Conference Agenda

The observation of organelles dynamics and macromolecular complex interactions inside living cells and tissues requires minimally invasive imaging strategies. In this context, photocontrollable fluorescent proteins (FPs) play a crucial role as tags in optical super-resolution microscopy and functional live cell imaging. To this end we have previously shown that reversibly switchable FPs enable fast (1 Hz for a 50 x 50 µm2) and gentler (< 1 kW/cm2 illuminations) nanoscopy (Masullo et al Nat. Comm 2018). Additionally, irreversibly photoconvertible FPs can achieve photolabeling with high spatiotemporal precision. Nevertheless, their photophysical complexity poses challenges in expanding such techniques toward multiplexing and in vivo imaging. Here, we explore novel photoswitching mechanisms for fluorescent proteins in the red and near-infrared region of the spectra and assess their compatibility with live cell imaging at the nanoscale (Pennacchietti et al, Nat. Meth, 2018). Finally, we present strategies to combine the spectral and photophysical fingerprint of distinct photocontrollable FPs to achieve multiplexing in live cell imaging at the nanoscale and photolabeling studies (Pennacchietti et al, Nat Comm, 2023).

Image Scanning Microscopy (ISM) enables good signal-to-noise ratio (SNR), super-resolution and high information content imaging by leveraging array detection in a laser-scanning architecture. However, the SNR is still limited by the size of the detector, which is conventionally small to avoid collecting out-of-focus light. Nonetheless, the ISM dataset inherently contains the axial information of the fluorescence emitters. We leverage this knowledge to achieve computational optical sectioning without sacrificing the conventional benefits of ISM. We invert the physical model to fuse the raw dataset into a single image with improved sampling, SNR, lateral resolution, and optical sectioning. We provide a complete theoretical framework and validate our approach with experimental images of biological samples acquired with a custom setup equipped with a single photon avalanche diode (SPAD) array detector. Furthermore, we generalize our method to other imaging techniques, such as multi-photon excitation fluorescence microscopy and fluoresce lifetime imaging. To enable this latter, we take advantage of the single-photon timing ability of SPAD arrays, accessing additional sample information. Our method outperforms conventional reconstruction techniques and opens new perspectives for exploring the unique spatio-temporal information provided by SPAD array detectors.

Simultaneous field- and aperture-plane (back-focal plane, BFP) imaging enriches the infor-mation content of fluorescence microscopy. In addition to the usual density and concentration maps of sample-plane images, BFP images provide information on the surface proximity and orientation of molecu-lar fluorophores. They also give access to the refractive index of the fluorophore-embedding medium. However, in the high-NA, wide-field detection geometry commonly used in single-molecule localisation microscopies, such measurements are averaged over all fluorophores present in the objective’s field of view, thus limiting spatial resolution and specificity. We here solve this problem and demonstrate how an oblique, variable-angle, coherent ring illumination can be used to generate a Bessel beam that - for supercritical exci-tation angles - produces an evanescent needle of light. Scanning the sample through the this evanescent needle enables us to acquire combined sample-plane and BFP images with sub-diffraction resolution and axial localisation precision. Background, resolution and polarisation considerations will be discussed.

We present the use of wavefront coding (WFC) combined with machine learning in a light sheet fluorescence microscopy (LSFM) system. We visualize the 3D dynamics of sperm flagellar motion at an imaging speed up to 80 volumes per second, which is faster than twice volumetric video rate. By using the WFC technique we achieve to extend the depth of field of the collection objective with high numerical aperture (NA=1) from 2.6 μm to 50 μm, i. e., more than one order of magnitude. To improve the quality of the final images, we applied a machine learning-based algorithm to the acquired sperm raw images and to the point spread function (PSF) of the generated cubic phase masks previous to the deconvolution process.

The ability to generate a structured illumination pattern in microscopy is a fundamental need of numerous optical microscopy techniques, such as Structured Illumination Microscopy (SIM) and HiLo microscopy. However, existing pattern generating techniques, such as using diffraction gratings or SLMs, are either slow, bulky, or very alignment-sensitive, making the widespread acquisition of such techniques harder. We present an integrated, monolithic device, fabricated in a glass substrate via Femtosecond Laser Micromachining, capable of generating and translating a highly stable structured pattern on top of the sample plane of a microscope, enabling a widefield microscope to perform SIM.