Fluorescence microscopy has succeeded in attaining super-resolution localization of single emitters in cellular biology. However, 3D localization deep inside tissue is still challenging. A few years ago, we developed SELFI: self-interference 3D super-resolution microscopy, a framework for 3D single-molecule localization within multicellular specimens and tissues. Here, we extend the capability of SELFI to the near-infrared (NIR) region where carbon nanotubes (CNTs) are strong emitters. The aim of this work is to develop NIR SELFI for single-particle tracking applications of CNTs in live brain tissues or NIR quantum dots. SELFI uses a diffraction grating placed on the optical path of the sample image, generating an interference pattern within diffraction limited images of point emitters. A single image obtained with NIR SELFI contains two independent variables: the intensity distribution to extract the intensity centroid to determine the lateral localization, and the wavefront curvature (provided by the interfringes) to get the axial super-localization. SELFI was first developed to localize red emitting dyes and quantum dots. The performance of the system is examined by means of the standard deviation and root mean square error of the localizations. The experiments performed show that the 3D-precision and accuracy achieved with NIR SELFI are both below 100 nm for emission around 1000 nm and high photon budget. Therefore, we can now achieve 3D localization in the NIR, permitting 3D single-particle tracking of CNTs at video rate in complex environments.
In localization microscopy, the position of isolated fluorescent emitters are estimated with a resolution better than the diffraction limit. In order to image thick samples, which are common in biological applications, there is considerable interest in extending the depth-of-field of such microscopes in order to make their accuracy as invariant as possible to defocus. For that purpose, we propose to optimize annular binary phase masks placed in the pupil of the microscope in order to generate a point spread function for which the localization accuracy is almost invariant along the optical axis. The optimization criterion is defined as the localization accuracy in the plane expressed in terms of the Cram´er-Rao bound. We show that the optimal masks significantly increase the depth-of-field of single-molecule imaging techniques relatively to an usual microscope objective.
The brain extracellular space (ECS) is a complex network that constitutes a key microenvironment for cellular communication, homeostasis, and clearance of toxic metabolites1. Signaling molecules, neuromodulators, and nutrients transit via the ECS, therefore mediating the communication between cells. Despite the relevance of this important part of the brain, its dynamics and structural organization at the nanoscale is still mostly unknown2. We have recently demonstrated that single-walled carbon nanotubes (SWCNTs) can be used to image and probe live brain tissue, providing super-resolved maps of the brain ECS and quantitative information on the local diffusion environment3,4. Here, we propose an important refinement of this approach by implementing a structured illumination technique (named HiLo microscopy5) to image fluorescently labelled neuronal structures in parallel to SWCNT NIR imaging. This technique is based on speckle illumination and relies on the acquisition of one structured and one uniform illumination image to obtain images deep into tissues with good optical sectioning. Having access to spatially resolved SWCNT diffusivity around specific neuronal structures will provide more precise insights about the heterogeneity of the brain environment.
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