A computer vision approach for analyzing label free leukocyte trafficking dynamics on a microvascular mimetic.

High-content imaging techniques in conjunction with in vitro microphysiological systems (MPS) allow for novel explorations of physiological phenomena with a high degree of translational relevance due to the usage of human cell lines. MPS featuring ultrathin and nanoporous silicon nitride membranes (µSiM) have been utilized in the past to facilitate high magnification phase contrast microscopy recordings of leukocyte trafficking events in a living mimetic of the human vascular microenvironment. Notably, the imaging plane can be set directly at the endothelial interface in a µSiM device, resulting in a high-resolution capture of an endothelial cell (EC) and leukocyte coculture reacting to different stimulatory conditions. The abundance of data generated from recording observations at this interface can be used to elucidate disease mechanisms related to vascular barrier dysfunction, such as sepsis. The appearance of leukocytes in these recordings is dynamic, changing in character, location and time. Consequently, conventional image processing techniques are incapable of extracting the spatiotemporal profiles and bulk statistics of numerous leukocytes responding to a disease state, necessitating labor-intensive manual processing, a significant limitation of this approach. Here we describe a machine learning pipeline that uses a semantic segmentation algorithm and classification script that, in combination, is capable of automated and label-free leukocyte trafficking analysis in a coculture mimetic. The developed computational toolset has demonstrable parity with manually tabulated datasets when characterizing leukocyte spatiotemporal behavior, is computationally efficient and capable of managing large imaging datasets in a semi-automated manner.

Sourcing cells for in vitro models of human vascular barriers of inflammation.

The vascular system plays a critical role in the progression and resolution of inflammation. The contributions of the vascular endothelium to these processes, however, vary with tissue and disease state. Recently, tissue chip models have emerged as promising tools to understand human disease and for the development of personalized medicine approaches. Inclusion of a vascular component within these platforms is critical for properly evaluating most diseases, but many models to date use "generic" endothelial cells, which can preclude the identification of biomedically meaningful pathways and mechanisms. As the knowledge of vascular heterogeneity and immune cell trafficking throughout the body advances, tissue chip models should also advance to incorporate tissue-specific cells where possible. Here, we discuss the known heterogeneity of leukocyte trafficking in vascular beds of some commonly modeled tissues. We comment on the availability of different tissue-specific cell sources for endothelial cells and pericytes, with a focus on stem cell sources for the full realization of personalized medicine. We discuss sources available for the immune cells needed to model inflammatory processes and the findings of tissue chip models that have used the cells to studying transmigration.

The Modular µSiM Reconfigured: Integration of Microfluidic Capabilities to Study In Vitro Barrier Tissue Models under Flow.

Microfluidic tissue barrier models have emerged to address the lack of physiological fluid flow in conventional "open-well" Transwell-like devices. However, microfluidic techniques have not achieved widespread usage in bioscience laboratories because they are not fully compatible with traditional experimental protocols. To advance barrier tissue research, there is a need for a platform that combines the key advantages of both conventional open-well and microfluidic systems. Here, a plug-and-play flow module is developed to introduce on-demand microfluidic flow capabilities to an open-well device that features a nanoporous membrane and live-cell imaging capabilities. The magnetic latching assembly of this design enables bi-directional reconfiguration and allows users to conduct an experiment in an open-well format with established protocols and then add or remove microfluidic capabilities as desired. This work also provides an experimentally-validated flow model to select flow conditions based on the experimental needs. As a proof-of-concept, flow-induced alignment of endothelial cells and the expression of shear-sensitive gene targets are demonstrated, and the different phases of neutrophil transmigration across a chemically stimulated endothelial monolayer under flow conditions are visualized. With these experimental capabilities, it is anticipated that both engineering and bioscience laboratories will adopt this reconfigurable design due to the compatibility with standard open-well protocols.

The Modular µSiM: A Mass Produced, Rapidly Assembled, and Reconfigurable Platform for the Study of Barrier Tissue Models In Vitro.

Advanced in vitro tissue chip models can reduce and replace animal experimentation and may eventually support "on-chip" clinical trials. To realize this potential, however, tissue chip platforms must be both mass-produced and reconfigurable to allow for customized design. To address these unmet needs, an extension of the µSiM (microdevice featuring a silicon-nitride membrane) platform is introduced. The modular µSiM (m-µSiM) uses mass-produced components to enable rapid assembly and reconfiguration by laboratories without knowledge of microfabrication. The utility of the m-µSiM is demonstrated by establishing an hiPSC-derived blood-brain barrier (BBB) in bioengineering and nonengineering, brain barriers focused laboratories. In situ and sampling-based assays of small molecule diffusion are developed and validated as a measure of barrier function. BBB properties show excellent interlaboratory agreement and match expectations from literature, validating the m-µSiM as a platform for barrier models and demonstrating successful dissemination of components and protocols. The ability to quickly reconfigure the m-µSiM for coculture and immune cell transmigration studies through addition of accessories and/or quick exchange of components is then demonstrated. Because the development of modified components and accessories is easily achieved, custom designs of the m-µSiM shall be accessible to any laboratory desiring a barrier-style tissue chip platform.

Molecular mechanisms underlying the heterogeneous barrier responses of two primary endothelial cell types to sphingosine-1-phosphate.

Sphingosine-1-phosphate (S1P) signals to enhance or destabilize the vascular endothelial barrier depending on the receptor engaged. Here, we investigated the differential barrier effects of S1P on two influential primary endothelial cell (EC) types, human umbilical vein endothelial cells (HUVECs) and human pulmonary microvascular endothelial cells (HPMECs). S1PR1 (barrier protective) and S1PR3 (barrier disruptive) surface and gene expression were quantified by flow cytometry and immunofluorescence, and RT-qPCR, respectively. Functional evaluation of EC monolayer permeability in response to S1P was quantified with transendothelial electrical resistance (TEER) and small molecule permeability. S1P significantly enhanced HUVEC barrier function, while promoting HPMEC barrier breakdown. Immunofluorescence and flow cytometry analysis showed select, S1PR3-high HPMECs, suggesting susceptibility to barrier destabilization following S1P exposure. Reevaluation of HPMEC barrier following S1P exposure under inflamed conditions demonstrated synergistic barrier disruptive effects of pro-inflammatory cytokine and S1P. The role of the Rho-ROCK signaling pathway under these conditions was confirmed through ROCK1/2 inhibition (Y-27632). Thus, the heterogeneous responses of ECs to S1P signaling are mediated through Rho-ROCK signaling, and potentially driven by differences in the surface expression of S1PR3.

Silicon Nanomembrane Filtration and Imaging for the Evaluation of Microplastic Entrainment along a Municipal Water Delivery Route.

To better understand the origin of microplastics in municipal drinking water, we evaluated 50 mL water samples from different stages of the City of Rochester's drinking water production and transport route, from Hemlock Lake to the University of Rochester. We directly filtered samples using silicon nitride nanomembrane filters with precisely patterned slit-shaped pores, capturing many of the smallest particulates (<20 µm) that could be absorbed by the human body. We employed machine learning algorithms to quantify the shapes and quantity of debris at different stages of the water transport process, while automatically segregating out fibrous structures from particulate. Particulate concentrations ranged from 13 to 720 particles/mL at different stages of the water transport process and fibrous pollution ranged from 0.4 to 8.3 fibers/mL. A subset of the debris (0.2-8.6%) stained positively with Nile red dye which identifies them as hydrophobic polymers. Further spectroscopic analysis also indicated the presence of many non-plastic particulates, including rust, silicates, and calcium scale. While water leaving the Hemlock Lake facility is mostly devoid of debris, transport through many miles of piping results in the entrainment of a significant amount of debris, including plastics, although in-route reservoirs and end-stage filtration serve to reduce these concentrations.