Search

Amyloid-β(Aβ) and islet amyloid polypeptide (IAPP) are small peptides, classified as amyloids, that have the potential to self-assemble and form cytotoxic species, such as small soluble oligomers and large insoluble fibrils. The formation of Aβaggregates facilitates the progression of Alzheimer’s disease (AD), while IAPP aggregates induce pancreatic β-cell apoptosis, leading to exacerbation of type 2 diabetes (T2D). Cross-amyloid interactions between Aβand IAPP have been described both in vivo and in vitro, implying the role of Aβor IAPP as modulators of cytotoxic self-aggregation of each species, and suggesting that Aβ-IAPP interactions are a potential molecular link between AD and T2D. Using molecular dynamics (MD) simulations, “hotspot” regions of the two peptides were studied to understand the formation of hexamers in a heterogeneous and homogeneous peptide-containing environment. Systems of only Aβ(16–22)peptides formed antiparallel, β-barrel-like structures, while systems of only IAPP(20–29)peptides formed stacked, parallel β-sheets and had relatively unstable aggregation structures after 2 μs of simulation time. Systems containing both Aβand IAPP (1:1 ratio) hexamers showed antiparallel, β-barrel-like structures, with an interdigitated arrangement of Aβ(16–22)and IAPP(20–29). These β-barrel structures have features of cytotoxic amyloid species identified in previous literature. Ultimately, this work seeks to provide atomistic insight into both the mechanism behind cross-amyloid interactions and structural morphologies of these toxic amyloid species.

Fluorescence spectroscopy at the single-molecule scale has been indispensable for studying conformational dynamics and rare states of biological macromolecules. Single-molecule two-dimensional (2D) fluorescence lifetime correlation spectroscopy is an emerging technique that holds promise for the study of protein and nucleic acid dynamics, as the technique is 1) capable of resolving conformational dynamics using a single chromophore, 2) resolves forward and reverse transitions independently, and 3) has a dynamic window ranging from microseconds to seconds. However, the calculation of a 2D fluorescence relaxation spectrum requires an inverse Laplace transform (ILT), which is an ill-conditioned inversion that must be estimated numerically through a regularized minimization. Current methods for performing ILTs of fluorescence relaxation can be computationally inefficient, sensitive to noise corruption, and difficult to implement. Here, we adopt an approach developed for NMR spectroscopy (T1-T2 relaxometry) to perform one-dimensional (1D) and 2D-ILTs on single-molecule fluorescence spectroscopy data using singular-valued decomposition and Tikhonov regularization. This approach provides fast, robust, and easy to implement Laplace inversions of single-molecule fluorescence data. We compare this approach to the widely used maximal entropy method.

Phase separation of biological molecules, such as nucleic acids and proteins, has garnered widespread attention across many fields in recent years. For instance, liquid-liquid phase separation has been implicated not only in membraneless intracellular organization but also in many biochemical processes, including transcription, translation, and cellular signaling. Here, we present a historical background of biological phase separation and survey current work on nuclear organization and its connection to DNA phase separation from the perspective of DNA sequence, structure, and genomic context.

Cell adhesion to the extracellular matrix (ECM) is highly active and plays a crucial role in various physiological functions. The active response of cells to physicochemical cues has been universally discovered in multiple microenvironments. However, the mechanisms to rule these active behaviors of cells are still poorly understood. Here, we establish an active model to probe the biomechanical mechanisms governing cell adhesion. The framework of cells is modeled as a tensional integrity that is maintained by cytoskeletons and extracellular matrices. Active movement of the cell model is self-driven by its intrinsic tendency to intracellular tensioning, defined as tensioning-taxis in this study. Tensioning-taxis is quantified as driving potential to actuate cell adhesion, and the traction forces are solved by our proposed numerical method of local free energy adaptation. The modeling results account for the active adhesion of cells with dynamic protruding of leading edge and power-law development of mechanical properties. Furthermore, the morphogenesis of cells evolves actively depending on actin filaments alignments by a predicted mechanism of scaling and directing traction forces. The proposed model provides a quantitative way to investigate the active mechanisms of cell adhesion and holds the potential to guide studies of more complex adhesion and motion of cells coupled with multiple external cues.

Liquid-liquid phase separation (LLPS) of proteins and nucleic acids has emerged as an important phenomenon in membraneless intracellular organization. We demonstrate that the linker histone H1 condenses into liquid-like droplets in the nuclei of HeLa cells. The droplets, observed during the interphase of the cell cycle, are colocalized with DNA-dense regions indicative of heterochromatin. In vitro, H1 readily undergoes LLPS with both DNA and nucleosomes of varying lengths but does not phase separate in the absence of DNA. The nucleosome core particle maintains its structural integrity inside the droplets, as demonstrated by FRET. Unexpectedly, H2A also forms droplets in the presence of DNA and nucleosomes in vitro, whereas the other core histones precipitate. The phase diagram of H1 with nucleosomes is invariant to the nucleosome length at physiological salt concentration, indicating that H1 is capable of partitioning large segments of DNA into liquid-like droplets. Of the proteins tested (H1, core histones, and the heterochromatin protein HP1α), this property is unique to H1. In addition, free nucleotides promote droplet formation of H1 nucleosome in a nucleotide-dependent manner, with droplet formation being most favorable with ATP. Although LLPS of HP1αis known to contribute to the organization of heterochromatin, our results indicate that H1 also plays a role. Based on our study, we propose that H1 and DNA act as scaffolds for phase-separated heterochromatin domains.

During metastasis, cancer cells navigate through a spatially heterogeneous extracellular matrix (ECM). Physical properties of ECM, including the degree of confinement, influence cell migration behavior. Here, utilizing in vitro three-dimensional collagen microtracks, we demonstrate that cell-ECM interactions, specifically the degree of spatial confinement, regulate migratory behavior. We found that cells migrate faster when they are fully confined, contacting all four walls (top, bottom, and two sides) of a collagen microtrack, compared with cells that are partially confined, contacting less than four walls. When fully confined, cells exhibit fewer but larger vinculin-containing adhesions and create greater strains in the surrounding matrix directed toward the cell body. In contrast, partially confined cells develop a more elongated morphology with smaller but significantly more vinculin-containing adhesions and displace the surrounding matrix less than fully confined cells. The resulting effect of increasing cell contractility via Rho activation is dependent on the number of walls with which the cell is in contact. Although matrix strains increase in both fully and partially confined cells, cells that are partially confined increase speed, whereas those in full confinement decrease speed. Together, these results suggest that the degree of cell-ECM contact during confined migration is a key determinant of speed, morphology, and cell-generated substrate strains during motility, and these factors may work in tandem to facilitate metastatic cell migration.

The γ-crystallins of the eye lens nucleus are among the longest-lived proteins in the human body. Synthesized in utero, they must remain folded and soluble throughout adulthood to maintain lens transparency and avoid cataracts. γD- and γS-crystallin are two major monomeric crystallins of the human lens. γD-crystallin is concentrated in the oldest lens fiber cells, the lens nucleus, whereas γS-crystallin is concentrated in the younger cells of the lens cortex. The kinetic stability parameters of these two-domain proteins and their isolated domains were determined and compared. Kinetic unfolding experiments monitored by fluorescence spectroscopy in varying concentrations of guanidinium chloride were used to extrapolate unfolding rate constants and half-lives of the crystallins in the absence of the denaturant. Consistent with their long lifespans in the lens, extrapolated half-lives for the initial unfolding step were on the timescale of years. Both proteins’ isolated N-terminal domains were less kinetically stable than their respective C-terminal domains at denaturant concentrations predicted to disrupt the domain interface, but at low denaturant concentrations, the relative kinetic stabilities were reversed. Cataract-associated aggregation has been shown to proceed from partially unfolded intermediates in these proteins; their extreme kinetic stability likely evolved to protect the lens from the initiation of aggregation reactions. Our findings indicate that the domain interface is the source of significant kinetic stability. The gene duplication and fusion event that produced the modern two-domain architecture of vertebrate lens crystallins may be the origin of their high kinetic as well as thermodynamic stability.

Phase separation of intracellular components has been recently realized as a mechanism by which cells achieve membraneless organization. Here, we study the associative liquid-liquid phase separation (LLPS) of DNA upon complexation with cationic polypeptides. Comparing the phase behavior of different single-stranded DNA as well as double-stranded DNA (dsDNA) sequences that differ in persistence lengths, we find that DNA local flexibility, not simply charge density, determines the LLPS. Furthermore, in a nucleotide- and DNA-dependent manner, free nucleotide triphosphates promote LLPS of polypeptide-dsDNA complexes that are otherwise prone to precipitation. Under these conditions, dsDNA undergoes a secondary phase separation forming liquid-crystalline subcompartments inside the droplets. These results point toward a role of local DNA flexibility, encoded in the sequence, in the regulation and selectivity of multicomponent LLPS in membraneless intracellular organization.

G-protein-coupled receptors (GPCRs) control vital cellular signaling pathways. GPCR oligomerization is proposed to increase signaling diversity. However, many reports have arrived at disparate conclusions regarding the existence, stability, and stoichiometry of GPCR oligomers, partly because of cellular complexity and ensemble averaging of intrareconstitution heterogeneities that complicate the interpretation of oligomerization data. To overcome these limitations, we exploited fluorescence-microscopy-based high-content analysis of single proteoliposomes. This allowed multidimensional quantification of intrinsic monomer-monomer interactions of three class A GPCRs (β2-adrenergic receptor, cannabinoid receptor type 1, and opsin). Using a billion-fold less protein than conventional assays, we quantified oligomer stoichiometries, association constants, and the influence of two ligands and membrane curvature on oligomerization, revealing key similarities and differences for three GPCRs with decidedly different physiological functions. The assays introduced here will assist with the quantitative experimental observation of oligomerization for transmembrane proteins in general.

Arterial hemodynamic shear stress and blood vessel stiffening both significantly influence the arterial endothelial cell (EC) phenotype and atherosclerosis progression, and both have been shown to signal through cell-matrix adhesions. However, the cooperative effects of fluid shear stress and matrix stiffness on ECs remain unknown. To investigate these cooperative effects, we cultured bovine aortic ECs on hydrogels matching the elasticity of the intima of compliant, young, or stiff, aging arteries. The cells were then exposed to laminar fluid shear stress of 12 dyn/cm2. Cells grown on more compliant matrices displayed increased elongation and tighter EC-cell junctions. Notably, cells cultured on more compliant substrates also showed decreased RhoA activation under laminar shear stress. Additionally, endothelial nitric oxide synthase and extracellular signal-regulated kinase phosphorylation in response to fluid shear stress occurred more rapidly in ECs cultured on more compliant substrates, and nitric oxide production was enhanced. Together, our results demonstrate that a signaling cross talk between stiffness and fluid shear stress exists within the vascular microenvironment, and, importantly, matrices mimicking young and healthy blood vessels can promote and augment the atheroprotective signals induced by fluid shear stress. These data suggest that targeting intimal stiffening and/or the EC response to intima stiffening clinically may improve vascular health.

Biophysical investigation of membrane proteins generally requires their extraction from native sources using detergents, a step that can lead, possibly irreversibly, to protein denaturation. The propensity of dodecylphosphocholine (DPC), a detergent widely utilized in NMR studies of membrane proteins, to distort their structure has been the subject of much controversy. It has been recently proposed that the binding specificity of the yeast mitochondrial ADP/ATP carrier (yAAC3) toward cardiolipins is preserved in DPC, thereby suggesting that DPC is a suitable environment in which to study membrane proteins. In this communication, we used all-atom molecular dynamics simulations to investigate the specific binding of cardiolipins to yAAC3. Our data demonstrate that the interaction interface observed in a native-like environment differs markedly from that inferred from an NMR investigation in DPC, implying that in this detergent, the protein structure is distorted. We further investigated yAAC3 solubilized in DPC and in the milder dodecylmaltoside with thermal-shift assays. The loss of thermal transition observed in DPC confirms that the protein is no longer properly folded in this environment.

Many aspects of chromatin biology are influenced by the nuclear compartment in which a locus resides, from transcriptional regulation to DNA repair. Further, the dynamic and variable localization of a particular locus across cell populations and over time makes analysis of a large number of cells critical. As a consequence, robust and automatable methods to measure the position of individual loci within the nuclear volume in populations of cells are necessary to support quantitative analysis of nuclear position. Here, we describe a three-dimensional membrane reconstruction approach that uses fluorescently tagged nuclear envelope or endoplasmic reticulum membrane marker proteins to precisely map the nuclear volume. This approach is robust to a variety of nuclear shapes, providing greater biological accuracy than alternative methods that enforce nuclear circularity, while also describing nuclear position in all three dimensions. By combining this method with established approaches to reconstruct the position of diffraction-limited chromatin markers—in this case, lac Operator arrays bound by lacI-GFP—the distribution of loci positions within the nuclear volume with respect to the nuclear periphery can be quantitatively obtained. This stand-alone image analysis pipeline should be of broad practical utility for individuals interested in various aspects of chromatin biology, while also providing, to our knowledge, a new conceptual framework for investigators who study organelle shape.

Protein structure predictions from deep learning models like AlphaFold2, despite their remarkable accuracy, are likely insufficient for direct use in downstream tasks like molecular docking. The functionality of such models could be improved with a combination of increased accuracy and physical intuition. We propose a new method to train deep learning protein structure prediction models using molecular dynamics force fields to work toward these goals. Our custom PyTorch loss function, OpenMM-Loss, represents the potential energy of a predicted structure. OpenMM-Loss can be applied to any all-atom representation of a protein structure capable of mapping into our software package, SidechainNet. We demonstrate our method’s efficacy by finetuning OpenFold. We show that subsequently predicted protein structures, both before and after a relaxation procedure, exhibit comparable accuracy while displaying lower potential energy and improved structural quality as assessed by MolProbity metrics.

CryoEM continues to produce density maps of larger and more complex assemblies with multiple protein components of mixed symmetries. Resolution is not always uniform throughout a cryoEM map, and it can be useful to estimate the resolution in specific molecular components of a large assembly. In this study, we present procedures to 1) estimate the resolution in subcomponents by gold-standard Fourier shell correlation (FSC); 2) validate modeling procedures, particularly at medium resolutions, which can include loop modeling and flexible fitting; and 3) build probabilistic models that combine high-accuracy priors (such as crystallographic structures) with medium-resolution cryoEM densities. As an example, we apply these methods to new cryoEM maps of the mature bacteriophage P22, reconstructed without imposing icosahedral symmetry. Resolution estimates based on gold-standard FSC show the highest resolution in the coat region (7.6 Å), whereas other components are at slightly lower resolutions: portal (9.2 Å), hub (8.5 Å), tailspike (10.9 Å), and needle (10.5 Å). These differences are indicative of inherent structural heterogeneity and/or reconstruction accuracy in different subcomponents of the map. Probabilistic models for these subcomponents provide new insights, to our knowledge, and structural information when taking into account uncertainty given the limitations of the observed density.

The B1 domain of protein G has been a classic model system of folding for decades, the subject of numerous experimental and computational studies. Most of the experimental work has focused on whether the protein folds via an intermediate, but the evidence is mostly limited to relatively slow kinetic observations with a few structural probes. In this work we observe folding on the submillisecond timescale with microfluidic mixers using a variety of probes including tryptophan fluorescence, circular dichroism, and photochemical oxidation. We find that each probe yields different kinetics and compare these observations with a Markov State Model constructed from large-scale molecular dynamics simulations and find a complex network of states that yield different kinetics for different observables. We conclude that there are many folding pathways before the final folding step and that these paths do not have large free energy barriers.

During cardiac thin-filament activation, the N-domain of cardiac troponin C (N-cTnC) binds to Ca2+and interacts with the actomyosin inhibitory troponin I (cTnI). The interaction between N-cTnC and cTnI stabilizes the Ca2+-induced opening of N-cTnC and is presumed to also destabilize cTnI–actin interactions that work together with steric effects of tropomyosin to inhibit force generation. Recently, our in situ steady-state FRET measurements based on N-cTnC opening suggested that at long sarcomere length, strongly bound cross-bridges indirectly stabilize this Ca2+-sensitizing N-cTnC–cTnI interaction through structural effects on tropomyosin and cTnI. However, the method previously used was unable to determine whether N-cTnC opening depends on sarcomere length. In this study, we used time-resolved FRET to monitor the effects of cross-bridge state and sarcomere length on the Ca2+-dependent conformational behavior of N-cTnC in skinned cardiac muscle fibers. FRET donor (AEDANS) and acceptor (DDPM)-labeled double-cysteine mutant cTnC(T13C/N51C)AEDANS-DDPMwas incorporated into skinned muscle fibers to monitor N-cTnC opening. To study the structural effects of sarcomere length on N-cTnC, we monitored N-cTnC opening at relaxing and saturating levels of Ca2+and 1.80 and 2.2-μm sarcomere length. Mg2+-ADP and orthovanadate were used to examine the structural effects of noncycling strong-binding and weak-binding cross-bridges, respectively. We found that the stabilizing effect of strongly bound cross-bridges on N-cTnC opening (which we interpret as transmitted through related changes in cTnI and tropomyosin) become diminished by decreases in sarcomere length. Additionally, orthovanadate blunted the effect of sarcomere length on N-cTnC conformational behavior such that weak-binding cross-bridges had no effect on N-cTnC opening at any tested [Ca2+] or sarcomere length. Based on our findings, we conclude that the observed sarcomere length-dependent positive feedback regulation is a key determinant in the length-dependent Ca2+sensitivity of myofilament activation and consequently the mechanism underlying the Frank-Starling law of the heart.

Leukocyte exposure to hemodynamic shear forces is critical for physiological functions including initial adhesion to the endothelium, the formation of pseudopods, and migration into tissues. G-protein coupled receptors on neutrophils, which bind to chemoattractants and play a role in neutrophil chemotaxis, have been implicated as fluid shear stress sensors that control neutrophil activation. Recently, exposure to physiological fluid shear stresses observed in the microvasculature was shown to reduce neutrophil activation in the presence of the chemoattractant formyl-methionyl-leucyl-phenylalanine. Here, however, human neutrophil preexposure to uniform shear stress (0.1–2.75 dyn/cm2) in a cone-and-plate viscometer for 1–120 min was shown to increase, rather than decrease, neutrophil activation in the presence of platelet activating factor (PAF). Fluid shear stress exposure increased PAF-induced neutrophil activation in terms of L-selectin shedding, αMβ2integrin activation, and morphological changes. Neutrophil activation via PAF was found to correlate with fluid shear stress exposure, as neutrophil activation increased in a shear stress magnitude- and time-dependent manner. These results indicate that fluid shear stress exposure increases neutrophil activation by PAF, and, taken together with previous observations, differentially controls how neutrophils respond to chemoattractants.

Förster resonance energy transfer (FRET) experiments are often used to study interactions between integral membrane proteins in cellular membranes. However, in addition to the FRET of sequence-specific interactions, these experiments invariably record a contribution due to proximity FRET, which occurs when a donor and an acceptor approach each other by chance within distances of ∼100 Å. This effect does not reflect specific interactions in the membrane and is frequently unappreciated, despite the fact that its magnitude can be significant. Here we develop a computational description of proximity FRET, simulating the cases of proximity FRET when fluorescent proteins are used to tag monomeric, dimeric, trimeric, and tetrameric membrane proteins, as well as membrane proteins existing in monomer-dimer equilibria. We also perform rigorous experimental measurements of this effect, by identifying membrane receptors that do not associate in mammalian membranes. We measure the FRET efficiencies between yellow fluorescent protein and mCherry-tagged versions of these receptors in plasma-membrane-derived vesicles as a function of receptor concentration. Finally, we demonstrate that the experimental measurements are well described by our predictions. The work presented here brings additional rigor to FRET-based studies of membrane protein interactions, and should have broad utility in membrane biophysics research.

Despite decades of intense experimental studies, we still lack a detailed understanding of synaptic function. Fortunately, using computational approaches, we can obtain important new insights into the inner workings of these important neural systems. Here, we report the development of a spatially realistic computational model of an entire frog active zone in which we constrained model parameters with experimental data, and then used Monte Carlo simulation methods to predict the Ca2+-binding stoichiometry and dynamics that underlie neurotransmitter release. Our model reveals that 20–40 independent Ca2+-binding sites on synaptic vesicles, only a fraction of which need to bind Ca2+to trigger fusion, are sufficient to predict physiological release. Our excess-Ca2+-binding-site model has many functional advantages, agrees with recent data on synaptotagmin copy number, and is the first (to our knowledge) to link detailed physiological observations with the molecular machinery of Ca2+-triggered exocytosis. In addition, our model provides detailed microscopic insight into the underlying Ca2+dynamics during synapse activation.