bioRxiv Science⌕ Search

bioRxiv · 10.1101/2023.01.20.524941

mini-MEndR: A miniaturized 96-well predictive assay to evaluate muscle stem cell mediated repair

Abstract

Functional evaluation of molecules that are predicted to promote stem cell mediated endogenous repair often requires in vivo transplant studies that are low throughput and hinder the rate of discovery. Here, we offer a strategy to rapidly test and prioritize molecules for functional validation studies. We miniaturized, simplified and expanded the functionality of a previously developed muscle endogenous repair (MEndR) in vitro assay that was shown to capture significant events of the first week of the in vivo muscle endogenous repair process. The new "mini-MEndR assay" consists of miniaturized cellulose scaffolds designed to fit in 96-well plates. The scaffold pores are infiltrated with myoblasts encapsulated in a fibrin-based hydrogel to form thin, engineered skeletal muscle tissues. By evaluating multiple commercially available human primary myoblast lines in 2D and 3D culture, we establish quality assurance metrics for cell line selection that standardize myotube template quality. Pre-adsorbing thrombin to the cellulose scaffolds facilitates in situ tissue polymerization, a critical modification that enables users proficient in myoblast culture to rapidly acquire myotube template fabrication expertise. Following the generation of the 3D myotube template, muscle stem cells (MuSCs), enriched from digested mouse skeletal muscle tissue using an improved magnetic-activated cell sorting protocol, are engrafted onto the engineered human muscle template. A regenerative milieu is then introduced by injuring the muscle tissue with a myotoxin. Addition of a known modulator of MuSC mediated repair recapitulates the in vivo outcomes (enhanced muscle production and Pax7+ cell expansion), but only in the presence of both the stem cells and the regenerative milieu. By fluorescently labeling the mouse MuSCs, we demonstrate the feasibility of co-evaluating human and mouse Pax7+ cell responses to drug treatment, thereby expanding the utility of the assay. Importantly, phenotypic data is collected with a high-content imaging system and is analyzed using CellProfiler-based image analysis pipelines. The miniaturized predictive assay offers a simple, scaled platform with which to co-investigate human and mouse skeletal muscle endogenous repair molecular modulators, and thus is a promising strategy to accelerate the muscle endogenous repair discovery pipeline.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Gulati, N., Davoudi, S., Xu, B., Rjaibi, S. T., Jacques, E., Pham, J., Fard, A., McGuigan, A. P., Gilbert, P. M.. 2023-01-21. mini-MEndR: A miniaturized 96-well predictive assay to evaluate muscle stem cell mediated repair. https://doi.org/10.1101/2023.01.20.524941

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

Dynamic Compression Platform for Live Imaging of Scaffold-Transmitted Cellular Mechanoresponses

Mechanical characterization of biomaterial scaffolds is essential to evaluate their capacity to meet the functional demands of target tissues in tissue engineering and regenerative medicine applications. Scaffolds designed to interface with living tissues must support the transmission of mechanical cues to resident cells and stimulate mechanosignaling pathways that are essential to their function. In joints, bone and cartilage cells act as primary mechanosensors, converting mechanical stimuli into biochemical signals that regulate tissue homeostasis and remodelling. Therefore, evaluating cellular mechanoresponses to scaffold-transmitted compression in vitro can inform the development of functional tissue-engineered constructs. For example, poly({epsilon}-caprolactone) (PCL) scaffolds are highly relevant for bone and cartilage tissue engineering due to their biocompatibility, stable mechanical properties and slow degradation. Here, we applied a custom-built device to study compression-induced mechanosignaling in MC3T3-E1 pre-osteoblast cells. The device is composed of a polydimethylsiloxane (PDMS) pillar, a force-sensing load cell, and a piezoelectric linear track. A protocol is described in which MC3T3-E1 cells are repeatedly compressed, while in parallel live tracking of force measurements and live imaging of intracellular calcium dynamics in MC3T3-E1 cells are recorded. PCL scaffolds fabricated by melt electrowriting (MEW) were subsequently integrated into the platform. Scaffold-transmitted compression triggered dynamic increases in cytosolic calcium; in MC3T3-E1 cells located directly under the PCL microfibers, but also in cells located in the interfiber spaces. This device and workflow facilitate in vitro investigations of real-time cellular mechanoresponses to dynamic compression applied with biomaterial scaffolds, and provides a testing platform for evaluating the mechanotransductive properties of scaffolds intended for tissue engineering applications.

bioengineering↗

Ultrasound Tracking Reveals Progressive Regional Strain Differences in Human Achilles Tendons During Fatigue Loading

Ultrasound is commonly used to assess structural changes in symptomatic Achilles tendons, but quantitative biomechanical metrics for progressive tendon deterioration remain limited. The goal of this study was to develop and validate an automated ultrasound tracking algorithm for regional tendon deformation and evaluate strain progression in survived and ruptured tendons during fatigue loading. We hypothesized that maximum strain, average strain, and strain heterogeneity would exhibit different trajectories between groups. Ten cadaveric Achilles tendons underwent cyclic loading with stress tests every 500 cycles until rupture or 150,000 cycles. Ultrasound images acquired during stress tests were analyzed using an automated tracking algorithm to generate spatially resolved regional strain fields. Ultrasound-derived bulk strain was highly correlated with actuator-derived strain in survived (R^2 = 0.968 +/- 0.017) and ruptured tendons (R^2 = 0.972 +/- 0.014). Maximum and average longitudinal strains progressively diverged between groups across fatigue life (Group x FatigueLife: p = 0.003 and p < 0.0001, respectively). During the first 10,000 cycles, average strain decreased in survived tendons ({beta} = -0.0268%, p = 0.0215) but not ruptured tendons ({beta} = 0.0147%, p = 0.1197), with a significant Group x Cycle interaction (p = 0.0061). This study demonstrates that the algorithm quantified Achilles tendon deformation with high fidelity and enabled spatially resolved strain assessment throughout fatigue loading. Maximum and average strain followed different trajectories between groups, whereas strain heterogeneity did not. Early differences in tendon biomechanics suggest that regional strain behavior may change before pronounced differences in absolute magnitude develop.

bioengineering↗

Brain organoid computing for robotic decision-making

Biomimicry has inspired the evolution of robotics toward greater autonomy, adaptability, and symbiosis with humans and dynamic environments. However, current robotic systems still face major challenges in recapitulating the high-efficiency decision-making capabilities of the human brain under complex and dynamic conditions. Here, we present Brainobot, a biohybrid robotic system that establishes a brain organoid controller as a high-level robotic decision-making layer for closed-loop embodiment. By leveraging brain organoid reservoir computing, Brainobot interacts with dynamic environments by receiving and processing sensory inputs and generating motor actions. As a proof-of-concept demonstration, Brainobot is implemented in a humanoid robotic system to perform real-world tasks, including object grasping and laser chasing. Interestingly, Brainobot exhibits unique features, including cross-task adaptivity, high computing efficiency, and low energy consumption. Thus, our approach may provide insights for advancing robotic embodiment and understanding biological decision-making.

bioengineering↗