4.7 Article

Improvements in Smartphone and Night Vision Imaging Technologies Enable Low Cost, On-Site Assays of Bioluminescent Cells

Journal

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/fbioe.2021.767313

Keywords

bioluminescence; luciferase; optical imaging; remote sensing; smartphone; portable analytical device; toxicity

Funding

  1. US National Institutes of Health (NIH) [NIMH-R43MH118186, NIGMS-R44GM112241, NIGMS-R42GM116622, NIEHS-R44ES022567, NIEHS-R44ES026269]
  2. US National Science Foundation [CBET-1530953]

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Technologies enabling on-site environmental detection or medical diagnostics in resource-limited settings have a strong disruptive potential compared to current analytical approaches; experimental results show that while in vivo and in vitro systems are more sensitive, smartphone and night vision systems can also detect changes in cellular signal dynamics, indicating potential application value.
Technologies enabling on-site environmental detection or medical diagnostics in resource-limited settings have a strong disruptive potential compared to current analytical approaches that require trained personnel in laboratories with immobile, resource intensive instrumentation. Handheld devices, such as smartphones, are now routinely produced with CPUs, RAM, wireless data transfer capabilities, and high-resolution complementary metal oxide semiconductor (CMOS) cameras capable of supporting the capture and processing of bioluminescent signals. In theory, combining the capabilities of these devices with continuously bioluminescent human cell-based bioreporters would allow them to replicate the functionality of more expensive, more complex, and less flexible platforms while supporting human-relevant conclusions. In this work, we compare the performance of smartphone (CMOS) and night vision (image intensifier) devices with in vivo (CCD camera), and in vitro (photomultiplier tube) laboratory instrumentation for monitoring signal dynamics from continuously bioluminescent human cellular models under toxic, stable, and induced expression scenarios. All systems detected bioluminescence from cells at common plating densities. While the in vivo and in vitro systems were more sensitive and detected signal dynamics representing cellular health changes earlier, the night vision and smartphone systems also detected these changes with relatively similar coefficients of variation and linear detection capabilities. The smartphone system did not detect transcriptional induction. The night vision system did detect transcriptional activation, but was less sensitive than the in vivo or in vitro systems and required a stronger induction before the change could be resolved.

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