An adaptive microscope for imaging biological surfaces


Left: Drawing of curved biological tissue. The hexagons represent the fluorescent outlines of cells organized into a cell sheet. The tissue may be covered with a second epithelium which can be ignored by the imaging process. Right: From a few acquisitions (green dots), the microscope automatically estimates the surface area of ​​the tissue (red mesh) and can then concentrate the acquisitions on this surface, or even only on the outlines of fluorescent cells using an acquisition algorithm. propagative. Credit: Faris Abouakil et al.

Modern biology relies on our ability to observe living cells using microscopes. The latest advances in light microscopy allow cellular and subcellular imaging in model organisms such as the vinegar fly, zebrafish and mice.

One of the fundamental limitations of current techniques is the toxicity associated with lighting, which compromises the biological processes studied. Until now, there was not much solution to this problem other than reducing the brightness level, which results in loss of image quality.

In a new article published in Light science and application, a team led by Drs. Loïc Le Goff and Frédéric Galland, both from the Fresnel Institute at Aix Marseille University, France, have developed a new smart microscope that automatically calculates where to send light to image the structures of interest in the sample as most effective using learning strategies.

The starting point of this project was the observation that most biological tissues have a well-characterized architecture. In particular, most embryos are organized into surfaces – sheets of cells – curved in space. Microscopes do not adapt their operation to this architecture: they scan a focused laser in all the 3D space that the embryo contains, which is very inefficient both in terms of speed and quantity of light irradiating the sample. The microscope developed at the Fresnel Institute automatically adapts its scanning scheme to the morphology of curved biological surfaces, without prior knowledge of the surface. On the samples tested, our smart scanning microscope reduced irradiation up to 100 times compared to a conventional confocal microscope.

This disruptive technology is the result of close collaboration between data scientists, physicists and biologists from the Fresnel Institute. The method opens a new way to image over long periods the behavior of very fragile objects such as embryos and organoids. Interestingly, the technology could be easily adapted on many of the commercial microscopes found in the imaging facilities of institutes of biology.

Researchers develop live adaptive imaging system of large living organisms

More information:
Faris Abouakil et al, An adaptive microscope for imaging biological surfaces, Light: science and applications (2021). DOI: 10.1038 / s41377-021-00649-9

Provided by the Chinese Academy of Sciences

Quote: An adaptive microscope for imaging biological surfaces (2021, October 12) retrieved October 12, 2021 from

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