The Energetics and Physiological Impact of Cohesin Extrusion.

Cohesin extrusion is thought to play a central role in establishing the architecture of mammalian genomes. However, extrusion has not been visualized in vivo, and thus, its functional impact and energetics are unknown. Using ultra-deep Hi-C, we show that loop domains form by a process that requires cohesin ATPases. Once formed, however, loops and compartments are maintained for hours without energy input. Strikingly, without ATP, we observe the emergence of hundreds of CTCF-independent loops that link regulatory DNA. We also identify architectural "stripes," where a loop anchor interacts with entire domains at high frequency. Stripes often tether super-enhancers to cognate promoters, and in B cells, they facilitate Igh transcription and recombination. Stripe anchors represent major hotspots for topoisomerase-mediated lesions, which promote chromosomal translocations and cancer. In plasmacytomas, stripes can deregulate Igh-translocated oncogenes. We propose that higher organisms have coopted cohesin extrusion to enhance transcription and recombination, with implications for tumor development.

Nucleosomes play a dual role in regulating transcription dynamics.

Transcription has a mechanical component, as the translocation of the transcription machinery or RNA polymerase (RNAP) on DNA or chromatin is dynamically coupled to the chromatin torsion. This posits chromatin mechanics as a possible regulator of eukaryotic transcription, however, the modes and mechanisms of this regulation are elusive. Here, we first take a statistical mechanics approach to model the torsional response of topology-constrained chromatin. Our model recapitulates the experimentally observed weaker torsional stiffness of chromatin compared to bare DNA and proposes structural transitions of nucleosomes into chirally distinct states as the driver of the contrasting torsional mechanics. Coupling chromatin mechanics with RNAP translocation in stochastic simulations, we reveal a complex interplay of DNA supercoiling and nucleosome dynamics in governing RNAP velocity. Nucleosomes play a dual role in controlling the transcription dynamics. The steric barrier aspect of nucleosomes in the gene body counteracts transcription via hindering RNAP motion, whereas the chiral transitions facilitate RNAP motion via driving a low restoring torque upon twisting the DNA. While nucleosomes with low dissociation rates are typically transcriptionally repressive, highly dynamic nucleosomes offer less of a steric barrier and enhance the transcription elongation dynamics of weakly transcribed genes via buffering DNA twist. We use the model to predict transcription-dependent levels of DNA supercoiling in segments of the budding yeast genome that are in accord with available experimental data. The model unveils a paradigm of DNA supercoiling-mediated interaction between genes and makes testable predictions that will guide experimental design.

Machine learning in biological physics: From biomolecular prediction to design.

Machine learning has been proposed as an alternative to theoretical modeling when dealing with complex problems in biological physics. However, in this perspective, we argue that a more successful approach is a proper combination of these two methodologies. We discuss how ideas coming from physical modeling neuronal processing led to early formulations of computational neural networks, e.g., Hopfield networks. We then show how modern learning approaches like Potts models, Boltzmann machines, and the transformer architecture are related to each other, specifically, through a shared energy representation. We summarize recent efforts to establish these connections and provide examples on how each of these formulations integrating physical modeling and machine learning have been successful in tackling recent problems in biomolecular structure, dynamics, function, evolution, and design. Instances include protein structure prediction; improvement in computational complexity and accuracy of molecular dynamics simulations; better inference of the effects of mutations in proteins leading to improved evolutionary modeling and finally how machine learning is revolutionizing protein engineering and design. Going beyond naturally existing protein sequences, a connection to protein design is discussed where synthetic sequences are able to fold to naturally occurring motifs driven by a model rooted in physical principles. We show that this model is "learnable" and propose its future use in the generation of unique sequences that can fold into a target structure.

CISD3/MiNT is required for complex I function, mitochondrial integrity, and skeletal muscle maintenance.

Mitochondria play a central role in muscle metabolism and function. A unique family of iron-sulfur proteins, termed CDGSH Iron Sulfur Domain-containing (CISD/NEET) proteins, support mitochondrial function in skeletal muscles. The abundance of these proteins declines during aging leading to muscle degeneration. Although the function of the outer mitochondrial CISD/NEET proteins, CISD1/mitoNEET and CISD2/NAF-1, has been defined in skeletal muscle cells, the role of the inner mitochondrial CISD protein, CISD3/MiNT, is currently unknown. Here, we show that CISD3 deficiency in mice results in muscle atrophy that shares proteomic features with Duchenne muscular dystrophy. We further reveal that CISD3 deficiency impairs the function and structure of skeletal muscles, as well as their mitochondria, and that CISD3 interacts with, and donates its [2Fe-2S] clusters to, complex I respiratory chain subunit NADH Ubiquinone Oxidoreductase Core Subunit V2 (NDUFV2). Using coevolutionary and structural computational tools, we model a CISD3-NDUFV2 complex with proximal coevolving residue interactions conducive of [2Fe-2S] cluster transfer reactions, placing the clusters of the two proteins 10 to 16 Å apart. Taken together, our findings reveal that CISD3/MiNT is important for supporting the biogenesis and function of complex I, essential for muscle maintenance and function. Interventions that target CISD3 could therefore impact different muscle degeneration syndromes, aging, and related conditions.

Magnesium Ions Mitigate Metastable States in the Regulatory Landscape of mRNA Elements.

Residing in the 5' untranslated region of the mRNA, the 2'-deoxyguanosine (2'-dG) riboswitch mRNA element adopts an alternative structure with the binding of the 2'-dG molecule, which terminates transcription. In general, RNA conformations are strongly affected by positively charged metal ions (especially Mg2+). We have quantitatively explored the combined effect of ligand (2'-dG) and Mg2+ binding on the energy landscape of the aptamer domain of the 2'-dG riboswitch with both explicit solvent all atom molecular dynamics simulations and SHAPE biochemical probing experiments. We show that both ligand and Mg2+ are required for the stabilization of the aptamer domain; however, the two factors function in different ways. While the addition of Mg2+ remodels the energy landscape and reduces its frustration by the formation of additional contacts, the binding of 2'-dG eliminates the metastable states by building a compact core for the aptamer domain. In particular, Mg2+ ions and ligand binding are required to stabilize the most unstable helix P1 (which needs to unfold to activate the transcription platform), and the riboswitch core formed by the backbone of the P2 and P3 helices. They also facilitate a more compact structure in the three-way junction region.

Road-blocker HSP disease mutation disrupts pre-organization for ATP hydrolysis in kinesin through a second sphere control.

Kinesin motor proteins perform several essential cellular functions powered by the adenosine triphosphate (ATP) hydrolysis reaction. Several single-point mutations in the kinesin motor protein KIF5A have been implicated to hereditary spastic paraplegia disease (HSP), a lethal neurodegenerative disease in humans. In earlier studies, we have shown that a series of HSP-related mutations can impair the kinesin's long-distance displacement or processivity by modulating the order-disorder transition of the linker connecting the heads to the coiled coil. On the other hand, the reduction of kinesin's ATP hydrolysis reaction rate by a distal asparagine-to-serine mutation is also known to cause HSP disease. However, the molecular mechanism of the ATP hydrolysis reaction in kinesin by this distal mutation is still not fully understood. Using classical molecular dynamics simulations combined with quantum mechanics/molecular mechanics calculations, the pre-organization geometry required for optimal hydrolysis in kinesin motor bound to α/ß-tubulin is determined. This optimal geometry has only a single salt-bridge (of the possible two) between Arg203-Glu236, putting a reactive water molecule at a perfect position for hydrolysis. Such geometry is also needed to create the appropriate configuration for proton translocation during ATP hydrolysis. The distal asparagine-to-serine mutation is found to disrupt this optimal geometry. Therefore, the current study along with our previous one demonstrates how two different effects on kinesin dynamics (processivity and ATP hydrolysis), caused by a different set of genotypes, can give rise to the same phenotype leading to HSP disease.

BAP1 is a novel regulator of HIF-1α.

BAP1 is a powerful tumor suppressor gene characterized by haplo insufficiency. Individuals carrying germline BAP1 mutations often develop mesothelioma, an aggressive malignancy of the serosal layers covering the lungs, pericardium, and abdominal cavity. Intriguingly, mesotheliomas developing in carriers of germline BAP1 mutations are less aggressive, and these patients have significantly improved survival. We investigated the apparent paradox of a tumor suppressor gene that, when mutated, causes less aggressive mesotheliomas. We discovered that mesothelioma biopsies with biallelic BAP1 mutations showed loss of nuclear HIF-1α staining. We demonstrated that during hypoxia, BAP1 binds, deubiquitylates, and stabilizes HIF-1α, the master regulator of the hypoxia response and tumor cell invasion. Moreover, primary cells from individuals carrying germline BAP1 mutations and primary cells in which BAP1 was silenced using siRNA had reduced HIF-1α protein levels in hypoxia. Computational modeling and co-immunoprecipitation experiments revealed that mutations of BAP1 residues I675, F678, I679, and L691 -encompassing the C-terminal domain-nuclear localization signal- to A, abolished the interaction with HIF-1α. We found that BAP1 binds to the N-terminal region of HIF-1α, where HIF-1α binds DNA and dimerizes with HIF-1ß forming the heterodimeric transactivating complex HIF. Our data identify BAP1 as a key positive regulator of HIF-1α in hypoxia. We propose that the significant reduction of HIF-1α activity in mesothelioma cells carrying biallelic BAP1 mutations, accompanied by the significant reduction of HIF-1α activity in hypoxic tissues containing germline BAP1 mutations, contributes to the reduced aggressiveness and improved survival of mesotheliomas developing in carriers of germline BAP1 mutations.

A VDAC1-mediated NEET protein chain transfers [2Fe-2S] clusters between the mitochondria and the cytosol and impacts mitochondrial dynamics.

Mitochondrial inner NEET (MiNT) and the outer mitochondrial membrane (OMM) mitoNEET (mNT) proteins belong to the NEET protein family. This family plays a key role in mitochondrial labile iron and reactive oxygen species (ROS) homeostasis. NEET proteins contain labile [2Fe-2S] clusters which can be transferred to apo-acceptor proteins. In eukaryotes, the biogenesis of [2Fe-2S] clusters occurs within the mitochondria by the iron-sulfur cluster (ISC) system; the clusters are then transferred to [2Fe-2S] proteins within the mitochondria or exported to cytosolic proteins and the cytosolic iron-sulfur cluster assembly (CIA) system. The last step of export of the [2Fe-2S] is not yet fully characterized. Here we show that MiNT interacts with voltage-dependent anion channel 1 (VDAC1), a major OMM protein that connects the intermembrane space with the cytosol and participates in regulating the levels of different ions including mitochondrial labile iron (mLI). We further show that VDAC1 is mediating the interaction between MiNT and mNT, in which MiNT transfers its [2Fe-2S] clusters from inside the mitochondria to mNT that is facing the cytosol. This MiNT-VDAC1-mNT interaction is shown both experimentally and by computational calculations. Additionally, we show that modifying MiNT expression in breast cancer cells affects the dynamics of mitochondrial structure and morphology, mitochondrial function, and breast cancer tumor growth. Our findings reveal a pathway for the transfer of [2Fe-2S] clusters, which are assembled inside the mitochondria, to the cytosol.

Residue coevolution and mutational landscape for OmpR and NarL response regulator subfamilies.

DNA-binding response regulators (DBRRs) are a broad class of proteins that operate in tandem with their partner kinase proteins to form two-component signal transduction systems in bacteria. Typical DBRRs are composed of two domains where the conserved N-terminal domain accepts transduced signals and the evolutionarily diverse C-terminal domain binds to DNA. These domains are assumed to be functionally independent, and hence recombination of the two domains should yield novel DBRRs of arbitrary input/output response, which can be used as biosensors. This idea has been proved to be successful in some cases; yet, the error rate is not trivial. Improvement of the success rate of this technique requires a deeper understanding of the linker-domain and inter-domain residue interactions, which have not yet been thoroughly examined. Here, we studied residue coevolution of DBRRs of the two main subfamilies (OmpR and NarL) using large collections of bacterial amino acid sequences to extensively investigate the evolutionary signatures of linker-domain and inter-domain residue interactions. Coevolutionary analysis uncovered evolutionarily selected linker-domain and inter-domain residue interactions of known experimental structures, as well as previously unknown inter-domain residue interactions. We examined the possibility of these inter-domain residue interactions as contacts that stabilize an inactive conformation of the DBRR where DNA binding is inhibited for both subfamilies. The newly gained insights on linker-domain/inter-domain residue interactions and shared inactivation mechanisms improve the understanding of the functional mechanism of DBRRs, providing clues to efficiently create functional DBRR-based biosensors. Additionally, we show the feasibility of applying coevolutionary landscape models to predict the functionality of domain-swapped DBRR proteins. The presented result demonstrates that sequence information can be used to filter out bioengineered DBRR proteins that are predicted to be nonfunctional due to a high negative predictive value.

An associative memory Hamiltonian model for DNA and nucleosomes.

A model for DNA and nucleosomes is introduced with the goal of studying chromosomes from a single base level all the way to higher-order chromatin structures. This model, dubbed the Widely Editable Chromatin Model (WEChroM), reproduces the complex mechanics of the double helix including its bending persistence length and twisting persistence length, and the temperature dependence of the former. The WEChroM Hamiltonian is composed of chain connectivity, steric interactions, and associative memory terms representing all remaining interactions leading to the structure, dynamics, and mechanical characteristics of the B-DNA. Several applications of this model are discussed to demonstrate its applicability. WEChroM is used to investigate the behavior of circular DNA in the presence of positive and negative supercoiling. We show that it recapitulates the formation of plectonemes and of structural defects that relax mechanical stress. The model spontaneously manifests an asymmetric behavior with respect to positive or negative supercoiling, similar to what was previously observed in experiments. Additionally, we show that the associative memory Hamiltonian is also capable of reproducing the free energy of partial DNA unwrapping from nucleosomes. WEChroM is designed to emulate the continuously variable mechanical properties of the 10nm fiber and, by virtue of its simplicity, is ready to be scaled up to molecular systems large enough to investigate the structural ensembles of genes. WEChroM is implemented in the OpenMM simulation toolkits and is freely available for public use.

DNA supercoiling-mediated collective behavior of co-transcribing RNA polymerases.

Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or 'push' between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate by modifying the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the DNA torsional response. Using stochastic simulations, we demonstrate DNA supercoiling-mediated long-range cooperation between co-transcribing RNAPs. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern transcriptional dynamics.

Shaping the genome via lengthwise compaction, phase separation, and lamina adhesion.

The link between genomic structure and biological function is yet to be consolidated, it is, however, clear that physical manipulation of the genome, driven by the activity of a variety of proteins, is a crucial step. To understand the consequences of the physical forces underlying genome organization, we build a coarse-grained polymer model of the genome, featuring three fundamentally distinct classes of interactions: lengthwise compaction, i.e., compaction of chromosomes along its contour, self-adhesion among epigenetically similar genomic segments, and adhesion of chromosome segments to the nuclear envelope or lamina. We postulate that these three types of interactions sufficiently represent the concerted action of the different proteins organizing the genome architecture and show that an interplay among these interactions can recapitulate the architectural variants observed across the tree of life. The model elucidates how an interplay of forces arising from the three classes of genomic interactions can drive drastic, yet predictable, changes in the global genome architecture, and makes testable predictions. We posit that precise control over these interactions in vivo is key to the regulation of genome architecture.

Mechanistic basis of propofol-induced disruption of kinesin processivity.

Propofol is a widely used general anesthetic to induce and maintain anesthesia, and its effects are thought to occur through impact on the ligand-gated channels including the GABAA receptor. Propofol also interacts with a large number of proteins including molecular motors and inhibits kinesin processivity, resulting in significant decrease in the run length for conventional kinesin-1 and kinesin-2. However, the molecular mechanism by which propofol achieves this outcome is not known. The structural transition in the kinesin neck-linker region is crucial for its processivity. In this study, we analyzed the effect of propofol and its fluorine derivative (fropofol) on the transition in the neck-linker region of kinesin. Propofol binds at two crucial surfaces in the leading head: one at the microtubule-binding interface and the other in the neck-linker region. We observed in both the cases the order-disorder transition of the neck-linker was disrupted and kinesin lost its signal for forward movement. In contrast, there was not an effect on the neck-linker transition with propofol binding at the trailing head. Free-energy calculations show that propofol at the microtubule-binding surface significantly reduces the microtubule-binding affinity of the kinesin head. While propofol makes pi-pi stacking and H-bond interactions with the propofol binding cavity, fropofol is unable to make a suitable interaction at this binding surface. Therefore, the binding affinity of fropofol is much lower compared to propofol. Hence, this study provides a mechanism by which propofol disrupts kinesin processivity and identifies transitions in the ATPase stepping cycle likely affected.

BAP1 forms a trimer with HMGB1 and HDAC1 that modulates gene × environment interaction with asbestos.

Carriers of heterozygous germline BAP1 mutations (BAP1+/-) are affected by the "BAP1 cancer syndrome." Although they can develop almost any cancer type, they are unusually susceptible to asbestos carcinogenesis and mesothelioma. Here we investigate why among all carcinogens, BAP1 mutations cooperate with asbestos. Asbestos carcinogenesis and mesothelioma have been linked to a chronic inflammatory process promoted by the extracellular release of the high-mobility group box 1 protein (HMGB1). We report that BAP1+/- cells secrete increased amounts of HMGB1, and that BAP1+/- carriers have detectable serum levels of acetylated HMGB1 that further increase when they develop mesothelioma. We linked these findings to our discovery that BAP1 forms a trimeric protein complex with HMGB1 and with histone deacetylase 1 (HDAC1) that modulates HMGB1 acetylation and its release. Reduced BAP1 levels caused increased ubiquitylation and degradation of HDAC1, leading to increased acetylation of HMGB1 and its active secretion that in turn promoted mesothelial cell transformation.

Design and proof of concept for targeted phage-based COVID-19 vaccination strategies with a streamlined cold-free supply chain.

Development of effective vaccines against coronavirus disease 2019 (COVID-19) is a global imperative. Rapid immunization of the entire human population against a widespread, continually evolving, and highly pathogenic virus is an unprecedented challenge, and different vaccine approaches are being pursued. Engineered filamentous bacteriophage (phage) particles have unique potential in vaccine development due to their inherent immunogenicity, genetic plasticity, stability, cost-effectiveness for large-scale production, and proven safety profile in humans. Herein we report the development and initial evaluation of two targeted phage-based vaccination approaches against SARS-CoV-2: dual ligand peptide-targeted phage and adeno-associated virus/phage (AAVP) particles. For peptide-targeted phage, we performed structure-guided antigen design to select six solvent-exposed epitopes of the SARS-CoV-2 spike (S) protein. One of these epitopes displayed on the major capsid protein pVIII of phage induced a specific and sustained humoral response when injected in mice. These phage were further engineered to simultaneously display the peptide CAKSMGDIVC on the minor capsid protein pIII to enable their transport from the lung epithelium into the systemic circulation. Aerosolization of these "dual-display" phage into the lungs of mice generated a systemic and specific antibody response. In the second approach, targeted AAVP particles were engineered to deliver the entire S protein gene under the control of a constitutive CMV promoter. This induced tissue-specific transgene expression, stimulating a systemic S protein-specific antibody response in mice. With these proof-of-concept preclinical experiments, we show that both targeted phage- and AAVP-based particles serve as robust yet versatile platforms that can promptly yield COVID-19 vaccine prototypes for translational development.

Structural reorganization and relaxation dynamics of axially stressed chromosomes.

Chromosomes endure mechanical stresses throughout the cell cycle; for example, resulting from the pulling of chromosomes by spindle fibers during mitosis or deformation of the nucleus during cell migration. The response to physical stress is closely related to chromosome structure and function. Micromechanical studies of mitotic chromosomes have revealed them to be remarkably extensible objects and informed early models of mitotic chromosome organization. We use a data-driven, coarse-grained polymer modeling approach to explore the relationship between the spatial organization of individual chromosomes and their emergent mechanical properties. In particular, we investigate the mechanical properties of our model chromosomes by axially stretching them. Simulated stretching led to a linear force-extension curve for small strain, with mitotic chromosomes behaving about 10-fold stiffer than interphase chromosomes. Studying their relaxation dynamics, we found that chromosomes are viscoelastic solids with a highly liquid-like, viscous behavior in interphase that becomes solid-like in mitosis. This emergent mechanical stiffness originates from lengthwise compaction, an effective potential capturing the activity of loop-extruding SMC complexes. Chromosomes denature under large strains via unraveling, which is characterized by opening of large-scale folding patterns. By quantifying the effect of mechanical perturbations on the chromosome's structural features, our model provides a nuanced understanding of in vivo mechanics of chromosomes.

Theoretical and computational tools to model multistable gene regulatory networks.

The last decade has witnessed a surge of theoretical and computational models to describe the dynamics of complex gene regulatory networks, and how these interactions can give rise to multistable and heterogeneous cell populations. As the use of theoretical modeling to describe genetic and biochemical circuits becomes more widespread, theoreticians with mathematical and physical backgrounds routinely apply concepts from statistical physics, non-linear dynamics, and network theory to biological systems. This review aims at providing a clear overview of the most important methodologies applied in the field while highlighting current and future challenges. It also includes hands-on tutorials to solve and simulate some of the archetypical biological system models used in the field. Furthermore, we provide concrete examples from the existing literature for theoreticians that wish to explore this fast-developing field. Whenever possible, we highlight the similarities and differences between biochemical and regulatory networks and 'classical' systems typically studied in non-equilibrium statistical and quantum mechanics.

Genetic and Structural Analysis of SARS-CoV-2 Spike Protein for Universal Epitope Selection.

Evaluation of immunogenic epitopes for universal vaccine development in the face of ongoing SARS-CoV-2 evolution remains a challenge. Herein, we investigate the genetic and structural conservation of an immunogenically relevant epitope (C662-C671) of spike (S) protein across SARS-CoV-2 variants to determine its potential utility as a broad-spectrum vaccine candidate against coronavirus diseases. Comparative sequence analysis, structural assessment, and molecular dynamics simulations of C662-C671 epitope were performed. Mathematical tools were employed to determine its mutational cost. We found that the amino acid sequence of C662-C671 epitope is entirely conserved across the observed major variants of SARS-CoV-2 in addition to SARS-CoV. Its conformation and accessibility are predicted to be conserved, even in the highly mutated Omicron variant. Costly mutational rate in the context of energy expenditure in genome replication and translation can explain this strict conservation. These observations may herald an approach to developing vaccine candidates for universal protection against emergent variants of coronavirus.

Stochastic fluctuations promote ordered pattern formation of cells in the Notch-Delta signaling pathway.

The Notch-Delta signaling pathway mediates cell differentiation implicated in many regulatory processes including spatiotemporal patterning in tissues by promoting alternate cell fates between neighboring cells. At the multicellular level, this "lateral inhibition" principle leads to checkerboard patterns with alternation of Sender and Receiver cells. While it is well known that stochasticity modulates cell fate specification, little is known about how stochastic fluctuations at the cellular level propagate during multicell pattern formation. Here, we model stochastic fluctuations in the Notch-Delta pathway in the presence of two different noise types-shot and white-for a multicell system. Our results show that intermediate fluctuations reduce disorder and guide the multicell lattice toward checkerboard-like patterns. By further analyzing cell fate transition events, we demonstrate that intermediate noise amplitudes provide enough perturbation to facilitate "proofreading" of disordered patterns and cause cells to switch to the correct ordered state (Sender surrounded by Receivers, and vice versa). Conversely, high noise can override environmental signals coming from neighboring cells and lead to switching between ordered and disordered patterns. Therefore, in analogy with spin glass systems, intermediate noise levels allow the multicell Notch system to escape frustrated patterns and relax towards the lower energy checkerboard pattern while at large noise levels the system is unable to find this ordered base of attraction.