Researchers at the Prakash Lab of Stanford University are aiming to make lab-grade microscopy more accessible to all, while considerably boosting how much useful research can be achieved within a given schedule — offering open source hardware and software through a project dubbed Squid.
"Squid [Simplifying Quantitive Imaging Development and Deployment] provides a full suite of hardware and software components for rapidly configuring high-performance microscopes tailored to users' applications with reduced cost, effort and turnaround time," the researchers, led by lab director Manu Prakash, explain. "Besides increasing accessibility of research microscopes and available microscope hours to labs, it is also designed to simplify development and dissemination of new or otherwise advanced microscopy techniques."
The Squid project was publicly announced in 2020 following the publication of a preprint paper detailing the platform's features — which, the team explained at the time, is capable of "deploying facility-grade widefield microscopes with advanced features like flat field fluorescence excitation, patterned illumination and tracking microscopy, at a fraction of the cost of commercial solutions" — but the team hasn't been resting on its laurels. The software is constantly updated, while revised hardware designs are scheduled for release some time next month.
The Squid platform has a range of use cases beyond academia, too. The team claims it can be used as a slide scanner for digital pathology at the point of care and in resource-constrained environments, without the need to wait for samples to be processed at a remote lab; for time-lapse imaging with two- or three-dimensional tiling; computational microscopy including label-free deep learning; super-resolution microscopy; and tracking microscopy, handled automatically in software.
In the latter example, the microscope is controlled from an NVIDIA Jetson system or a "regular laptop/workstation" running Ubuntu Linux. The software controls the movement of the microscope through an Arduino Due, offering full automated computer-controlled tracking of a selected object of interest at a considerably lower cost compared to equivalent commercial platforms.
"Developed with the goal of helping translate the rapid advances in the field of microscopy and microscopy-enabled methods, including those powered by deep learning, we envision Squid will simplify roll-out of microscopy-based applications," the team claims, "including at point of care and in low resource settings, make adoption of new or otherwise advanced techniques easier, and significantly increase the available microscope-hours to labs."
The original Squid paper is available on the Cold Spring Harbor Laboratory bioRxiv preprint server, with more information available on the Squid website. Source code for the microscope is available on GitHub under an unspecified open source license — along with the tracking software, in a separate repository published under the reciprocal GNU General Public License 3.