The analysis of tissue cultures requires a sophisticated integration and coordination of multiple technologies for monitoring and measuring. We have developed an automated research platform enabling independent devices to achieve collaborative objectives for feedback-driven cell culture studies. Our approach enables continuous, communicative, non-invasive interactions within an Internet of Things (IoT) architecture among various sensing and actuation devices, achieving precisely timed control of in vitro biological experiments. The framework integrates microfluidics, electrophysiology, and imaging devices to maintain cerebral cortex organoids while measuring their neuronal activity. The organoids are cultured in custom, 3D-printed chambers affixed to commercial microelectrode arrays. Periodic feeding is achieved using programmable microfluidic pumps. We developed a computer vision fluid volume estimator used as feedback to rectify deviations in microfluidic perfusion during media feeding/aspiration cycles. We validated the system with a set of 7-day studies of mouse cerebral cortex organoids, comparing manual and automated protocols. It was shown that the automated protocols maintained robust neural activity throughout the experiment while enabling hourly electrophysiology recordings during the experiments. The median firing rates of neural units increased for each sample, and dynamic patterns of organoid firing rates were revealed by high-frequency recordings. Surprisingly, feeding did not affect the firing rate. Furthermore, media exchange during a recording did not show acute effects on firing rate, enabling the use of this automated platform for reagent screening studies.

Electrophysiology offers a high-resolution method for real-time measurement of neural activity. Longitudinal recordings from high-density microelectrode arrays (HD-MEAs) can be of considerable size for local storage and of substantial complexity for extracting neural features and network dynamics. Analysis is often demanding due to the need for multiple software tools with different runtime dependencies. To address these challenges, we developed an open-source cloud-based pipeline to store, analyze, and visualize neuronal electrophysiology recordings from HD-MEAs. This pipeline is dependency agnostic by utilizing cloud storage, cloud computing resources, and an Internet of Things messaging protocol. We containerized the services and algorithms to serve as scalable and flexible building blocks within the pipeline. In this paper, we applied this pipeline on two types of cultures, cortical organoids and ex vivo brain slice recordings to show that this pipeline simplifies the data analysis process and facilitates understanding neuronal activity.

Organ-on-a-chip systems combine microfluidics, cell biology, and tissue engineering to culture 3D organ-specific in vitro models that recapitulate the biology and physiology of their in vivo counterparts. Here, we have developed a multiplex platform that automates the culture of individual organoids in isolated microenvironments at user-defined media flow rates. Programmable workflows allow the use of multiple reagent reservoirs that may be applied to direct differentiation, study temporal variables, and grow cultures long term. Novel techniques in polydimethylsiloxane (PDMS) chip fabrication are described here that enable features on the upper and lower planes of a single PDMS substrate. RNA sequencing (RNA-seq) analysis of automated cerebral cortex organoid cultures shows benefits in reducing glycolytic and endoplasmic reticulum stress compared to conventional in vitro cell cultures.

The SARS-CoV-2 pandemic has challenged humankind's ability to quickly determine the cascade of health effects caused by a novel infection. Even with the unprecedented speed at which vaccines were developed and introduced into society, identifying therapeutic interventions and drug targets for patients infected with the virus remains important as new strains of the virus evolve, or future coronaviruses may emerge that are resistant to current vaccines. The application of transcriptomic RNA sequencing of infected samples may shed new light on the pathways involved in viral mechanisms and host responses. We describe the application of the previously developed "dual RNA-seq" approach to investigate, for the first time, the co-regulation between the human and SARS-CoV-2 transcriptomes. Together with differential expression analysis, we describe the tissue specificity of SARS-CoV-2 expression, an inferred lipopolysaccharide response, and co-regulation of CXCL's, SPRR's, S100's with SARS-CoV-2 expression. Lipopolysaccharide response pathways in particular offer promise for future therapeutic research and the prospect of subgrouping patients based on chemokine expression that may help explain the vastly different reactions patients have to infection. Taken together these findings highlight unappreciated SARS-CoV-2 expression signatures and emphasize new considerations and mechanisms for SARS-CoV-2 therapeutic intervention.

The Internet of Things (IoT) provides a simple framework to easily control online devices. IoT is now a commonplace tool used by technology companies, but it is rarely used in biology experiments. IoT can benefit research through alarm notifications, automation, and the real-time monitoring of experiments. We developed and implemented an IoT architecture to control biological devices used in experiments. We developed our own electrophysiology, microscopy, and microfluidic devices so that may be controlled through a unified IoT architecture. The system allows each device to be monitored and controlled through an online web tool. We present our IoT architecture so other labs may replicate it for their own experiments.

Simultaneous longitudinal imaging across multiple conditions and replicates has been crucial for scientific studies aiming to understand biological processes and disease. Yet, imaging systems capable of accomplishing these tasks are economically unattainable for most academic and teaching laboratories around the world. Here, we propose the Picroscope, which is the first low-cost system for simultaneous longitudinal biological imaging made primarily using off-the-shelf and 3D-printed materials. The Picroscope is compatible with standard 24-well cell culture plates and captures 3D z-stack image data. The Picroscope can be controlled remotely, allowing for automatic imaging with minimal intervention from the investigator. Here, we use this system in a range of applications. We gathered longitudinal whole organism image data for frogs, zebrafish, and planaria worms. We also gathered image data inside an incubator to observe 2D monolayers and 3D mammalian tissue culture models. Using this tool, we can measure the behavior of entire organisms or individual cells over long-time periods.

Optical sensing is an important research field due to its proven ability to be extremely sensitive, nondestructive, and applicable to sensing a wide range of chemical, thermal, electric, or magnetic phenomena. Beyond traditional optical sensors that often rely on bulky setups, plasmonic nanostructures can offer many advantages based on their sensitivity, compact form, cost-effectiveness, multiplexing compatibility, and compatibility with many standard semiconductor nanofabrication techniques. In particular, plasmonenhanced optical transmission through arrays of nanostructured holes has led to the development of a new generation of optical sensors. In this chapter we present a simple fabrication technique to use plasmonic nanostructures as compact sensors. We position the nanohole array, an LED illumination source, and a spacer layer directly on top of a standard complementary metal-oxide-semiconductor (CMOS) imager chip. This setup is a viable sensor platform in both liquid and gas environments. These devices could operate as low-cost sensors for environmental monitoring, security, food safety, or monitoring smallmolecule binding to extract affinity information and binding constants.

Plasmon-enhanced optical transmission through arrays of nano-structured holes has led to the development of a new generation of optical sensors. In this paper, to dramatically simplify the standard optical setups of these sensors, we position the nanoholes, an LED illumination source and a spacer layer directly on top of a CMOS imager chip. Transmitted light diffracts from the nanohole array, spreading into a spectrum over the space of a millimeter to land on the imager as a full spectrum. Our chip is used as a sensor in both a liquid and a gas environment. The spectrum is monitored in real-time and the plasmon-enhanced transmission peaks shift upon exposure to different concentrations of glycerol-in-water solutions or ethanol vapors in nitrogen. While liquids provide good refractive index contrast for sensing, to enhance sensitivity to solvent vapors, we filled the nanoholes with solvatochromic dyes. This on-chip solution circumvents the bulky components (e.g. microscopes, coupling optics, and spectrometers) needed for traditional plasmonic sensing setups, uses the nanohole array as both the sensing surface and a diffraction grating, and maintains good sensitivity. Finally, we show simultaneous sensing from two side-by-side locations, demonstrating potential for multiplexing and lab on a chip integration.