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Astore, M. A.

Publications and source records attributed to Astore, M. A..

8 recordsLinked to original sources

Quantifying RNA Folding Equilibria from Unclassified Cryo-EM Particle Images

Functional RNA structures are typically far more dynamic than most proteins solved by cryo-electron microscopy (cryo-EM). Flexible junctions and weak tertiary contacts produce broad conformational ensembles, and cryo-EM particle classification analyses discard unaligned particles, which inherently contain the information needed to quantify such broad ensembles. Here, we infer compositional and conformational distributions from unclassified particle images by Bayesian ensemble reweighting. We tested our approach on the P4-P6 domain of the Tetrahymena thermophila group I intron, a classic model system of Mg2+-dependent RNA folding. While stable monomeric and dimeric states yielded high-resolution reconstructions, analyses of abundant, flexible conformations required Bayesian ensemble inference. Our approach quantitatively captured the Mg2+-dependent folding transition, indicating that cryo-EM can report the abundance of coexisting RNA states in agreement with bulk solution measurements. These results showcase how quantitative studies of RNA folding can be achieved by combining cryo-EM measurements with statistical ensemble-inference tools.

biochemistry↗

RNA 3D Motif Dynamics Guide Assembly of the Replication Initiation Complex in Flaviviruses

Viral RNA genomes contain structured elements that recruit the machinery necessary for their replication. However, these mechanisms remain poorly understood because of RNA structures dynamic nature. Using cryo-EM and single-molecule Forster resonance energy transfer, we show that the flaviviral stem-loop A (SLA)--which recruits the viral polymerase NS5 to initiate negative-strand synthesis--populates a conserved, multi-state conformational ensemble governed by a dynamic three-dimensional (3D) motif. Structures of Zika and dengue SLA-NS5 complexes reveal that NS5 engages a preorganized SLA conformation. Notably, destabilizing this conformation impairs negative-strand synthesis without affecting NS5 binding. Thus, the conserved SLA 3D ensemble guides a post-binding conformational search that converts an initial encounter complex into a productive replication-initiation complex--revealing how RNA conformational ensembles, rather than static structures, dictate function. SUMMARYViral genomes encode dynamic RNA structures that are specifically recognized by proteins to regulate critical steps of the viral life cycle. Although these RNAs exist as multi-state conformational ensembles, structural studies have largely captured single conformations, limiting our mechanistic understanding of RNA-protein recognition and function. Here, using single-particle cryo-electron microscopy (cryo-EM), single-molecule Forster resonance energy transfer, and biochemical assays, we show how flaviviral genomes use structural dynamics encoded in their stem-loop A (SLA) to guide a conserved, multi-step mechanism of negative-strand synthesis initiation by non-structural protein 5 (NS5). Cryo-EM ensembles of SLAs from dengue, Zika, West Nile, and yellow fever viruses reveal a conserved conformational landscape dictated by alternative stacking configurations of a central three-way junction (3WJ). Cryo-EM structures of SLA-NS5 complexes from dengue and Zika show that NS5 engages a specific state within SLA 3D ensemble, one in which the 3WJ adopts a GRR/A tetraloop-like motif that we identify across diverse structural RNAs. Strikingly, mutations that substantially destabilize this state impair negative-strand synthesis without affecting NS5 binding--decoupling binding from function and ruling out a simple conformational-capture mechanism. Instead, the SLAs intrinsic structural dynamics direct a post-binding conformational search that converts an initial, conformationally heterogeneous encounter complex into a productive replication-initiation complex. These results demonstrate a mechanism of RNA-protein recognition in which the 3D conformational ensemble of an RNA guides formation of the functional state downstream of binding, and identify a ubiquitous, intrinsically dynamic 3D motif within the SLAs 3WJ as a critical determinant of flavivirus negative-strand synthesis.

biochemistry↗

Cooling fast and slow: Characterising the effects of vitrification in cryo-EM and the subsequent recovery of equilibrium populations

Single-particle cryogenic electron microscopy (cryo-EM) has enabled near-atomic resolution structure determination of diverse biomolecules. Because the high vacuum required for electron microscopy prevents the imaging of liquid-phase samples, cryo-EM samples are prepared by plunging the sample into a cryogen, rapidly cooling the sample and suspending the ensemble of biomolecules in a matrix of water glass. However, the effects of this vitrification on the biomolecular ensemble are unknown, complicating efforts to use cryo-EM to derive conformational ensembles of biomolecules. To study these effects, we carried out extensive molecular dynamics simulations (over 50 milliseconds) of the Trp-cage miniprotein at equilibrium and undergoing rapid cooling. We simulated seven cooling rates spanning three orders of magnitude, with the slowest coolings matching experimental rates. By inspecting molecular mobility and density-temperature equations of state for water with and without protein, we found that water vitrification is unaltered by the protein. To track protein conformation changes, and to relate them to conformational kinetics, we made a Markov State Model (MSM) of Trp-cage from 5.4 milliseconds of equilibrium sampling at 277 K. We observed that MSM states with a characteristic time longer than the duration of the non-equilibrium cooling, tend to be more robust to artefacts induced by such cooling. Critically, although we observe that some states vanish in the equilibrium ensemble at 230 K, none do in our nonequilibrium cooled ensembles. However, to account for perturbations induced by nonequilibrium cooling for more labile states, we developed a thermodynamic inference framework for recovering equilibrium populations from the measured vitrified ensembles. These results indicate that cryo-EM has the capacity to be a reliable and accurate biophysical technique for the study of biomolecular ensembles. SignificanceCryogenic electron microscopy images biomolecules trapped in vitreous ice. To vitrify the sample, it must be cooled over the course of 22 microseconds. However, the degree to which this cooling causes the ensemble of the molecules to be perturbed from equilibrium is unknown. Here we present extensive molecular dynamics simulations to quantify the equilibrium dynamics of the Trp-cage miniprotein and the effects of cooling on its conformational ensemble. By simulating cooling at seven different rates, including the slowest experimental rates that still result in vitrification, we connect the kinetic properties of a proteins conformational state to the change in state population from cooling. We show that cooling-induced population shifts are small but observable. We further introduce a thermodynamic-inference method to recover equilibrium populations from the cooled ensembles.

biophysics↗

CryoJAX - A Cryo-Electron Microscopy Image Simulation Library in JAX

While cryo-electron microscopy (cryo-EM) has come to prominence in the last decade due to its ability to resolve biomolecular complexes at atomic resolution, advancements in experimental and computational methods have made cryo-EM promising for investigating intracellular organization and heterogeneous molecular states. A primary challenge for these alternative applications is the development of techniques for cryo-EM data analysis, which are very computationally demanding. To this end, it is advantageous to leverage advanced scientific computing frameworks for statistical analysis. One such framework is JAX, an emerging array-oriented Python numerical computing package for automatic differentiation and vectorization with a growing ecosystem for statistical inference and machine learning. We have developed cryoJAX, a cryo-EM image simulation library for building computational data analysis applications in JAX. CryoJAX is a flexible modeling language for cryo-EM image formation and therefore can support a wide range of data analysis downstream. By integrating with the JAX ecosystem, cryoJAX enables the development and deployment of algorithms for the growing breadth of scientific applications for cryo-EM. SynopsisThe authors have developed cryoJAX, a cryo-EM image simulation library for developing data analysis techniques across cryo-EM modalities. CryoJAX is built on JAX, an emerging scientific computing framework in Python well suited for cryo-EM data analysis.

biophysics↗

The Inaugural Flatiron Institute Cryo-EM Conformational Heterogeneity Challenge

Despite the rise of single particle cryo-electron microscopy (cryo-EM) as a premier method for resolving macromolecular structures at atomic resolution, methods to address molecular heterogeneity in vitrified samples have yet to reach maturity. With an increasing number of new methods to analyze the multitude of heterogeneous states captured in single particle images, a systematic approach to validation in this field is needed. With this motivation, we issued a challenge to the community to analyze two cryo-EM particle image sets of thyroglobulin that exhibit continuous conformational heterogeneity. The first dataset was experimental and the second was generated with a simulator, allowing control over the distribution of molecular structures and enabled direct comparison between participants submissions and the ground truth molecular structures and distributions. Participants were asked to submit 80 volumes representing the heterogeneous ensemble and estimate their respective populations in the image sets provided. Participation of the research community in the challenge was strong, with submissions from nearly all developers of heterogeneity methods, resulting in 41 submissions across both datasets. Submissions qualitatively exceeded expectations, with the molecular motions identified by methods resembling both each other and the ground truth motion. However, quantitatively assessing these similarities was a challenge in and of itself. In the process of assessing the submissions, we developed several validation metrics, most of which require reference to the underlying ground truth volumes. However, we have also explored the use of metrics that do not necessarily reference ground truth. This is particularly apt for experimental datasets where ground truth is inaccessible. These approaches allowed us to assess the similarity and accuracy in volume quality, molecular motions, and conformational distribution of di!erent submissions. These metrics and the e!orts of all participants help chart a path forward for the improvements of heterogeneity methods for cryo-EM and for future challenges to validate these new methods as they continue to be developed by the community.

biophysics↗

Heterogeneity in ligand-bound TRPV1: A comparison of methods in cryo-EM and molecular dynamics simulation

Cryogenic electron microscopy (cryo-EM) has emerged as a powerful method for resolving the atomistic details of cellular components. In recent years, several computational methods have been developed to study the heterogeneity of molecules in single-particle cryo-EM. In this study, we analyzed a publicly available single-particle dataset of TRPV1 using five of these methods: 3D Flexible Refinement, 3D Variability Analysis, cryoDRGN, ManifoldEM, and Bayesian ensemble reweighting. Beyond what we initially expected, we have found that this dataset contains significant heterogeneity-- indicating that single particle datasets likely contain a rich spectrum of biologically relevant states. Further, we have found that different methods are best suited to studying different kinds of heterogeneity, with some methods being more sensitive to either compositional or conformational heterogeneity. We also apply a combination of Bayesian ensemble reweighting and molecular dynamics as supporting evidence for the presence of these rarer states within the sample. Finally, we developed a quantitative metric based on the analysis of the singular value decomposition and power spectra to compare the resulting volumes from each method. This work represents a detailed view of the variable outcomes of different heterogeneity methods used to analyze a single real dataset and presents a pathway to a deeper understanding of the biology of complex macromolecules like the TRPV1 ion channel.

biophysics↗

Mitochondrial electron transport chain, ceramide and Coenzyme Q are linked in a pathway that drives insulin resistance in skeletal muscle

Insulin resistance (IR) is a complex metabolic disorder that underlies several human diseases, including type 2 diabetes and cardiovascular disease. Despite extensive research, the precise mechanisms underlying IR development remain poorly understood. Here, we provide new insights into the mechanistic connections between cellular alterations associated with IR, including increased ceramides, deficiency of coenzyme Q (CoQ), mitochondrial dysfunction, and oxidative stress. We demonstrate that elevated levels of ceramide in the mitochondria of skeletal muscle cells results in CoQ depletion and loss of mitochondrial respiratory chain components, leading to mitochondrial dysfunction and IR. Further, decreasing mitochondrial ceramide levels in vitro and in animal models (under chow and high fat diet) increased CoQ levels and was protective against IR. CoQ supplementation also rescued ceramide-associated IR. Examination of the mitochondrial proteome from human muscle biopsies revealed a strong correlation between the respirasome system and mitochondrial ceramide as key determinants of insulin sensitivity. Our findings highlight the mitochondrial Ceramide-CoQ-respiratory chain nexus as a potential foundation of an IR pathway that may also play a critical role in other conditions associated with ceramide accumulation and mitochondrial dysfunction, such as heart failure, cancer, and aging. These insights may have important clinical implications for the development of novel therapeutic strategies for the treatment of IR and related metabolic disorders.

cell biology↗

Molecular dynamics and theratyping in airway and gut organoids reveal R352Q-CFTR conductance defect

A significant challenge to making targeted CFTR modulator therapies accessible to all individuals with cystic fibrosis (CF) are many mutations in the CFTR gene that can cause CF, most of which remain uncharacterized. Here, we characterized the structural and functional defects of the rare CFTR mutation R352Q - with potential role contributing to intrapore chloride ion permeation - in patient-derived cell models of the airway and gut. CFTR function in differentiated nasal epithelial cultures and matched intestinal organoids was assessed using ion transport assay and forskolin-induced swelling (FIS) assay respectively. Two CFTR potentiators (VX-770, GLPG1837) and a corrector (VX-809) were tested. Data from R352Q-CFTR were compared to that of participants with mutations with known impact on CFTR function. R352Q-CFTR has residual CFTR function which was restored to functional CFTR activity by CFTR potentiators but not the corrector. Molecular dynamics (MD) simulations of R352Q-CFTR were carried out which indicated the presence of a chloride conductance defect, with little evidence supporting a gating defect. The combination approach of in vitro patient-derived cell models and in silico MD simulations to characterize rare CFTR mutations can improve the specificity and sensitivity of modulator response predictions and aid in their translational use for CF precision medicine.

molecular biology↗