Symposium SB01—Engineered Functional Multicellular Circuits, Devices and Systems

We focus on developing a new class of nanoscale materials and novel strategies for the investigation of biological entities at multiple length scales, from the molecular level to complex cellular networks. Our highly flexible bottom-up nanomaterials synthesis capabilities allow us to form unique hybrid-nanomaterials that can be used in various input/output bioelectrical interfaces, i.e., bioelectrical platforms for chemical and physical sensing and actuation. We developed a breakthrough bioelectrical interface, a 3D self-rolled biosensor arrays (3D-SR-BAs) of either active field effect transistors or passive microelectrodes to measure both cardiac and neural spheroids electrophysiology in 3D. This approach enables electrophysiological investigation and monitoring of the complex signal transduction in 3D cellular assemblies toward an organ-on-an-electronic-chip (organ-on-e-chip) platform for tissue maturation investigations and development of drugs for disease treatment. Utilizing graphene, a two-dimensional (2D) atomically thin carbon allotrope, we demonstrated a new technique to simultaneously record the intracellular electrical activity of multiple excitable cells with ultra-microelectrodes that can be as small as the size as an axon ca. 2µm in size. The outstanding electrochemical properties of our hybrid-nanomaterials allowed us to develop electrical sensors and actuators, e.g., sensors to explore the brain chemistry and sensors/actuators that are deployed in a large volumetric muscle loss animal model. Finally, using the unique optical properties of nanocarbons, e.g., graphene-based hybrid-nanomaterials and 2D nanocarbides, we have formed remote, non-genetic bioelectrical interfaces with excitable cells and modulated cellular and network activity with high precision and low needed energy. In summary, the exceptional synthetic control and flexible assembly of nanomaterials provide powerful tools for fundamental studies and applications in life science and potentially seamlessly merge nanomaterials-based platforms with cells, fusing nonliving and living systems together.

The fields of biology and robotics have seen an emergence of interdisciplinary work aimed at building machines that contain biological components, designed to solve a wide variety of problems that challenge traditional robots including; robustness to damage, increased biocompatibility, and a programmable internal biochemistry. These efforts have largely coalesced around biohybrid designs, combining synthetic scaffolds or components alongside living cells and tissues. In complement to this approach, we have developed methods for constructing fully biological machines from embryonic amphibian cells, engineered to exhibit a specific behavior. As part of these studies, we demonstrate a scalable pipeline for creating functional computer designed organisms: AI methods automatically design diverse candidate lifeforms in silico to perform some desired function, and transferable designs are then created using a cell-based construction toolkit to realize living systems with the predicted behaviors. Although some steps in this pipeline still require manual intervention, complete automation in future would pave the way to designing and deploying unique, bespoke living systems for a wide range of functions.

Diatoms are early Jurassic microalgae, a photosynthetic group with a major environmental role on the planet due to the biogeochemical cycling of silica and global fixation of carbon. However, they can evolve into harmful blooms through a resourceful communication mechanism, not yet fully understood. Harmful algae blooms in water supply reservoirs must be eradicated due to unwanted toxin production and filter blocking at water treatment works. Until now there has been no efficient consensus that harmful microorganisms such as diatoms communicate with each other and no accurate and self-sustained tool to monitor such communication.

Here, we demonstrate the ability to electrically monitor a diatom cohort. The breakthrough is realized by means of a unique measurement setup based on low impedance electrodes that exploit the large Helmholtz-Gouy-Chapman double-layer capacitance. The sensing system comprises a transducer based on a metal/Si/SiO₂/Au electrode. Small extracellular voltages of diatoms adhered to the electrode induce a displacement current that is enhanced by a gain factor proportional to the double-layer capacitance.

The origin is paracrine signalling, which is a feedback, or survival, mechanism that counteracts changes in the physicochemical environment. The intracellular messenger could be related to Ca²⁺ ions since spatiotemporal changes in their concentration match the characteristics of the intercellular waves. Our conclusion is supported by using a Ca²⁺ channel inhibitor. The transport of Ca²⁺ ions through the membrane to the extracellular medium is blocked and the intercellular waves disappear. The translation of microalgae cooperative signalling paves the way for early detection and prevention of harmful blooms and an extensive range of stress-induced alterations in the aquatic ecosystem

The rise of Artificial Intelligence and the Internet of Things applications in biological domains poses questions about the best way to build computing devices that are biocompatible, low-power, and adaptable. We believe an approach that takes inspiration from the brain could grant an answer. For instance, biological neurons process signals and compute by integrating incoming stimuli and initiating action potentials to convey information within the nervous system without loss. The process from generation to propagation is regulated by membrane potential and voltage-activated sodium and potassium channels. Moreover, synaptic plasticity is responsible for learning, processing, and information retention. These key features inspire and guide the design of neuron-and synapse-like materials for applications in signal processing, computing, and lossless propagation of information. To this end, we have recently demonstrated that lipid bilayer membranes formed between two lipid-encased water droplets in oil (i.e., droplet interface bilayers or DIBs) can exhibit memcapacitive and memristive properties, suitable for emulating synapse and neuron functions. Here, we describe a dynamic neuristor consisting of two biomolecular memristors in parallel, while operating according to the same principles as the Hodgkin-Huxley model. The biomolecular memristors consist of insulating biomembrane doped with voltage-driven, pore-forming alamethicin peptides. To capture the switching dynamics of the sodium and potassium channels, we used DPhPC- and BTLE-based memristors, which can offer fast and slow switching dynamics, respectively. The neuristor exhibits a firing behavior similar to a biological neuron and a power efficiency that far exceeds metal oxide-based memristors. This novel neuristor can be implemented in applications ranging from adaptive nonlinear control to signal processing. Additionally, we will discuss our approach to scaling up networks of biomolecular synapses and neurons using microfluidic crossbar array devices. We describe how these devices can be implemented in online learning and reservoir computing applications. These results serve as a foundation for a new class of low-cost, low-power biomolecular materials to support neuromorphic computing applications in biological environments.

In this work, we demonstrate, for the first time, spatially controlled differentiation of human pluripotent stem cells (hPSCs) into the anterior foregut (AFG) and mid/hindgut (MHG) cell types within a single cell monolayer using chemical gradient-generating microfluidics. This result represents an advance in the ongoing efforts to harness the processes by which complex tissues arise during embryonic development in vitro—a long-standing goal of tissue engineering and regenerative medicine. In embryos, uniform populations of stem cells are exposed to spatial gradients of diffusible extracellular signaling proteins, known as morphogens. Varying levels of these signaling proteins induce stem cells to differentiate into distinct cell types at different positions along the gradient, thus creating spatially patterned tissues.

To accomplish this spatially controlled differentiation, or patterning, we combined principles of engineering and biology to develop a novel, reproducible, and easily accessible method for the anterior-posterior patterning of hPSCs. We performed a 6-day, on-chip differentiation protocol within a commercially available microfluidic chip. We used finite element analysis to model the distribution of morphogens within the microfluidic device and determined that the chip can generate two stable and opposing linear morphogen gradients. Quantitative analysis of immunofluorescence data showed that expression of AFG and MHG markers is localized to their respective morphogen sources and that both display a decreasing linear profile with increasing distance from their sources. This platform thus allows us to explore fundamental questions about how a single population of stem cells differentiate into multiple cell types along a body axis in response to exposure to morphogen gradients, such as whether the response in marker expression is graded or discretized as well as the influence of neighboring cells on cell fate decisions. Our in vitro model contributes to the stem cell and developmental biology toolkit and may eventually pave the way to create increasingly spatially patterned tissue-like constructs in vitro.

We study the structural evolution of biologically relevant phospholipid membranes adsorbed onto deformable 2D substrates. We introduce a novel way to remodel lipid bilayers using polydimethylsiloxane substrates or graphene, which can be uniaxially stretched and wrinkled on demand. X-ray, microscopy and simulation data revealed that phospholipid membranes undergo restructuring at the nano and molecular scale. These observations have repercussions on membrane order, permeation, and directing the insertion of proteins for applications in biotechnological applications such as biosensing.

In vitro neural cultures have been used as an experimental model system to study basic neuroscience, design advanced cell-based biosensing platform, and utilize as testbeds for novel neurotechnology. Many types of primary cultured neurons (e.g. rat/mouse cortical or hippocampal neurons) go through developmental processes (neurite outgrowth, axon/dendrite formation), and form a matured neuronal network with functional synapses during the extended cultivation period. To investigate the functional developments during the network formation, neurons are cultivated on a planar-type microelectrode array (MEA) chip, and electrophysiological activity is measured from multiple sites in the network. Conventional MEA chips provide a few millimeter-sized recoding area with sparse or dense microelectrodes, which limits the physical size of the cultured neuronal networks under the investigation. Large-scale neuronal networks on the order of a few centimeters are rarely investigated by the limited availability of the MEA chips that provide recording electrodes distributed over a large area. This talk introduces a scaling up the network size to centimeter scale on a microslide-sized MEA chip. The chip is equipped with 256 channels which are subdivided into 16 millimeter-sized recording areas with 16 channels. The large-scale MEA chips were fabricated by conventional microfabrication processes, and recording sites were made of low-impedance electropolymerized conductive polymers (PEDOT:PSS). On this large-scale MEA chip with clustered recording areas, we designed an ultra-large-scale, modular neuronal network connected by biological connections (e.g. axons). Neuronal network modules, composed of primary cultured neurons, were patterned on the MEA chip using soft-lithography, and each module was connected later by removing alginate hydrogel mask. The alginate hydrogel was used as a removable cell-repulsive surface to temporarily limit the cell adhesion and neurite outgrowth. Using this method, the development of network activity could be more precisely measured and analyzed. The emergence of synchronized, propagating network bursts were readily measured, and their time course could be analyzed. We found network-size dependent signal propagation properties in the cultured neuronal networks.

While manufacturing is evolving and new devices are coming out one after another, it is still difficult to artificially create functions such as molecular recognition, material production, and self-organization that are found in living organisms. We have developed a biohybrid device that combines living organisms and machines. The biohybrid devices can be categorized into 4 groups: (i) biohybrid-sensors that can detect target molecules at highly selective and sensitive manner, (ii) biohybrid-reactors that mimic biological reaction in our body, and thus are useful for drug testing or tissue transplant for cell therapy, (iii) biohybrid-actuators that shows highly energy efficient motion and (iv) biohybrid-processors that achieve low-energy and highly parallel computing like our brain. Here, I would like to talk about a couple of our recent results regarding biohybrid sensors and actuators.

A rapid and simple antibiotic susceptibility testing (AST) is critical to provide valuable information on the antibiotic efficacy and their right doses for treatment against bacterial infections. Although emerging genotypic ASTs are very useful and fast, it is difficult to characterize unknown bacteria. Even “gold standard” phenotypic ASTs require a relatively long time for culturing and monitoring. This work creates a powerful yet simple method to assess antibiotic effectiveness against electrogenic bacteria, which enables rapid, high-throughput, and real-time monitoring. The proposed AST approach continuously monitors extracellular electron transfer by bacterial cells, parallelly and controllably formed on a paper-based sensing array. The transferred electrons are based on microbial metabolic activities and are inversely proportional to the concentration of potential antibiotics, leading to the early detection of antimicrobial drug resistance in bacteria.
Extracellular electron transfer (EET) is a remarkable bioelectrochemical process used by certain microorganisms for growth, overall cell maintenance, and information exchange with surrounding microorganisms or environments. Almost all environments, even those involving harsh conditions, host microorganisms performing EET. Recent studies have demonstrated electrogenicity by even Gram-positive microorganisms, which have thick cell walls that limit effective electron transfer. Other microorganisms have demonstrated weak electrogenic capacity in microbial consortia, involving direct interspecies electron transfer (DIET) and EET-involved cell-to-cell communications. Even many microbial pathogens such as Pseudomonas aeruginosa use quorum sensing inter-cellular communication by producing diffusible signaling molecules (e.g., autoinducers) and redox active compounds to control virulence during infections and defend their immediate niche against competing microorganisms and environmental stresses. The redox-active compounds can also serve as extracellular soluble mediators for microbial EET. Therefore, the electrical outputs from the bacterial EET can be used as a measurement to evaluate the antibiotic efficacy. When the antibiotics are effective against those pathogenic exoelectrogens, their metabolic activities can be inhibited, thus decreasing their electron transfer reactions. The changes in electrical outputs can be measured to assess the antibiotic effectiveness against the pathogen.
In this work, a paper-based 8-well sensing array offers a rapid and simple approach to characterize bacterial electrical response in the different concentrations of antibiotics. A common Gram-negative pathogenic bacterium Pseudomonas aeruginosa wild-type PAO1 and first-line antibiotic gentamicin (GEN) are used in our experiments. Eight different concentrations of antibiotics (1, 2, 4, 8, 16, 32, 64, and 128 ug/ml) are pre-loaded and dried on the sensing units. When bacterial samples are loaded into the array, antibiotic exposures allow sufficient inhibition to the bacterial metabolisms, and the readout becomes sensitive enough to show small variations in electric output caused by changes in antibiotic effectiveness. The result generates quantitative, actionable minimum inhibitory concentration (MIC) values within an hour by measuring electricity produced by bacterial metabolism instead of the days needed for growth-observation methods. This work will explore the viability of this system as a practical and reliable AST tool. The project outcomes will address grand challenges in microbial infections critical to U.S. healthcare and the economy, through enabling sensors that will augment human health, safety, and well-being by providing information to effectively treat the infections and better control the spread of the antibiotic resistance.

Inspired by the natural biological system's efficiency and complexity, biocomputing that utilizes or mimics natural information processing inherent in living organisms provides a new computational approach that performs computing in a massively parallel way with energy efficiency. Here, we present a new biocomputing platform, a cardiac muscle-cell-based bio-oscillator network, for solving computationally hard problems such as vertex coloring problems, which entail computing the minimum number of colors required to assign colors to all vertices in a graph such that every adjacent vertex have a different color. The computing components of the network are composed of bio-oscillators, cardiomyocytes (CMs), and coupling elements, cardiac fibroblasts (CFs). We aim to harness the unique phase ordering produced by the coupled bio-oscillators to approximate the optimal solution to the vertex coloring problem. We first studied the synchronization behavior of a pair of coupled bio-oscillators that exhibited stable phase delays caused by the time lag in transporting electrical signals through the coupling elements. Such delays can be exploited to build up the phase ordering in multi-node oscillators. Then, we aimed to use the bio-oscillator network to solve multi-node vertex coloring problems (9 nodes and 64 nodes) through mapping the vertices and edges onto the CMs and CFs. The micropatterning method based on topographic features and mobile blockers was implemented for creating the controlled cell distribution. On the theoretical front, we developed a polynomial-time post-processing scheme that uses the bio-oscillator solution as a starting point to improve the solution to be comparable to the heuristic algorithm. Moreover, the bio-oscillator-based computational model can have a performance advantage at large nodes compared to the heuristic algorithm. We also benchmarked the energy and latency for graph coloring using coupled bio-oscillators and conventional CMOS oscillators. The energy consumption of the cardiac-cell and CMOS oscillators for networks of different sizes indicated that cardiac cells consume lesser energy in computing the graph coloring solution which can lead to significant energy savings in larger networks.

Electromicrobiology is a discipline emerging from studies of microbial electron exchange with external electrodes and of novel electrochemical properties of microorganisms. Intensive study in electromicrobiological engineering has created a plethora of new concepts and potential applications, offering sustainable environmental solutions for the production of energy as well as valuable products. However, the microbial electrochemical technique has not yet been leveraged for practical applications. Several significant research gaps must be addressed before electromicrobiology is viable and scalable, and the need to address these gaps is growing more urgent with the increasing concerns over the energy-climate crisis and environment pollution. For example, researchers do not yet fully understand the interplay between electrodes and active microbes, and factors controlling the rate and extent of the exchange process are still ill-defined. Additionally, more research is needed to ascertain which microbial species or consortia of species are best suited for efficient electron transfer.
The overarching purpose of this work is to pursue advanced, innovative approaches that elucidate/maximize microbial electron exchange with electrodes, and translate basic findings within the field of electromicrobiology into practical, real-world applications that support environmental sustainability. In this work, a range of innovative approaches are investigated with the major goals of investigating fundamental factors responsible for determining efficient electron exchange with external devices, and exploring three-dimensional biofabrication and engineering of synthetic polymicrobial biofilms. This research provides a foundation for enhanced performance in electromicrobiology. The project uses the new field of 3D, paper-based cell culturing, sensing and biofabrication platforms that mimic microbe-electrode interactions in biofilms. In particular, stacks of patterned papers provide creative and unique solutions for 3D bacterial cultures of controlled biofilm geometry, high-throughput monitoring of microbial electrical properties and layer-by-layer construction of an artificial biofilm. This research addresses key issues in electromicrobiology: (i) promote/accelerate the discovery and characterization of customized and novel exoelectrogens, (ii) establish fundamental knowledge to determine critical factors in electron transfer at the microbial/anode interface, and (iii) optimize bacterial synergistic interactions in synthetic bacterial communities.
Multiple layers of paper containing bacterial cells can be stacked to form a layered 3D model of the overall biofilm construct and mass transport of nutrients/oxygen into this 3D system can be regulated to explore the microbial energy production within controlled biofilms. Different stack configurations allow us to generate many different experimental setups to better understand key mechanisms underlying electron harvesting from microorganisms and other fundamental factors determining their electron-generating capabilities. De-stacking the multi-layered biofilm construct also allow layer-by-layer analysis for pH distribution and cellular viability. In this 3D model system, Synechocystis sp. PCC 6803 on the top layer exploits photosynthesis to produce carbohydrates, which are used as a carbon source by other microbial communities. Then, the facultative aerobe Bacillus subtilis are inserted into the middle layer of the co-culture to produce riboflavin as an electron shuttle, which significantly improves power generation of exoelectrogens, Shewanella oneidensis, on the bottom layer. Furthermore, Bacillus subtilis can remove oxygen and thus maintain an anaerobic condition for the optimized electrogenic process of Shewanella sp. This 3D system demonstrates a significantly increased power output.

Introduction: Dysfunction of the blood-brain barrier (BBB) is implicated in several neurological disorders. As such, it is highly desirable to develop new models to study BBB pathology. However, these studies are hampered by the complex multi-cellular hierarchy and cellular interactions that are required to create a physiologically relevant model that accurately depicts the structure and function of the BBB. To address these limitations, we have been developing a vascularized, anatomically-representative three-dimensional (3D) model of the BBB in a perfusable, 3D printed microfluidic chip using ex vivo mouse and human tissue embedded in a biomimetic hydrogel. Overall, our 3D BBB model provides a unique system that allows for dynamic interrogation of the BBB in healthy and diseased tissue.
Methods and Materials: Microfluidic devices were fabricated using a stereolithographic 3D printed mold. This mold was vapor deposited with Parylene C to provide a physical barrier to prevent cytotoxic leaching into the casted polydimethylsiloxane and hydrogel. Fresh mouse and/or human brain tissue were collected and minced in a 1mL conical tube filled with 500µL of Hank’s Balanced Salt solution for 5 minutes. The vial was then centrifuged at 2500 rpm. After centrifugation, the vial was tilted and the liquid top layer was aspirated. Then, 100µL of minced tissue was transferred to 1mL of 10% gelatin conjugated with an N-cadherin biomimetic peptide and thoroughly mixed. Subsequently, microbial transglutaminase was added to the hydrogel for crosslinking (2% final solution), mixed and poured into the microfluidic device. The hydrogel was cured for 30 minutes at 37°C, followed by immediate perfusion of the peripheral channels. Vascular growth in the hydrogels was imaged with confocal immunofluorescence 7 days following tissue embedding.
Results and Discussion: We established a neurovascular ex vivo model using mouse and human brain tissue embedded in a hydrogel containing a peptide from the extracellular epitope of N-cadherin. This tissue spontaneously sprouts vasculature in our microfluidic platform to form a perfusable vascular network. The two flanking perfusion channels are independently perfusable with media and growth factors to direct vascularization to the channels, while the middle channel was designed for 3D hydrogels impregnated with tissue. Neovascularization could be observed in real-time from the embedded tissue, and immunostaining revealed vessels that were several millimeters in length and consisted of anatomically correct positioning of endothelial cells and pericytes separated by a collagen IV basement membrane. Excitingly, human brain tissue from a patient with CAA, a disease characterized by the accumulation of amyloid-β deposition in the vascular walls, could grow vasculature that exhibited hallmarks of the disease including amyloid accumulation and arterioles devoid of smooth muscle cells.
Conclusions: We have shown that human and mouse brain tissue in our hydrogel exhibits continuous vascular growth with anatomically correct hierarchy and expression of characteristic markers of vascular cell phenotypes. This new platform also supports the use of diseased primary human tissue to produce brain vasculature with alterations characteristic of the underlying cerebral vascular architecture pathology. Thus, we believe this new tool will be a powerful platform for building more complex brain models with proper organization and assessing therapeutic efficacy of drugs for a broad range of neurological disorders.

With the growing demand for point-of-care (POC) and in-field diagnostic testing, paper attracts significant attention as a substrate for simple, low-cost, and disposable analytical devices. A porous, hydrophilic network of intertwined cellulose fibers promotes excellent mechanical, dielectrical and fluidic properties in paper. These properties mean microfluidic assays and electronic/mechanical components can be built into paper, offering the transformative potential of generating important function for POC diagnostic devices. Recent advances in paperfluidic and papertronic technologies offer more decentralized diagnostic analyses with portability, automation, and the capacity to produce test results in shorter times at a reduced cost. However, there has been a significant challenge in realizing a truly stand-alone and self-sustainable diagnostic platform that does not rely on a competent laboratory service or smartphone’s built-in functions. The key challenge is to develop a miniaturized on-chip power source for those paper-based POC devices in a more effective and efficient way. Power autonomy is one of the most critical requirements for the devices so they can work independently and self-sustainably in limited-resource and remote regions, where a stable electrical supply is not available. Even standard batteries are not suitable in those areas because of their cost, incompatibility with paper, and potential danger to the environment. Smartphone built-in batteries are not always available. Also, conventional energy harvesting technologies (e.g. solar, thermal, mechanical, chemical energy) are too overqualified and expensive as a power source for single-use, disposable POC tests, which require relatively small power consumption for only a couple of minutes. What is needed is a low-cost, disposable, and eco-friendly micro-power source that can be easily integrated with paper-based devices and be readily activated even in those challenging field conditions.
Here we provide a realistic and accessible solution as a novel power source that can enable a self-powered paper-based diagnostic test for anyone, anywhere, and anytime. The work creates a paper-based microbial fuel cell (MFC) device that is pre-inoculated with Bacillus subtilis endospores and can be activated with a drop of human body fluids, such as sweat or saliva. B. subtilis endospores are a resilient, desiccation-resistant state of the bacteria that can develop in a nutrient-deficient environment. These endospores are pre-loaded into the anode of the device and begin germination and electricity generation once nutrients become available. Dropping bodily fluids onto the device’s inlet introduces these nutrients to the endospores and activates the biobattery. The design consists of several individual MFC units that can be easily connected through a simple folding mechanism to achieve a higher output power.
Since they are low-cost, fast-acting, and disposable, paper-based MFCs have shown potential for applications in powering a variety of low-power, POC diagnostic tools, especially in resource-limited environments that lack dependable access to other forms of power. Conventional MFC operation often requires exoelectrogen-containing or nutrient-rich water from the environment to be applied to the MFC for activation, but access to such a water source may not always be available. Using bodily fluids to activate the device allows for it to be readily used even in dry climates without access to nutrient-rich environmental water. Since local bacteria may also be incapable of generating electricity, some previous MFC devices have included pre-inoculated, lyophilized exoelectrogens, but lyophilized bacteria have been shown to suffer from significant performance decline over time during storage. Using dehydrated B. subtilis endospores instead extends the durability and shelf-life of the MFC, while still allowing for rapid, on-demand electricity generation once activated.

Nervous tissue has the extraordinary ability to reconfigure the synaptic connections between its neurons and form new neural pathways. This mechanism of neuroplasticity allows for dynamic adaptations in reponse to learning or to repair tissue damaged by injury. Achieving this reconfigurability in engineered systems could allow future machines and electronics to be more adaptive, sustainable, and robust to damage. Such capabilities will be especially critical in emerging fields like soft robotics and stretchable electronics, which are designed to match the versatility and rich multifunctionality of soft natural organisms and tissue. In this talk, I will highlight progress in creating bioinspired circuits that are soft, stretchable, and electrically reconfigurable. This includes recent work on electrically conductive hydrogel composites in which a soft hydrogel is embedded with percolating networks of silver flakes that reversibly reconfigure under hydration, heat, and electrical stimulation. I will also present our ongoing work on creating self-reconfigurable soft circuits using liquid metal (LM). Eutectic gallium indium (EGaIn) is selected as the LM alloy due to its enabling combination of high electrical conductivity and fluidic deformability. When embedded in soft elastomer, microscale droplets of EGaIn can be selectively connected to form electrically conductive pathways that reconfigure in response to mechanical loading and damage. To demonstrate their potential role in future soft material technologies, I will present examples of how these Ag-hydrogel and LM-elastomer composites can be used for sensing, power transmission, and actuation in soft robotics and stretchable electronics applications.