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Understanding muscle contraction mechanisms is a standing challenge, and one of the approaches has been to create models of the sarcomere–the basic contractile unit of striated muscle. While these models have been successful in elucidating many aspects of muscle contraction, they fall short in explaining the energetics of functional phenomena, such as rigor, and in particular, their dependence on the concentrations of the biomolecules involved in the cross-bridge cycle. Our hypothesis posits that the stochastic time delay between ATP adsorption and ADP/Pi release in the cross-bridge cycle necessitates a modeling approach where the rates of these two reaction steps are controlled by two independent parts of the total free energy change of the hydrolysis reaction. To test this hypothesis, we built a two-filament, stochastic-mechanical half-sarcomere model that separates the energetic roles of ATP and ADP/Pi in the cross-bridge cycle’s free energy landscape. Our results clearly demonstrate that there is a nontrivial dependence of the cross-bridge cycle’s kinetics on the independent concentrations of ATP, ADP, and Pi. The simplicity of the proposed model allows for analytical solutions of the more basic systems, which provide novel insight into the dominant mechanisms driving some of the experimentally observed contractile phenomena. 

Cardiac adaptation to hypoxic injury is regulated by dynamic interactions between cardiomyocytes and macrophages, yet the impacts of immune phenotypes on cardiac structure and contractility remain poorly understood. To address this, we developed the immuno-heart on a chip, a novel in vitro platform to investigate cardiomyocyte–macrophage interactions under normoxic and hypoxic conditions. By integrating neonatal rat ventricular myocytes (NRVMs) and bone marrow-derived macrophages—polarized to pro-inflammatory (M1) or pro-healing (M2/M2*) phenotypes—we elucidated the dual protective and detrimental roles macrophages play in modulating cardiomyocyte cytoskeletal architecture and contractility. Pro-inflammatory stimulation reduced cardiomyocyte structural metrics (z-line length, fraction, and integrity) in normoxic co-cultures. Under hypoxia, M1-stimulated NRVM monocultures exhibited declines in cytoskeletal organization—quantified by actin and z-line orientational order parameters. Relative to monocultures, M1-stimulated co-cultures attenuated hypoxia-induced active stress declines but produced weaker normoxic stresses. In contrast, pro-healing stimulation improved normoxic z-line metrics and preserved post-hypoxia cytoskeletal organization but reduced normoxic contractility. Notably, M2-stimulated macrophages restored normoxic contractility and preserved post-hypoxia systolic stress, albeit with increased diastolic stress. RNAseq analysis of M2-stimulated co-cultures identified upregulated structural and immune pathways driving these hypoxia-induced changes. Cytokine profiles revealed stimulation-specific and density-dependent tumor necrosis factor-alpha and interleukin-10 secretion patterns. Together, these findings quantitatively link clinically relevant macrophage phenotypes and cytokines to distinct changes in cardiac structure and contractility, offering mechanistic insights into immune modulation of hypoxia-induced dysfunction. Moreover, the immuno-heart on a chip represents an innovative framework to guide the development of future therapies that integrate immune and cardiac targets to enhance patient outcomes. 

LMNA-related dilated cardiomyopathy (DCM) is an autosomal-dominant genetic condition with cardiomyocyte and conduction system dysfunction often resulting in heart failure or sudden death. The condition is caused by mutation in the Lamin A/C (LMNA) gene encoding Type-A nuclear lamin proteins involved in nuclear integrity, epigenetic regulation of gene expression, and differentiation. The molecular mechanisms of the disease are not completely understood, and there are no definitive treatments to reverse progression or prevent mortality. We investigated possible mechanisms of LMNA-related DCM using induced pluripotent stem cells derived from a family with a heterozygous LMNA c.357-2A>G splice-site mutation. We differentiated one LMNA-mutant iPSC line derived from an affected female (Patient) and two non-mutant iPSC lines derived from her unaffected sister (Control) and conducted single-cell RNA sequencing for 12 samples (four from Patients and eight from Controls) across seven time points: Day 0, 2, 4, 9, 16, 19, and 30. Our bioinformatics workflow identified 125,554 cells in raw data and 110,521 (88%) high-quality cells in sequentially processed data. Unsupervised clustering, cell annotation, and trajectory inference found complex heterogeneity: ten main cell types; many possible subtypes; and lineage bifurcation for cardiac progenitors to cardiomyocytes (CMs) and epicardium-derived cells (EPDCs). Data integration and comparative analyses of Patient and Control cells found cell type and lineage-specific differentially expressed genes (DEGs) with enrichment, supporting pathway dysregulation. Top DEGs and enriched pathways included 10 ZNF genes and RNA polymerase II transcription in pluripotent cells (PP); BMP4 and TGF Beta/BMP signaling, sarcomere gene subsets and cardiogenesis, CDH2 and EMT in CMs; LMNA and epigenetic regulation, as well as DDIT4 and mTORC1 signaling in EPDCs. Top DEGs also included XIST and other X-linked genes, six imprinted genes (SNRPN, PWAR6, NDN, PEG10, MEG3, MEG8), and enriched gene sets related to metabolism, proliferation, and homeostasis. We confirmed Lamin A/C haploinsufficiency by allelic expression and Western blot. Our complex Patient-derived iPSC model for Lamin A/C haploinsufficiency in PP, CM, and EPDC provided support for dysregulation of genes and pathways, many previously associated with Lamin A/C defects, such as epigenetic gene expression, signaling, and differentiation. Our findings support disruption of epigenomic developmental programs, as proposed in other LMNA disease models. We recognized other factors influencing epigenetics and differentiation; thus, our approach needs improvement to further investigate this mechanism in an iPSC-derived model. 

Unbiased evaluation of morphology is crucial to understanding development, mechanics, and pathology of striated muscle tissues. Indeed, the ability of striated muscles to contract and the strength of their contraction is dependent on their tissue-, cellular-, and cytoskeletal-level organization. Accordingly, the study of striated muscles often requires imaging and assessing aspects of their architecture at multiple different spatial scales. While an expert may be able to qualitatively appraise tissues, it is imperative to have robust, repeatable tools to quantify striated myocyte morphology and behavior that can be used to compare across different labs and experiments. There has been a recent effort to define the criteria used by experts to evaluate striated myocyte architecture. In this review, we will describe metrics that have been developed to summarize distinct aspects of striated muscle architecture in multiple different tissues, imaged with various modalities. Additionally, we will provide an overview of metrics and image processing software that needs to be developed. Importantly to any lab working on striated muscle platforms, characterization of striated myocyte morphology using the image processing pipelines discussed in this review can be used to quantitatively evaluate striated muscle tissues and contribute to a robust understanding of the development and mechanics of striated muscles. 

Abstract Through a variety of mechanisms, a healthy heart is able to regulate its structure and dynamics across multiple length scales. Disruption of these mechanisms can have a cascading effect, resulting in severe structural and/or functional changes that permeate across different length scales. Due to this hierarchical structure, there is interest in understanding how the components at the various scales coordinate and influence each other. However, much is unknown regarding how myofibril bundles are organized within a densely packed cell and the influence of the subcellular components on the architecture that is formed. To elucidate potential factors influencing cytoskeletal development, we proposed a computational model that integrated interactions at both the cellular and subcellular scale to predict the location of individual myofibril bundles that contributed to the formation of an energetically favorable cytoskeletal network. Our model was tested and validated using experimental metrics derived from analyzing single-cell cardiomyocytes. We demonstrated that our model-generated networks were capable of reproducing the variation observed in experimental cells at different length scales as a result of the stochasticity inherent in the different interactions between the various cellular components. Additionally, we showed that incorporating length-scale parameters resulted in physical constraints that directed cytoskeletal architecture toward a structurally consistent motif. Understanding the mechanisms guiding the formation and organization of the cytoskeleton in individual cardiomyocytes can aid tissue engineers toward developing functional cardiac tissue. 

The heart has a dynamic mechanical environment contributed by its unique cellular composition and the resultant complex tissue structure. In pathological heart tissue, both the mechanics and cell composition can change and influence each other. As a result, the interplay between the cell phenotype and mechanical stimulation needs to be considered to understand the biophysical cell interactions and organization in healthy and diseased myocardium. In this work, we hypothesized that the overall tissue organization is controlled by varying densities of cardiomyocytes and fibroblasts in the heart. In order to test this hypothesis, we utilized a combination of mechanical strain, co-cultures of different cell types, and inhibitory drugs that block intercellular junction formation. To accomplish this, an image analysis pipeline was developed to automatically measure cell type-specific organization relative to the stretch direction. The results indicated that cardiac cell type-specific densities influence the overall organization of heart tissue such that it is possible to model healthy and fibrotic heart tissue in vitro. This study provides insight into how to mimic the dynamic mechanical environment of the heart in engineered tissue as well as providing valuable information about the process of cardiac remodeling and repair in diseased hearts. 

Understanding force propagation through the fibrous extracellular matrix can elucidate how cells interact mechanically with their surrounding tissue. Presumably, due to elastic nonlinearities of the constituent filaments and their random connection topology, force propagation in fiber networks is quite complex, and the basic problem of force propagation in structurally heterogeneous networks remains unsolved. We report on a new technique to detect displacements through such networks in response to a localized force, using a fibrin hydrogel as an example. By studying the displacements of fibers surrounding a two-micron bead that is driven sinusoidally by optical tweezers, we develop maps of displacements in the network. Fiber movement is measured by fluorescence intensity fluctuations recorded by a laser scanning confocal microscope. We find that the Fourier magnitude of these intensity fluctuations at the drive frequency identifies fibers that are mechanically coupled to the driven bead. By examining the phase relation between the drive and the displacements, we show that the fiber displacements are, indeed, due to elastic couplings within the network. Both the Fourier magnitude and phase depend on the direction of the drive force, such that displacements typically propagate farther, but not exclusively, along the drive direction. This technique may be used to characterize the local mechanical response in 3-D tissue cultures, and to address fundamental questions about force propagation within fiber networks. 

While the fundamental steps outlining myofibril formation share a similar scheme for different cell and species types, various granular details involved in the development of a functional contractile muscle are not well understood. Many studies of myofibrillogenesis focus on the protein interactions that are involved in myofibril maturation with the assumption that there is a fully formed premyofibril at the start of the process. However, there is little known regarding how the premyofibril is initially constructed. Fortunately, the protein α-actinin, which has been consistently identified throughout the maturation process, is found in premyofibrils as punctate aggregates known as z-bodies. We propose a theoretical model based on the particle swarm optimization algorithm that can explore how these α-actinin clusters form into the patterns observed experimentally. Our algorithm can produce different pattern configurations by manipulating specific parameters that can be related to α-actinin mobility and binding affinity. These patterns, which vary experimentally according to species and muscle cell type, speak to the versatility of α-actinin and demonstrate how its behavior may be altered through interactions with various regulatory, signaling, and metabolic proteins. The results of our simulations invite speculation that premyofibrils can be influenced toward developing different patterns by altering the behavior of individual α-actinin molecules, which may be linked to key differences present in different cell types. 

Abstract Genetic mutations to the Lamin A/C gene (LMNA) can cause heart disease, but the mechanisms making cardiac tissues uniquely vulnerable to the mutations remain largely unknown. Further, patients withLMNAmutations have highly variable presentation of heart disease progression and type.In vitropatient-specific experiments could provide a powerful platform for studying this phenomenon, but the use of induced pluripotent stem cell-derived cardiomyocytes (iPSC-CM) introduces heterogeneity in maturity and function thus complicating the interpretation of the results of any single experiment. We hypothesized that integrating single cell RNA sequencing (scRNA-seq) with analysis of the tissue architecture and contractile function would elucidate some of the probable mechanisms. To test this, we investigated five iPSC-CM lines, three controls and two patients with a (c.357-2A>G) mutation. The patient iPSC-CM tissues had significantly weaker stress generation potential than control iPSC-CM tissues demonstrating the viability of ourin vitroapproach. Through scRNA-seq, differentially expressed genes between control and patient lines were identified. Some of these genes, linked to quantitative structural and functional changes, were cardiac specific, explaining the targeted nature of the disease progression seen in patients. The results of this work demonstrate the utility of combiningin vitrotools in exploring heart disease mechanics.