Correlative light and volume electron microscopy to study brain development

Volume electron microscopy for genetically and molecularly defined neural circuits

The brain networks responsible for adaptive behavioral changes are based on the physical connections between neurons. Light and electron microscopy have long been used to study neural projections and the physical connections between neurons. Volume electron microscopy has recently expanded its scale of analysis due to methodological advances, resulting in complete wiring maps of neurites in a large volume of brain tissues and even entire nervous systems in a growing number of species. However, structural approaches frequently suffer from inherent limitations in which elements in images are identified solely by morphological criteria. Recently, an increasing number of tools and technologies have been developed to characterize cells and cellular components in the context of molecules and gene expression. These advancements include newly developed probes for visualization in electron microscopic images as well as correlative integration methods for the same elements across multiple microscopic modalities. Such approaches advance our understanding of interactions between specific neurons and circuits and may help to elucidate novel aspects of the basal ganglia network involving dopamine neurons. These advancements are expected to reveal mechanisms for processing adaptive changes in specific neural circuits that modulate brain functions.

To see or not to see: In vivo nanocarrier detection methods in the brain and their challenges

Nanoparticles have a great potential to significantly improve the delivery of therapeutics to the brain and may also be equipped with properties to investigate brain function. The brain, being a highly complex organ shielded by selective barriers, requires its own specialized detection system. However, a significant hurdle to achieve these goals is still the identification of individual nanoparticles within the brain with sufficient cellular, subcellular, and temporal resolution. This review aims to provide a comprehensive summary of the current knowledge on detection systems for tracking nanoparticles across the blood-brain barrier and within the brain. We discuss commonly employed in vivo and ex vivo nanoparticle identification and quantification methods, as well as various imaging modalities able to detect nanoparticles in the brain. Advantages and weaknesses of these modalities as well as the biological factors that must be considered when interpreting results obtained through nanotechnologies are summarized. Finally, we critically evaluate the prevailing limitations of existing technologies and explore potential solutions.

The advent of preventive high-resolution structural histopathology by artificial-intelligence-powered cryogenic electron tomography

Advances in cryogenic electron microscopy (cryoEM) single particle analysis have revolutionized structural biology by facilitating the in vitro determination of atomic- and near-atomic-resolution structures for fully hydrated macromolecular complexes exhibiting compositional and conformational heterogeneity across a wide range of sizes. Cryogenic electron tomography (cryoET) and subtomogram averaging are rapidly progressing toward delivering similar insights for macromolecular complexes in situ, without requiring tags or harsh biochemical purification. Furthermore, cryoET enables the visualization of cellular and tissue phenotypes directly at molecular, nanometric resolution without chemical fixation or staining artifacts. This forward-looking review covers recent developments in cryoEM/ET and related technologies such as cryogenic focused ion beam milling scanning electron microscopy and correlative light microscopy, increasingly enhanced and supported by artificial intelligence algorithms. Their potential application to emerging concepts is discussed, primarily the prospect of complementing medical histopathology analysis. Machine learning solutions are poised to address current challenges posed by "big data" in cryoET of tissues, cells, and macromolecules, offering the promise of enabling novel, quantitative insights into disease processes, which may translate into the clinic and lead to improved diagnostics and targeted therapeutics.

Perineuronal Net Microscopy: From Brain Pathology to Artificial Intelligence

Perineuronal nets (PNN) are a special highly structured type of extracellular matrix encapsulating synapses on large populations of CNS neurons. PNN undergo structural changes in schizophrenia, epilepsy, Alzheimer's disease, stroke, post-traumatic conditions, and some other brain disorders. The functional role of the PNN microstructure in brain pathologies has remained largely unstudied until recently. Here, we review recent research implicating PNN microstructural changes in schizophrenia and other disorders. We further concentrate on high-resolution studies of the PNN mesh units surrounding synaptic boutons to elucidate fine structural details behind the mutual functional regulation between the ECM and the synaptic terminal. We also review some updates regarding PNN as a potential pharmacological target. Artificial intelligence (AI)-based methods are now arriving as a new tool that may have the potential to grasp the brain's complexity through a wide range of organization levels-from synaptic molecular events to large scale tissue rearrangements and the whole-brain connectome function. This scope matches exactly the complex role of PNN in brain physiology and pathology processes, and the first AI-assisted PNN microscopy studies have been reported. To that end, we report here on a machine learning-assisted tool for PNN mesh contour tracing.

Three-dimensional ultrastructure analysis of organelles in injured motor neuron

Morphological analysis of organelles is one of the important clues for understanding the cellular conditions and mechanisms occurring in cells. In particular, nanoscale information within crowded intracellular organelles of tissues provide more direct implications when compared to analyses of cells in culture or isolation. However, there are some difficulties in detecting individual shape using light microscopy, including super-resolution microscopy. Transmission electron microscopy (TEM), wherein the ultrastructure can be imaged at the membrane level, cannot determine the whole structure, and analyze it quantitatively. Volume EM, such as focused ion beam/scanning electron microscopy (FIB/SEM), can be a powerful tool to explore the details of three-dimensional ultrastructures even within a certain volume, and to measure several parameters from them. In this review, the advantages of FIB/SEM analysis in organelle studies are highlighted along with the introduction of mitochondrial analysis in injured motor neurons. This would aid in understanding the morphological details of mitochondria, especially those distributed in the cell bodies as well as in the axon initial segment (AIS) in mouse tissues. These regions have not been explored thus far due to the difficulties encountered in accessing their images by conditional microscopies. Some mechanisms of nerve regeneration have also been discussed with reference to the obtained findings. Finally, future perspectives on FIB/SEM are introduced. The combination of biochemical and genetic understanding of organelle structures and a nanoscale understanding of their three-dimensional distribution and morphology will help to match achievements in genomics and structural biology.