Optical mesoscopy, machine learning, and computational microscopy enable high information content diagnostic imaging of blood films

Mesoscale standing wave imaging

Standing wave (SW) microscopy is a method that uses an interference pattern to excite fluorescence from labelled cellular structures and produces high-resolution images of three-dimensional objects in a two-dimensional dataset. SW microscopy is performed with high-magnification, high-numerical aperture objective lenses, and while this results in high-resolution images, the field of view is very small. Here we report upscaling of this interference imaging method from the microscale to the mesoscale using the Mesolens, which has the unusual combination of a low-magnification and high-numerical aperture. With this method, we produce SW images within a field of view of 4.4 mm × 3.0 mm that can readily accommodate over 16,000 cells in a single dataset. We demonstrate the method using both single-wavelength excitation and the multi-wavelength SW method TartanSW. We show application of the method for imaging of fixed and living cells specimens, with the first application of SW imaging to study cells under flow conditions.

Light-sheet mesoscopy with the Mesolens provides fast sub-cellular resolution imaging throughout large tissue volumes

Rapid imaging of large biological tissue specimens such as ultrathick sections of mouse brain cannot easily be performed with a standard microscope. Optical mesoscopy offers a solution, but thus far imaging has been too slow to be useful for routine use. We have developed two different illuminators for light-sheet mesoscopy with the Mesolens and we demonstrate their use in high-speed optical mesoscale imaging of large tissue specimens. The first light-sheet approach uses Gaussian optics and is straightforward to implement. It provides excellent lateral resolution and high-speed imaging, but the axial resolution is poor. The second light-sheet is a more complex Airy light-sheet that provides sub-cellular resolution in three dimensions that is comparable in quality to point-scanning confocal mesoscopy, but the light-sheet method of illuminating the specimen reduces the imaging time by a factor of 14. This creates new possibilities for high-content, higher-throughput optical bioimaging at the mesoscale.

Application of Light-Sheet Mesoscopy to Image Host-Pathogen Interactions in Intact Organs

Human African Trypanosomiasis (HAT) is a disease caused by the extracellular parasite Trypanosoma brucei that affects the central nervous system (CNS) during the chronic stage of the infection, inducing neuroinflammation, coma, and death if left untreated. However, little is known about the structural change happening in the brain as result of the infection. So far, infection-induced neuroinflammation has been observed with conventional methods, such as immunohistochemistry, electron microscopy, and 2-photon microscopy only in small portions of the brain, which may not be representative of the disease. In this paper, we have used a newly-developed light-sheet illuminator to image the level of neuroinflammation in chronically infected mice and compared it to naïve controls. This system was developed for imaging in combination with the Mesolens objective lens, providing fast sub-cellular resolution for tens of mm3-large imaging volumes. The mouse brain specimens were cleared using CUBIC+, followed by antibody staining to locate Glial Fibrillary Acid Protein (GFAP) expressing cells, primarily astrocytes and ependymocytes, used here as a proxy for cell reactivity and gliosis. The large capture volume allowed us to detect GFAP+ cells and spatially resolve the response to T. brucei infection. Based on morphometric analyses and spatial distribution of GFAP+ cells, our data demonstrates a significant increase in cell dendrite branching around the lateral ventricle, as well as dorsal and ventral third ventricles, that are negatively correlated with the branch extension in distal sites from the circumventricular spaces. To our knowledge, this is the first report highlighting the potential of light-sheet mesoscopy to characterise the inflammatory responses of the mouse brain to parasitic infection at the cellular level in intact cleared organs, opening new avenues for the development of new mesoscale imaging techniques for the study of host-pathogen interactions.

Paving the Way: Contributions of Big Data to Apicomplexan and Kinetoplastid Research

In the age of big data an important question is how to ensure we make the most out of the resources we generate. In this review, we discuss the major methods used in Apicomplexan and Kinetoplastid research to produce big datasets and advance our understanding of Plasmodium, Toxoplasma, Cryptosporidium, Trypanosoma and Leishmania biology. We debate the benefits and limitations of the current technologies, and propose future advancements that may be key to improving our use of these techniques. Finally, we consider the difficulties the field faces when trying to make the most of the abundance of data that has already been, and will continue to be, generated.

Challenges and advances in optical 3D mesoscale imaging

Optical mesoscale imaging is a rapidly developing field that allows the visualisation of larger samples than is possible with standard light microscopy, and fills a gap between cell and organism resolution. It spans from advanced fluorescence imaging of micrometric cell clusters to centimetre-size complete organisms. However, with larger volume specimens, new problems arise. Imaging deeper into tissues at high resolution poses challenges ranging from optical distortions to shadowing from opaque structures. This manuscript discusses the latest developments in mesoscale imaging and highlights limitations, namely labelling, clearing, absorption, scattering, and also sample handling. We then focus on approaches that seek to turn mesoscale imaging into a more quantitative technique, analogous to quantitative tomography in medical imaging, highlighting a future role for digital and physical phantoms as well as artificial intelligence.