Detection of Extracellular Nitric Oxide Released by Different Cells Via Carbon Nanotube Sensor Platforms

Introduction:: Cell communication is the ability to receive, process, and transmit signals from the environment and within cells to ensure functional coordination during physiological events. Cells communicate between themselves using waves of chemical concentration that change in both direction and time. Nitric Oxide (NO) is a gaseous, ubiquitous, intra - and inter-cellular signaling molecule. NO’s small size and lipophilic nature allows it to diffuse through cell membranes and reach intracellular compartments of nearby cells¹. However, NO detection in biomedical applications represents a challenge due to NO’s short half-life in the range of seconds before breaking down into different subproducts. The lack of biological sensors that can detect NO, not an upstream or downstream indicator of NO's presence in a spatial format, has hindered understanding of the extracellular NO dynamic signaling during both physiological and pathological events. However, single carbon nanotube (SWNT) fluorescent sensors present specificity to NO, and, when immobilized into a glass substrate, they present uniform distribution to quantify extracellular NO in a spatial-temporal manner^2-3. This research aims to detect extracellular NO efflux fluorescence maps from different cell lines: THP-1 monocytes, which are known for their NO production under inflammatory responses, and from MDA-MB-231 triple-negative breast cancer cells as a diseased breast cancer model. Mapping the levels of extracellular NO for different cell types will allow for a closer understanding of cell function as in the cell microenvironment and favor the development of more effective treatments in the future.


Materials and Methods:: SWNT were immobilized into the glass substrate. Cells were seeded on the SWNT platform surface overnight to favor the attachment. The cellular NO production in MDA-MB-231 cells was induced with the incubation of O2-(2,4-dinitrophenyl) 1-[(4-ethoxycarbonyl)piperazin-1-yl]diazen-1-ium-1,2-diolate (JS-K) for 48 h. The THP-1 monocytes were seeded on the SWNT platforms and differentiated into macrophages with 2-O-Tetradecanoylphorbol-13-Acetate (TPA) for 14 h. The macrophage NO production was boosted with the inflammatory response after the incubation with Liposaccharides (LPS) over 24 h. The SWNT platform’s sensing response to NO was detected by changes in fluorescence intensity. Fluorescence data were collected on a custom-built hyperspectral microscope located within the Iverson Laboratory. Images were collected before and after the respective NO induction method. To analyze the extracellular NO mappings, bright field images of the cells were overlapped to the fluorescent images. Hyperspectral image analysis was performed with MATLAB, Figure 1a. Furthermore, to validate that the change in the fluorescence response was attributed to NO and not for cellular interaction with the SWNT sensor, at the end of the respective experiments, we added 2-Phenyl-4,4,5,5-tetramethylimidazoline-1-oxyl 3-oxide (PTIO), a NO scavenger to recover the initial fluorescence signal.

Results, Conclusions, and Discussions:: We identified the functional concentration and incubation time for the NO cellular inducers JS-K and LPS, and for the NO scavenger PTIO. Satisfactorily, in this first in vitro application for the SWNT platform, the cells didn’t affect the fluorescence functionality, as indicated by the recovery of the initial fluorescence intensity once NO is scavenged from the system with PTIO. Through fluorescence intensity changes with pixel specificity on the image acquisition, we were able to quantify NO released by cells.



The newly developed platform provides the means to quantify extracellular NO. Here we are reporting findings for two cell lines, but the platforms will allow for the quantification of NO for other cell types as well. By comparing extracellular NO concentrations for different types of cancer cells, we will be able to better understand cancer progression and potentially find better methods for treatment.




Acknowledgements (Optional): : We thank Carley Conover for her contributions to the project. We thank NIH for their financial support through the 1R35GM138245 grant.

References (Optional): : 1. Mishra, D., Patel, V., Banerjee, D. Breast Cancer Basic Clin Res., 2020,14.

2. Ulissi, Z., Sen, F., Gong, X., et al. Nano Lett. 2014;14(8).

3. Stapleton, J., Hofferber, E., Meier J, Acosta Ramirez I., Iverson N. ACS Appl Nano Mater. 2021;4(1)