Biology subjects

Webster-Wood, V. A.

Publications and source records attributed to Webster-Wood, V. A..

4 recordsLinked to original sources

bioRxiv2025

AggreBots: configuring CiliaBots through guided, modular tissue aggregation

Ciliated biobots, or CiliaBots, are a class of engineered multicellular tissues that are capable of self-actuated motility propelled by the motile cilia located on their exterior surface. Correlations have been observed between CiliaBot motility patterns and their morphology and cilia distribution. However, precise control of these structural parameters to generate desired motility patterns predictably remains lacking. Here, we developed a novel Aggregated CiliaBot (AggreBot) platform capable of producing designer motility patterns through spatially controlled aggregation of epithelial spheroids made from human airway cells (referred to as CiliaBot Building Blocks or CBBs), yielding AggreBots with configurable geometry and distribution of active cilia. Guided multi-CBB aggregation led to the production of rod-, triangle-, and diamond-shaped AggreBots, which consistently effected greater motility than traditional single-spheroid CiliaBots. Furthermore, CBBs were found to maintain internal boundaries post-aggregation through the combined action of pathways controlling cellular fluidity and tissue polarity. This boundary fidelity, combined with the use of CBBs with immotile cilia due to mutations in the CCDC39 gene, allowed for the generation of hybrid AggreBots with precision control over the coverage and distribution of active cilia, further empowering control of motility patterns. Our results demonstrate the potential of AggreBots as self-propelling biological tissues through the establishment of morphological "levers" by which alterations to tissue motility can be theoretically planned and experimentally verified.

bioengineering↗

bioRxiv2024

Cytotoxicity and Characterization of 3D-Printable Resins Using a Low-Cost Printer for Muscle-based Biohybrid Devices

Biohybrid devices integrate biological and synthetic materials. The selection of an appropriate synthetic material to interface with living cells and tissues is crucial due to cellular chemical and mechanical sensitivities. As such, the stiffness of the material and its biocompatibility while in direct contact must be considered. In this study, the material properties and biocompatibility of six commercially available, 3D printable resins (three rigid and three elastomeric) were assessed for their suitability for biohybrid actuators. To characterize the material, uniaxial tension and compression tests with post-hoc Hookean and Yeoh model analyses were conducted for both nonsterile and sterilized (ethanol-soaking or autoclaved) samples. The mechanical properties of the elastomeric resins were minimally impacted by the different sterilization techniques. However, both Phrozen AquaGray 8K and Liqcreate Bio-Med Clear rigid resins were significantly softer in tensile tests after sterilization, and AquaGray became far more ductile. Asiga DentaGUIDE was much more stable in its mechanical properties than the other rigid resins. It was also shown that long-term exposure to saline solutions leads to a decrease in the Youngs moduli of these rigid resins before any sterilization has occurred. The print fidelity was also assessed for nonsterile and sterilized samples via manual scoring to determine the impacts of the sterilization processes on the part fidelity. Sterilization techniques had a minimal impact on print fidelity for both elastomeric and ridged resins with two exceptions. In both Formlabs Silicone 40A IPA/BuOAc post-treatment and Phrozen AquaGrey 8K groups, ethanol/UV-sterilization caused more degradation compared to autoclave-sterilization. In addition to the material analyses, cytotoxicity analyses using calcein AM and ethidium homodimer-1 fluorescence markers were conducted by directly culturing C2C12, a common myoblast cell line used in bioactuators, with sterilized resin samples. Of the elastomeric resins, only Formlabs Silicone 40A was shown to have minimal impacts on cell viability. For the rigid resins, Asiga DentaGUIDE, Liqcreate Bio-Med Clear, and ethanol-sterilized Phrozen AquaGray 8K demonstrated minimal impacts on cell viability. Based on these analyses, Asiga DentaGUIDE and Formlabs Silicone 40A demonstrate potential for applications in biohybrid muscle-based actuators when using low-cost 3D printers.

bioengineering↗

bioRxiv2024

Incorporating buccal mass planar mechanics and anatomical features improves neuromechanical modeling of Aplysia feeding behavior

To understand how behaviors arise in animals, it is necessary to investigate both the neural circuits and the biomechanics of the periphery. A tractable model system for studying multifunctional control is the feeding apparatus of the marine mollusk Aplysia californica. Previous in silico and in roboto models have investigated how the nervous and muscular systems interact in this system. However, these models are still limited in their ability to match in vivo data both qualitatively and quantitatively. We introduce a new neuromechanical model of Aplysia feeding that combines a modified version of a previously developed neural model with a novel biomechanical model that better reflects the anatomy and kinematics of Aplysia feeding. The model was calibrated using a combination of previously measured biomechanical parameters and hand-tuning to behavioral data. Using this model, simulation feeding experiments were conducted, and the resulting behavioral metrics were compared to animal data. The model successfully produces three key behaviors seen in Aplysia and demonstrates a good quantitative agreement with biting and swallowing behaviors. Additional work is needed to match rejection behavior quantitatively and to reflect qualitative observations related to the relative contributions of two key muscles, the hinge and I3. Future improvements will focus on incorporating the effects of deformable 3D structures in the simulated buccal mass. Author summaryAnimals need to produce a wide array of behaviors so that they can adapt to changes in their environment. To understand how behaviors are performed, we need to understand how the brain and the body work together in their environment. One tractable system in which to study this brain-body relationship is the feeding behavior of the sea slug Aplysia californica. Despite having a small fraction of the number of neurons that humans have, this animal can produce many behaviors, respond to a changing environment, and learn from previous experiences. We have create an improved computer model of the slugs mouthparts that simulates many of its key muscles and the forces they produce, together with a representation of the network of neurons that control them. With this model, we can recreate the feeding behaviors that we observe in the real animal, including biting, swallowing, and rejection, and use it to make quantitative predictions of how the animal will behave and respond to different stimuli. We found however that some aspects of the system were not well represented by simple 1-dimensional muscles, as has been done in most biomechanical models to date, but requires us to consider more complicated deformations of these soft bodies. Using this model as a tool, we aim to test hypotheses about brain-body interactions in the sea slug to better understand the behavior of small, slowly moving animals.

neuroscience↗

bioRxiv2023

Human subcutaneous adipose tissue variability is driven by VEGFA, ACTA2, adipocyte density, and ancestral history of the patient

Adipose tissue is a dynamic regulatory organ that has profound effects on the overall health of patients. Unfortunately, inconsistencies in human adipose tissues are extensive and multifactorial including large variability in cellular sizes, lipid content, inflammation, extracellular matrix components, mechanics, and cytokines secreted. Given the high human variability, and since much of what is known about adipose tissue is from animal models, we sought to establish correlations and patterns between biological, mechanical, and epidemiological properties of human adipose tissues. To do this, twenty-six independent variables were cataloged for twenty patients that included patient demographics and factors that drive health, obesity, and fibrosis. A factorial analysis for mixed data (FAMD) was used to analyze patterns in the dataset (with BMI > 25) and a correlation matrix was used to identify interactions between quantitative variables. Vascular endothelial growth factor A (VEGFA) and actin alpha 2, smooth muscle (ACTA2) gene expression were the highest loading in the first two dimensions of the FAMD. The number of adipocytes was also a key driver of patient-related differences, where a decrease in the density of adipocytes was associated with aging. Aging was also correlated with a decrease in overall lipid percentage of subcutaneous tissue (with lipid deposition being favored extracellularly), an increase in transforming growth factor-{beta}1 (TGF{beta}1), and an increase in M1 macrophage polarization. An important finding was that self-identified race contributed to variance between patients in this study, where Black patients had significantly lower gene expression levels of TGF{beta}1 and ACTA2. This finding supports the urgent need to account for patient ancestry in biomedical research to develop better therapeutic strategies for all patients. Another important finding was that TGF{beta} induced factor homeobox 1 (TGIF1), an understudied signaling molecule, is highly correlated with leptin signaling and was correlated with metabolic inflammation. Finally, this study revealed an interesting gene expression pattern where M1 and M2 macrophage markers were correlated with each other, and leptin, in patients with a BMI > 25. This finding supports growing evidence that macrophage polarization in obesity involves a complex, interconnecting network system rather than a full switch in activation patterns from M2 to M1 with increasing body mass. Overall, this study reinforces key findings in animal studies and identifies important areas for future research, where human and animal studies are divergent. Understanding key drivers of human patient variability is required to unravel the complex metabolic health of unique patients.

physiology↗