End‐to‐end image analysis pipeline for liquid‐phase electron microscopy

SimpliPyTEM: An open-source Python library and app to simplify transmission electron microscopy and in situ-TEM image analysis

Introducing SimpliPyTEM, a Python library and accompanying GUI that simplifies the post-acquisition evaluation of transmission electron microscopy (TEM) images, helping streamline the workflow. After an imaging session, a folder of image and/or video files, typically containing low contrast and large file size 32-bit images, can be quickly processed via SimpliPyTEM into high-quality, high-contrast.jpg images with suitably sized scale bars. The app can also generate HTML or PDF files containing the processed images for easy viewing and sharing. Additionally, SimpliPyTEM specifically focuses on in situ TEM videos, an emerging field of EM involving the study of dynamic processes whilst imaging. The package allows fast data processing into preview movies, averages, image series, or motion-corrected averages. The accompanying Python library offers many standard image processing methods, all simplified to a single command, plus a module to analyse particle morphology and population. This latter application is particularly useful for life sciences investigations. User-friendly tutorials and clear documentation are included to help guide users through the processing and analysis. We invite the EM community to contribute to and further develop this open-source package.

Caught in Action: Visualizing Dynamic Nanostructures Within Supramolecular Systems Chemistry

Supramolecular systems chemistry has been an area of active research to develop nanomaterials with life-like functions. Progress in systems chemistry relies on our ability to probe the nanostructure formation in solution. Often visualizing the dynamics of nanostructures which transform over time is a formidable challenge. This necessitates a paradigm shift from dry sample imaging towards solution-based techniques. We review the application of state-of-the-art techniques for real-time, in situ visualization of dynamic self-assembly processes. We present how solution-based techniques namely optical super-resolution microscopy, solution-state atomic force microscopy, liquid-phase transmission electron microscopy, molecular dynamics simulations and other emerging techniques are revolutionizing our understanding of active and adaptive nanomaterials with life-like functions. This Review provides the visualization toolbox and futuristic vision to tap the potential of dynamic nanomaterials.

In Situ, Noncovalent Labeling and Stimulated Emission Depletion-Based Super-Resolution Imaging of Supramolecular Peptide Nanostructures

Supramolecular materials have gained substantial interest for a number biological and nonbiological applications. However, for optimum utilization of these dynamic self-assembled materials, it is important to visualize and understand their structures at the nanoscale, in solution and in real time. Previous approaches for imaging these structures have utilized super-resolution optical imaging methods such as STORM, which has provided important insights, but suffers from drawbacks of complex sample preparation and slow acquisition times, thus limiting real-time in situ imaging of dynamic processes. We demonstrate a noncovalent fluorescent labeling design for STED-based super-resolution imaging of self-assembling peptides. This is achieved by in situ, electrostatic binding of anionic sulfonates of Alexa-488 dye to the cationic sites of lysine (or arginine) residues exposed on the peptide nanostructure surface. A direct, multiscale visualization of static structures reveals hierarchical organization of supramolecular fibers with sub-60 nm resolution. In addition, the degradation of nanofibers upon enzymatic hydrolysis of peptide could be directly imaged in real time, and although resolution was compromised in this dynamic process, it provided mechanistic insights into the enzymatic degradation process. Noncovalent Alexa-488 labeling and subsequent imaging of a range of cationic self-assembling peptides and peptide-functionalized gold nanoparticles demonstrated the versatility of the methodology for the imaging of cationic supramolecular structures. Overall, our approach presents a general and simple method for the electrostatic fluorescent labeling of cationic peptide nanostructures for nanoscale imaging under physiological conditions and probe dynamic processes in real time and in situ.