Caenorhabditis elegans is a tiny (1 mm in length) nematode which has been used as a model for the last 60 years due to its stereotypic body plan, transparent skin, and well-characterized nervous system. Copyright © 2022, Luis Felipe Morales-Curiel, Michael Krieg et al.
In bioluminescence microscopy, the signal is generated by a chemical reaction of an enzyme (luciferase) with its substrate (luciferin). The general approach and the information content of bioluminescence microscopy are similar to that of fluorescence microscopy. However, one significant advantage is that bioluminescence does not use excitation light. This increases the specificity of the signal since endogenous autofluorescence will not create any background signal, potentially hiding the specific signal under investigation.
Another advantage is the reduced stress of the sample, since the intense excitation light – as used in fluorescence microscopy, might induce some unwanted, potentially toxic effects in the sample, as can be seen in Application Example 1.
Application Example 1 : Fluorescence vs bioluminescence on C. elegans after induced stress1;
The cellular stress response of C. elegans was measured using a mNeonGreen-NanoLantern fused to DAF-16, which acts as a stress reporter. Without any stressors, DAF-16 is located in the cytoplasm, however, under stress, DAF-16 is mostly found in the nucleus. The experiment was performed using fluorescence microscopy of the mNeonGreen (panel b) as well as bioluminescence using the mNeonGreen-Nanolantern fusion (panel c). The ratio of signal from the nucleus to the cytoplasm is shown in panel d. Following a heat shock, the stress response is detected both with fluorescence as well as bioluminescence, but the effect is more prominent with bioluminescence detection, likely due to the absence of non-specific autofluorescence. Interestingly the control experiment (shown in the insets in b and c) indicates a stress response for fluorescence imaging, most likely due to the exposed excitation radiation.
Fluorescent markers also tend to bleach over time, limiting long-time observation of live samples. Those effects are efficiently mitigated using bioluminescence microscopy, which obtains the energy required for the signal generation from chemical processes rather than the photophysical process involved in fluorescence.
Nonetheless, a major drawback of bioluminescence is its rather low signal intensity, resulting in long exposure times and low SNR images in microscopy, limiting its applicability in dynamic processes, which are of big interest when observing living specimens.
Dr. Michael Krieg and his Graduate student, Luis Felipe Morales-Curiel using the highly light-efficient microscope “LowLiteScope”
In his experiment, Dr. Michael Krieg and his group optimized every aspect of the experimental pipeline for bioluminescence. Using extremely photon-starved samples to challenge these limitations, they aimed to provide high SNR images at high temporal resolution. To achieve this, he used Nanolanterns for the dyes, which are brighter and more varied in their spectral properties than the classically used luciferases. Since a standard widefield microscope did not provide any signal, they built a highly light-efficient microscope termed “LowLiteScope”.
Additionally, as the resulting images were still difficult to inspect due to the low signal available, content aware image restoration (CARE) was applied to improve these, which provided clear, high contrast images at millisecond exposure times.
To ensure the most efficient detection, the quantitative CMOS (qCMOS) camera ORCA-Quest was used to offer the best images from the available photons. Its extremely low readout noise of 0.27 e-, alongside its high quantum efficiency, provides the optimal signal-to-noise ratio down to almost the single photon level.
Apart from the raw sensitivity, another advantage of the ORCA-Quest in the presented bioluminescence setting lies within its geometrical design: in combination with the optics of the LowLiteScope, the pixel pitch of 4.6 μm provides a perfect tradeoff between light collection efficiency and spatial resolution.
Since the ORCA-Quest delivers a pixel count of 9.4 MP, no sacrifices in regard to the field of view needed to be made. The pixel pitch and pixel count also benefitted another evolution of the method: in order to increase the speed of 3D acquisitions, lightfield microscopy was also included. The small pixel sizes and the high pixel count of the ORCA-Quest allowed the projecting of the 3D lightfield onto the two dimensional camera sensor, enabling rapid 3D imaging of the whole C. elegans using bioluminescence. Classical lightfield imaging requires a complicated computational reconstruction of the 3D object which might take up to 30 minutes. To speed up this process, a neural network was employed, reducing the time for 3D reconstruction down to 100 ms. Using this scheme, satisfactory results can be achieved with exposure time down to 5 s. To further reduce the minimum exposure time in order to image sample dynamics in three dimensions, CARE was applied before the reconstruction. This reduced the achievable exposure times further up to a factor of 20 while keeping acceptable exposure times. An example of bioluminescence AI reconstructed lightfield microscopy at 5 volumes per second is shown in Application Example 2 below.
Application Example 2 : Raw lightfield images of a bioluminescent calcium reporter in muscles of a freely moving C. elegans
Luis Felipe Morales-Curiel and Dr. Michael Krieg have now established bioluminescence microscopy as a versatile addition to the biologist toolbox. Bioluminescence offers the benefits over fluorescence of lower stress to the samples as well as higher specificity. The common drawbacks of bioluminescence techniques, typically being low signal yield and resulting long exposure times were overcome by optimizing the whole imaging pipeline. This included using the brightest bioluminescence dyes available, recording the data with instrumentation optimized for low light sensitivity, and finally processing the data with modern machine learning based approaches.
In the Krieg lab, the bioluminescence framework will be used to further study mechanobiology and neuroscience of C. elegans, other model organisms but also stem cell-derived organoids. In a recent study2, this framework has been applied to visualize the performance of calcium-triggered photon emitters for establishing a photon-based synaptic communication pathway.
Dr. Michael Krieg was a Postdoctoral Research Fellow in the Department of Molecular and Cellular Physiology at Stanford University. In the lab of Dr. Miriam Goodman, Michael investigated basic mechanotransduction pathways in neurons of the model organism, C. elegans. Michael earned his Ph.D. in Developmental Biology/Biophysics from the Technical University Dresden. Currently, Dr. Krieg is the Group Leader of the Neurophotonics and Mechanical Systems Biology Research Group at the Institute of Photonic Sciences, ICFO, Spain.
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