Z45 - Real-time gene expression mapping in a tissue-engineeered microvessel

Saturday, October 11, 2025

10:00 AM - 11:00 AM PDT

Location: Exhibit Hall F, G & H

Presenting Author(s)

Amelia Koehn

Undergraduate Researcher
Kansas State University, United States

Co-Author(s)

Ava Hornung

Undergraduate Researcher
Kansas State University, United States

Primary Investigator(s)

Ninghao Zhu, PhD

Assistant Professor
Kansas State University
Manhattan, Kansas, United States

Introduction: : Microvessels play an important role in the exchange of nutrients and waste between blood and tissue. Microvessel abnormalities, especially in the brain, can be initiated from endothelium inflammation and atherosclerosis and lead to stroke or other neurological diseases. Therefore, efforts have been devoted to construct microvessel models in vitro to investigate human microvasculature in health and diseases. Current microvessel models include tissue-engineered models that recapitulate the structural and biological characteristics of native human microvessels in vitro, supporting the research in microvessel structural integrity under inflammation, drug delivery and the discovery of potential disease pathways. However, investigating the dynamic gene expression in these microvessel models has been challenging due to the lack of real-time gene expression monitoring methods. Currently, approaches to study gene expression in tissue-engineered microvessels include qRT-PCR, RNA fluorescence in situ hybridization, and next-generation sequencing. However, these methods require fixation or lysis of the cells, which limits their ability to detect gene expression in a living system. Here, we propose the integration of a novel nanobiosensor into a tissue-engineered microvessel to allow the real-time gene expression in live cells. We monitored the ß-actin mRNA expression in the living tissue-engineered microvessel. This platform is an unprecedented tool to monitor gene expression in a reliable human model, which will allow us to develop more accurate models of a wide range of diseases, paving the way for therapeutic development and treatments.

Materials and

Methods: : A nanobiosensor was created by mixing gold nanorod (GNR) with biocompatible coating and a fluorophore-labeled locked nucleic acid (LNA) probe designed to hybridize with the accessible region of target mRNA (Fig. A). The GNR-LNA nanobiosensor was then delivered into live human endothelial cells (ECs, Human Umbilical Vein Endothelial Cells) (Fig. B). The LNA will be released from GNR when combined with target RNA and generate a fluorescence signal.
A tissue-engineered microvessel was constructed by first injecting a 7 mg/mL collagen hydrogel into a PDMS device with a 150 µm diameter template rod in the center of the channel. To form the microvessel lumen, the template rod was pulled from the collagen and the vessel was filled with EC medium.
The microvessel was seeded with the ECs containing GNR-LNA, prepared at a concentration of 20x106 cells/mL, for 30 minutes in the incubator to allow the cells to adhere to the sides of the lumen. Reservoirs were inserted to the inlet and outlet ports, allowing the perfusion of gravity-driven culture media (Fig. D and Fig. E). EPI-fluorescence microscopy was used to image both the ECs with GNR-LNA and completed microvessel. Confocal microscopy was applied to acquire 3D images of the microvessel with step size of 0.95 µm. The fluorescence signals from the nanobiosensor were analyzed and presented with Fiji ImageJ.

Results, Conclusions, and Discussions:: We applied the GNR-LNA nanobiosensor to monitor the ß-actin mRNA expression in ECs (Fig. C). The fluorescence signals, representing the ß-actin mRNAs, distributed uniformly in the cells with high transfection efficiency. The mean fluorescence intensity of the GNR-LNA signal was measured for 20 cells in 2D (Fig. C) and 3D (Fig. F). The GNR-LNA fluorescence signals in 3D images have a reduced mean fluorescence intensity (41.2% compared to the 2D cell culture), indicating that the microvessel fabrication process and the 3D imaging lead to the photobleaching and scattering of the fluorescence intensity. Figures F and H shows the ECs, ß-actin mRNA, and merged images of the live microvessel at the equatorial, top and bottom plane of the 3D microvessel. High resolution 3D images of the microvessel from a confocal microscope (Fig. H) show that fluorescence signals from the nanobiosensor were uniformly distributed in the microvessel. To our knowledge, this is the first tissue-engineered microvessel model to monitor gene expression in live cells, providing a powerful platform to investigate disease signaling pathways with dynamic gene expression.
In the future, we will further solidify the validity of the technology by obtaining more quantitative data. A random sequence will be applied as a negative control to evaluate the fluorescence signals from the GNR-LNA nanobiosensor. We also plan to apply this technology to create disease models that have real-time gene monitoring in the live tissue-engineered microvessel. We will use GAD2 and NPTX2, the mRNAs responsible for cognitive decline in Alzheimer’s disease.
In conclusion, the combination of a tissue-engineered microvessel and nanobiosensor shows an unprecedented approach to real-time gene expression in live cells. This platform will pave the way for accurate disease modeling and aid in the development of pharmaceuticals using human models.

Acknowledgements and/or References (Optional): : We acknowledge the support of K-INBRE grant (P20 GM103418).