Nuclear receptor Nur77 regulates immunomechanics of macrophages.

Nuclear receptor Nur77 plays a pivotal role in immune regulation across various tissues, influencing pro-inflammatory signaling pathways and cellular metabolism. While cellular mechanics have been implicated in inflammation, the contribution of Nur77 to these mechanical processes remains elusive. Macrophages exhibit remarkable plasticity in their morphology and mechanics, enabling them to adapt and execute essential inflammatory functions, such as navigating through inflamed tissue and pathogen engulfment. However, the precise regulatory mechanisms governing these dynamic changes in macrophage mechanics during inflammation remain poorly understood. To establish the potential correlation of Nur77 with cellular mechanics, we compared bone marrow-derived macrophages (BMDMs) from wild-type (WT) and Nur77-deficient (Nur77-KO) mice and employed cytoskeletal imaging, single-cell acoustic force spectroscopy (AFS), migration and phagocytosis assays, and RNA-sequencing. Our findings reveal that Nur77-KO BMDMs exhibit changes to their actin networks compared to WT BMDMs, which is associated with a stiffer and more rigid phenotype. Subsequent in vitro experiments validated our observations, showcasing that Nur77 deficiency leads to enhanced migration, reduced adhesion, and increased phagocytic activity. The transcriptomics data confirmed altered mechanics-related pathways in Nur77-deficient macrophage that are accompanied by a robust pro-inflammatory phenotype. Utilizing previously obtained ChIP-data, we revealed that Nur77 directly targets differentially expressed genes associated with cellular mechanics. In conclusion, while Nur77 is recognized for its role in reducing inflammation of macrophages by inhibiting the expression of pro-inflammatory genes, our study identifies a novel regulatory mechanism where Nur77 governs macrophage inflammation through the modulation of expression of genes involved in cellular mechanics. Our findings suggest that immune regulation by Nur77 may be partially mediated through alterations in cellular mechanics, highlighting a potential avenue for therapeutic targeting.

Probing human immune cell mechanics using acoustic force spectroscopy.

Immune cells continuously adapt their mechanical properties for proper circulation and elicitation of immune responses. Here, we provide a step-by-step protocol for probing the single-cell mechanical properties of primary human monocytes using acoustic force spectroscopy (AFS). We describe steps for the calibration of the AFS chips, the isolation of monocytes from buffy coats, and the probing of monocyte mechanics using AFS. We then detail the data analysis strategy. The protocol is useful for characterizing a wide range of immune cells under various conditions in physiology and pathology. For complete details on the use and execution of this protocol, please refer to Evers et al. 1 and Evers et al.2.

Aggregation and structural phase transitions of semiflexible polymer bundles: A braided circuit topology approach.

We present a braided circuit topology framework for investigating topology and structural phase transitions in aggregates of semiflexible polymers. In the conventional approach to circuit topology, which specifically applies to single isolated folded linear chains, the number and arrangement of contacts within the circuitry of a folded chain give rise to increasingly complex fold topologies. Another avenue for achieving complexity is through the interaction and entanglement of two or more folded linear chains. The braided circuit topology approach describes the topology of such multiple-chain systems and offers topological measures such as writhe, complexity, braid length, and isotopy class. This extension of circuit topology to multichains reveals the interplay between collapse, aggregation, and entanglement. In this work, we show that circuit topological motif fractions are ideally suited order parameters to characterize structural phase transitions in entangled systems that can detect structural re-ordering other measures cannot.

Random forest and live single-cell metabolomics reveal metabolic profiles of human macrophages upon polarization.

Human macrophages are innate immune cells with diverse, functionally distinct phenotypes, namely, pro-inflammatory M1 and anti-inflammatory M2 macrophages. Both are involved in multiple physiological and pathological processes, including would healing, infection, and cancer. However, the metabolic differences between these phenotypes are largely unexplored at single-cell resolution. To address this knowledge gap, an untargeted live single-cell mass spectrometry-based metabolomic profiling coupled with a machine-learning data analysis approach was developed to investigate the metabolic profile of each phenotype at the single-cell level. Results show that M1 and M2 macrophages have distinct metabolic profiles, with differential levels of fatty acyls, glycerophospholipids, and sterol lipids, which are important components of plasma membrane and involved in multiple biological processes. Furthermore, we could discern several putatively annotated molecules that contribute to inflammatory response of macrophages. The combination of random forest and live single-cell metabolomics provided an in-depth profile of the metabolome of primary human M1 and M2 macrophages at the single-cell level for the first time, which will pave the way for future studies targeting the differentiation of other immune cells.

Decoding chirality in circuit topology of a self entangled chain through braiding.

Circuit topology employs fundamental units of entanglement, known as soft contacts, for constructing knots from the bottom up, utilizing circuit topology relations, namely parallel, series, cross, and concerted relations. In this article, we further develop this approach to facilitate the analysis of chirality, which is a significant quantity in polymer chemistry. To achieve this, we translate the circuit topology approach to knot engineering into a braid-theoretic framework. This enables us to calculate the Jones polynomial for all possible binary combinations of contacts in cross or concerted relations and to show that, for series and parallel relations, the polynomial factorises. Our results demonstrate that the Jones polynomial provides a powerful tool for analysing the chirality of molecular knots constructed using circuit topology. The framework presented here can be used to design and engineer a wide range of entangled chain with desired chiral properties, with potential applications in fields such as materials science and nanotechnology.

Cytosolic Interactome Protects Against Protein Unfolding in a Single Molecule Experiment.

Single molecule techniques are particularly well suited for investigating the processes of protein folding and chaperone assistance. However, current assays provide only a limited perspective on the various ways in which the cellular environment can influence the folding pathway of a protein. In this study, a single molecule mechanical interrogation assay is developed and used to monitor protein unfolding and refolding within a cytosolic solution. This allows to test the cumulative topological effect of the cytoplasmic interactome on the folding process. The results reveal a stabilization against forced unfolding for partial folds, which are attributed to the protective effect of the cytoplasmic environment against unfolding and aggregation. This research opens the possibility of conducting single molecule molecular folding experiments in quasi-biological environments.

A tile model of circuit topology for self-entangled biopolymers.

Building on the theory of circuit topology for intra-chain contacts in entangled proteins, we introduce tiles as a way to rigorously model local entanglements which are held in place by molecular forces. We develop operations that combine tiles so that entangled chains can be represented by algebraic expressions. Then we use our model to show that the only knot types that such entangled chains can have are [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text], [Formula: see text] and connected sums of these knots. This includes all proteins knots that have thus far been identified.

Circuit Topology Approach for the Comparative Analysis of Intrinsically Disordered Proteins.

Intrinsically disordered proteins (IDPs) lack a stable native conformation, making it challenging to characterize their structure and dynamics. Key topological motifs with fundamental biological relevance are often hidden in the conformational noise, eluding detection. Here, we develop a circuit topology toolbox to extract conformational patterns, critical contacts, and timescales from simulated dynamics of intrinsically disordered proteins. We follow the dynamics of IDPs by providing a smart low-dimensionality representation of their three-dimensional (3D) configuration in the topology space. Such an approach allows us to quantify topological similarity in dynamic systems, therefore providing a pipeline for structural comparison of IDPs.

Ebola virus-like particles reprogram cellular metabolism.

Ebola virus can trigger a release of pro-inflammatory cytokines with subsequent vascular leakage and impairment of clotting finally leading to multiorgan failure and shock after entering and infecting patients. Ebola virus is known to directly target endothelial cells and macrophages, even without infecting them, through direct interactions with viral proteins. These interactions affect cellular mechanics and immune processes, which are tightly linked to other key cellular functions such as metabolism. However, research regarding metabolic activity of these cells upon viral exposure remains limited, hampering our understanding of its pathophysiology and progression. Therefore, in the present study, an untargeted cellular metabolomic approach was performed to investigate the metabolic alterations of primary human endothelial cells and M1 and M2 macrophages upon exposure to Ebola virus-like particles (VLP). The results show that Ebola VLP led to metabolic changes among endothelial, M1, and M2 cells. Differential metabolite abundance and perturbed signaling pathway analysis further identified specific metabolic features, mainly in fatty acid-, steroid-, and amino acid-related metabolism pathways for all the three cell types, in a host cell specific manner. Taken together, this work characterized for the first time the metabolic alternations of endothelial cells and two primary human macrophage subtypes after Ebola VLP exposure, and identified the potential metabolites and pathways differentially affected, highlighting the important role of those host cells in disease development and progression. KEY MESSAGES: • Ebola VLP can lead to metabolic alternations in endothelial cells and M1 and M2 macrophages. • Differential abundance of metabolites, mainly including fatty acids and sterol lipids, was observed after Ebola VLP exposure. • Multiple fatty acid-, steroid-, and amino acid-related metabolism pathways were observed perturbed.

Biochemical reaction network topology defines dose-dependent Drug-Drug interactions.

Drug combination therapy is a promising strategy to enhance the desired therapeutic effect, while reducing side effects. High-throughput pairwise drug combination screening is a commonly used method for discovering favorable drug interactions, but is time-consuming and costly. Here, we investigate the use of reaction network topology-guided design of combination therapy as a predictive in silico drug-drug interaction screening approach. We focused on three-node enzymatic networks, with general Michaelis-Menten kinetics. The results revealed that drug-drug interactions critically depend on the choice of target arrangement in a given topology, the nature of the drug, and the desired level of change in the network output. The results showed a negative correlation between antagonistic interactions and the dosage of drugs. Overall, the negative feedback loops showed the highest synergistic interactions (the lowest average combination index) and, intriguingly, required the highest drug doses compared to other topologies under the same condition.

Direct observation of Hsp90-induced compaction in a protein chain.

The chaperone heat shock protein 90 (Hsp90) is well known to undergo important conformational changes, which depend on nucleotide and substrate interactions. Conversely, how the conformations of its unstable and disordered substrates are affected by Hsp90 is difficult to address experimentally yet is central to its function. Here, using optical tweezers, we find that Hsp90 promotes local contractions in unfolded chains that drive their global compaction down to dimensions of folded states. This compaction has a gradual nature while showing small steps, is stimulated by ATP, and performs mechanical work against counteracting forces that expand the chain dimensions. The Hsp90 interactions suppress the formation of larger-scale folded, misfolded, and aggregated structures. The observations support a model in which Hsp90 alters client conformations directly by promoting local intra-chain interactions while suppressing distant ones. We conjecture that chain compaction may be central to how Hsp90 protects unstable clients and cooperates with Hsp70.

ProteinCT: An implementation of the protein circuit topology framework.

The ability to describe the topology of a folded protein conformation is critically important for functional analysis, protein engineering, and drug design. Circuit topology is a unique topological framework which is widely applicable to protein analysis, yet a state-of-the art implementation of this concept is lacking. Here, we present an open-source Python-implemented circuit topology tool called ProteinCT. The platform provides a method for acquiring, visualizing, analyzing, and quantifying circuit topology data from proteins of interest. We mapped the universe of human proteins to a circuit topology space using conventional hardware within a few hours, demonstrating the performance of ProteinCT. In brief,•A Python-implemented circuit topology tool is developed to extract global and local topological information from a protein structure file.•Modules are developed to combine topological information with geometric and energetic information.•It is demonstrated that the method can be efficiently applied to a large set of proteins, opening a wide range of possibilities for structural proteomics research.

Histone lysine demethylase inhibition reprograms prostate cancer metabolism and mechanics.

OBJECTIVE: Aberrant activity of androgen receptor (AR) is the primary cause underlying development and progression of prostate cancer (PCa) and castration-resistant PCa (CRPC). Androgen signaling regulates gene transcription and lipid metabolism, facilitating tumor growth and therapy resistance in early and advanced PCa. Although direct AR signaling inhibitors exist, AR expression and function can also be epigenetically regulated. Specifically, lysine (K)-specific demethylases (KDMs), which are often overexpressed in PCa and CRPC phenotypes, regulate the AR transcriptional program. METHODS: We investigated LSD1/UTX inhibition, two KDMs, in PCa and CRPC using a multi-omics approach. We first performed a mitochondrial stress test to evaluate respiratory capacity after treatment with MC3324, a dual KDM-inhibitor, and then carried out lipidomic, proteomic, and metabolic analyses. We also investigated mechanical cellular properties with acoustic force spectroscopy. RESULTS: MC3324 induced a global increase in H3K4me2 and H3K27me3 accompanied by significant growth arrest and apoptosis in androgen-responsive and -unresponsive PCa systems. LSD1/UTX inhibition downregulated AR at both transcriptional and non-transcriptional level, showing cancer selectivity, indicating its potential use in resistance to androgen deprivation therapy. Since MC3324 impaired metabolic activity, by modifying the protein and lipid content in PCa and CRPC cell lines. Epigenetic inhibition of LSD1/UTX disrupted mitochondrial ATP production and mediated lipid plasticity, which affected the phosphocholine class, an important structural element for the cell membrane in PCa and CRPC associated with changes in physical and mechanical properties of cancer cells. CONCLUSIONS: Our data suggest a network in which epigenetics, hormone signaling, metabolite availability, lipid content, and mechano-metabolic process are closely related. This network may be able to identify additional hotspots for pharmacological intervention and underscores the key role of KDM-mediated epigenetic modulation in PCa and CRPC.

Topological dynamics of an intrinsically disordered N-terminal domain of the human androgen receptor.

Human androgen receptor contains a large N-terminal domain (AR-NTD) that is highly dynamic and this poses a major challenge for experimental and computational analysis to decipher its conformation. Misfolding of the AR-NTD is implicated in prostate cancer and Kennedy's disease, yet our knowledge of its structure is limited to primary sequence information of the chain and a few functionally important secondary structure motifs. Here, we employed an innovative combination of molecular dynamics simulations and circuit topology (CT) analysis to identify the tertiary structure of AR-NTD. We found that the AR-NTD adopts highly dynamic loopy conformations with two identifiable regions with distinct topological make-up and dynamics. This consists of a N-terminal region (NR, residues 1-224) and a C-terminal region (CR, residues 225-538), which carries a dense core. Topological mapping of the dynamics reveals a traceable time-scale dependent topological evolution. NR adopts different positioning with respect to the CR and forms a cleft that can partly enclose the hormone-bound ligand-binding domain (LBD) of the androgen receptor. Furthermore, our data suggest a model in which dynamic NR and CR compete for binding to the DNA-binding domain of the receptor, thereby regulating the accessibility of its DNA-binding site. Our approach allowed for the identification of a previously unknown regulatory binding site within the CR core, revealing the structural mechanisms of action of AR inhibitor EPI-001, and paving the way for other drug discovery applications.

Capillary microsampling-based single-cell metabolomics by mass spectrometry and its applications in medicine and drug discovery.

Characterization of cellular metabolic states is a technical challenge in biomedicine. Cellular heterogeneity caused by inherent diversity in expression of metabolic enzymes or due to sensitivity of metabolic reactions to perturbations, necessitates single cell analysis of metabolism. Heterogeneity is typically seen in cancer and thus, single-cell metabolomics is expectedly useful in studying cancer progression, metastasis, and variations in cancer drug response. However, low sample volumes and analyte concentrations limit detection of critically important metabolites. Capillary microsampling-based mass spectrometry approaches are emerging as a promising solution for achieving single-cell omics. Herein, we focus on the recent advances in capillary microsampling-based mass spectrometry techniques for single-cell metabolomics. We discuss recent technical developments and applications to cancer medicine and drug discovery.

Circuit topology predicts pathogenicity of missense mutations.

The contact topology of a protein determines important aspects of the folding process. The topological measure of contact order has been shown to be predictive of the rate of folding. Circuit topology is emerging as another fundamental descriptor of biomolecular structure, with predicted effects on the folding rate. We analyze the residue-based circuit topological environments of 21 K mutations labeled as pathogenic or benign. Multiple statistical lines of reasoning support the conclusion that the number of contacts in two specific circuit topological arrangements, namely inverse parallel and cross relations, with contacts involving the mutated residue have discriminatory value in determining the pathogenicity of human variants. We investigate how results vary with residue type and according to whether the gene is essential. We further explore the relationship to a number of structural features and find that circuit topology provides nonredundant information on protein structures and pathogenicity of mutations. Results may have implications for the polymer physics of protein folding and suggest that "local" topological information, including residue-based circuit topology and residue contact order, could be useful in improving state-of-the-art machine learning algorithms for pathogenicity prediction.

Circuit topology analysis of cellular genome reveals signature motifs, conformational heterogeneity, and scaling.

Reciprocal regulation of genome topology and function is a fundamental and enduring puzzle in biology. The wealth of data provided by Hi-C libraries offers the opportunity to unravel this relationship. However, there is a need for a comprehensive theoretical framework in order to extract topological information for genome characterization and comparison. Here, we develop a toolbox for topological analysis based on Circuit Topology, allowing for the quantification of inter- and intracellular genomic heterogeneity, at various levels of fold complexity: pairwise contact arrangement, higher-order contact arrangement, and topological fractal dimension. Single-cell Hi-C data were analyzed and characterized based on topological content, revealing not only a strong multiscale heterogeneity but also highly conserved features such as a characteristic topological length scale and topological signature motifs in the genome. We propose that these motifs inform on the topological state of the nucleus and indicate the presence of active loop extrusion.

Single cell force spectroscopy of erythrocytes at physiological and febrile temperatures reveals mechano-modulatory effects of atorvastatin.

RBCs are mechanically active cells and constantly deform as they circulate through vasculature. Their mechanical properties can be significantly altered by various pathophysiological conditions, and the alterations in RBC mechanics can, in turn, have functional consequences. Although numerous mechanical studies have been conducted on RBCs, surprisingly, strain-rate and temperature dependent mechanics of RBCs have not been systematically examined, and current data is primarily based on measurements at room temperature. Here, we have used state-of-the-art single-cell optical tweezers to probe atorvastatin-induced changes of RBC mechanics and its strain-rate dependency at physiologically and medically relevant temperatures. Our data indicate that RBC mechanics is strain-rate and temperature dependent, and atorvastatin treatment softens RBCs at physiological temperature, but not at febrile temperature. The observed mechanical change is a notable side effect of the drug in some therapeutic applications. However, the mechano-modulatory effects of atorvastatin on erythrocytes at physiological temperature might offer new therapeutic possibilities for diseases related to blood cell mechanics.

Single-cell analysis reveals chemokine-mediated differential regulation of monocyte mechanics.

Monocytes continuously adapt their shapes for proper circulation and elicitation of effective immune responses. Although these functions depend on the cell mechanical properties, the mechanical behavior of monocytes is still poorly understood and accurate physiologically relevant data on basic mechanical properties are lacking almost entirely. By combining several complementary single-cell force spectroscopy techniques, we report that the mechanical properties of human monocyte are strain-rate dependent, and that chemokines can induce alterations in viscoelastic behavior. In addition, our findings indicate that human monocytes are heterogeneous mechanically and this heterogeneity is regulated by chemokine CCL2. The technology presented here can be readily used to reveal mechanical complexity of the blood cell population in disease conditions, where viscoelastic properties may serve as physical biomarkers for disease progression and response to therapy.

A Microfluidics-Based Screening Tool to Assess the Impact of Blood Plasma Factors on Microvascular Integrity.

This study provides a method to assess the impact of circulating plasma factors on microvascular integrity by using a recently developed microvessel-on-a-chip platform featuring the human endothelium that is partly surrounded by the extracellular matrix. The system is high-throughput, which allows parallel analysis of organ-level microvessel pathophysiology, including vascular leakage. Ethylenediaminetetraacetic acid plasma samples are mixed with inhibitors for recalcification of the plasma samples to avoid activation of the coagulation- or complement system. Moreover, the assay is validated by spiking vascular endothelial growth factor, histamine, or tumor necrosis factor alpha to recalcified plasma and confirms their modulation of microvessel barrier function at physiologically relevant concentrations. Finally, this study shows that perfusing the microvessels with recalcified plasma samples of coronavirus disease-2019 patients, with a confirmed proinflammatory profile, results in markedly increased leakage of the microvessels. The assay provides opportunities for diagnostic screening of inflammatory or endothelial disrupting plasma factors associated with endothelial dysfunction.