Electron microscopy for imaging organelles in plants and algae

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.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3-20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Optimize Electron Beam Energy toward In Situ Imaging of Thick Frozen Bio-Samples with Nanometer Resolution Using MeV-STEM

To optimize electron energy for in situ imaging of large biological samples up to 10 μm in thickness with nanoscale resolutions, we implemented an analytical model based on elastic and inelastic characteristic angles. This model has been benchmarked by Monte Carlo simulations and can be used to predict the transverse beam size broadening as a function of electron energy while the probe beam traverses through the sample. As a result, the optimal choice of the electron beam energy can be realized. In addition, the impact of the dose-limited resolution was analysed. While the sample thickness is less than 10 μm, there exists an optimal electron beam energy below 10 MeV regarding a specific sample thickness. However, for samples thicker than 10 μm, the optimal beam energy is 10 MeV or higher depending on the sample thickness, and the ultimate resolution could become worse with the increase in the sample thickness. Moreover, a MeV-STEM column based on a two-stage lens system can be applied to reduce the beam size from one micron at aperture to one nanometre at the sample with the energy tuning range from 3 to 10 MeV. In conjunction with the state-of-the-art ultralow emittance electron source that we recently implemented, the maximum size of an electron beam when it traverses through an up to 10 μm thick bio-sample can be kept less than 10 nm. This is a critical step toward the in situ imaging of large, thick biological samples with nanometer resolution.

A century journey of organelles research in the plant endomembrane system

We are entering an exciting century in the study of the plant organelles in the endomembrane system. Over the past century, especially within the past 50 years, tremendous advancements have been made in the complex plant cell to generate a much clearer and informative picture of plant organelles, including the molecular/morphological features, dynamic/spatial behavior, and physiological functions. Importantly, all these discoveries and achievements in the identification and characterization of organelles in the endomembrane system would not have been possible without: (1) the innovations and timely applications of various state-of-art cell biology tools and technologies for organelle biology research; (2) the continuous efforts in developing and characterizing new organelle markers by the plant biology community; and (3) the landmark studies on the identification and characterization of the elusive organelles. While molecular aspects and results for individual organelles have been extensively reviewed, the development of the techniques for organelle research in plant cell biology is less appreciated. As one of the ASPB Centennial Reviews on "organelle biology," here we aim to take a journey across a century of organelle biology research in plants by highlighting the important tools (or landmark technologies) and key scientists that contributed to visualize organelles. We then highlight the landmark studies leading to the identification and characterization of individual organelles in the plant endomembrane systems.

Missing Wedge Completion via Unsupervised Learning with Coordinate Networks

Cryogenic electron tomography (cryoET) is a powerful tool in structural biology, enabling detailed 3D imaging of biological specimens at a resolution of nanometers. Despite its potential, cryoET faces challenges such as the missing wedge problem, which limits reconstruction quality due to incomplete data collection angles. Recently, supervised deep learning methods leveraging convolutional neural networks (CNNs) have considerably addressed this issue; however, their pretraining requirements render them susceptible to inaccuracies and artifacts, particularly when representative training data is scarce. To overcome these limitations, we introduce a proof-of-concept unsupervised learning approach using coordinate networks (CNs) that optimizes network weights directly against input projections. This eliminates the need for pretraining, reducing reconstruction runtime by 3 - 20× compared to supervised methods. Our in silico results show improved shape completion and reduction of missing wedge artifacts, assessed through several voxel-based image quality metrics in real space and a novel directional Fourier Shell Correlation (FSC) metric. Our study illuminates benefits and considerations of both supervised and unsupervised approaches, guiding the development of improved reconstruction strategies.

Plant microphenotype: from innovative imaging to computational analysis

The microphenotype plays a key role in bridging the gap between the genotype and the complex macro phenotype. In this article, we review the advances in data acquisition and the intelligent analysis of plant microphenotyping and present applications of microphenotyping in plant science over the past two decades. We then point out several challenges in this field and suggest that cross-scale image acquisition strategies, powerful artificial intelligence algorithms, advanced genetic analysis, and computational phenotyping need to be established and performed to better understand interactions among genotype, environment, and management. Microphenotyping has entered the era of Microphenotyping 3.0 and will largely advance functional genomics and plant science.

The Arabidopsis leaf quantitative atlas: a cellular and subcellular mapping through unified data integration

Quantitative analyses and models are required to connect a plant's cellular organisation with its metabolism. However, quantitative data are often scattered over multiple studies, and finding such data and converting them into useful information is time-consuming. Consequently, there is a need to centralise the available data and to highlight the remaining knowledge gaps. Here, we present a step-by-step approach to manually extract quantitative data from various information sources, and to unify the data format. First, data from Arabidopsis leaf were collated, checked for consistency and correctness and curated by cross-checking sources. Second, quantitative data were combined by applying calculation rules. They were then integrated into a unique comprehensive, referenced, modifiable and reusable data compendium representing an Arabidopsis reference leaf. This atlas contains the metrics of the 15 cell types found in leaves at the cellular and subcellular levels.

Correlative Imaging to Detect Rare HIV Reservoirs and Associated Damage in Tissues

Correlative light-electron microscopy (CLEM) has evolved in the last decades, especially after significant developments in sample preparation, imaging acquisition, software, spatial resolution, and equipment, including confocal, live-cell, super-resolution, and electron microscopy (scanning, transmission, focused ion beam, and cryo-electron microscopy). However, the recent evolution of different laser-related techniques, such as mass spectrometry imaging (MSI) and laser capture microdissection, could further expand spatial imaging capabilities into high-resolution OMIC approaches such as proteomic, lipidomics, small molecule, and drug discovery. Here, we will describe a protocol to integrate the detection of rare viral reservoirs with imaging mass spectrometry.

Elevated nocturnal respiratory rates in the mitochondria of CAM plants: current knowledge and unanswered questions

Crassulacean acid metabolism (CAM) is a metabolic adaptation that has evolved convergently in 38 plant families to aid survival in water-limited niches. Whilst primarily considered a photosynthetic adaptation, CAM also has substantial consequences for nocturnal respiratory metabolism. Here, we outline the history, current state and future of nocturnal respiration research in CAM plants, with a particular focus on the energetics of nocturnal respiratory oxygen consumption. Throughout the 20th century, research interest in nocturnal respiration occurred alongside initial discoveries of CAM, although the energetic and mechanistic implications of nocturnal oxygen consumption and links to the operation of the CAM cycle were not fully understood. Recent flux balance analysis (FBA) models have provided new insights into the role that mitochondria play in the CAM cycle. Several FBA models have predicted that CAM requires elevated nocturnal respiratory rates, compared to C3 species, to power vacuolar malic acid accumulation. We provide physiological data, from the genus Clusia, to corroborate these modelling predictions, thereby reinforcing the importance of elevated nocturnal respiratory rates for CAM. Finally, we outline five unanswered questions pertaining to nocturnal respiration which must be addressed if we are to fully understand and utilize CAM plants in a hotter, drier world.

Preparing Arabidopsis thaliana root protoplasts for cryo electron tomography

The use of protoplasts in plant biology has become a convenient tool for the application of transient gene expression. This model system has allowed the study of plant responses to biotic and abiotic stresses, protein location and trafficking, cell wall dynamics, and single-cell transcriptomics, among others. Although well-established protocols for isolating protoplasts from different plant tissues are available, they have never been used for studying plant cells using cryo electron microscopy (cryo-EM) and cryo electron tomography (cryo-ET). Here we describe a workflow to prepare root protoplasts from Arabidopsis thaliana plants for cryo-ET. The process includes protoplast isolation and vitrification on EM grids, and cryo-focused ion beam milling (cryo-FIB), with the aim of tilt series acquisition. The whole workflow, from growing the plants to the acquisition of the tilt series, may take a few months. Our protocol provides a novel application to use plant protoplasts as a tool for cryo-ET.

Minimal resin embedding of SBF-SEM samples reduces charging and facilitates finding a surface-linked region of interest

BACKGROUND

For decoding the mechanism of how cells and organs function information on their ultrastructure is essential. High-resolution 3D imaging has revolutionized morphology. Serial block face scanning electron microscopy (SBF-SEM) offers non-laborious, automated imaging in 3D of up to ~ 1 mm3 large biological objects at nanometer-scale resolution. For many samples there are obstacles. Quality imaging is often hampered by charging effects, which originate in the nonconductive resin used for embedding. Especially, if the imaged region of interest (ROI) includes the surface of the sample and neighbours the empty resin, which insulates the object. This extra resin also obscures the sample's morphology, thus making navigation to the ROI difficult.

RESULTS

Using the example of small arthropods and a fish roe we describe a workflow to prepare samples for SBF-SEM using the minimal resin (MR) embedding method. We show that for imaging of surface structures this simple approach conveniently tackles and solves both of the two major problems-charging and ROI localization-that complicate imaging of SBF-SEM samples embedded in an excess of overlying resin. As the surface ROI is not masked by the resin, samples can be precisely trimmed before they are placed into the imaging chamber. The initial approaching step is fast and easy. No extra trimming inside the microscope is necessary. Importantly, charging is absent or greatly reduced meaning that imaging can be accomplished under good vacuum conditions, typically at the optimal high vacuum. This leads to better resolution, better signal to noise ratio, and faster image acquisition.

CONCLUSIONS

In MR embedded samples charging is minimized and ROI easily targeted. MR embedding does not require any special equipment or skills. It saves effort, microscope time and eventually leads to high quality data. Studies on surface-linked ROIs, or any samples normally surrounded by the excess of resin, would benefit from adopting the technique.

A conventional fixation volume electron microscopy protocol for plants

Volume electron microscopy techniques play an important role in plant research from understanding organelles and unicellular forms to developmental studies, environmental effects and microbial interactions with large plant structures, to name a few. Due to large air voids central vacuole, cell wall and waxy cuticle, many plant tissues pose challenges when trying to achieve high quality morphology, metal staining and adequate conductivity for high-resolution volume EM studies. Here, we applied a robust conventional chemical fixation strategy to address the special challenges of plant samples and suitable for, but not limited to, serial block-face and focused ion beam scanning electron microscopy. The chemistry of this protocol was modified from an approach developed for improved and uniform staining of large brain volumes. Briefly, primary fixation was in paraformaldehyde and glutaraldehyde with malachite green followed by secondary fixation with osmium tetroxide, potassium ferrocyanide, thiocarbohydrazide, osmium tetroxide and finally uranyl acetate and lead aspartate staining. Samples were then dehydrated in acetone with a propylene oxide transition and embedded in a hard formulation Quetol 651 resin. The samples were trimmed and mounted with silver epoxy, metal coated and imaged via serial block-face scanning electron microscopy and focal charge compensation for charge suppression. High-contrast plant tobacco and duckweed leaf cellular structures were readily visible including mitochondria, Golgi, endoplasmic reticulum and nuclear envelope membranes, as well as prominent chloroplast thylakoid membranes and individual lamella in grana stacks. This sample preparation protocol serves as a reliable starting point for routine plant volume electron microscopy.

Realizing the Full Potential of Advanced Microscopy Approaches for Interrogating Plant-Microbe Interactions

Microscopy has served as a fundamental tool for insight and discovery in plant-microbe interactions for centuries. From classical light and electron microscopy to corresponding specialized methods for sample preparation and cellular contrasting agents, these approaches have become routine components in the toolkit of plant and microbiology scientists alike to visualize, probe and understand the nature of host-microbe relationships. Over the last three decades, three-dimensional perspectives led by the development of electron tomography, and especially, confocal techniques continue to provide remarkable clarity and spatial detail of tissue and cellular phenomena. Confocal and electron microscopy provide novel revelations that are now commonplace in medium and large institutions. However, many other cutting-edge technologies and sample preparation workflows are relatively unexploited yet offer tremendous potential for unprecedented advancement in our understanding of the inner workings of pathogenic, beneficial, and symbiotic plant-microbe interactions. Here, we highlight key applications, benefits, and challenges of contemporary advanced imaging platforms for plant-microbe systems with special emphasis on several recently developed approaches, such as light-sheet, single molecule, super-resolution, and adaptive optics microscopy, as well as ambient and cryo-volume electron microscopy, X-ray microscopy, and cryo-electron tomography. Furthermore, the potential for complementary sample preparation methodologies, such as optical clearing, expansion microscopy, and multiplex imaging, will be reviewed. Our ultimate goal is to stimulate awareness of these powerful cutting-edge technologies and facilitate their appropriate application and adoption to solve important and unresolved biological questions in the field. [Formula: see text] Copyright © 2023 The Author(s). This is an open access article distributed under the CC BY 4.0 International license.

Imaging the Plant Cytoskeleton by High-Pressure Freezing and Electron Tomography

Electron tomography (ET) imaging of high-pressure frozen/freeze-substituted samples provides a unique opportunity to study structural details of organelles and cytoskeletal arrays in plant cells. In this chapter, we discuss approaches for sample preparation by cryofixation at high pressure, freeze substitution, and resin embedding. We also include pipelines for data collection for electron tomography at ambient temperature, tomogram calculation, and segmentation.

Multiscale imaging reveals the presence of autophagic vacuoles in developing maize endosperm

Cereal endosperm is solely devoted to the storage of proteins and starch that will be used by the embryo upon germination. The high degree of specialization of this tissue is reflected in its endomembrane system, in which ER derived protein bodies and protein storage vacuoles (PSVs) are of particular interest. In maize seeds, the main storage proteins are zeins, that form transport incompetent aggregates within the ER lumen and finally build protein bodies that bud from the ER. In contrast to the zeins, the maize globulins are not very abundant and the vacuolar storage compartment of maize endosperm is not fully described. Whereas in other cereals, including wheat and barley, the PSV serves as the main protein storage compartment, only small, globulin-containing PSVs have been identified in maize so far. We present here a multi-scale set of data, ranging from live-cell imaging to more sophisticated 3D electron microscopy techniques (SBF-SEM), that has allowed us to investigate in detail the vacuoles in maize endosperm cells, including a novel, autophagic vacuole that is present in early developmental stages.

Super resolution live imaging: The key for unveiling the true dynamics of membrane traffic around the Golgi apparatus in plant cells

In contrast to the relatively static image of the plants, the world inside each cell is surprisingly dynamic. Membrane-bounded organelles move actively on the cytoskeletons and exchange materials by vesicles, tubules, or direct contact between each other. In order to understand what is happening during those events, it is essential to visualize the working components in vivo. After the breakthrough made by the application of fluorescent proteins, the development of light microscopy enabled many discoveries in cell biology, including those about the membrane traffic in plant cells. Especially, super-resolution microscopy, which is becoming more and more accessible, is now one of the most powerful techniques. However, although the spatial resolution has improved a lot, there are still some difficulties in terms of the temporal resolution, which is also a crucial parameter for the visualization of the living nature of the intracellular structures. In this review, we will introduce the super resolution microscopy developed especially for live-cell imaging with high temporal resolution, and show some examples that were made by this tool in plant membrane research.

Correlation of vacuole morphology with stomatal lineage development by whole-cell electron tomography

Stomatal movement is essential for plants to optimize transpiration and therefore photosynthesis. Rapid changes in the stomatal aperture are accompanied by adjustment of vacuole volume and morphology in guard cells (GCs). In Arabidopsis (Arabidopsis thaliana) leaf epidermis, stomatal development undergoes a cell-fate transition including four stomatal lineage cells: meristemoid, guard mother cell, young GC, and GC. Little is known about the mechanism underlying vacuole dynamics and vacuole formation during stomatal development. Here, we utilized whole-cell electron tomography (ET) analysis to elucidate vacuole morphology, formation, and development in different stages of stomatal lineage cells at nanometer resolution. The whole-cell ET models demonstrated that large vacuoles were generated from small vacuole stepwise fusion/maturation along stomatal development stages. Further ET analyses verified the existence of swollen intraluminal vesicles inside distinct vacuoles at certain developmental stages of stomatal lineage cells, implying a role of multivesicular body fusion in stomatal vacuole formation. Collectively, our findings demonstrate a mechanism mediating vacuole formation in Arabidopsis stomatal development and may shed light on the role of vacuoles in stomatal movement.