and mechanical strength. Mutations in GFAP are implicated in the pathology of Alexander disease, a neurodegenerative disease characterized by cytoplasmic inclusions of protein, known as Rosenthal fibers. GFAP has a typical type III intermediate filament domain structure, consisting of a highly conserved alpha-helical rod domain bracketed by an intrinsically disordered N-terminal head and C-terminal tail domains. While the general domain organization of monomeric GFAP and the assembly process for higher order quaternary structures are known, we lack an atomic resolution mechanistic understanding of GFAP assembly into mature filaments. Understanding the structure of GFAP filaments and how mutations disrupt this structure will provide vital information into how mutations produce Alexander disease pathology. As a first step towards a mechanistic description, we characterized GFAP wild type tetrameric and filamentous assemblies using solid state NMR and compared the results to those obtained from an assembly-deficient GFAP mutant. For wild-type GFAP, we observe surprisingly uniform rigid alpha helical structure and can spectroscopically resolve highly mobile intrinsically disordered regions in the filament assemblies. Wild type tetramers show increased mobility, likely arising from the head and tail domains. Mutation of the highly conserved cysteine at position 294 to serine results in an inability to form full-length filament assemblies. We show that the rigid regions of the C294S mutant assemblies largely remain structurally consistent with wild type tetrameric assemblies but differ from wild-type filament assemblies. There is an increase in highly mobile regions for the C294S mutant relative to the wild-type. Our results provide a foundation for developing solid state NMR approaches to characterize intermediate filament assembly mechanisms and the interfering effect of disease mutations.

The patch-clamp experimental technique is widely used to study the electrical properties of ion channels in biological and artificial lipid membranes. The key to the high quality of the experiments is the manufacturing of glass pipettes that provide highly electrically resistant contact between the edge of the pipette tip and the lipid bilayer. Preparation of the pipettes is particularly challenging for studies of the mitochondrial membranes due to the need for very small pipette tip sizes. Here, we present a robust procedure for producing pipettes suitable for experiments with native mitochondrial membranes. This procedure involves a two-step approach: initial fabrication of relatively large glass micropipettes using a standard micropipette puller, followed by tip refinement using a microforger to achieve smooth glass surface and reduced opening size. Pipette tip diameters and surface structure were examined using field emission - scanning electron microscopy (FE-SEM) imaging to assess the effects of variable parameters on pipette geometry and size. The resulting pipettes were validated in patch-clamp recording of the mitochondrial inner membranes. This approach enables the reproducible production of optimized pipettes for mitochondrial patch-clamp experiments, improving the quality and throughput of electrophysiological recordings of the mitochondrial ion channels.

Frustrated phagocytosis occurs when phagocytes fail to fully engulf large targets, yet the geometric origins of this physical limit remain poorly defined. Here we present a geometric model that identifies the cell nucleus as an intracellular constraint on engulfment. Extending membrane-limited frameworks, we distinguish an intrinsic phagocytic capacity set by membrane availability from an apparent capacity reduced by nuclear exclusion. Using minimal geometric assumptions, we derive closed-form expressions linking experimentally measurable parameters, including target coverage, volume ratio, and size, to phagocytic capacity and a normalized axial separation that quantifies nuclear accommodation. The model predicts a size- and curvature-independent geometric criterion for nuclear involvement applicable to both spherical and planar targets. These results establish nuclear geometry as a fundamental physical bottleneck in phagocytosis and provide a quantitative framework for interpreting stalled engulfment and nuclear deformation-dependent responses.

Membrane association is governed by the thermodynamics of amino acid partitioning between water and the lipid bilayer. Here, we quantified amino acid side-chain insertion energetics in a 1-palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine (POPC) bilayer using unbiased molecular dynamics simulations. Equilibrium depth distributions of 28 analogs, including multiple protonation states, were converted into potentials of mean force (PMFs) by Boltzmann inversion. The resulting PMFs reproduced the main features of bilayer partitioning. Hydrophobic analogs favored the bilayer core, aromatic analogs were stabilized in interfacial regions, and polar or charged analogs remained unfavorable in the hydrophobic interior. A diglycine analog representing the peptide backbone behaved similarly to uncharged polar residues. Depth-dependent pKa profiles and orientational analyses further showed how protonation equilibria and aromatic-ring alignment influence insertion energetics. Agreement with experimental hydrophobicity scales supports the robustness of the approach. These results provide an efficient and internally consistent framework for characterizing bilayer insertion energetics and establish a reference for future studies in more complex lipid environments. O_FIG O_LINKSMALLFIG WIDTH=198 HEIGHT=200 SRC="FIGDIR/small/723583v1_ufig1.gif" ALT="Figure 1"> View larger version (79K): org.highwire.dtl.DTLVardef@127b12org.highwire.dtl.DTLVardef@14de924org.highwire.dtl.DTLVardef@53b27org.highwire.dtl.DTLVardef@16e8ee4_HPS_FORMAT_FIGEXP M_FIG C_FIG SIGNIFICANCEMembrane-associated proteins represent a large fraction of the proteome and include many major drug targets, yet quantitative understanding of their interactions with lipid bilayers remains limited. Here, we present an unbiased molecular dynamics framework for systematically determining amino acid side-chain insertion free energies in a model bilayer. By deriving potentials of mean force directly from equilibrium depth distributions, this approach enables internally consistent comparisons across residue classes and protonation states without biasing restraints. The resulting free-energy profiles reproduce established hydrophobicity trends and show how protonation equilibria and aromatic-ring orientation modulate bilayer partitioning. This scalable strategy provides a quantitative reference for residue-level membrane thermodynamics and establishes a foundation for extending insertion energetics to more diverse lipid compositions and more complex membrane-associated systems.

The molten globule (MG) state is an intermediate in the unfolding pathway of proteins, typically triggered by denaturing agents such as urea, extreme pH, high pressure, or heat. The microscopic details of such states are far from understood. Here we study the MG states in protein Hen Egg-White Lysozyme (PDB ID: 1AKI) using microscopic constant pH molecular dynamics (CpHMD) simulations and experiments across a wide pH range. We observe that the titratable residues act as key drivers of conformational fluctuations, promoting the emergence of MG states at extreme pH. These states display partial unfolding, and small global structural changes (< 7% deviation). Hydration around the fluctuating acidic residues shows reduced water density and weakened hydrogen bonding at low pH. At high pH, hydration around acidic residues increases relative to pH = 7, whereas hydration around basic residues decreases. The translational and rotational dynamics of hydration water also exhibit pronounced pH dependence: the translational diffusion coefficient (Dtrans) increases linearly with decrease in pH in acidic medium and increases linearly with increasing pH in the basic regime. The rotational diffusion (Drot) shows similar dependencies on pH except a break at pH {approx} 4 corresponding to acidic residue pKa values. Our results may be useful to identify ligand binding of lysozyme in extreme pH conditions.

Time-resolved measurements are central to calibrating mechanistic dynamical models, but current inference frameworks typically assume that reported measurement times are exact. In practice, actual sampling times may deviate from reported times because of sample-handling delays, imper-fect synchronization, or reporting errors. Here, we present a Bayesian framework for parameter inference in ordinary differential equation models that explicitly accounts for uncertainty in measurement times. We formulate latent measurement times as random variables and derive a joint and marginalized posterior. To compute the marginal likelihood efficiently, we augment the original dynamical system with additional state variables that evaluate the required integrals during numerical simulation. This reduces the dimensionality of the estimation problems and allows for efficient and reliable Markov chain Monte Carlo sampling. Across synthetic examples and a published model of carotenoid cleavage in Arabidopsis thaliana, neglecting time uncertainty led to biased estimates and overconfident uncertainty quantification, whereas the proposed marginalized formulation recovered reliable parameter estimates while substantially improving sampling efficiency and scalability. These results identify measurement time uncertainty as an important source of variability in dynamic modeling and establish posterior marginalization as a practical strategy for robust mechanistic inference.

Myosin 3A (MYO3A) is an unconventional myosin involved in the formation and maintenance of hair-cell stereocilia of the sensory epithelia in the inner ear. The kinase domain has been implicated in phosphoregulation of MYO3A activity through intermolecular autophosphorylation. Previous studies using mass spectrometry identified two potential phosphorylation sites in the motor domain. To investigate the regulatory roles of these sites, we generated glutamic acid point mutations in our mchr-MYO3A{Delta}K construct to mimic phosphorylation and assayed the constructs for their ability to tip-localize and influence filopodial density via transfection into COS7 cells. The phosphomimic constructs were less able to generate filopodia when compared to wildtype constructs. To gain a better understanding of the phosphoregulation of MYO3A, we transfected COS7 cells with mchr-MYO3A{Delta}K in combination with GFP-tagged full-length MYO3A (GFP-MYO3AFL), or GFP attached to just the kinase domain of MYO3A (GFP-MYO3AKIN). Coexpression of mchr-MYO3A{Delta}K with either construct resulted in decreased mchr-MYO3A levels at the tips of filopodia and fewer filopodia at the edge of the cell, compared to cells expressing mchr-MYO3A{Delta}K alone. This implies that the kinase domain does not require motor activity to contribute to phosphoregulation of MYO3A, and that MYO3A phosphoregulation may be influencing filopodia initiation. Informatic analyses and structural predictions suggest that the two phosphorylation sites in the motor domain inhibit actin/MYO3A interactions. Taken together, these analyses link MYO3A phosphorylation with the regulation of its ability to create actin protrusions such as filopodia and stereocilia.

Cell migration is fundamental to various biological processes, including morphogenesis, wound healing, and cancer metastasis. Durotaxis--directed migration of cells in response to spatial variations in stiffness--has been extensively studied using engineered substrates with prescribed stiffness. However, recent work has increasingly shifted toward understanding cell migration in fibrous matrices that can be actively remodeled by the actomyosin contractility, as commonly observed in tumor and epithelial cells. Despite these advances, a theoretical framework explaining how cells structurally remodel their surrounding matrix to promote their own durotaxis, and which cellular forces govern this behavior, remains elusive. To address this gap, we developed a biomechanical model in which polarized cells contract and migrate over a fibrous matrix. Using this model, we first confirmed that cells on an externally strained matrix preferentially migrate along the direction of applied strain. Then, we investigated how cells autonomously remodel the matrix to create stiffness patterns favorable for durotaxis. In the presence of intercellular adhesion, cells acted collectively to stiffen the matrix, after which a small subset of cells escaped the main population and migrated outward. This behavior is reminiscent of intravasation during cancer metastasis, where cohesive cell clusters generate local matrix remodeling that facilitates the departure of more motile subpopulations. These results illustrate how matrix stiffening driven by cell cohesion and contractility regulates durotactic behavior and provide mechanistic insight into collective invasion processes relevant to cancer metastasis.

Cell migration plays a central role in numerous physiological and pathological processes and emerges from the coordinated interplay between intracellular force generation, adhesion dynamics, and mechanical interactions with the environment. A minimal, mechanistically grounded understanding of these processes is required to disentangle the respective contributions of cell-intrinsic and environmental cues. Here, a two-dimensional in silico cell motility model is introduced to describe mesenchymal migration driven by intracellular traction forces generated within actin-rich protrusions anchored to a substrate. The model explicitly accounts for adhesion nucleation, maturation, force buildup and rupture, and relies on a small set of physically interpretable parameters. A systematic mechanical analysis identifies parameter regimes that permit effective cell translocation and delineates conditions leading to stalled or mobile cells. Within motile regimes, the model reproduces a broad spectrum of cell morphologies and migratory behaviours. In particular, cell trajectories exhibit the statistical features of a persistent random walk, with a crossover from ballistic to diffusive motion that arises solely from adhesion dynamics and force balance, without imposing polarization or directional bias. Cell morphology is shown to strongly regulate migration speed, persistence, and pausing behaviour. Altogether, this model provides a minimal reference framework for cell migration on non-deformable substrates and establishes a baseline for future studies of mechanically driven guidance. By construction, it is well suited for extension to deformable fibrous substrates, where cell-induced matrix remodeling and stiffness feedback are expected to bias migration and regulate cell encounters relevant to tissue morphogenesis and anastomosis.

The Tar-DNA Binding Protein-43 C-terminal region, TDP43LC, has been previously shown to form amyloid-like fibrils with distinct folds in ALS and FTD. In both diseases, proteinaceous inclusions contain TDP43 C-terminal protein fragments as well as phosphorylated TDP43. Here, we use solution NMR to show that soluble phosphomimetic TDP43LC, P-TDP43LC, is structurally similar to wild-type TDP43LC. Disperse P-TDP43LC, like wild-type protein, contains a central helical region flanked by long disordered regions. Despite this similarity, our turbidity measurements, imaging, and kinetic assays show that P-TDP43LC has different aggregation behavior than wild-type protein. Using solid state NMR measurements we find that that phosphomimetic mutations alter the wild-type fibril conformation. Electrostatic repulsion from negatively charged sidechains, despite having little effect on the soluble proteins structure, perturbs amyloid-like fibril formation and selects for a different conformation in vitro. These results shed light on the structural role of TDP43LC phosphorylation in fibril formation in disease. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/725298v1_ufig1.gif" ALT="Figure 1"> View larger version (16K): org.highwire.dtl.DTLVardef@1c63aforg.highwire.dtl.DTLVardef@1d48ed6org.highwire.dtl.DTLVardef@1ed8fd3org.highwire.dtl.DTLVardef@17d67a8_HPS_FORMAT_FIGEXP M_FIG C_FIG SynopsisPhosphomimetic mutations at ALS and FTD neurodegeneration-associated sites in an amyloid forming protein perturbs the aggregated structure compared to wild-type protein.

The Poisson-Nernst-Planck (PNP) system is an accurate model of electrodiffusion of ionic species. It is commonly used in situations where nanoscale resolution is required, for instance close to ion channels in the membranes of biological cells. The inherent stiffness of the equations has made them challenging to solve and has limited the applicability of the system. In particular, the time step required for stable solutions has typically needed to be very short (nanoseconds), which makes simulations on the time scale of an action potential (milliseconds) difficult. Recently, it has been observed that avoiding operator splitting and instead solving the concentration equations and the electrostatic equation in a coupled manner relaxes the time-step limitation considerably. However, no theoretical explanation of this observation has been provided. Here, we aim to explain why the coupled scheme allows much larger time steps. We illustrate the mechanism by considering special cases that define necessary, but not sufficient, conditions for stability. We also show that these conditions remain relevant for the fully coupled PNP model in 3D.

Embryonically, the vertebrate brain begins as an approximately uniform, fluid-filled epithelial tube that undergoes rapid volumetric expansion and regionalization to form the morphologically distinct primary brain vesicles. Hydrostatic pressure from fluid secretion into the inner lumen generates tension in the neural tube that has been implicated as a potential driver of cell proliferation during these early stages of brain development. However, a quantitatively rigorous view of 3D morphology and cellular proliferation has remained elusive. Here, we provide a standardized mapping for the mechanical and biological landscape of the developing neuroepithelium along anatomical axes. Using this 3D morphometric framework in chicken embryos, we show that localized curvature characterizes compartmental boundaries. While rapid inflation would typically be expected to stretch and thin the epithelium, we find the opposite: global expansion is coupled with significant tissue thickening, identifying the early brain as an active shell. Moreover, spatial patterns of thickness remain invariant to local curvature. Our results demonstrate a decoupling of geometry and growth, showing that spatially stable distributions of tissue thickness and mitotic activity are maintained throughout massive volumetric expansion, independent of the dramatic geometric reorganization driven by luminal pressure. We conclude that, while tension in the neuroepithelium may contribute to proliferative growth at some level, biological pre-pattern likely plays a driving role in the regionalized expansion of the early embryonic brain. Why it mattersThe embryonic brain begins as a simple fluid-filled tube that undergoes rapid and heterogeneous expansion to set up the basic organizational plan of the adult brain. Errors in this process are linked to severe neurological and congenital disorders. This work investigates the biophysical basis of expansion and regionalization of the early brain, a complex three-dimensional process driven by inflation from internal fluid pressure together with active cell behaviors that ultimately produce regionally distinct growth and curvature profiles amid a complex mechanical landscape. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/726048v1_ufig1.gif" ALT="Figure 1"> View larger version (49K): org.highwire.dtl.DTLVardef@17c442forg.highwire.dtl.DTLVardef@1609374org.highwire.dtl.DTLVardef@170c00corg.highwire.dtl.DTLVardef@15080ad_HPS_FORMAT_FIGEXP M_FIG C_FIG

Mechanical properties of epithelial tissues play essential roles in morphogenesis and physiological function. In this study, we analytically derived the in-plane bulk modulus, shear modulus, and Poissons ratio of a three-dimensional cell vertex model of epithelial monolayers. We showed that the model can robustly reproduce a near-zero in-plane Poissons ratio, a mechanical feature reported in cultured epithelial tissues. Numerical simulations further confirmed that the theoretically predicted Poissons ratio accurately describes the response of the model under finite, biologically relevant strains. In addition, the model exhibits not only morphological bistability between squamous-like and columnar-like states, but also mechanical bistability characterized by distinct elastic responses. Together, these results provide a minimal three-dimensional framework that links cell-scale mechanical interactions and epithelial morphology to tissue-scale elastic properties.

-Synuclein (Syn) is an intrinsically disordered protein whose interactions with lipid membranes are central to both its physiological function and its role in synucleopathies. While membrane charge, phase, and curvature are each known to influence Syn binding, these properties are typically examined independently, leaving their combined effects on both equilibrium and dynamic membrane association unresolved. Here, we systematically investigate how membrane phase and charge jointly regulate Syn binding, curvature sensitivity, and exchange dynamics using fluorescence microscopy, circular dichroism spectroscopy, and fluorescence recovery after photobleaching (FRAP), complemented by coarse-grained molecular dynamics simulations. Under zwitterionic conditions, Syn preferentially binds highly curved gel-phase membranes, driven by curvature-dependent enrichment of packing defects arising from faceted vesicle morphologies. Incorporation of anionic lipids selectively enhances binding in liquid-phase membranes while attenuating curvature-dependent partitioning in gel-phase membranes. Dynamic measurements reveal that membrane phase and charge also govern the stability of membrane-associated Syn, with gel-phase membranes and anionic lipids promoting kinetically stabilized states. Simulations show that curvature-induced defect formation is strongly amplified in gel-phase membranes but largely insensitive to charge. These findings establish that Syn-membrane interactions are governed by a cooperative interplay between membrane phase, curvature, and charge and highlight the importance of resolving both thermodynamic and kinetic contributions to protein-membrane binding.