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Alternative computing approaches that interface readily with physical systems are well suited for embedded control of those systems. We demonstrate finite state machines implemented as pneumatic circuits of microfluidic valves and use these controllers to direct microfluidic liquid handling procedures on the same chip. These monolithic integrated systems require only power to be supplied externally, in the form of a vacuum source. User input can be provided directly to the chip by covering pneumatic ports with a finger. State machines with up to four bits of state memory are demonstrated, and next-state combinational logic can be fully reprogrammed by changing the hole-punch pattern on a membrane in the chip. These pneumatic computers demonstrate a framework for the embedded control of physical systems and open a path to stand-alone lab-on-a-chip devices capable of highly complex functionality.

Dry film photoresists are widely employed to fabricate high-aspect-ratio microstructures, such as molds for microfluidic devices. Unlike liquid resists, such as SU-8, dry films do not require a cleanroom facility, and it is straightforward to prepare uniform and reproducible films as thick as 500 µm. Multilayer patterning, however, can be problematic with dry film resists even though it is critical for a number of microfluidic devices. Layer-to-layer mask alignment typically requires the first layer to be fully developed, making the pattern visible, before applying and patterning the second layer. While a liquid resist can flow over the topography of previous layers, this is not the case with dry film lamination. We found that post-exposure baking of dry film photoresists can preserve a flat topography while revealing an image of the patterned features that is suitable for alignment to the next layer. We demonstrate the use of this technique with two different types of dry film resist to fabricate master molds for a hydrophoresis size-sorting device and a cell chemotaxis device.

Microfluidic droplet generation typically entails an initial stabilization period on the order of minutes, exhibiting higher variation in droplet volume until the system reaches monodisperse production. The material lost during this period can be problematic when preparing droplets from limited samples such as patient biopsies. Active droplet generation strategies such as antiphase peristaltic pumping effectively reduce stabilization time but have required off-chip control hardware that reduces system accessibility. We present a fully integrated device that employs on-chip pneumatic logic to control phase-optimized peristaltic pumping. Droplet generation stabilizes in about a second, with only one or two non-uniform droplets produced initially.

Microfluidic devices are traditionally monitored by bulky and expensive off-chip sensors. We have developed a soft piezoresistive sensor capable of measuring micron-level strains that can be easily integrated into devices via soft lithography. We apply this sensor to achieve fast and localized monitoring of pressure, flow, and valve actuation.

We present a simple method to pattern multiple cell populations inside a microfluidic channel. The microchannel is partially filled with a cell suspension, and the position of the liquid boundary remains pinned by surface tension. Cells then adhere only in the filled portion of the channel, producing a very sharp boundary. The process can be performed in an unmodified microfluidic channel with only a manual syringe and can be repeated multiple times to pattern cocultures or tricultures. We demonstrate the patterning method with two different mammalian cell types, 3T3 fibroblasts and NMuMG epithelial cells, and channel heights of 1.5 mm and 0.5 mm. We anticipate that this method will be useful for studies of cell-cell interactions where precise control of the fluidic microenvironment is required.

Tissues are increasingly being analyzed at the single cell level in order to characterize cellular diversity and identify rare cell types. Single cell analysis efforts are greatly limited, however, by the need to first break down tissues into single cell suspensions. Current dissociation methods are inefficient, leaving a significant portion of the tissue as aggregates that are filtered away or left to confound results. Here, we present a simple and inexpensive microfluidic device that simultaneously filters large tissue fragments and dissociates smaller aggregates into single cells, thereby improving single cell yield and purity. The device incorporates two nylon mesh membranes with well-defined, micron-sized pores that operate on aggregates of different size scales. We also designed the device so that the first filtration could be performed under tangential flow to minimize clogging. Using cancer cell lines, we demonstrated that aggregates were effectively dissociated using high flow rates and pore sizes that were smaller than a single cell. However, pore sizes that were less than half the cell size caused significant damage. We then improved results by passing the sample through two filter devices in series, with single cell yield and purity predominantly determined by the pore size of the second membrane. Next, we optimized performance using minced and digested murine kidney tissue samples, and determined that the combination of 50 and 15 μm membranes was optimal. Finally, we integrated these two membranes into a single filter device and performed validation experiments using minced and digested murine kidney, liver, and mammary tumor tissue samples. The dual membrane microfluidic filter device increased single cell numbers by at least 3-fold for each tissue type, and in some cases by more than 10-fold. These results were obtained in minutes without affecting cell viability, and additional filtering would not be required prior to downstream applications. In future work, we will create complete tissue analysis platforms by integrating the dual membrane microfluidic filter device with additional upstream tissue processing technologies, as well as downstream operations such as cell sorting and detection.

The ability to harvest single cells from tissues is currently a bottleneck for cell-based diagnostic technologies, and remains crucial in the fields of tissue engineering and regenerative medicine. Tissues are typically broken down using proteolytic digestion and various mechanical treatments, but success has been limited due to long processing times, low yield, and high manual labor burden. Here, we present a novel microfluidic device that utilizes precision fluid flows to improve the speed and efficiency of tissue digestion. The microfluidic channels were designed to apply hydrodynamic shear forces at discrete locations on tissue specimens up to 1 cm in length and 1 mm in diameter, thereby accelerating digestion through hydrodynamic shear forces and improved enzyme-tissue contact. We show using animal organs that our digestion device with hydro-mincing capabilities was superior to conventional scalpel mincing and digestion based on recovery of DNA and viable single cells. Thus, our microfluidic digestion device can eliminate or reduce the need to mince tissue samples with a scalpel, while reducing sample processing time and preserving cell viability. Another advantage is that downstream microfluidic operations could be integrated to enable advanced cell processing and analysis capabilities. We envision our novel device being used in research and clinical settings to promote single cell-based analysis technologies, as well as to isolate primary, progenitor, and stem cells for use in the fields of tissue engineering and regenerative medicine.

The endometrium is the inner lining of the uterus. Following specific cyclic hormonal stimulation, endometrial stromal fibroblasts (stroma) and vascular endothelial cells exhibit morphological and biochemical changes to support embryo implantation and regulate vascular function, respectively. Herein, we integrated a resin-based porous membrane in a dual chamber microfluidic device in polydimethylsiloxane that allows long term in vitro co-culture of human endometrial stromal and endothelial cells. This transparent, 2-μm porous membrane separates the two chambers, allows for the diffusion of small molecules and enables high resolution bright field and fluorescent imaging. Within our primary human co-culture model of stromal and endothelial cells, we simulated the temporal hormone changes occurring during an idealized 28-day menstrual cycle. We observed the successful differentiation of stroma into functional decidual cells, determined by morphology as well as biochemically as measured by increased production of prolactin. By controlling the microfluidic properties of the device, we additionally found that shear stress forces promoted cytoskeleton alignment and tight junction formation in the endothelial layer. Finally, we demonstrated that the endometrial perivascular stroma model was sustainable for up to 4 weeks, remained sensitive to steroids and is suitable for quantitative biochemical analysis. Future utilization of this device will allow the direct evaluation of paracrine and endocrine crosstalk between these two cell types as well as studies of immunological events associated with normal vs. disease-related endometrial microenvironments.

Micropatterned cocultures are a useful experimental tool for the study of cell-cell interactions. Patterning methods often rely on sequential seeding of different cell types or removal of a barrier separating two populations, but it is difficult to pattern sharp interfaces between pure populations with low cross-contamination when using these approaches. Patterning by the use of reconfigurable substrates can overcome these limitations, but such methods can be costly and challenging to employ in a typical biology laboratory. Here, we describe a low-cost and simple-to-use reconfigurable substrate comprised of a transparent elastic material that is partially cut to form a slit that opens when the device is stretched. The slit seals back up when released, allowing two initially separate, adherent cell populations to be brought together to form a contact interface. Fluorescent imaging of patterned cocultures demonstrates the early establishment of a sharp cellular interface. As a proof of principle, we demonstrate the use of this device to study competition at the interface of two stem cell populations.

The spatial organization of cellular communities plays a fundamental role in determining intercellular communication and emergent behavior. However, few tools exist to modulate tissue organization at the scale of individual cells, particularly in the case of dynamic manipulation. Micromechanical reconfigurable culture achieves dynamic control of tissue organization by culturing adherent cells on microfabricated plates that can be shifted to reorganize the arrangement of the cells. While biological studies utilizing this approach have been previously reported, this paper focuses on the engineering of the device, including the mechanism for translating manual manipulation to precise microscale position control, fault-tolerant design for manufacture, and the synthetic-to-living interface.

Microporous membranes are widely utilized in cell biology to study cell-cell signaling and cell migration. However, the thickness and low porosity of commercial track-etched membranes limit the quality of cell imaging and the degree of cell-cell contact that can be achieved on such devices. We employ photolithography-based microfabrication to achieve porous membranes with pore diameter as small as 0.9 μm, up to 40% porosity, and less than 5% variation in pore size. Through the use of a soap release layer, membranes as thin as 1 μm can be achieved. The thin membranes minimally disrupt contrast enhancement optics, thus allowing good quality imaging of unlabeled cells under white light, unlike commercial membranes. In addition, the polymer membrane materials display low autofluorescence even after patterning, facilitating high quality fluorescence microscopy. Finally, confocal imaging suggests that substantial cell-cell contact is possible through the pores of these thin membranes. This membrane technology can enhance existing uses of porous membranes in cell biology as well as enable new types of experiments.

Self-monitoring of blood glucose is a critical component of diabetes management. However, patients often do not maintain the testing schedule recommended by their healthcare provider. Many barriers to testing have been cited, including cost and pain. We present a small pilot study to explore whether the use of financial incentives and pain-free lancets could improve adherence to glucose testing in a community health center patient population consisting largely of non-English speaking ethnic minorities with low health literacy. The proportion of patients lost to follow-up was 17%, suggesting that a larger scale study is feasible in this type of setting, but we found no preliminary evidence suggesting a positive effect on adherence by either financial incentives or pain-free lancets. Results from this pilot study will guide the design of larger-scale studies to evaluate approaches to overcome the variety of barriers to glucose testing that are present in disadvantaged patient populations.

Frequency references are fundamental to most digital systems, providing the basis for process synchronization, timing of outputs, and waveform synthesis. Recently, there has been growing interest in digital logic systems that are constructed out of microfluidics rather than electronics, as a possible means toward fully integrated laboratory-on-a-chip systems that do not require any external control apparatus. However, the full realization of this goal has not been possible due to the lack of on-chip frequency references, thus requiring timing signals to be provided from off-chip. Although microfluidic oscillators have been demonstrated, there have been no reported efforts to characterize, model, or optimize timing accuracy, which is the fundamental metric of a clock. Here, we report pneumatic ring oscillator circuits built from microfluidic valves and channels. Further, we present a compressible-flow analysis that differs fundamentally from conventional circuit theory, and we show the utility of this physically based model for the optimization of oscillator stability. Finally, we leverage microfluidic clocks to demonstrate circuits for the generation of phase-shifted waveforms, self-driving peristaltic pumps, and frequency division. Thus, pneumatic oscillators can serve as on-chip frequency references for microfluidic digital logic circuits. On-chip clocks and pumps both constitute critical building blocks on the path toward achieving autonomous laboratory-on-a-chip devices.

Cell behavior on 2-D in vitro cultures is continually being improved to better mimic in vivo physiological conditions by combining niche cues including multiple cell types and substrate stiffness, which are well known to impact cell phenotype. However, no system exists in which a user can systematically examine cell behavior on a substrate with a specific stiffness (elastic modulus) in culture with a different cell type, while maintaining distinct cell populations. We demonstrate the modification of a silicon reconfigurable co-culture system with a covalently linked hydrogel of user-defined stiffness. This device allows the user to control whether two separate cell populations are in contact with each other or only experience paracrine interactions on substrates of controllable stiffness. To illustrate the utility of this device, we examined the role of substrate stiffness combined with myoblast co-culture on adipose derived stem cell (ASC) differentiation and found that the presence of myoblasts and a 10 kPa substrate stiffness increased ASC myogenesis versus co-culture on stiff substrates. As this example highlights, this technology better controls the in vitro microenvironment, allowing the user to develop a more thorough understanding of the combined effects of cell-cell and cell-matrix interactions.

PIEZO1 is critical to numerous physiological processes, transducing diverse mechanical stimuli into electrical and chemical signals. Recent studies underscore the importance of visualizing endogenous PIEZO1 activity and localization to understand its functional roles. To enable physiologically and clinically relevant studies on human PIEZO1, we genetically engineered human induced pluripotent stem cells (hiPSCs) to express a HaloTag fused to endogenous PIEZO1. Combined with advanced imaging, our chemogenetic platform allows precise visualization of PIEZO1 localization dynamics in various cell types. Furthermore, the PIEZO1-HaloTag hiPSC technology facilitates the non-invasive monitoring of channel activity across diverse cell types using Ca 2+ -sensitive HaloTag ligands, achieving temporal resolution approaching that of patch clamp electrophysiology. Finally, we used lightsheet imaging of hiPSC-derived neural organoids to achieve molecular scale imaging of PIEZO1 in three-dimensional tissue organoids. Our advances offer a novel platform for studying PIEZO1 mechanotransduction in human cells and tissues, with potential for elucidating disease mechanisms and targeted therapeutic development.

Systems biology models are useful models of complex biological systems that may require a large amount of experimental data to fit each model's parameters or to approximate a likelihood function. These models range from a few to thousands of parameters depending on the complexity of the biological system modeled, potentially making the task of fitting parameters to the model difficult - especially when new experimental data cannot be gathered. We demonstrate a method that uses structural biology predictions to augment systems biology models to improve systems biology models' predictions without having to gather more experimental data. Additionally, we show how systems biology models' predictions can help evaluate novel structural biology hypotheses, which may also be expensive or infeasible to validate.

Simulation-based inference (SBI) methods tackle complex scientific models with challenging inverse problems. However, SBI models often face a significant hurdle due to their non-differentiable nature, which hampers the use of gradient-based optimization techniques. Bayesian Optimal Experimental Design (BOED) is a powerful approach that aims to make the most efficient use of experimental resources for improved inferences. While stochastic gradient BOED methods have shown promising results in high-dimensional design problems, they have mostly neglected the integration of BOED with SBI due to the difficult non-differentiable property of many SBI simulators. In this work, we establish a crucial connection between ratio-based SBI inference algorithms and stochastic gradient-based variational inference by leveraging mutual information bounds. This connection allows us to extend BOED to SBI applications, enabling the simultaneous optimization of experimental designs and amortized inference functions. We demonstrate our approach on a simple linear model and offer implementation details for practitioners.