Unraveling the molecular mechanisms of thermo-responsive properties of silk-elastin-like proteins by integrating multiscale modeling and experiment

Adaptive hydrogels tailor-made from silk-elastin-like proteins (SELPs) possess excellent biocompatibility and biodegradability with properties that are tunable and responsive to multiple simultaneous external stimuli. To unravel the molecular mechanisms of their physical response to external stimuli in tandem with experiments, here we predict and measure the variation in structural properties as a function of temperature through coarse-grained (CG) modeling of individual and crosslinked SE8Y and S4E8Y molecules, which have ratios of 1:8 and 4:8 of silk to elastin blocks respectively. Extensive structural reshuffling in single SE8Y molecules led to the increased compactness of the structure, whereas S4E8Y molecules did not experience any significant changes as they already adopted very compact structures at low temperatures. Crosslinking of SE8Y molecules at high concentrations impeded their structural transition at high temperatures that drastically reduced the degree of deswelling through extensive suppression of the structural shuffling and the trapping of the molecules in high potential energy states due to inter-molecular constraints. This integrative experimental and computational understanding of the thermal response in single molecules of SELPs and their crosslinked networks should lead to further improvements in the properties of SELP hydrogels through predictive designs and their wider applications in biomaterials and tissue engineering.United States. Department of Defense. Office of Naval Research (Grant N00014-16-1-233)United States. National Institutes of Health (Grant U01 EB014976)Singapore. Agency for Science, Technology and Research (Grant A1786a0031)United States. National Science Foundation. (Grant ACI-1053575

Subtle balance of tropoelastin molecular shape and flexibility regulates dynamics and hierarchical assembly

The assembly of the tropoelastin monomer into elastin is vital for conferring elasticity on blood vessels, skin, and lungs. Tropoelastin has dual needs for flexibility and structure in self-assembly. We explore the structure-dynamics-function interplay, consider the duality of molecular order and disorder, and identify equally significant functional contributions by local and global structures. To study these organizational stratifications, we perturb a key hinge region by expressing an exon that is universally spliced out in human tropoelastins. We find a herniated nanostructure with a displaced C terminus and explain by molecular modeling that flexible helices are replaced with substantial β sheets. We see atypical higher-order cross-linking and inefficient assembly into discontinuous, thick elastic fibers. We explain this dysfunction by correlating local and global structural effects with changes in the molecule’s assembly dynamics. This work has general implications for our understanding of elastomeric proteins, which balance disordered regions with defined structural modules at multiple scales for functional assembly.United States. Office of Naval Research (Presidential Early Career Award for Scientists and Engineers)National Institutes of Health (U.S.) (U01 EB014976

Weakly-Supervised Deep Learning Model for Prostate Cancer Diagnosis and Gleason Grading of Histopathology Images

Prostate cancer is the most common cancer in men worldwide and the second leading cause of cancer death in the United States. One of the prognostic features in prostate cancer is the Gleason grading of histopathology images. The Gleason grade is assigned based on tumor architecture on Hematoxylin and Eosin (H&E) stained whole slide images (WSI) by the pathologists. This process is time-consuming and has known interobserver variability. In the past few years, deep learning algorithms have been used to analyze histopathology images, delivering promising results for grading prostate cancer. However, most of the algorithms rely on the fully annotated datasets which are expensive to generate. In this work, we proposed a novel weakly-supervised algorithm to classify prostate cancer grades. The proposed algorithm consists of three steps: (1) extracting discriminative areas in a histopathology image by employing the Multiple Instance Learning (MIL) algorithm based on Transformers, (2) representing the image by constructing a graph using the discriminative patches, and (3) classifying the image into its Gleason grades by developing a Graph Convolutional Neural Network (GCN) based on the gated attention mechanism. We evaluated our algorithm using publicly available datasets, including TCGAPRAD, PANDA, and Gleason 2019 challenge datasets. We also cross validated the algorithm on an independent dataset. Results show that the proposed model achieved state-of-the-art performance in the Gleason grading task in terms of accuracy, F1 score, and cohen-kappa. The code is available at https://github.com/NabaviLab/Prostate-Cancer

Virology under the microscope—a call for rational discourse

Viruses have brought humanity many challenges: respiratory infection, cancer, neurological impairment and immunosuppression to name a few. Virology research over the last 60+ years has responded to reduce this disease burden with vaccines and antivirals. Despite this long history, the COVID-19 pandemic has brought unprecedented attention to the field of virology. Some of this attention is focused on concern about the safe conduct of research with human pathogens. A small but vocal group of individuals has seized upon these concerns – conflating legitimate questions about safely conducting virus-related research with uncertainties over the origins of SARS-CoV-2. The result has fueled public confusion and, in many instances, ill-informed condemnation of virology. With this article, we seek to promote a return to rational discourse. We explain the use of gain-of-function approaches in science, discuss the possible origins of SARS-CoV-2 and outline current regulatory structures that provide oversight for virological research in the United States. By offering our expertise, we – a broad group of working virologists – seek to aid policy makers in navigating these controversial issues. Balanced, evidence-based discourse is essential to addressing public concern while maintaining and expanding much-needed research in virology

Molecular structure, hierarchical assembly and stimuli-responsive mechanics of tropoelastin and elastin biomaterials

Thesis: Ph. D., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2017.Cataloged from PDF version of thesis.Includes bibliographical references.The elastin polymer, assembled from its molecular precursor tropoelastin, is the dominant component of elastic fibers, which confer elasticity and structural integrity to skin, lung, connective and vascular tissue. Historically, elastin's dynamic nature has precluded traditional approaches such as X-ray crystallography to understand its detailed features. Solving tropoelastin's atomistic structure is key to characterizing elastin's complex biological function, disease-related mechanisms associated with mutations therein, and assembly process, to replicate natural function upon impairment. From the materials perspective, elastin-based materials display tunable thermal sensitivity, presenting opportunities to mimic and control these responsive features for biomedical applications. First, we develop and validate an elastic network model of tropoelastin based on small-angle X-ray scattering to realize near-equilibrium dynamics. We identify a geometry-driven lock-and-key mechanism implicated in cell binding and multi-molecular assembly. We introduce a constitutively quiescent domain to explain the effect of local stiffness perturbation on dynamics, reconciling the contradictory needs for overall structural flexibility and the organizational requirement of specific domains towards protein self-assembly. Second, we develop an atomistic model of tropoelastin and validate it against experimental data. We introduce artificial mutations to probe the function of key molecular regions and cutis laxa-associated mutations to study disease etiology. We reveal mechanisms behind variation in structure and hierarchical assembly based on molecular geometry, secondary structure, location and exposure of hydrophobic domains, and dynamic models, correlating these with experimental results, to build a foundation for studying elastin mechanics, assembly, and disease. Third, we characterize the temperature response spectrum of elastin-like peptides to design synthetic polymers with tunable switching. We resolve the effect of peptide chemistry, chain length, and solvent environment on structural transitions, based on local molecular structure, peptide dynamics and interaction with nearest hydration shells. We build a model for a chimera silk-elastin-like protein polymer combining silk's strength with elastin's extensibility and responsive features to study temperature transition effects on molecular-scale mechanics. Simulating molecular unfolding pathways, we analyze the associated free-energy landscape with the Bell-Evans model to interpret temperature-induced phase transitions. We develop a feedback loop between simulation and experiment for predictive biomaterial design, enabling new applications in drug delivery and tissue engineering.by Anna Tarakanova.Ph. D

Implications of structural hierarchies to materials-based evolution

Thesis: S.M., Massachusetts Institute of Technology, Department of Civil and Environmental Engineering, 2015.Cataloged from PDF version of thesis.Includes bibliographical references (pages 65-69).Among a myriad of spider web geometries, the orb web presents a fascinating, exquisite example in architecture and evolution. Its structural component, the silk protein, is an exemplary natural material because its superior properties stem intrinsically from the synergistic cooperativity of hierarchically-organized components, rather than from the particular properties of the building blocks themselves. By bridging together different levels of hierarchy in the web, we elucidate the mechanisms by which structure at each composite level contributes to organization and material phenomena at subsequent levels, demonstrating that the web is a highly adapted system where both material and hierarchical structure across all length-scales is critical for its functional properties. Further, the material hierarchy scheme within the orb web is exploited to address questions of silk evolution. Spider orb webs can be divided into two categories distinguished by the capture silk used in construction: cribellate orb webs composed of pseudoflagelliform silk coated with dry cribellate threads and ecribellate orb webs, composed of viscid flagelliform silk fibers, coated by adhesive glue droplets. Cribellate capture silk is generally stronger but less extensible than viscid capture silk and a body of phylogenic evidence suggests that cribellate capture silk is more closely related to the ancestral form of capture spiral silk. Here, we use a coarse-grained web model to investigate how the mechanical properties of spiral capture silk affect the behavior of the web system, illustrating that more extensible capture spiral silk yields a decrease in the web's energy absorption, suggesting that the function of the capture spiral shifted from prey capture to other structural roles. Additionally, we observe that in webs with more extensible capture silk, the effect of thread strength on web performance is reduced, indicating that thread extensibility is a dominant driving factor in web diversification. In this thesis, we propose a novel model-centered materials-hierarchy based approach to studying evolutionary trends and suggest possible applications for other fields.by Anna Tarakanova.S.M

Coarse-Grained Model of Tropoelastin Self-Assembly into Nascent Fibrils

Elastin is the dominant building block of elastic fibers that impart structural integrity and elasticity to a range of important tissues, including the lungs, blood vessels, and skin. The elastic fiber assembly process begins with a coacervation stage where tropoelastin monomers reversibly self-assemble into coacervate aggregates that consist of multiple molecules. In this paper, an atomistically based coarse-grained model of tropoelastin assembly is developed. Using the previously determined atomistic structure of tropoelastin, the precursor molecule to elastic fibers, as the basis for coarse-graining, the atomistic model is mapped to a MARTINI-based coarse-grained framework to account for chemical details of protein–protein interactions, coupled to an elastic network model to stabilize the structure. We find that self-assembly of monomers generates up to ∼70 ​nm of dense aggregates that are distinct at different temperatures, displaying high temperature sensitivity. Resulting assembled structures exhibit a combination of fibrillar and globular substructures within the bulk aggregates. The results suggest that the coalescence of tropoelastin assemblies into higher order structures may be reinforced in the initial stages of coacervation by directed assembly, supporting the experimentally observed presence of heterogeneous cross-linking. Self-assembly of tropoelastin is driven by interactions of specific hydrophobic domains and the reordering of water molecules in the system. Domain pair orientation analysis throughout the self-assembly process at different temperatures suggests coacervation is a driving force to orient domains for heterogeneous downstream cross-linking. The model provides a framework to characterize macromolecular self-assembly for elastin, and the formulation could easily be adapted to similar assembly systems.National Science Foundation (U.S.) (Grant ACI-1053575)United States. Office of Naval Research. Defense University Research Instrumentation Program (Grant N00014-17-1-2320)United States. Office of Naval Research (Grant N000141612333)National Institutes of Health (U.S.) (Grant U01 EB014976)National Institutes of Health (U.S.) (Grant 5U01EB014976

Allysine modifications perturb tropoelastin structure and mobility on a local and global scale

Elastin provides elastic tissues with resilience through stretch and recoil cycles, and is primarily made of itsextensively cross-linked monomer, tropoelastin. Here, we leverage the recently published full atomistic modelof tropoelastin to assess how allysine modifications, which are essential to cross-linking, contribute to thedynamics and structural changes that occur in tropoelastin in the context of elastin assembly. We used replicaexchange molecular dynamics to generate structural ensembles of allysine containing tropoelastin. Weconducted principal component analysis on these ensembles and found that the molecule departs from thecanonical structural ensemble. Furthermore, we showed that, while the canonical scissors-twist movementwas retained, new movements emerged that deviated from those of the wild type protein, providing evidencefor the involvement of a variety of molecular motions in elastin assembly. Additionally, we highlighted secondary structural changes and linked these perturbations to the longevity of specific salt bridges. Wepropose a model where allysines in tropoelastin contribute to hierarchical elastin assembly through global andlocal perturbations to molecular structure and dynamics.National Science Foundation (U.S.) (Grant ACI-1053575)United States. Office of Naval Research. Defense University Research Instrumentation Program (Grant N00014-17-1-2320)United States. Office of Naval Research (Grant N000141612333)National Institutes of Health (U.S.) (Grant 5U01EB014976