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bioRxiv2022

Cryo-EM structure of an atypical proton-coupled peptide transporter: Di- and tripeptide permease C

Proton-coupled Oligopeptide Transporters (POTs) of the Major Facilitator Superfamily (MFS) mediate the uptake of short di- and tripeptides in all phyla of life. POTs are thought to constitute the most promiscuous class of MFS transporters, with the potential to transport more than 8400 unique substrates. Over the past two decades, transport assays and biophysical studies have shown that various orthologues and paralogues display differences in substrate selectivity. The E. coli genome codes for four different POTs, known as Di- and Tripeptide permeases A-D (DtpA-D). DtpC was shown previously to favor positively charged peptides as substrates. In this study, we describe, how we determined the structure of the 53 kDa DtpC by cryogenic electron microscopy (cryo-EM), and provide structural insights into the ligand specificity of this atypical POT. We collected and analyzed data on the transporter fused to split superfolder GFP (split sfGFP), in complex with a 52 kDa macrobody and with a 13 kDa nanobody. The latter sample was more stable, rigid and a significant fraction dimeric, allowing us to reconstruct a 3D volume of DtpC at a resolution of 2.7 [A]. This work provides a molecular explanation for the selectivity of DtpC, and highlights the value of small and rigid fiducial markers such as nanobodies for structure determination of low molecular weight integral membrane proteins lacking soluble domains.

biophysics↗

bioRxiv2022

Individual activator and repressor transcription factors induce global changes in chromatin mobility

The control of eukaryotic gene expression is intimately connected to highly dynamic chromatin structures. Gene regulation relies on activator and repressor transcription factors (TFs) that induce local chromatin opening and closing. However, it is unclear how nucleus-wide chromatin organization responds dynamically to the activity of specific TFs. Here we examined how two TFs with opposite effects on local chromatin accessibility modulate chromatin dynamics nucleus-wide. We combine High-resolution Diffusion mapping (Hi-D) and Dense Flow reConstruction and Correlation (DFCC) in living cells to obtain an imaging-based, nanometer-scale analysis of local diffusion processes and long-range coordinated movements of both chromatin and TFs. We show that the expression of either an individual transcriptional activator (CDX2) or repressor (SIX6) increases local chromatin mobility nucleus-wide, yet induces opposite coherent chromatin motions at the micron scale. Hi-C analysis of higher-order chromatin structures shows that induction of CDX2 leads to changes in local chromatin interactions and compartmentalization. These results thus document a close relation between chromatin dynamics on the microscale and changes in compartmental structures. Given that inhibition of transcription initiation and elongation by RNA Pol II have almost no impact on the global chromatin dynamics induced by CDX2, we suggest that CDX2 alters chromatin structures independently from transcription. Our biophysical analysis shows that sequence-specific TFs mobilize long-range chromatin structure on multiple levels, providing evidence that local chromatin changes brought about by TFs can alter both the dynamics and the long-range organization of chromatin in living cells. Significance statementIn eukaryotes, DNA is embedded into a higher-order structure called chromatin that varies between a closed state that is inaccessible to DNA-binding proteins, and an open state that allows the assembly of the transcriptional machinery on DNA. The state of chromatin is dynamic and locally controlled by sequence-specific transcription factors (TFs). How local chromatin opening and closing initiated by TFs alter long-range dynamics of chromatin structures is unknown. Here we combine two nucleus-wide live-imaging techniques, Hi-D and DFCC, along with Hi-C (genomic analysis technique) to quantify both local and global chromatin dynamics, then to correlate these dynamics to structural changes. Our quantitative analysis reveals a differential impact of TFs in shaping and mobilizing long-range chromatin structures in living cells.

biophysics↗

bioRxiv2022

Origin of Protein Quake: Energy Waves Conducted by a Precise Mechanical Machine

A long-standing challenge in protein biophysics is to understand protein quake in myoglobin--the structural dynamics responsible for redistributing the excess heme energy after photolysis. Despite extensive efforts, the molecular mechanism of this process remains elusive. Using the energy flow theory, we uncovered a fundamental new phenomenon: the heme energy is redistributed by energy waves with a ubiquitous fundamental frequency and two overtones. Energy waves emanate from the heme into the myoglobin backbone via a conduit of five consecutive dihedrals of the proximal histidine, then travel quickly along the backbone to reach sidechains across the protein. This mechanism is far more effective than the diffusion-based mechanism from previous studies because waves are systematic while diffusion is random. To propagate energy waves, coordinates must cooperate, resulting in collective modes that are singular vectors of the generalized work functional. These modes show task partitioning: a handful of high-energy modes generate large-scale breathing motion, which loosens up the protein matrix to enable hundreds of low-energy vibrational modes for energy transduction.

biophysics↗

bioRxiv2022

Prediction of allosterically acting mutations using MD simulations and Rosetta

Computationally modeling how mutations affect protein-protein binding not only helps uncover the biophysics of protein interfaces, but also enables the redesign and optimization of protein interactions. Traditional high-throughput methods for estimating binding free energy changes are currently limited to mutations directly at the interface due to difficulties in accurately modeling how long-distance mutations propagate their effects through the protein structure. However, the modeling and design of such mutations is of substantial interest as it allows for greater control and flexibility in protein design applications. We have developed a method that combines high-throughput Rosetta-based side-chain optimization with conformational sampling using classical molecular dynamics simulations, finding significant improvements in our ability to accurately predict long-distance mutational perturbations to protein binding. Our approach uses an analytical framework grounded in alchemical free energy calculations while enabling exploration of a vastly larger sequence space. When comparing to experimental data, we find that our method can predict internal long-distance mutational perturbations with a level of accuracy similar to that of traditional methods in predicting the effects of mutations at the protein-protein interface. This work represents a new and generalizable approach to optimize protein free energy landscapes for desired biological functions. Author SummaryProtein-protein interactions are vital to almost all biological processes, and therefore the ability to accurately and efficiently predict how mutations alter protein binding has far-reaching applications in protein analysis and design. Current approaches to predict such mutational free energy changes are limited to mutations directly at the interaction interface. Much research has underlined the prevalence of allosteric protein regulation in biological processes, indicating the importance of understanding and predicting the effects of protein perturbations which act over long distances. In this work we develop a novel method based on molecular dynamics simulations, the Rosetta macromolecular modeling suite, and an analytical framework from alchemical free energy calculations which can predict the effects of long-distance mutations with levels of accuracy rivaling state of the art interface-specific methods. We hope that our method will serve as a novel framework for high throughput mutational analysis and therefore benefit future protein design efforts.

biophysics↗

bioRxiv2022

Detergent headgroups control TolC folding in vitro

TolC is the trimeric outer membrane component of the efflux pump system in E. coli responsible for antibiotic efflux from bacterial cells. Over-expression of efflux pumps has been reported to decrease susceptibility to antibiotics in a variety of bacterial pathogens. Reliable production of membrane proteins allows for the biophysical and structural characterization needed to better understand efflux and for the development of therapeutics. Preparation of recombinant protein for biochemical/structural studies often involves the production of proteins as inclusion body aggregates from which bioactive proteins are recovered. Here we find that the in vitro folding of TolC into its functional trimeric state from inclusion bodies is dependent on the headgroup composition of detergent micelles used. Nonionic detergent favors the formation of functional trimeric TolC, whereas zwitterionic detergents induce the formation of a non-native trimeric TolC fold. We also find that nonionic detergents with shorter alkyl lengths facilitate TolC folding. It remains to be seen whether the charges in lipid headgroups have similar effects on membrane insertion and folding in biological systems.

biophysics↗

bioRxiv2022

Evolution avoids a pathological stabilizing interaction in the immune protein S100A9

Stability constrains evolution. While much is known about constraints on destabilizing mutations, less is known about the constraints on stabilizing mutations. We recently identified a mutation in the innate immune protein S100A9 that provides insight into such constraints. When introduced into human S100A9, M63F simultaneously increases the stability of the protein and disrupts its natural ability to activate Toll-like receptor 4. Using chemical denaturation, we found that M63F stabilizes a calcium-bound conformation of hS100A9. We then used NMR to solve the structure of the mutant protein, revealing that the mutation distorts the hydrophobic binding surface of hS100A9, explaining its deleterious effect on function. Hydrogen deuterium exchange (HDX) experiments revealed stabilization of the region around M63F in the structure, notably Phe37. In the structure of the M63F mutant, the Phe37 and Phe63 sidechains are in contact, plausibly forming an edge-face {nu}-stack. Mutating Phe37 to Leu abolished the stabilizing effect of M63F as probed by both chemical denaturation and HDX. It also restored the biological activity of S100A9 disrupted by M63F. These findings reveal that Phe63 creates a "molecular staple" with Phe37 that stabilizes a non-functional conformation of the protein, thus disrupting function. Using a bioinformatic analysis, we found that S100A9 proteins from different organisms rarely have Phe at both positions 37 and 63, suggesting that avoiding a pathological stabilizing interaction indeed constrains S100A9 evolution. This work highlights an important evolutionary constraint on stabilizing mutations: they must avoid inappropriately stabilizing non-functional protein conformations. SIGNIFICANCE STATEMENTProtein stability constrains protein evolution. While much is known about evolutionary constraints on destabilizing mutations, less is known about the constraints on stabilizing mutations. We recently found a mutation to an innate immune protein that increases its stability but disrupts its function. Here we show, through careful biophysical and functional studies, that this mutation stabilizes a nonfunctional form of the protein through a direct interaction with another amino acid. We find that specific amino acids can be tolerated at each of the interacting positions individually, but not at both simultaneously. This pattern has been conserved over millions of years of evolution. Our work highlights an underappreciated evolutionary constraint on stabilizing mutations: they must avoid inappropriately stabilizing non-functional protein conformations.

biophysics↗

bioRxiv2022

Single molecule microscopy to profile the effect of zinc status of transcription factor dynamics

Transcription factors (TFs) are DNA binding proteins that control the expression of genes. The regulation of transcription is a complex process that involves binding of TFs to specific sequences, recruitment of cofactors and chromatin remodelers, assembly of the pre-initiation complex and ultimately the recruitment of RNA polymerase II. Increasing evidence suggests that TFs are highly dynamic and interact only transiently with DNA. Single molecule microscopy techniques are powerful approaches for visualizing and tracking individual TF molecules as they diffuse in the nucleus and interact with DNA. In this work, we employ multifocus microscopy and highly inclined and laminated optical sheet microscopy to track TF dynamics in response to perturbations in labile zinc inside cells. We sought to define whether zinc-dependent TFs sense changes in the labile zinc pool by determining whether their dynamics and DNA binding can be modulated by zinc. While it is widely appreciated that TFs need zinc to bind DNA, whether zinc occupancy and hence TF function are sensitive to changes in cellular zinc remain open questions. We utilized fluorescently tagged versions of the glucocorticoid receptor (GR), with two C4 zinc finger domains, and CCCTC-binding factor (CTCF), with eleven C2H2 zinc finger domains. We found that the biophysical dynamics of both TFs are susceptible to changes in zinc, but in subtly different ways. These results indicate that at least some transcription factors are sensitive to zinc dynamics, revealing a potential new layer of transcriptional regulation.

biophysics↗

bioRxiv2022

The ClpP Peptidase Forcefully Grips Protein Substrates

ATPases Associated with diverse cellular Activities (AAA+) proteases power the maintenance of protein homeostasis by coupling ATP hydrolysis to mechanical protein unfolding, translocation, and ultimately degradation. Though ATPase activity drives a large portion of the mechanical work these molecular machines perform, how the peptidase contributes to the forceful denaturation and processive threading of substrates remains unknown. Here, using single-molecule optical trapping, we examine the mechanical activity of the Caseinolytic Peptidase P (ClpP) from Escherichia coli in the absence of a partner ATPase and in the presence of an activating small molecule acyldepsipeptide. We demonstrate that ClpP grips protein substrate under mechanical loads exceeding 40 pN, which are greater than those observed for the AAA+ unfoldase ClpX and the AAA+ protease complexes ClpXP and ClpAP. We further characterize substrate-ClpP bond lifetimes and rupture forces under varying loads. We find that the resulting slip bond behavior does not depend on ClpP peptidase activity. Additionally, we find that unloaded bond lifetimes between ClpP and protein substrate are on a timescale relevant to unfolding times (up to [~]160 s) for difficult to unfold model substrate proteins. These direct measurements of the substrate-peptidase bond under load define key properties required by AAA+ proteases to mechanically unfold and degrade protein substrates. STATEMENT OF SIGNIFICANCEEnergy-dependent proteases drive essential protein degradation to maintain cellular homeostasis and to rapidly regulate protein levels in response to changes in cellular environment. Using single-molecule optical tweezers, several studies demonstrate that the molecular process of degradation involves the mechanical unfolding and translocation of protein substrates by the ATP hydrolyzing enzyme component of these protease complexes. This study provides evidence that the chambered peptidase component of these molecular machines also contributes to the mechanical process of degradation by gripping substrate under load in a manner independent of peptide hydrolysis. Our results suggest that the peptidase actively contributes to the biophysical mechanisms underlying processive protein degradation by energy-dependent proteolytic machines.

biophysics↗

bioRxiv2022

Super-resolved imaging deciphers ligand dependent membrane behaviour of the onco-immunogenic CCR5 receptor.

The ability of tumors to establish a pro-tumorigenic microenvironment is becoming an important point of investigation in the search for new therapeutics. Tumors form microenvironments in part by the education of immune cells attracted via chemotactic axes such as that of CCR5-CCL5. Further, CCR5 upregulation by cancer cells, coupled with its association with pro-tumorigenic features such as drug-resistance and metastasis, has suggested CCR5 as a target for therapeutic inhibition. However, with several conformational "pools" being reported, phenotypic investigations must be capable of unveiling heterogeneity. Addressing this challenge, we performed structured illumination (SIM) and Partially TIRF coupled HILO (PaTCH) microscopy for super-resolution imaging and single-molecule imaging of CCR5 in fixed cells. Determining the positions of super-resolved CCR5 assemblies revealed a non-random spatial orientation. Further, intensity-tracking of assemblies revealed a distribution of molecular stoichiometries indicative of dimeric sub-units independent of CCL5 perturbation. These biophysical methods can provide important insights into the structure and function of onco-immunogenic receptors and a plethora of other biomolecules. HighlightsO_LIWe use SIM and novel PaTCH microscopy for precise bioimaging and single-molecule tracking of receptor protein CCR5 in model cell line C_LIO_LIBy tracking the position of CCR5 assemblies we conclude that they are clustered in the plasma membrane beyond a level expected from a random distribution C_LIO_LIWe use these high-precision data to determine molecular stoichiometries of CCR5 assemblies C_LI

biophysics↗

bioRxiv2022

Identification and Quantification of Within-Burst Dynamics in Singly-Labeled Single-Molecule Fluorescence Lifetime Experiments

Single-molecule spectroscopy has revolutionized molecular biophysics and provided means to probe how structural moieties within biomolecules spatially reorganize at different timescales. There are several single-molecule methodologies that probe local structural dynamics in the vicinity of a single dye-labeled residue, which rely on fluorescence lifetimes as readout. Nevertheless, an analytical framework to quantify dynamics in such single-molecule single-dye fluorescence bursts, at timescales of microseconds to milliseconds, has not yet been demonstrated. Here, we suggest an analytical framework for identifying and quantifying within-burst lifetime-based dynamics, such as conformational dynamics recorded in single-molecule photo-isomerization related fluorescence enhancement. After testing the capabilities of the analysis on simulations, we proceed to exhibit within-burst millisecond local structural dynamics in the unbound -synuclein monomer. The analytical framework provided in this work paves the way for extracting a full picture of the energy landscape for the coordinate probed by fluorescence-lifetime based single-molecule measurements.

biophysics↗

bioRxiv2022

TriMem: A Parallelized Hybrid Monte Carlo Software for Efficient Simulations of Lipid Membranes

Lipid membranes are integral building blocks of living cells and perform a multitude of biological functions. Currently, molecular simulations of cellular-scale membrane structures at atomic resolution are nearly impossible, due to their size, complexity, and the large times-scales required. Instead, elastic membrane models are used to simulate membrane topologies and transitions between them, and to infer their properties and functions. Unfortunately, efficiently parallelized open-source simulation code to do so has been lacking. Here, we present TriMem, a parallel hybrid Monte Carlo simulation engine for triangulated lipid membranes. The kernels are efficiently coded in C++ and wrapped with Python for ease-of-use. The parallel implementation of the energy and gradient calculations and of Monte Carlo flip moves of edges in the triangulated membrane enable us to simulate also large and highly curved sub-cellular structures. For validation, we reproduce phase diagrams of vesicles with varying surface-to-volume ratios and area difference. The software can tackle a range of membrane remodelling processes on sub-cellular and cellular scales. Additionally, extensive documentation make the software accessible to the broad biophysics and computational cell biology communities.

biophysics↗

bioRxiv2022

Long-term label-free assessments of individual bacteria using three-dimensional quantitative phase imaging and hydrogel-based immobilization

Three-dimensional (3D) quantitative phase imaging (QPI) enables long-term label-free tomographic imaging and quantitative analysis of live individual bacteria. However, the Brownian motion or motility of bacteria in a liquid medium produces motion artifacts during 3D measurements and hinders precise cell imaging and analysis. Meanwhile, existing cell immobilization methods produce noisy backgrounds and even alter cellular physiology. Here, we introduce a protocol that utilizes hydrogels for high-quality 3D QPI of live bacteria maintaining bacterial physiology. We demonstrate long-term high-resolution quantitative imaging and analysis of individual bacteria, including measuring the biophysical parameters of bacteria and responses to antibiotic treatments. O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

biophysics↗

bioRxiv2022

Multivalency, autoinhibition, and protein disorder in the regulation of interactions of dynein intermediate chain with dynactin and the nuclear distribution protein

Cytoplasmic dynein plays crucial roles in the intracellular transport of organelles and other cargoes. Central to dynein function is the intrinsically disordered N-terminal domain of dynein intermediate chain (IC), which binds the three dimeric dynein light chains at multivalent sites, and dynactin p150Glued and nuclear distribution protein (NudE) at overlapping sites. The disorder in IC has hindered cryo-electron microscopy and X-ray crystallography studies of its structure and interactions. Here we use a suite of biophysical methods to reveal how multivalent binding of the three light chains regulate IC interactions with p150Glued and NudE. Using the N-terminal domain or the full-length IC from Chaetomium thermophilum, a tractable species to interrogate IC interactions, we identify a significant reduction in ICs binding affinity for p150Glued and a loss of binding to NudE in contrast to the tight binding observed with small IC constructs. We attribute this difference to autoinhibition caused by strong long-range intramolecular interactions that cover ICs N-terminal single -helix, the site for p150Glued and NudE binding. Reconstitution of IC subcomplexes demonstrate that autoinhibition is differentially regulated by light chains binding underscoring their importance both in assembly and organization of IC, and in selection between multiple binding partners at the same site.

biophysics↗

bioRxiv2022

Emergent Actin Flows Explain Diverse Parasite Gliding Modes

During host infection, single-celled apicomplexan parasites like Plasmodium and Toxoplasma use a motility mechanism called gliding, which differs fundamentally from other known mechanisms of eukaryotic cell motility. Gliding is thought to be powered by a thin layer of flowing filamentous (F)-actin1- 3 sandwiched between the plasma membrane and a myosin-coated4,5 inner membrane complex. How this surface actin layer drives the diverse apicomplexan gliding modes observed experimentally - helical, circular, and twirling6,7, and patch8, pendulum9, or rolling2 - presents a rich biophysical puzzle. Here, we use single-molecule imaging to track individual actin filaments and myosin complexes in live Toxoplasma gondii. Based on these data, we hypothesize that F-actin flows arise by self-organization, rather than following a microtubule-based template as previously believed. We develop a continuum model of emergent F-actin flow within the unusual confines provided by parasite geometry. In the presence of F-actin turnover, our model predicts the emergence of a steady-state mode in which actin transport is largely rearward. Removing actin turnover leads to actin patches that recirculate up and down the cell, a "cyclosis" that we observe experimentally for drug-stabilized actin bundles in live parasites. These findings provide a mechanism by which actin turnover governs a transition between distinct self-organized F-actin states, whose properties can account for the diverse gliding modes known to occur. More broadly, we illustrate how different forms of gliding motility can emerge as an intrinsic consequence of the self-organizing properties of F-actin flow in a confined geometry.

biophysics↗

bioRxiv2022

Markov State Modelling Reveals Heterogeneous Drug-Inhibition Mechanism of Calmodulin

Calmodulin (CaM) is a calcium sensor which binds and regulates a wide range of target-proteins. This implicitly enables the concentration of calcium to influence many downstream physiological responses, including muscle contraction, learning and depression. The antipsychotic drug trifluoperazine (TFP) is a known CaM inhibitor. By binding to various sites, TFP prevents CaM from associating to target-proteins. However, the molecular and state-dependent mechanisms behind CaM inhibition by drugs such as TFP are largely unknown. Here, we build a Markov state model (MSM) from adaptively sampled molecular dynamics simulations and reveal the structural and dynamical features behind the inhibitory mechanism of TFP-binding to the C-terminal domain of CaM. We specifically identify three major TFP binding-modes from the MSM macrostates, and distinguish their effect on CaM conformation by using a systematic analysis protocol based on biophysical descriptors and tools from machine learning. The results show that depending on the binding orientation, TFP effectively stabilizes features of the calcium-unbound CaM, either affecting the CaM hydrophobic binding pocket, the calcium binding sites or the secondary structure content in the bound domain. The conclusions drawn from this work may in the future serve to formulate a complete model of pharmacological modulation of CaM, which furthers our understanding of how these drugs affect signaling pathways as well as associated diseases. Author summaryCalmodulin (CaM) is a calcium-sensing protein which makes other proteins dependent on the surrounding calcium concentration by binding to these proteins. Such protein-protein interactions with CaM are vital for calcium to control many physiological pathways within the cell. The antipsychotic drug trifluoperazine (TFP) inhibits CaMs ability to bind and regulate other proteins. Here, we use molecular dynamics simulations together with Markov state modeling and machine learning to understand the structural and dynamical features by which TFP bound to the one domain of CaM prevents association to other proteins. We find that TFP encourages CaM to adopt a conformation that is like the one stabilized in absence of calcium: depending on the binding orientation of TFP, the drug indeed either affects the CaM hydrophobic binding pocket, the calcium binding sites or the secondary structure content in the domain. Understanding TFP binding is a first step towards designing better drugs targeting CaM.

biophysics↗

bioRxiv2022

Beyond the circuit architecture: attractor dynamics reveals the mechanism of improved performance in decision-making and working memory

Understanding the underlying mechanisms of cognitive functions such as decision-making(DM) and working memory(WM) is always one of the most essential concerns in modern neuroscience.Recent experimental and modelling works suggest that decision-making is supported by the selective subnetwork of inhibitory neurons, rejecting the previously proposed circuit mechanisms assuming a single non-selective pool of inhibitory neurons. The mechanism underlying decision-making and working memory functions based on such circuit architecture is still unclear. Here we applied a general non-equilibrium landscape and flux approach to a biophysically based model that can perform the decision-making and working memory functions. The quantified attractor landscapes reveal that the accuracy in decision-making can be improved due to the stronger resting state in the circuit architecture with selective inhibition, while robustness of working memory against distractors is weakened, which implies a trade-off between DM and WM. We found that the presence of a ramping non-selective input during the delay period of the decision-making tasks can serve as a cost-effective mechanism of temporal gating of distractors. This temporal gating mechanism, combined with the selective-inhibition circuit architecture, can support a dynamical modulation for emphasizing the robustness or the flexibility to incoming stimuli in working memory tasks according to the cognitive task demands. These mechanisms can also achieve an optimal balance in the trade-off between DM and WM. Our approach can provide a global and physical quantification which helps to uncover the underlying mechanisms of various biological functions beyond the circuit architectures.

biophysics↗

bioRxiv2022

CaV1.2 channelopathic mutations evoke diverse pathophysiological mechanisms

The first pathogenic mutation in CaV1.2 was identified in 2004 and was shown to cause a severe multisystem disorder known as Timothy syndrome (TS). The mutation was localized to the distal S6 region of the channel, a region known to play a major role in channel activation. TS patients suffer from life-threatening cardiac symptoms as well as significant neurodevelopmental deficits including autism spectrum disorder (ASD). Since this discovery, the number and variety of mutations identified in CaV1.2 has grown tremendously, and the distal S6 regions remains a frequent locus for many of these mutations. While the majority of patients harboring these mutations exhibit cardiac symptoms which can be well explained by known pathogenic mechanisms, the same cannot be said for the ASD or neurodevelopmental phenotypes seen in some patients, indicating a gap in our understanding of the pathogenesis of CaV1.2 channelopathies. Here, we use of whole cell patch clamp, quantitative Ca2+ imaging, and single channel recordings to expand the known mechanisms underlying the pathogenesis of CaV1.2 channelopathies. Specifically, we find that mutations within the S6 region can exert independent and separable effects on activation, voltage-dependent inactivation (VDI) and Ca2+-dependent inactivation (CDI). Moreover, the mechanisms underlying the CDI effects of these mutations are varied and include altered channel opening and possible disruption of CDI transduction. Overall, these results provide a structure-function framework to conceptualize the role of S6 mutations in pathophysiology and offer insight into the biophysical defects associated with distinct clinical manifestations.

biophysics↗

bioRxiv2022

Nucleoid-Associated Proteins Undergo Liquid-Liquid Phase Separation with DNA into Multiphasic Condensates Resembling Bacterial Nucleoids

Liquid-liquid phase separation offers unique spatiotemporal control over myriad complex intracellular biochemical processes through compartmentalization of biomolecules into highly dynamic, liquid-like condensates known as membrane-less organelles. The bacterial nucleoid is thought to be one such phase-separated condensate; however, its formation, regulation, and biophysical characteristics are poorly understood. Our super-resolution imaging data suggests that nucleoids are dynamic assemblages of sub-micron-sized liquid-like droplets. We demonstrate that non-sequence-specific Nucleoid-Associated Proteins (NAPs) such as HU-A, HU-B and Dps, accrete nucleic acids and spontaneously condense with them into liquid-like, multicomponent, multiphasic, heterotypic phase-separated droplets. Upon mixing of HU-B, DNA and Dps, HU-B-enriched droplets are seen to contain demixed Dps-enriched droplets. Our findings indicate scope for the possible existence of multiphasic liquid-like compartments within nucleoids, providing insights into bacterial growth phase-dependent variations in the levels of different NAPs.

biophysics↗