Highly contractile 3D tissue engineered skeletal muscles from human iPSCs reveal similarities with primary myoblast-derived tissues

Soft Biological Actuators for Meter-Scale Homeostatic Biohybrid Robots

Skeletal muscle's elegant protein-based architecture powers motion throughout the animal kingdom, with its constituent actomyosin complexes driving intra- and extra-cellular motion. Classical motors and recently developed soft actuators cannot match the packing density and contractility of individual muscle fibers that scale to power the motion of ants and elephants alike. Accordingly, the interdisciplinary fields of robotics and tissue engineering have combined efforts to build living muscle actuators that can power a new class of robots to be more energy-efficient, dexterous, and safe than existing motor-powered and hydraulic paradigms. Doing so ethically and at scale─creating meter-scale tissue constructs from sustainable muscle progenitor cell lines─has inspired innovations in biomaterials and tissue culture methodology. We weave discussions of muscle cell biology, materials chemistry, tissue engineering, and biohybrid design to review the state of the art in soft actuator biofabrication. Looking forward, we outline a vision for meter-scale biohybrid robotic systems and tie discussions of recent progress to long-term research goals.

Actuating Extracellular Matrices Decouple the Mechanical and Biochemical Effects of Muscle Contraction on Motor Neurons

Emerging in vivo evidence suggests that repeated muscle contraction, or exercise, impacts peripheral nerves. However, the difficulty of isolating the muscle-specific impact on motor neurons in vivo, as well as the inability to decouple the biochemical and mechanical impacts of muscle contraction in this setting, motivates investigating this phenomenon in vitro. This study demonstrates that tuning the mechanical properties of fibrin enables longitudinal culture of highly contractile skeletal muscle monolayers, enabling functional characterization of and long-term secretome harvesting from exercised tissues. Motor neurons stimulated with exercised muscle-secreted factors significantly upregulate neurite outgrowth and migration, with an effect size dependent on muscle contraction intensity. Actuating magnetic microparticles embedded within fibrin hydrogels enable dynamically stretching motor neurons and non-invasively mimicking the mechanical effects of muscle contraction. Interestingly, axonogenesis is similarly upregulated in both mechanically and biochemically stimulated motor neurons, but RNA sequencing reveals different transcriptomic signatures between groups, with biochemical stimulation having a greater impact on cell signaling related to axonogenesis and synapse maturation. This study leverages actuating extracellular matrices to robustly validate a previously hypothesized role for muscle contraction in regulating motor neuron growth and maturation from the bottom-up through both mechanical and biochemical signaling.

Biohybrid hand actuated by multiple human muscle tissues

Cultured muscle tissue serves as a power source in biohybrid robots that demonstrate diverse motions. However, current designs typically only drive simple substrates on a small scale, limiting flexibility and controllability. To address this, we proposed a biohybrid hand with multijointed fingers powered by multiple muscle tissue actuators (MuMuTAs), bundles of thin muscle tissues. The MuMuTA can provide linear actuation with high contractile force (~8 millinewtons) and high contractile length (~4 millimeters), which can be converted into the flexion of multijointed fingers by a cable-driven mechanism. We successfully powered the biohybrid hand achieving individual control of fingers and a variety of motions using different signaling controls. This study showcases the potential of MuMuTAs as a driving source for advanced biohybrid robotics.

Multitasking muscle: engineering iPSC-derived myogenic progenitors to do more

The generation of myogenic progenitors from iPSCs (iMPs) with therapeutic potential for in vivo tissue regeneration has long been a goal in the skeletal muscle community. Today, protocols enable the production of potent, albeit immature, iMPs that resemble Pax7+ adult muscle stem cells. While muscular dystrophies are often the primary therapeutic target for these cells, an underexplored application is their use in treating traumatic muscle injuries. Notably absent from recent reviews on iMPs is the concept of engineering these cells to perform functions post-transplantation that non-transgenic cells cannot. Here, we highlight protocols to enhance the generation, purification, and maturation of iMPs, and introduce the idea of engineering these cells to perform functions beyond their normal capacities, envisioning novel therapeutic applications.

Proteomics and machine learning: Leveraging domain knowledge for feature selection in a skeletal muscle tissue meta-analysis

Omics techniques, such as proteomics, contain crucial data for understanding biological processes, but they remain underutilized due to their high dimensionality. Typically, proteomics research focuses narrowly on using a limited number of datasets, hindering cross-study comparisons, a problem that can potentially be addressed by machine learning. Despite this potential, machine learning has seen limited adoption in the field of proteomics. Here, skeletal muscle proteomics datasets from five separate studies were combined. These studies included conditions such as in vitro models (both 2D and 3D), in vivo skeletal muscle tissue, and adjacent tissues such as tendons. The collected data was preprocessed using MaxQuant, and then enriched using a Python script fetching structural and compositional details from UniProt and Ensembl databases. This was used to handle high-dimensional and sparsely labeled dataset by breaking it down into five smaller categories using cellular composition information and then training a Random Forest model for each category separately. Using biological context for interpreting the data resulted in improved model performance and made tailored analysis possible by reducing the dimensionality and increasing signal-to-noise ratio as well as only preserving biologically relevant features in each category. This integration of domain knowledge into data analysis and model training facilitated the discovery of new patterns while ensuring the retention of critical details, often overlooked when blind feature selection methods are used to exclude proteins with minimal expressions or variances. This approach was shown to be suitable for performing diverse analyses on individual as well as combined datasets within a broader biological context, ultimately leading to the identification of biologically relevant patterns. Besides from generating new biological insights, this approach can be used to perform tasks such as biomarker discovery, cluster analysis, classification, and anomaly detection more accurately, but incorporation of more datasets is needed to further expand the computational capabilities of such models in clinical settings.

Dynamic and Static Workout of In Vitro Skeletal Muscle Tissue through a Weight Training Device

Enhancing muscle strength through workouts is a key factor in improving physical activity and maintaining metabolic profiles. The controversial results concerning the impacts of weight training often arise from clinical experiments that require controlled experimental conditions. In this study, a weight training system for a muscle development model is presented, which is capable of performing weight training motions with adjustable weight loads. Through the implementation of cultured skeletal muscle tissue with floating structures and a flexible ribbon, both isotonic (dynamic change in muscle length) and isometric (static in muscle length) exercises can be performed without the deflection of the tissue. Quantitative analysis of contraction force, changes in metabolic processes, and muscle morphology under different weight training conditions demonstrates the effectiveness of the proposed system. Our proposed system holds potential for establishing effective muscle development and for further applications in rehabilitation training methods.

A knock down strategy for rapid, generic, and versatile modelling of muscular dystrophies in 3D-tissue-engineered-skeletal muscle

BACKGROUND

Human iPSC-derived 3D-tissue-engineered-skeletal muscles (3D-TESMs) offer advanced technology for disease modelling. However, due to the inherent genetic heterogeneity among human individuals, it is often difficult to distinguish disease-related readouts from random variability. The generation of genetically matched isogenic controls using gene editing can reduce variability, but the generation of isogenic hiPSC-derived 3D-TESMs can take up to 6 months, thereby reducing throughput.

METHODS

Here, by combining 3D-TESM and shRNA technologies, we developed a disease modelling strategy to induce distinct genetic deficiencies in a single hiPSC-derived myogenic progenitor cell line within 1 week.

RESULTS

As proof of principle, we recapitulated disease-associated pathology of Duchenne muscular dystrophy and limb-girdle muscular dystrophy type 2A caused by loss of function of DMD and CAPN3, respectively. shRNA-mediated knock down of DMD or CAPN3 induced a loss of contractile function, disruption of tissue architecture, and disease-specific proteomes. Pathology in DMD-deficient 3D-TESMs was partially rescued by a candidate gene therapy treatment using micro-dystrophin, with similar efficacy compared to animal models.

CONCLUSIONS

These results show that isogenic shRNA-based humanized 3D-TESM models provide a fast, cheap, and efficient tool to model muscular dystrophies and are useful for the preclinical evaluation of novel therapies.

Generation of Human-Induced Pluripotent Stem Cells from Peripheral Blood Mononuclear Cells of C9ORF72-Associated Amyotrophic Lateral Sclerosis Patients

Disease modeling of neuromuscular disorders, such as amyotrophic lateral sclerosis (ALS), is hindered by limited accessibility of affected cells. This problem can be overcome by generation of human induced pluripotent stem cells (hiPSC), which can be then differentiated into required cells. Here, we describe the detailed protocol of hiPSC establishment from peripheral blood mononuclear cells (PBMC) of two ALS patients with detected expansion of G4C2 (GGGGCC) repeats in the first intron of C9ORF72 gene, known to be linked with the most common form of familial ALS.Successful PBMC reprogramming with non-integrating Sendai vectors was confirmed by expression of pluripotency markers: OCT4, NANOG, SSEA4, and TRA-1-60 in obtained hiPSC and their ability to differentiate into cells of three germ layers.The generated ALS-patient-specific hiPSC create a possibility for deciphering molecular basis of this devastating neuromuscular disease.