A More Biomimetic Cell Migration Assay with High Reliability and Its Applications

Yang

Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022)

et al. 2023

Cell migration assay is the most common research approach for cell migration. Quantitative research and analysis are carried out by measuring the migration of cells into the region that is artificially created among confluent monolayer cells. To improve the efficiency and accuracy of the analysis, the software/tools were developed to assist the image analysis process. However, these software and tools are still at the stage of measuring a single sample, which cannot satisfy the requirement of large sample size for cell migration assay device. In this paper, an image analysis tool based on Fiji is developed, which can segment multiple samples from a scanned image and then analyze a single sample in batch. In addition, the screening function should be added for the application scenario of large sample size. The samples can be filtered according to different conditions to improve the consistency of experimental conditions. The results show that the developed analysis tool ATCA has high accuracy in identifying cell-free zones, with a difference of 2.3% from the tool WHST and 2.9% from manual operation. The analysis efficiency of this tool is 15 times that of manual operation.

Section: Resultsmentioning

confidence: 99%

“…The scanned images are from a cell migration assay device made in previous work. The quantitative analysis results of fluid shear environment are derived from the shear stress distribution simulated by finite element method in our previous work [12] .…”

Section: Introductionmentioning

confidence: 99%

An image analysis tool for cell migration assay with a large sample size

Yang

Fifth International Conference on Computer Information Science and Artificial Intelligence (CISAI 2022)

et al. 2023

“…In future work, achieving full automation and fast data collection will also enable many samples to be collected in a single device under the same conditions, which will allow thorough evaluation of the reproducibility of biological data collected in OOC studies. In a recent study, large sample sizes collected under controlled conditions enabled evaluation of data reproducibility for a cell migration assay 50 .…”

Section: Discussionmentioning

confidence: 99%

Measurement of oxygen consumption rates of human renal proximal tubule cells in an array of organ-on-chip devices to monitor drug-induced metabolic shifts

et al. 2022

Measurement of cell metabolism in moderate-throughput to high-throughput organ-on-chip (OOC) systems would expand the range of data collected for studying drug effects or disease in physiologically relevant tissue models. However, current measurement approaches rely on fluorescent imaging or colorimetric assays that are focused on endpoints, require labels or added substrates, and lack real-time data. Here, we integrated optical-based oxygen sensors in a high-throughput OOC platform and developed an approach for monitoring cell metabolic activity in an array of membrane bilayer devices. Each membrane bilayer device supported a culture of human renal proximal tubule epithelial cells on a porous membrane suspended between two microchannels and exposed to controlled, unidirectional perfusion and physiologically relevant shear stress for several days. For the first time, we measured changes in oxygen in a membrane bilayer format and used a finite element analysis model to estimate cell oxygen consumption rates (OCRs), allowing comparison with OCRs from other cell culture systems. Finally, we demonstrated label-free detection of metabolic shifts in human renal proximal tubule cells following exposure to FCCP, a drug known for increasing cell oxygen consumption, as well as oligomycin and antimycin A, drugs known for decreasing cell oxygen consumption. The capability to measure cell OCRs and detect metabolic shifts in an array of membrane bilayer devices contained within an industry standard microtiter plate format will be valuable for analyzing flow-responsive and physiologically complex tissues during drug development and disease research.

“…Alternatively, researchers have also applied migration assays without injury as a comparison. Injury-free assays such as cell stamping, Figure 1c, provide a baseline cell migration that may be affected by factors outside of wounding ( Yin et al, 2022 ), for example, exposure to diabetic conditions. Sano et al conducted a scientific investigation to examine the impact of fluctuating oxygen environments on the progression of wound healing in a murine model ( Sano et al, 2012 ).…”

Section: Introductionmentioning

confidence: 99%

Tradeoffs in ATP metabolisms via hypoxic gradient migration assays

Orabi,

Duan,

Zhou

et al. 2024

Preprint

Migration and scratch assays are helpful tools to investigate wound healing and tissue regeneration processes, especially under disease conditions such as diabetes. However, traditional migration (injury-free) assays and scratch (with injury) assays are limited in their control over cellular environments and provide only simplified read-outs of their results. On the other hand, microfluidic-based cell assays offer a distinct advantage in their integration and scalability for multiple modalities and concentrations in a single device. Additionally, in situ stimulation and detection helps to avoid variabilities between individual bioassays. To realize an enhanced, smarter migration assay, we leveraged our multilayered oxygen gradient (1-16%) to study HaCaT migrations in diabetic conditions with spatial and metabolic read-outs. An analysis of the spatial migration over time observed a new dynamic between hypoxia (at 4.16-9.14% O2) and hyperglycemia. Furthermore, in situ adenosine triphosphate (ATP) and reactive oxygen species (ROS) responses suggest that this dynamic represents a switch between stationary versus motile modes of metabolism. Thus, elevated glucose and hypoxia are synergistic triggers of this switch under disease conditions. These findings illustrate the benefits of spatial microfluidics for modeling complex diseases such as hypoxia and diabetes, where multimodal measurements provide a more deterministic view of the underlying processes.