The role of the Arp2/3 complex in shaping the dynamics and structures of branched actomyosin networks.

Actomyosin networks give cells the ability to move and divide. These networks contract and expand while being driven by active energy-consuming processes such as motor protein walking and actin polymerization. Actin dynamics is also regulated by actin-binding proteins, such as the actin-related protein 2/3 (Arp2/3) complex. This complex generates branched filaments, thereby changing the overall organization of the network. In this work, the spatiotemporal patterns of dynamical actin assembly accompanying the branching-induced reorganization caused by Arp2/3 were studied using a computational model (mechanochemical dynamics of active networks [MEDYAN]); this model simulates actomyosin network dynamics as a result of chemical reactions whose rates are modulated by rapid mechanical equilibration. We show that branched actomyosin networks relax significantly more slowly than do unbranched networks. Also, branched networks undergo rare convulsive movements, "avalanches," that release strain in the network. These avalanches are associated with the more heterogeneous distribution of mechanically linked filaments displayed by branched networks. These far-from-equilibrium events arising from the marginal stability of growing actomyosin networks provide a possible mechanism of the "cytoquakes" recently seen in experiments.

Chemistry-informed Machine Learning Explains Calcium-binding Proteins' Fuzzy Shape for Communicating Changes in the Atomic States of Calcium Ions.

Proteins' fuzziness are features for communicating changes in cell signaling instigated by binding with secondary messengers, such as calcium ions, associated with the coordination of muscle contraction, neurotransmitter release, and gene expression. Binding with the disordered parts of a protein, calcium ions must balance their charge states with the shape of calcium-binding proteins and their versatile pool of partners depending on the circumstances they transmit, but it is unclear whether the limited experimental data available can be used to train models to accurately predict the charges of calcium-binding protein variants. Here, we developed a chemistry-informed, machine-learning algorithm that implements a game theoretic approach to explain the output of a machine-learning model without the prerequisite of an excessively large database for high-performance prediction of atomic charges. We used the ab initio electronic structure data representing calcium ions and the structures of the disordered segments of calcium-binding peptides with surrounding water molecules to train several explainable models. Network theory was used to extract the topological features of atomic interactions in the structurally complex data dictated by the coordination chemistry of a calcium ion, a potent indicator of its charge state in protein. With our designs, we provided a framework of explainable machine learning model to annotate atomic charges of calcium ions in calcium-binding proteins with domain knowledge in response to the chemical changes in an environment based on the limited size of scientific data in a genome space.

OffRisk: a docker image for annotating CRISPR off-target sites in the human genome.

Summary: The CRISPR-Cas9 system has been adapted to achieve targeted genome editing as well as transcriptional control by customizing 20-nt guide RNA (gRNA) molecules for desired regions in the target genome. Designing gRNAs must consider nonspecific and unintended binding, known as off-targets, since these may have potentially harmful effects. To assist in gRNA design, we have developed OffRisk. This Docker-based tool annotates off-target sites in the human genome and assigns them a potential risk label by incorporating functional and regulatory information at different molecular levels. Availability and implementation: OffRisk is available at https://github.com/IsanaVekslerLublinsky/OffRisk and https://github.com/IsanaVekslerLublinsky/OffRisk-ui (including code, user guide, docker installation guide, and running examples).All processed datasets are available at https://zenodo.org/record/8289271.

Chromatin alternates between A and B compartments at kilobase scale for subgenic organization.

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling. Producing a large Hi-C map with 33 billion contacts in conjunction with an algorithm for performing principal component analysis on sparse, super massive matrices (POSSUMM), we resolve compartments to 500 bp. Our results demonstrate that essentially all active promoters and distal enhancers localize in the A compartment, even when flanking sequences do not. Furthermore, we find that the TSS and TTS of paused genes are often segregated into separate compartments. We then identify diffuse interactions that radiate from CTCF loop anchors, which correlate with strong enhancer-promoter interactions and proximal transcription. We also find that these diffuse interactions depend on CTCF's RNA binding domains. In this work, we demonstrate features of fine-scale chromatin organization consistent with a revised model in which compartments are more precise than commonly thought while CTCF loops are more protracted.

The ENCODE Uniform Analysis Pipelines.

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.

The ENCODE Uniform Analysis Pipelines.

The Encyclopedia of DNA elements (ENCODE) project is a collaborative effort to create a comprehensive catalog of functional elements in the human genome. The current database comprises more than 19000 functional genomics experiments across more than 1000 cell lines and tissues using a wide array of experimental techniques to study the chromatin structure, regulatory and transcriptional landscape of the Homo sapiens and Mus musculus genomes. All experimental data, metadata, and associated computational analyses created by the ENCODE consortium are submitted to the Data Coordination Center (DCC) for validation, tracking, storage, and distribution to community resources and the scientific community. The ENCODE project has engineered and distributed uniform processing pipelines in order to promote data provenance and reproducibility as well as allow interoperability between genomic resources and other consortia. All data files, reference genome versions, software versions, and parameters used by the pipelines are captured and available via the ENCODE Portal. The pipeline code, developed using Docker and Workflow Description Language (WDL; https://openwdl.org/) is publicly available in GitHub, with images available on Dockerhub (https://hub.docker.com), enabling access to a diverse range of biomedical researchers. ENCODE pipelines maintained and used by the DCC can be installed to run on personal computers, local HPC clusters, or in cloud computing environments via Cromwell. Access to the pipelines and data via the cloud allows small labs the ability to use the data or software without access to institutional compute clusters. Standardization of the computational methodologies for analysis and quality control leads to comparable results from different ENCODE collections - a prerequisite for successful integrative analyses.

Forecasting Avalanches in Branched Actomyosin Networks with Network Science and Machine Learning.

We explored the dynamic and structural effects of actin-related proteins 2/3 (Arp2/3) on actomyosin networks using mechanochemical simulations of active matter networks. On the nanoscale, the Arp2/3 complex alters the topology of actomyosin by nucleating a daughter filament at an angle with respect to a mother filament. At a subcellular scale, they orchestrate the formation of a branched actomyosin network. Using a coarse-grained approach, we sought to understand how an actomyosin network temporally and spatially reorganizes itself by varying the concentration of the Arp2/3 complexes. Driven by motor dynamics, the network stalls at a high concentration of Arp2/3 and contracts at a low Arp2/3 concentration. At an intermediate Arp2/3 concentration, however, the actomyosin network is formed by loosely connected clusters that may collapse suddenly when driven by motors. This physical phenomenon is called an "avalanche" largely due to the marginal instability inherent to the morphology of a branched actomyosin network when the Arp2/3 complex is present. While embracing the data science approaches, we unveiled the higher-order patterns in the branched actomyosin networks and discovered a sudden change in the "social" network topology of actomyosin, which is a new type of avalanche in addition to the two types of avalanches associated with a sudden change in the size or shape of the whole actomyosin network, as shown in a previous investigation. Our new finding promotes the importance of using network theory and machine learning models to forecast avalanches in actomyosin networks. The mechanisms of the Arp2/3 complexes in shaping the architecture of branched actomyosin networks obtained in this paper will help us better understand the emergent reorganization of the topology in dense actomyosin networks that are difficult to detect in experiments.

A genome-scale CRISPR Cas9 dropout screen identifies synthetically lethal targets in SRC-3 inhibited cancer cells.

Steroid receptor coactivator 3 (SRC-3/NCoA3/AIB1), is a key regulator of gene transcription and it plays a central role in breast cancer (BC) tumorigenesis, making it a potential therapeutic target. Beyond its function as an important regulator of estrogen receptor transcriptional activity, SRC-3 also functions as a coactivator for a wide range of other transcription factors, suggesting SRC-3 inhibition can be beneficial in hormone-independent cancers as well. The recent discovery of a potent SRC-3 small molecule inhibitor, SI-2, enabled the further development of additional related compounds. SI-12 is an improved version of SI-2 that like SI-2 has anti-proliferative activity in various cancer types, including BC. Here, we sought to identify gene targets, that when inhibited in the presence of SI-12, would lead to enhanced BC cell cytotoxicity. We performed a genome-scale CRISPR-Cas9 screen in MCF-7 BC cells under conditions of pharmacological pressure with SI-12. A parallel screen was performed with an ER inhibitor, fulvestrant, to shed light on both common and distinct activities between SRC-3 and ERα inhibition. Bearing in mind the key role of SRC-3 in tumorigenesis of other types of cancer, we extended our study by validating potential hits identified from the MCF-7 screen in other cancer cell lines.

CTCF loss has limited effects on global genome architecture in Drosophila despite critical regulatory functions.

Vertebrate genomes are partitioned into contact domains defined by enhanced internal contact frequency and formed by two principal mechanisms: compartmentalization of transcriptionally active and inactive domains, and stalling of chromosomal loop-extruding cohesin by CTCF bound at domain boundaries. While Drosophila has widespread contact domains and CTCF, it is currently unclear whether CTCF-dependent domains exist in flies. We genetically ablate CTCF in Drosophila and examine impacts on genome folding and transcriptional regulation in the central nervous system. We find that CTCF is required to form a small fraction of all domain boundaries, while critically controlling expression patterns of certain genes and supporting nervous system function. We also find that CTCF recruits the pervasive boundary-associated factor Cp190 to CTCF-occupied boundaries and co-regulates a subset of genes near boundaries together with Cp190. These results highlight a profound difference in CTCF-requirement for genome folding in flies and vertebrates, in which a large fraction of boundaries are CTCF-dependent and suggest that CTCF has played mutable roles in genome architecture and direct gene expression control during metazoan evolution.

Insights from graph theory on the morphologies of actomyosin networks with multilinkers.

Quantifying the influence of microscopic details on the dynamics of development of the overall structure of a filamentous network is important in a number of biologically relevant contexts, but it is not obvious what order parameters can be used to adequately describe this complex process. In this paper we investigated the role of multivalent actin-binding proteins (ABPs) in reorganizing actin filaments into higher-order complex networks via a computer model of semiflexible filaments. We characterize the importance of local connectivity among actin filaments, as well as the global features of actomyosin networks. We first map the networks into local graph representations and then, using principles from network-theory order parameters, combine properties from these representations to gain insight into the heterogeneous morphologies of actomyosin networks at a global level. We find that ABPs with a valency greater than 2 promote filament bundles and large filament clusters to a much greater extent than bivalent multilinkers. We also show that active myosinlike motor proteins promote the formation of dendritic branches from a stalk of actin bundles. Our work motivates future studies to embrace network theory as a tool to characterize complex morphologies of actomyosin detected by experiments, leading to a quantitative understanding of the role of ABPs in manipulating the self-assembly of actin filaments into unique architectures that underlie the structural scaffold of a cell relating to its mobility and shape.

Author Correction: Drug-induced PD-L1 expression and cell stress response in breast cancer cells can be balanced by drug combination.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Drug-induced PD-L1 expression and cell stress response in breast cancer cells can be balanced by drug combination.

The impact of chemotherapy on tumor-immune system interaction can be either beneficial or harmful, which is represented by the immunogenic cell death (ICD) paradigm or overexpression of the immunosuppressive protein - programmed death ligand 1 (PD-L1). In this study we explore the impact of steroid receptor coactivator inhibitor, other targeted anti-cancer compounds and traditional chemotherapeutic agents on the expression of PD-L1 in four breast cancer (BC) cell lines. Our results show that these agents induce PD-L1 expression, yet the magnitude of this induction varies substantially across the different compounds. In addition, we utilized the E0771 ER + BC cells as a model to examine in greater detail the relationship between pharmacological pressure, cell stress and the induction of PD-L1. Our results imply that drug induced PD-L1 expression occurs in the broader context of cell-stress, without conferring acquired drug-resistance. Furthermore, a balance between BC cytotoxicity, induction of cell-stress and the overexpression of PD-L1 can be achieved through the selection of appropriate combinations of anti-cancer compounds. Therefore, we propose that drug combination can be employed not only for increasing the direct kill of cancer cells, but also as a strategy to minimize the activation of immunosuppressive and cancer cell pro-survival program responses during drug treatment.

Impact of hydrodynamic interactions on protein folding rates depends on temperature.

We investigated the impact of hydrodynamic interactions (HI) on protein folding using a coarse-grained model. The extent of the impact of hydrodynamic interactions, whether it accelerates, retards, or has no effect on protein folding, has been controversial. Together with a theoretical framework of the energy landscape theory (ELT) for protein folding that describes the dynamics of the collective motion with a single reaction coordinate across a folding barrier, we compared the kinetic effects of HI on the folding rates of two protein models that use a chain of single beads with distinctive topologies: a 64-residue α/ß chymotrypsin inhibitor 2 (CI2) protein, and a 57-residue ß-barrel α-spectrin Src-homology 3 domain (SH3) protein. When comparing the protein folding kinetics simulated with Brownian dynamics in the presence of HI to that in the absence of HI, we find that the effect of HI on protein folding appears to have a "crossover" behavior about the folding temperature. This means that at a temperature greater than the folding temperature, the enhanced friction from the hydrodynamic solvents between the beads in an unfolded configuration results in lowered folding rate; conversely, at a temperature lower than the folding temperature, HI accelerates folding by the backflow of solvent toward the folded configuration of a protein. Additionally, the extent of acceleration depends on the topology of a protein: for a protein like CI2, where its folding nucleus is rather diffuse in a transition state, HI channels the formation of contacts by favoring a major folding pathway in a complex free energy landscape, thus accelerating folding. For a protein like SH3, where its folding nucleus is already specific and less diffuse, HI matters less at a temperature lower than the folding temperature. Our findings provide further theoretical insight to protein folding kinetic experiments and simulations.