In Silico and In Vivo Experiments Reveal M-CSF Injections Accelerate Regeneration Following Muscle Laceration

Freeze-Dried Porous Collagen Scaffolds for the Repair of Volumetric Muscle Loss Injuries

Volumetric muscle loss (VML) injuries are characterized by the traumatic loss of skeletal muscle, resulting in permanent damage to both tissue architecture and electrical excitability. To address this challenge, we previously developed a three-dimensional (3D) aligned collagen-glycosaminoglycan (CG) scaffold platform that supported in vitro myotube alignment and maturation. In this work, we assessed the ability of CG scaffolds to facilitate functional muscle recovery in a rat tibialis anterior (TA) model of VML. Functional muscle recovery was assessed following implantation of either nonconductive CG or electrically conductive CG-polypyrrole (PPy) scaffolds at 4, 8, and 12 weeks postinjury by in vivo electrical stimulation of the peroneal nerve. After 12 weeks, scaffold-treated muscles produced maximum isometric torque that was significantly greater than nontreated tissues. Histological analysis further supported these reparative outcomes with evidence of regenerating muscle fibers at the material-tissue interface in scaffold-treated tissues that were not observed in nonrepaired muscles. Scaffold-treated muscles possessed higher numbers of M1 and M2 macrophages at the injury, while conductive CG-PPy scaffold-treated muscles showed significantly higher levels of neovascularization as indicated by the presence of pericytes and endothelial cells, suggesting a persistent wound repair response not observed in nontreated tissues. Finally, only tissues treated with nonconductive CG scaffolds displayed neurofilament staining similar to native muscle, further corroborating isometric contraction data. Together, these findings show that both conductive and nonconductive CG scaffolds can facilitate improved skeletal muscle function and endogenous cellular repair, highlighting their potential use as therapeutics for VML injuries.

Multiscale computational model predicts how environmental changes and treatments affect microvascular remodeling in fibrotic disease

Investigating the molecular, cellular, and tissue-level changes caused by disease, and the effects of pharmacological treatments across these biological scales, necessitates the use of multiscale computational modeling in combination with experimentation. Many diseases dynamically alter the tissue microenvironment in ways that trigger microvascular network remodeling, which leads to the expansion or regression of microvessel networks. When microvessels undergo remodeling in idiopathic pulmonary fibrosis (IPF), functional gas exchange is impaired and lung function declines. We integrated a multiscale computational model with independent experiments to investigate how combinations of biomechanical and biochemical cues in IPF alter cell fate decisions leading to microvascular remodeling. Our computational model predicted that extracellular matrix (ECM) stiffening reduced microvessel area, which was accompanied by physical uncoupling of endothelial cell (EC) and pericytes, the cells that comprise microvessels. Nintedanib, an Food and Drug Administration-approved drug for treating IPF, was predicted to further potentiate microvessel regression by decreasing the percentage of quiescent pericytes while increasing the percentage of pericytes undergoing pericyte-myofibroblast transition in high ECM stiffnesses. Importantly, the model suggested that YAP/TAZ inhibition may overcome the deleterious effects of nintedanib by promoting EC-pericyte coupling and maintaining microvessel homeostasis. Overall, our combination of computational and experimental modeling can predict and explain how cell decisions affect tissue changes during disease and in response to treatments.

Causal roles of circulating cytokines in sarcopenia-related traits: a Mendelian randomization study

Background

Epidemiological and experimental evidence suggests that chronic inflammation plays an important role in the onset and progression of sarcopenia. However, there is inconsistent data on the inflammatory cytokines involved in the pathogenesis of sarcopenia. Therefore, we performed a two-sample Mendelian randomization (MR) analysis to explore the causal relationship between circulating cytokines and sarcopenia-related traits.

Methods

The MR analysis utilized genetic data from genome-wide association study that included genetic variations in 41 circulating cytokines and genetic variant data for appendicular lean mass (ALM), hand grip strength, and usual walking pace. Causal associations were primarily explored using the inverse variance-weighted (IVW) method, supplemented by MR-Egger, simple mode, weighted median, and weighted mode analyses. Additionally, sensitivity analyses were also performed to ensure the reliability and stability of the results.

Results

Three cytokines [hepatocyte growth factor (HGF), interferon gamma-induced protein 10 (IP-10), and macrophage colony-stimulating factor (M-CSF)] were positively associated with ALM (β: 0.0221, 95% confidence interval (CI): 0.0071, 0.0372, P= 0.0039 for HGF; β: 0.0096, 95%CI: 4e-04, 0.0189, P= 0.0419 for IP-10; and β: 0.0100, 95%CI: 0.0035, 0.0165, P= 0.0025 for M-CSF). Conversely, higher levels of interleukin-7 (IL-7), monocyte chemotactic protein 3 (MCP-3), and regulated on activation, normal T cell expressed and secreted (RANTES) were associated with decreased hand grip strength (β: -0.0071, 95%CI: -0.0127, -0.0014, P= 0.0140 for IL-7; β: -0.0064, 95%CI: -0.0123, -6e-04, P= 0.0313 for MCP-3; and β: -0.0082, 95%CI: -0.0164, -1e-04, P= 0.0480 for RANTES). Similarly, interleukin 1 receptor antagonist (IL-1RA) was negatively correlated with usual walking pace (β: -0.0104, 95%CI: -0.0195, -0.0013, P= 0.0254). Sensitivity analysis confirmed the robustness of these findings.

Conclusions

Our study provides additional insights into the pivotal role of specific inflammatory cytokines in the pathogenesis of sarcopenia. Further research is required to determine whether these cytokines can be used as targets for the prevention and treatment of sarcopenia.

Freeze-dried porous collagen scaffolds for the repair of volumetric muscle loss injuries

Volumetric muscle loss (VML) injuries are characterized by the traumatic loss of skeletal muscle resulting in permanent damage to both tissue architecture and electrical excitability. To address this challenge, we previously developed a 3D aligned collagen-glycosaminoglycan (CG) scaffold platform that supported in vitro myotube alignment and maturation. In this work, we assessed the ability of CG scaffolds to facilitate functional muscle recovery in a rat tibialis anterior (TA) model of VML. Functional muscle recovery was assessed following implantation of either non-conductive CG or electrically conductive CG-polypyrrole (PPy) scaffolds at 4, 8, and 12 weeks post-injury by in vivo electrical stimulation of the peroneal nerve. After 12 weeks, scaffold-treated muscles produced maximum isometric torque that was significantly greater than non-treated tissues. Histological analysis further supported these reparative outcomes with evidence of regenerating muscle fibers at the material-tissue interface in scaffold-treated tissues that was not observed in non-repaired muscles. Scaffold-treated muscles possessed higher numbers of M1 and M2 macrophages at the injury while conductive CG-PPy scaffold-treated muscles showed significantly higher levels of neovascularization as indicated by the presence of pericytes and endothelial cells, suggesting a persistent wound repair response not observed in non-treated tissues. Finally, only tissues treated with non-conductive CG scaffolds displayed neurofilament staining similar to native muscle, further corroborating isometric contraction data. Together, these findings show that CG scaffolds can facilitate improved skeletal muscle function and endogenous cellular repair, highlighting their potential use as therapeutics for VML injuries.

The Wound Environment Agent-based Model (WEABM): a digital twin platform for characterization and complex therapeutic discovery for volumetric muscle loss

Volumetric Muscle Loss (VML) injuries are characterized by significant loss of muscle mass, usually due to trauma or surgical resection, often with a residual open wound in clinical settings and subsequent loss of limb function due to the replacement of the lost muscle mass with non-functional scar. Being able to regrow functional muscle in VML injuries is a complex control problem that needs to override robust, evolutionarily conserved healing processes aimed at rapidly closing the defect in lieu of restoration of function. We propose that discovering and implementing this complex control can be accomplished by the development of a Medical Digital Twin of VML. Digital Twins (DTs) are the subject of a recent report from the National Academies of Science, Engineering and Medicine (NASEM), which provides guidance as to the definition, capabilities and research challenges associated with the development and implementation of DTs. Specifically, DTs are defined as dynamic computational models that can be personalized to an individual real world "twin" and are connected to that twin via an ongoing data link. DTs can be used to provide control on the real-world twin that is, by the ongoing data connection, adaptive. We have developed an anatomic scale cell-level agent-based model of VML termed the Wound Environment Agent Based Model (WEABM) that can serve as the computational specification for a DT of VML. Simulations of the WEABM provided fundamental insights into the biology of VML, and we used the WEABM in our previously developed pipeline for simulation-based Deep Reinforcement Learning (DRL) to train an artificial intelligence (AI) to implement a robust generalizable control policy aimed at increasing the healing of VML with functional muscle. The insights into VML obtained include: 1) a competition between fibrosis and myogenesis due to spatial constraints on available edges of intact myofibrils to initiate the myoblast differentiation process, 2) the need to biologically "close" the wound from atmospheric/environmental exposure, which represents an ongoing inflammatory stimulus that promotes fibrosis and 3) that selective, multimodal and adaptive local mediator-level control can shift the trajectory of healing away from a highly evolutionarily beneficial imperative to close the wound via fibrosis. Control discovery with the WEABM identified the following design principles: 1) multimodal adaptive tissue-level mediator control to mitigate pro-inflammation as well as the pro-fibrotic aspects of compensatory anti-inflammation, 2) tissue-level mediator manipulation to promote myogenesis, 3) the use of an engineered extracellular matrix (ECM) to functionally close the wound and 4) the administration of an anti-fibrotic agent focused on the collagen-producing function of fibroblasts and myofibroblasts. The WEABM-trained DRL AI integrates these control modalities and provides design specifications for a potential device that can implement the required wound sensing and intervention delivery capabilities needed. The proposed cyber-physical system integrates the control AI with a physical sense-and-actuate device that meets the tenets of DTs put forth in the NASEM report and can serve as an example schema for the future development of Medical DTs.

Agent-based model demonstrates the impact of nonlinear, complex interactions between cytokinces on muscle regeneration

Muscle regeneration is a complex process due to dynamic and multiscale biochemical and cellular interactions, making it difficult to identify microenvironmental conditions that are beneficial to muscle recovery from injury using experimental approaches alone. To understand the degree to which individual cellular behaviors impact endogenous mechanisms of muscle recovery, we developed an agent-based model (ABM) using the Cellular-Potts framework to simulate the dynamic microenvironment of a cross-section of murine skeletal muscle tissue. We referenced more than 100 published studies to define over 100 parameters and rules that dictate the behavior of muscle fibers, satellite stem cells (SSCs), fibroblasts, neutrophils, macrophages, microvessels, and lymphatic vessels, as well as their interactions with each other and the microenvironment. We utilized parameter density estimation to calibrate the model to temporal biological datasets describing cross-sectional area (CSA) recovery, SSC, and fibroblast cell counts at multiple timepoints following injury. The calibrated model was validated by comparison of other model outputs (macrophage, neutrophil, and capillaries counts) to experimental observations. Predictions for eight model perturbations that varied cell or cytokine input conditions were compared to published experimental studies to validate model predictive capabilities. We used Latin hypercube sampling and partial rank correlation coefficient to identify in silico perturbations of cytokine diffusion coefficients and decay rates to enhance CSA recovery. This analysis suggests that combined alterations of specific cytokine decay and diffusion parameters result in greater fibroblast and SSC proliferation compared to individual perturbations with a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. These results enable guided development of therapeutic strategies that similarly alter muscle physiology (i.e. converting extracellular matrix [ECM]-bound cytokines into freely diffusible forms as studied in cancer therapeutics or delivery of exogenous cytokines) during regeneration to enhance muscle recovery after injury.

Duchenne and Becker muscular dystrophy: Cellular mechanisms, image analysis, and computational models: A review

The muscle is the principal tissue that is capable to transform potential energy into kinetic energy. This process is due to the transformation of chemical energy into mechanical energy to enhance the movements and all the daily activities. However, muscular tissues can be affected by some pathologies associated with genetic alterations that affect the expression of proteins. As the muscle is a highly organized structure in which most of the signaling pathways and proteins are related to one another, pathologies may overlap. Duchenne muscular dystrophy (DMD) is one of the most severe muscle pathologies triggering degeneration and muscle necrosis. Several mathematical models have been developed to predict muscle response to different scenarios and pathologies. The aim of this review is to describe DMD and Becker muscular dystrophy in terms of cellular behavior and molecular disorders and to present an overview of the computational models implemented to understand muscle behavior with the aim of improving regenerative therapy.

Agent-based model demonstrates the impact of nonlinear, complex interactions between cytokines on muscle regeneration

Muscle regeneration is a complex process due to dynamic and multiscale biochemical and cellular interactions, making it difficult to identify microenvironmental conditions that are beneficial to muscle recovery from injury using experimental approaches alone. To understand the degree to which individual cellular behaviors impact endogenous mechanisms of muscle recovery, we developed an agent-based model (ABM) using the Cellular Potts framework to simulate the dynamic microenvironment of a cross-section of murine skeletal muscle tissue. We referenced more than 100 published studies to define over 100 parameters and rules that dictate the behavior of muscle fibers, satellite stem cells (SSC), fibroblasts, neutrophils, macrophages, microvessels, and lymphatic vessels, as well as their interactions with each other and the microenvironment. We utilized parameter density estimation to calibrate the model to temporal biological datasets describing cross-sectional area (CSA) recovery, SSC, and fibroblast cell counts at multiple time points following injury. The calibrated model was validated by comparison of other model outputs (macrophage, neutrophil, and capillaries counts) to experimental observations. Predictions for eight model perturbations that varied cell or cytokine input conditions were compared to published experimental studies to validate model predictive capabilities. We used Latin hypercube sampling and partial rank correlation coefficient to identify in silico perturbations of cytokine diffusion coefficients and decay rates to enhance CSA recovery. This analysis suggests that combined alterations of specific cytokine decay and diffusion parameters result in greater fibroblast and SSC proliferation compared to individual perturbations with a 13% increase in CSA recovery compared to unaltered regeneration at 28 days. These results enable guided development of therapeutic strategies that similarly alter muscle physiology (i.e. converting ECM-bound cytokines into freely diffusible forms as studied in cancer therapeutics or delivery of exogenous cytokines) during regeneration to enhance muscle recovery after injury.

Macrophage immunomodulation accelerates skeletal muscle functional recovery in aged mice following disuse atrophy

Poor recovery of muscle size and strength with aging coincides with a dysregulated macrophage response during the early stages of regrowth. Immunomodulation in the form of ex vivo cytokine (macrophage-colony stimulating factor) or polarized macrophage delivery has been demonstrated to improve skeletal muscle regeneration. However, it is unclear if these macrophage-promoting approaches would be effective to improve skeletal muscle recovery following disuse in aged animals. Here, we isolated bone marrow-derived macrophages from donor mice of different ages under various experimental conditions and polarized them into proinflammatory macrophages. Macrophages were delivered intramuscularly into young adult or aged recipient mice during the early recovery period following a period of hindlimb unloading (HU). Delivery of proinflammatory macrophages from donor young adults or aged mice was sufficient to increase muscle function of aged mice during the recovery period. Moreover, proinflammatory macrophages derived from aged donor mice collected during recovery were similarly able to increase muscle function of aged mice following disuse. In addition to the delivery of macrophages, we showed that the intramuscular injection of the cytokine, macrophage-colony stimulating factor, to the muscle of aged mice following HU was able to increase muscle macrophage content and muscle force production during recovery. Together, these results suggest that macrophage immunomodulation approaches in the form of ex vivo proinflammatory macrophage or macrophage-colony stimulating factor delivery during the early recovery phase following disuse atrophy were sufficient to restore the loss of aged skeletal muscle function.NEW & NOTEWORTHY A single intramuscular administration of polarized macrophages into muscles of aged mice following a bout of disuse atrophy was sufficient to improve functional recover similarly to young adults after disuse atrophy regardless of the age or experimental condition of the donor mice. Additionally, intramuscular delivery of macrophage-colony stimulating factor into aged mice was similarly effective. Targeting macrophage function early during the regrowth phase may be a novel tool to bolster muscle recovery in aging.

Dynamic Multiscale Regulation of Perfusion Recovery in Experimental Peripheral Arterial Disease: A Mechanistic Computational Model

In peripheral arterial disease (PAD), the degree of endogenous capacity to modulate revascularization of limb muscle is central to the management of leg ischemia. To characterize the multiscale and multicellular nature of revascularization in PAD, we have developed the first computational systems biology model that mechanistically incorporates intracellular, cellular, and tissue-level features critical for the dynamic reconstitution of perfusion after occlusion-induced ischemia. The computational model was specifically formulated for a preclinical animal model of PAD (mouse hindlimb ischemia [HLI]), and it has gone through multilevel model calibration and validation against a comprehensive set of experimental data so that it accurately captures the complex cellular signaling, cell-cell communication, and function during post-HLI perfusion recovery. As an example, our model simulations generated a highly detailed description of the time-dependent spectrum-like macrophage phenotypes in HLI, and through model sensitivity analysis we identified key cellular processes with potential therapeutic significance in the pathophysiology of PAD. Furthermore, we computationally evaluated the in vivo effects of different targeted interventions on post-HLI tissue perfusion recovery in a model-based, data-driven, virtual mouse population and experimentally confirmed the therapeutic effect of a novel model-predicted intervention in real HLI mice. This novel multiscale model opens up a new avenue to use integrative systems biology modeling to facilitate translational research in PAD.

Photoreactive hydrogel stiffness influences volumetric muscle loss repair

Volumetric muscle loss (VML) injuries are characterized by permanent loss of muscle mass, structure, and function. Hydrogel biomaterials provide an attractive platform for skeletal muscle tissue engineering due to the ability to easily modulate their biophysical and biochemical properties to match a range of tissue characteristics. In this work we successfully developed a mechanically tunable hyaluronic acid (HA) hydrogel system to investigate the influence of hydrogel stiffness on VML repair. HA was functionalized with photoreactive norbornene groups to create hydrogel networks that rapidly crosslink via thiol-ene click chemistry with tailored mechanics. Mechanical properties were controlled by modulating the amount of matrix metalloproteinase (MMP)-degradable peptide crosslinker to produce hydrogels with increasing elastic moduli of 1.1 ± 0.002, 3.0 ± 0.002, and 10.6 ± 0.006 kPa mimicking a relevant range of developing and mature muscle stiffnesses. Functional muscle recovery was assessed following implantation of the HA hydrogels by in situ photopolymerization into rat latissimus dorsi (LD) VML defects at 12 and 24 weeks post-injury. After 12 weeks, muscles treated with medium stiffness (3.0 kPa) hydrogels produced maximum isometric forces most similar to contralateral healthy LD muscles. This trend persisted at 24 weeks post-injury, suggestive of sustained functional recovery. Histological analysis revealed a significantly larger zone of regeneration with more de novo muscle fibers following implantation of medium stiffness hydrogels in VML-injured muscles compared to other experimental groups. Lower (low and medium) stiffness hydrogels also appeared to attenuate the chronic inflammatory response characteristic of VML injuries, displaying similar levels of macrophage infiltration and polarization to healthy muscle. Together these findings illustrate the importance of hydrogel mechanical properties in supporting functional repair of VML injuries.

Agent-based model provides insight into the mechanisms behind failed regeneration following volumetric muscle loss injury

Skeletal muscle possesses a remarkable capacity for repair and regeneration following a variety of injuries. When successful, this highly orchestrated regenerative process requires the contribution of several muscle resident cell populations including satellite stem cells (SSCs), fibroblasts, macrophages and vascular cells. However, volumetric muscle loss injuries (VML) involve simultaneous destruction of multiple tissue components (e.g., as a result of battlefield injuries or vehicular accidents) and are so extensive that they exceed the intrinsic capability for scarless wound healing and result in permanent cosmetic and functional deficits. In this scenario, the regenerative process fails and is dominated by an unproductive inflammatory response and accompanying fibrosis. The failure of current regenerative therapeutics to completely restore functional muscle tissue is not surprising considering the incomplete understanding of the cellular mechanisms that drive the regeneration response in the setting of VML injury. To begin to address this profound knowledge gap, we developed an agent-based model to predict the tissue remodeling response following surgical creation of a VML injury. Once the model was able to recapitulate key aspects of the tissue remodeling response in the absence of repair, we validated the model by simulating the tissue remodeling response to VML injury following implantation of either a decellularized extracellular matrix scaffold or a minced muscle graft. The model suggested that the SSC microenvironment and absence of pro-differentiation SSC signals were the most important aspects of failed muscle regeneration in VML injuries. The major implication of this work is that agent-based models may provide a much-needed predictive tool to optimize the design of new therapies, and thereby, accelerate the clinical translation of regenerative therapeutics for VML injuries.

Computational Models Provide Insight into In Vivo Studies and Reveal the Complex Role of Fibrosis in mdx Muscle Regeneration

Duchenne muscular dystrophy is a pro-fibrotic, muscle wasting disease. Reducing fibrosis is a potential therapeutic target; however, its effect on muscle regeneration is not fully understood. This study (1) used an agent-based model to predict the effect of increased fibrosis in mdx muscle on regeneration from injury, and (2) experimentally tested the resulting model-derived hypothesis. The model predicted that increasing the area fraction of fibrosis decreased regeneration 28 days post injury due to limited growth factor diffusion and impaired cell migration. WT, mdx, and TGFβ-treated mdx mice were used to test this experimentally. TGFβ injections increased the extracellular matrix (ECM) area fraction; however, the passive stiffness of the treated muscle, which was assumed to correlate with ECM protein density, decreased following injections, suggesting that ECM protein density was lower. Further, there was no cross-sectional area (CSA) difference during recovery between the groups. Additional simulations revealed that decreasing the ECM protein density resulted in no difference in CSA, similar to the experiment. These results suggest that increases in ECM area fraction alone are not sufficient to reduce the regenerative capacity of mdx muscle, and that fibrosis is a complex pathological condition requiring further understanding.

Multiscale Coupling of an Agent-Based Model of Tissue Fibrosis and a Logic-Based Model of Intracellular Signaling

Wound healing and fibrosis following myocardial infarction (MI) is a dynamic process involving many cell types, extracellular matrix (ECM), and inflammatory cues. As both incidence and survival rates for MI increase, management of post-MI recovery and associated complications are an increasingly important focus. Complexity of the wound healing process and the need for improved therapeutics necessitate a better understanding of the biochemical cues that drive fibrosis. To study the progression of cardiac fibrosis across spatial and temporal scales, we developed a novel hybrid multiscale model that couples a logic-based differential equation (LDE) model of the fibroblast intracellular signaling network with an agent-based model (ABM) of multi-cellular tissue remodeling. The ABM computes information about cytokine and growth factor levels in the environment including TGFβ, TNFα, IL-1β, and IL-6, which are passed as inputs to the LDE model. The LDE model then computes the network signaling state of individual cardiac fibroblasts within the ABM. Based on the current network state, fibroblasts make decisions regarding cytokine secretion and deposition and degradation of collagen. Simulated fibroblasts respond dynamically to rapidly changing extracellular environments and contribute to spatial heterogeneity in model predicted fibrosis, which is governed by many parameters including cell density, cell migration speeds, and cytokine levels. Verification tests confirmed that predictions of the coupled model and network model alone were consistent in response to constant cytokine inputs and furthermore, a subset of coupled model predictions were validated with in vitro experiments with human cardiac fibroblasts. This multiscale framework for cardiac fibrosis will allow for systematic screening of the effects of molecular perturbations in fibroblast signaling on tissue-scale extracellular matrix composition and organization.

Agent-based models of inflammation in translational systems biology: A decade later

Agent-based modeling is a rule-based, discrete-event, and spatially explicit computational modeling method that employs computational objects that instantiate the rules and interactions among the individual components ("agents") of system. Agent-based modeling is well suited to translating into a computational model the knowledge generated from basic science research, particularly with respect to translating across scales the mechanisms of cellular behavior into aggregated cell population dynamics manifesting at the tissue and organ level. This capacity has made agent-based modeling an integral method in translational systems biology (TSB), an approach that uses multiscale dynamic computational modeling to explicitly represent disease processes in a clinically relevant fashion. The initial work in the early 2000s using agent-based models (ABMs) in TSB focused on examining acute inflammation and its intersection with wound healing; the decade since has seen vast growth in both the application of agent-based modeling to a wide array of disease processes as well as methodological advancements in the use and analysis of ABM. This report presents an update on an earlier review of ABMs in TSB and presents examples of exciting progress in the modeling of various organs and diseases that involve inflammation. This review also describes developments that integrate the use of ABMs with cutting-edge technologies such as high-performance computing, machine learning, and artificial intelligence, with a view toward the future integration of these methodologies. This article is categorized under: Translational, Genomic, and Systems Medicine > Translational Medicine Models of Systems Properties and Processes > Mechanistic Models Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Models of Systems Properties and Processes > Organismal Models.

Combining Mathematical Models With Experimentation to Drive Novel Mechanistic Insights Into Macrophage Function

This perspective outlines an approach to improve mechanistic understanding of macrophages in inflammation and tissue homeostasis, with a focus on human inflammatory bowel disease (IBD). The approach integrates wet-lab and in-silico experimentation, driven by mechanistic mathematical models of relevant biological processes. Although wet-lab experimentation with genetically modified mouse models and primary human cells and tissues have provided important insights, the role of macrophages in human IBD remains poorly understood. Key open questions include: (1) To what degree hyperinflammatory processes (e.g., gain of cytokine production) and immunodeficiency (e.g., loss of bacterial killing) intersect to drive IBD pathophysiology? and (2) What are the roles of macrophage heterogeneity in IBD onset and progression? Mathematical modeling offers a synergistic approach that can be used to address such questions. Mechanistic models are useful for informing wet-lab experimental designs and provide a knowledge constrained framework for quantitative analysis and interpretation of resulting experimental data. The majority of published mathematical models of macrophage function are based either on animal models, or immortalized human cell lines. These experimental models do not recapitulate important features of human gastrointestinal pathophysiology, and, therefore are limited in the extent to which they can fully inform understanding of human IBD. Thus, we envision a future where mechanistic mathematical models are based on features relevant to human disease and parametrized by richer human datasets, including biopsy tissues taken from IBD patients, human organ-on-a-chip systems and other high-throughput clinical data derived from experimental medicine studies and/or clinical trials on IBD patients.

Data-Driven Model Validation Across Dimensions

Data-driven model validation across dimensions in mathematical and computational biology assumptions are often made (e.g., symmetry) to reduce the problem from three spatial dimensions (3D) to two (2D). However, some experimental datasets, such as cell counts obtained via flow cytometry, represent the entire 3D biological object. For purpose of model calibration and validation, it is sometimes necessary to compare these biological datasets with model outputs. We propose a methodology for scaling 2D model outputs to compare with 3D experimental datasets, and we discuss the application of this methodology to two examples: agent-based models of granuloma formation and skeletal muscle tissue. The accuracy of the method is evaluated in artificially generated scenarios.

Agent-based model illustrates the role of the microenvironment in regeneration in healthy and mdx skeletal muscle

Duchenne muscular dystrophy (DMD) is a progressive muscle-wasting disease with no effective treatment. Multiple mechanisms are thought to contribute to muscle wasting, including increased susceptibility to contraction-induced damage, chronic inflammation, fibrosis, altered satellite stem cell (SSC) dynamics, and impaired regenerative capacity. The goals of this project were to 1) develop an agent-based model of skeletal muscle that predicts the dynamic regenerative response of muscle cells, fibroblasts, SSCs, and inflammatory cells as a result of contraction-induced injury, 2) calibrate and validate the model parameters based on comparisons with published experimental measurements, and 3) use the model to investigate how changing isolated and combined factors known to be associated with DMD (e.g., altered fibroblast or SSC behaviors) influence muscle regeneration. Our predictions revealed that the percent of injured muscle that recovered 28 days after injury was dependent on the peak SSC counts following injury. In simulations with near-full cross-sectional area recovery (healthy, 4-wk mdx, 3-mo mdx), the SSC counts correlated with the extent of initial injury; however, in simulations with impaired regeneration (9-mo mdx), the peak SSC counts were suppressed relative to initial injury. The differences in SSC counts between these groups were emergent predictions dependent on altered microenvironment factors known to be associated with DMD. Multiple cell types influenced the peak number of SSCs, but no individual parameter predicted the differences in SSC counts. This finding suggests that interventions to target the microenvironment rather than SSCs directly could be an effective method for improving regeneration in impaired muscle. NEW & NOTEWORTHY A computational model predicted that satellite stem cell (SSC) counts are correlated with muscle cross-sectional area (CSA) recovery following injury. In simulations with impaired CSA recovery, SSC counts are suppressed relative to healthy muscle. The suppressed SSC counts were an emergent model prediction, because all simulations had equal initial SSC counts. Fibroblast and anti-inflammatory macrophage counts influenced SSC counts, but no single factor was able to predict the pathological differences in SSC counts that lead to impaired regeneration.

Skeletal muscle mechanics, energetics and plasticity

The following papers by Richard Lieber (Skeletal Muscle as an Actuator), Thomas Roberts (Elastic Mechanisms and Muscle Function), Silvia Blemker (Skeletal Muscle has a Mind of its Own: a Computational Framework to Model the Complex Process of Muscle Adaptation) and Sabrina Lee (Muscle Properties of Spastic Muscle (Stroke and CP) are summaries of their representative contributions for the session on skeletal muscle mechanics, energetics and plasticity at the 2016 Biomechanics and Neural Control of Movement Conference (BANCOM 2016). Dr. Lieber revisits the topic of sarcomere length as a fundamental property of skeletal muscle contraction. Specifically, problems associated with sarcomere length non-uniformity and the role of sarcomerogenesis in diseases such as cerebral palsy are critically discussed. Dr. Roberts then makes us aware of the (often neglected) role of the passive tissues in muscles and discusses the properties of parallel elasticity and series elasticity, and their role in muscle function. Specifically, he identifies the merits of analyzing muscle deformations in three dimensions (rather than just two), because of the potential decoupling of the parallel elastic element length from the contractile element length, and reviews the associated implications for the architectural gear ratio of skeletal muscle contraction. Dr. Blemker then tackles muscle adaptation using a novel way of looking at adaptive processes and what might drive adaptation. She argues that cells do not have pre-programmed behaviors that are controlled by the nervous system. Rather, the adaptive responses of muscle fibers are determined by sub-cellular signaling pathways that are affected by mechanical and biochemical stimuli; an exciting framework with lots of potential. Finally, Dr. Lee takes on the challenging task of determining human muscle properties in vivo. She identifies the dilemma of how we can demonstrate the effectiveness of a treatment, specifically in cases of muscle spasticity following stroke or in children with cerebral palsy. She then discusses the merits of ultrasound based elastography, and the clinical possibilities this technique might hold. Overall, we are treated to a vast array of basic and clinical problems in skeletal muscle mechanics and physiology, with some solutions, and many suggestions for future research.

Spatial and age-related changes in the microstructure of dystrophic and healthy diaphragms

Duchenne muscular dystrophy (DMD) is a progressive degenerative disease that results in fibrosis and atrophy of muscles. The main cause of death associated with DMD is failure of the diaphragm. The diaphragm is a dome-shaped muscle with a fiber microstructure that differs across regions of the muscle. However, no studies to our knowledge have examined spatial variations of muscle fibers in dystrophic diaphragm or how aging affects those variations in DMD. In this study, diaphragms were obtained from mdx and healthy mice at ages three, seven, and ten months in the dorsal, midcostal, and ventral regions. Through immunostaining and confocal imaging, we quantified sarcomere length, interstitial space between fibers, fiber branching, fiber cross sectional area (CSA), and fiber regeneration measured by centrally located nuclei. Because DMD is associated with chronic inflammation, we also investigated the number of macrophages in diaphragm muscle cross-sections. We saw regional differences in the number of regenerating fibers and macrophages during the progression of DMD in the mdx diaphragm. Additionally, the number of regenerating fibers increased with age, while CSA and the number of branching fibers decreased. Dystrophic diaphragms had shorter sarcomere lengths than age-matched controls. Our results suggest that the dystrophic diaphragm in the mdx mouse is structurally heterogeneous and remodels non-uniformly over time. Understanding regional changes in dystrophic diaphragms over time will facilitate the development of targeted therapies to prevent or minimize respiratory failure in DMD patients.

Fibroblasts: Diverse Cells Critical to Biomaterials Integration

Fibroblasts are key participants in wound healing and inflammation, and are capable of driving the progression of tissue repair to fully functional tissue or pathologic scar, or fibrosis, depending on the specific mechanical and biochemical cues with which they are presented. Thus, understanding and modulating the fibroblastic response to implanted materials is paramount to achieving desirable outcomes, such as long-term implant function or tissue regeneration. However, fibroblasts are remarkably heterogeneous and can differ vastly in their contributions to regeneration and fibrosis. This heterogeneity exists between tissues and within tissues, down to the level of individual cells. This review will discuss the role of fibroblasts, the pitfalls of describing them as a collective, the specifics of their function, and potential future directions to better understand and organize their highly variable biology.

Arteriogenesis in murine adipose tissue is contingent on CD68+ /CD206+ macrophages

OBJECTIVE

The surgical transfer of skin, fat, and/or muscle from a donor site to a recipient site within the same patient is a widely performed procedure in reconstructive surgeries. A surgical pretreatment strategy that is intended to increase perfusion in the flap, termed "flap delay," is a commonly employed technique by plastic surgeons prior to flap transplantation. Here, we explored whether CD68+ /CD206+ macrophages are required for arteriogenesis within the flap by performing gain-of-function and loss-of-function studies in a previously published flap delay murine model.

METHODS AND RESULTS

Local injection of M2-polarized macrophages into the flap resulted in an increase in collateral vessel diameter. Application of a thin biomaterial film loaded with a pharmacological agent (FTY720), which has been previously shown to recruit CD68+ /CD206+ macrophages to remodeling tissue, increased CD68+ /CD206+ cell recruitment and collateral vessel enlargement. Conversely, when local macrophage populations were depleted within the inguinal fat pad via clodronate liposome delivery, we observed fewer CD68+ cells accompanied by diminished collateral vessel enlargement.

CONCLUSIONS

Our study underscores the importance of macrophages during microvascular adaptations that are induced by flap delay. These studies suggest a mechanism for a translatable therapeutic target that may be used to enhance the clinical flap delay procedure.