Mesoscale imaging with cryo-light and X-rays: Larger than molecular machines, smaller than a cell

Subcellular Feature-Based Classification of α and β Cells Using Soft X-ray Tomography

The dysfunction of α and β cells in pancreatic islets can lead to diabetes. Many questions remain on the subcellular organization of islet cells during the progression of disease. Existing three-dimensional cellular mapping approaches face challenges such as time-intensive sample sectioning and subjective cellular identification. To address these challenges, we have developed a subcellular feature-based classification approach, which allows us to identify α and β cells and quantify their subcellular structural characteristics using soft X-ray tomography (SXT). We observed significant differences in whole-cell morphological and organelle statistics between the two cell types. Additionally, we characterize subtle biophysical differences between individual insulin and glucagon vesicles by analyzing vesicle size and molecular density distributions, which were not previously possible using other methods. These sub-vesicular parameters enable us to predict cell types systematically using supervised machine learning. We also visualize distinct vesicle and cell subtypes using Uniform Manifold Approximation and Projection (UMAP) embeddings, which provides us with an innovative approach to explore structural heterogeneity in islet cells. This methodology presents an innovative approach for tracking biologically meaningful heterogeneity in cells that can be applied to any cellular system.

mRNA condensation fluidizes the cytoplasm

The intracellular environment is packed with macromolecules of mesoscale size, and this crowded milieu significantly influences cell physiology. When exposed to stress, mRNAs released after translational arrest condense with RNA binding proteins, resulting in the formation of membraneless RNA protein (RNP) condensates known as processing bodies (P-bodies) and stress granules (SGs). However, the impact of the assembly of these condensates on the biophysical properties of the crowded cytoplasmic environment remains unclear. Here, we find that upon exposure to stress, polysome collapse and condensation of mRNAs increases mesoscale particle diffusivity in the cytoplasm. Increased mesoscale diffusivity is required for the efficient formation of Q-bodies, membraneless organelles that coordinate degradation of misfolded peptides that accumulate during stress. Additionally, we demonstrate that polysome collapse and stress granule formation has a similar effect in mammalian cells, fluidizing the cytoplasm at the mesoscale. We find that synthetic, light-induced RNA condensation is sufficient to fluidize the cytoplasm, demonstrating a causal effect of RNA condensation. Together, our work reveals a new functional role for stress-induced translation inhibition and formation of RNP condensates in modulating the physical properties of the cytoplasm to effectively respond to stressful conditions.

Nuclear and cytoplasmic spatial protein quality control is coordinated by nuclear-vacuolar junctions and perinuclear ESCRT

Effective protein quality control (PQC), essential for cellular health, relies on spatial sequestration of misfolded proteins into defined inclusions. Here we reveal the coordination of nuclear and cytoplasmic spatial PQC. Cytoplasmic misfolded proteins concentrate in a cytoplasmic juxtanuclear quality control compartment, while nuclear misfolded proteins sequester into an intranuclear quality control compartment (INQ). Particle tracking reveals that INQ and the juxtanuclear quality control compartment converge to face each other across the nuclear envelope at a site proximal to the nuclear-vacuolar junction marked by perinuclear ESCRT-II/III protein Chm7. Strikingly, convergence at nuclear-vacuolar junction contacts facilitates VPS4-dependent vacuolar clearance of misfolded cytoplasmic and nuclear proteins, the latter entailing extrusion of nuclear INQ into the vacuole. Finding that nuclear-vacuolar contact sites are cellular hubs of spatial PQC to facilitate vacuolar clearance of nuclear and cytoplasmic inclusions highlights the role of cellular architecture in proteostasis maintenance.

Increased mesoscale diffusivity in response to acute glucose starvation

Macromolecular crowding is an important parameter that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) in response to acute glucose starvation. mRNP diffusivity was reduced upon glucose starvation as previously reported. In contrast, we observed increased diffusivity of μNS particles. Our results suggest that, upon glucose starvation, mRNP granule diffusivity may be reduced due to changes in physical interactions, while global crowding in the cytoplasm may be reduced.

Increased mesoscale diffusivity in response to acute glucose starvation

Macromolecular crowding is an important property of cells that impacts multiple biological processes. Passive microrheology using single particle tracking is a powerful means of studying macromolecular crowding. Here we monitored the diffusivity of self-assembling fluorescent nanoparticles (μNS) and mRNPs ( GFA1 -PP7) in response to acute glucose starvation. mRNP diffusivity was reduced upon glucose starvation as previously reported. By contrast, we observed increased diffusivity of μNS particles. Our results suggest that, upon glucose starvation, mRNP granule diffusivity may be reduced due to increased physical interactions, whereas macromolecular crowding in the cytoplasm may be globally reduced.

An intensity-based post-processing tool for 3D instance segmentation of organelles in soft X-ray tomograms

Investigating the 3D structures and rearrangements of organelles within a single cell is critical for better characterizing cellular function. Imaging approaches such as soft X-ray tomography have been widely applied to reveal a complex subcellular organization involving multiple inter-organelle interactions. However, 3D segmentation of organelle instances has been challenging despite its importance in organelle characterization. Here we propose an intensity-based post-processing tool to identify and separate organelle instances. Our tool separates sphere-like (insulin vesicle) and columnar-shaped organelle instances (mitochondrion) based on the intensity of raw tomograms, semantic segmentation masks, and organelle morphology. We validate our tool using synthetic tomograms of organelles and experimental tomograms of pancreatic β-cells to separate insulin vesicle and mitochondria instances. As compared to the commonly used connected regions labeling, watershed, and watershed + Gaussian filter methods, our tool results in improved accuracy in identifying organelles in the synthetic tomograms and an improved description of organelle structures in β-cell tomograms. In addition, under different experimental treatment conditions, significant changes in volumes and intensities of both insulin vesicle and mitochondrion are observed in our instance results, revealing their potential roles in maintaining normal β-cell function. Our tool is expected to be applicable for improving the instance segmentation of other images obtained from different cell types using multiple imaging modalities.

Advanced Light Source Analytical Techniques for Exploring the Biological Behavior and Fate of Nanomedicines

Exploration of the biological behavior and fate of nanoparticles, as affected by the nanomaterial-biology (nano-bio) interaction, has become progressively critical for guiding the rational design and optimization of nanomedicines to minimize adverse effects, support clinical translation, and aid in evaluation by regulatory agencies. Because of the complexity of the biological environment and the dynamic variations in the bioactivity of nanomedicines, in-situ, label-free analysis of the transport and transformation of nanomedicines has remained a challenge. Recent improvements in optics, detectors, and light sources have allowed the expansion of advanced light source (ALS) analytical technologies to dig into the underexplored behavior and fate of nanomedicines in vivo. It is increasingly important to further develop ALS-based analytical technologies with higher spatial and temporal resolution, multimodal data fusion, and intelligent prediction abilities to fully unlock the potential of nanomedicines. In this Outlook, we focus on several selected ALS analytical technologies, including imaging and spectroscopy, and provide an overview of the emerging opportunities for their applications in the exploration of the biological behavior and fate of nanomedicines. We also discuss the challenges and limitations faced by current approaches and tools and the expectations for the future development of advanced light sources and technologies. Improved ALS imaging and spectroscopy techniques will accelerate a profound understanding of the biological behavior of new nanomedicines. Such advancements are expected to inspire new insights into nanomedicine research and promote the development of ALS capabilities and methods more suitable for nanomedicine evaluation with the goal of clinical translation.

Soft X-ray tomography to map and quantify organelle interactions at the mesoscale

Inter-organelle interactions are a vital part of normal cellular function; however, these have proven difficult to quantify due to the range of scales encountered in cell biology and the throughput limitations of traditional imaging approaches. Here, we demonstrate that soft X-ray tomography (SXT) can be used to rapidly map ultrastructural reorganization and inter-organelle interactions in intact cells. SXT takes advantage of the naturally occurring, differential X-ray absorption of the carbon-rich compounds in each organelle. Specifically, we use SXT to map the spatiotemporal evolution of insulin vesicles and their co-localization and interaction with mitochondria in pancreatic β cells during insulin secretion and in response to different stimuli. We quantify changes in the morphology, biochemical composition, and relative position of mitochondria and insulin vesicles. These findings highlight the importance of a comprehensive and unbiased mapping at the mesoscale to characterize cell reorganization that would be difficult to detect with other existing methodologies.

The use of soft X-ray tomography to explore mitochondrial structure and function

Background

Mitochondria are cellular organelles responsible for energy production, and dysregulation of the mitochondrial network is associated with many disease states. To fully characterize the mitochondrial network's structure and function, a three-dimensional whole cell mapping technique is required.

Scope of review

This review highlights the use of soft X-ray tomography (SXT) as a relatively high-throughput approach to quantify mitochondrial structure and function under multiple cellular conditions.

Major conclusions

The use of SXT opens the door for mapping cellular rearrangements during critical processes such as insulin secretion, stem cell differentiation, or disease progression. SXT provides unique information such as biochemical compositions or molecular densities of organelles and allows for unbiased, label-free imaging of intact whole cells. Mapping mitochondria in the context of the near-native cellular environment will reveal more information regarding mitochondrial network functions within the cell.

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Soft X-ray tomography (SXT) generates 3D organelle maps of intact cells.

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3D maps reveal the positions of mitochondria and their molecular densities.

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SXT can be used to quantify and compare organelle contacts between conditions.

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SXT is unbiased imaging that identifies the contents of subcellular neighborhoods.

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SXT provides an exciting path for exploring metabolic dysfunction.

Imaging of Virus-Infected Cells with Soft X-ray Tomography

Viruses are obligate parasites that depend on a host cell for replication and survival. Consequently, to fully understand the viral processes involved in infection and replication, it is fundamental to study them in the cellular context. Often, viral infections induce significant changes in the subcellular organization of the host cell due to the formation of viral factories, alteration of cell cytoskeleton and/or budding of newly formed particles. Accurate 3D mapping of organelle reorganization in infected cells can thus provide valuable information for both basic virus research and antiviral drug development. Among the available techniques for 3D cell imaging, cryo-soft X-ray tomography stands out for its large depth of view (allowing for 10 µm thick biological samples to be imaged without further thinning), its resolution (about 50 nm for tomographies, sufficient to detect viral particles), the minimal requirements for sample manipulation (can be used on frozen, unfixed and unstained whole cells) and the potential to be combined with other techniques (i.e., correlative fluorescence microscopy). In this review we describe the fundamentals of cryo-soft X-ray tomography, its sample requirements, its advantages and its limitations. To highlight the potential of this technique, examples of virus research performed at BL09-MISTRAL beamline in ALBA synchrotron are also presented.

Single Cell Cryo-Soft X-ray Tomography Shows That Each Chlamydia Trachomatis Inclusion Is a Unique Community of Bacteria

Chlamydiae are strict intracellular pathogens residing within a specialised membrane-bound compartment called the inclusion. Therefore, each infected cell can, be considered as a single entity where bacteria form a community within the inclusion. It remains unclear as to how the population of bacteria within the inclusion influences individual bacterium. The life cycle of Chlamydia involves transitioning between the invasive elementary bodies (EBs) and replicative reticulate bodies (RBs). We have used cryo-soft X-ray tomography to observe individual inclusions, an approach that combines 40 nm spatial resolution and large volume imaging (up to 16 µm). Using semi-automated segmentation pipeline, we considered each inclusion as an individual bacterial niche. Within each inclusion, we identifyed and classified different forms of the bacteria and confirmed the recent finding that RBs have a variety of volumes (small, large and abnormal). We demonstrate that the proportions of these different RB forms depend on the bacterial concentration in the inclusion. We conclude that each inclusion operates as an autonomous community that influences the characteristics of individual bacteria within the inclusion.

Visualizing subcellular rearrangements in intact β cells using soft x-ray tomography

Characterizing relationships between cell structures and functions requires mesoscale mapping of intact cells showing subcellular rearrangements following stimulation; however, current approaches are limited in this regard. Here, we report a unique application of soft x-ray tomography to generate three-dimensional reconstructions of whole pancreatic β cells at different time points following glucose-stimulated insulin secretion. Reconstructions following stimulation showed distinct insulin vesicle distribution patterns reflective of altered vesicle pool sizes as they travel through the secretory pathway. Our results show that glucose stimulation caused rapid changes in biochemical composition and/or density of insulin packing, increased mitochondrial volume, and closer proximity of insulin vesicles to mitochondria. Costimulation with exendin-4 (a glucagon-like peptide-1 receptor agonist) prolonged these effects and increased insulin packaging efficiency and vesicle maturation. This study provides unique perspectives on the coordinated structural reorganization and interactions of organelles that dictate cell responses.

Assaying three-dimensional cellular architecture using X-ray tomographic and correlated imaging approaches

Much of our understanding of the spatial organization of and interactions between cellular organelles and macromolecular complexes has been the result of imaging studies utilizing either light- or electron-based microscopic analyses. These classical approaches, while insightful, are nonetheless limited either by restrictions in resolution or by the sheer complexity of generating multidimensional data. Recent advances in the use and application of X-rays to acquire micro- and nanotomographic data sets offer an alternative methodology to visualize cellular architecture at the nanoscale. These new approaches allow for the subcellular analyses of unstained vitrified cells and three-dimensional localization of specific protein targets and have served as an essential tool in bridging light and electron correlative microscopy experiments. Here, we review the theory, instrumentation details, acquisition principles, and applications of both soft X-ray tomography and X-ray microscopy and how the use of these techniques offers a succinct means of analyzing three-dimensional cellular architecture. We discuss some of the recent work that has taken advantage of these approaches and detail how they have become integral in correlative microscopy workflows.

From 2D STXM to 3D Imaging: Soft X-ray Laminography of Thin Specimens

X-ray tomography has become an indispensable tool for studying complex 3D interior structures with high spatial resolution. Three-dimensional imaging using soft X-rays offers powerful contrast mechanisms but has seen limited success with tomography due to the restrictions imposed by the much lower energy of the probe beam. The generalized geometry of laminography, characterized by a tilted axis of rotation, provides nm-scale 3D resolution for the investigation of extended (mm range) but thin (μm to nm) samples that are well suited to soft X-ray studies. This work reports on the implementation of soft X-ray laminography (SoXL) at the scanning transmission X-ray spectromicroscope of the PolLux beamline at the Swiss Light Source, Paul Scherrer Institut, which enables 3D imaging of extended specimens from 270 to 1500 eV. Soft X-ray imaging provides contrast mechanisms for both chemical sensitivity to molecular bonds and oxidation states and magnetic dichroism due to the much stronger attenuation of X-rays in this energy range. The presented examples of applications range from functionalized nanomaterials to biological photonic crystals and sophisticated nanoscaled magnetic domain patterns, thus illustrating the wide fields of research that can benefit from SoXL.

Precise correlative method of Cryo-SXT and Cryo-FM for organelle identification

Cryogenic soft X-ray tomography (Cryo-SXT) is ideally suitable to image the 3D sub-cellular architecture and organization of cells with high resolution in the near-native preservation state. Cryogenic fluorescence microscopy (Cryo-FM) can determine the location of a molecule of interest that has been labeled with a fluorescent tag, thus revealing the function of the cells. To understand the relations between the sub-cellular architecture and the function of cells, correlative Cryo-SXT and Cryo-FM was applied. This method required the matching of images of different modalities, and the accuracy of the matching is important. Here, a precise correlative method of Cryo-SXT and Cryo-FM is introduced. The capability of matching images of different modalities with high resolution was verified by simulations and practical experiments, and the method was used to identify vacuoles and mitochondria.

Soft X-ray tomography: virtual sculptures from cell cultures

Cellular complexity is represented best in high-spatial resolution, three-dimensional (3D) reconstructions. Soft X-ray tomography (SXT) generates detailed volumetric reconstructions of cells preserved in a near-to-native, frozen-hydrated state. SXT is broadly applicable and can image specimens ranging from bacteria to large mammalian cells. As a reference, we summarize light and electron microscopic methods. We then present an overview of SXT and discuss its role in cellular imaging. We detail the methods used to image biological specimens and present recent highlights that illustrate the capabilities of the technique. We conclude by discussing correlative imaging, specifically the combination of SXT and fluorescence microscopy performed on the same specimen. This correlated approach combines the structural morphology of a cell with its physiological characteristics to build a deeply informative composite view.

Enabling technologies in super-resolution fluorescence microscopy: reporters, labeling, and methods of measurement

Super-resolution fluorescence microscopy continues to experience a period of extraordinary development. New instrumentation and fluorescent labeling strategies provide access to molecular and cellular processes that occur on length scales ranging from nanometers to millimeters and on time scales ranging from milliseconds to hours. At the shortest length scales, single-molecule imaging methods now allow measurement of nanoscale localization, motion, and binding kinetics of individual biomolecules. At cellular and intercellular length scales, super-resolution microscopy allows structural and functional imaging of individual cells in tissues and even in whole animals. Here, we review recent advances that have enabled entirely new types of experiments and greatly potentiated existing technologies.

Evolving SAXS versatility: solution X-ray scattering for macromolecular architecture, functional landscapes, and integrative structural biology

Small-angle X-ray scattering (SAXS) has emerged as an enabling integrative technique for comprehensive analyses of macromolecular structures and interactions in solution. Over the past two decades, SAXS has become a mainstay of the structural biologist’s toolbox, supplying multiplexed measurements of molecular shape and dynamics that unveil biological function. Here, we discuss evolving SAXS theory, methods, and applications that extend the field of small-angle scattering beyond simple shape characterization. SAXS, coupled with size-exclusion chromatography (SEC-SAXS) and time-resolved (TR-SAXS) methods, is now providing high-resolution insight into macromolecular flexibility and ensembles, delineating biophysical landscapes, and facilitating high-throughput library screening to assess macromolecular properties and to create opportunities for drug discovery. Looking forward, we consider SAXS in the integrative era of hybrid structural biology methods, its potential for illuminating cellular supramolecular and mesoscale structures, and its capacity to complement high-throughput bioinformatics sequencing data. As advances in the field continue, we look forward to proliferating uses of SAXS based upon its abilities to robustly produce mechanistic insights for biology and medicine.

Securing the future of research computing in the biosciences

Improvements in technology often drive scientific discovery. Therefore, research requires sustained investment in the latest equipment and training for the researchers who are going to use it. Prioritising and administering infrastructure investment is challenging because future needs are difficult to predict. In the past, highly computationally demanding research was associated primarily with particle physics and astronomy experiments. However, as biology becomes more quantitative and bioscientists generate more and more data, their computational requirements may ultimately exceed those of physical scientists. Computation has always been central to bioinformatics, but now imaging experiments have rapidly growing data processing and storage requirements. There is also an urgent need for new modelling and simulation tools to provide insight and understanding of these biophysical experiments. Bioscience communities must work together to provide the software and skills training needed in their areas. Research-active institutions need to recognise that computation is now vital in many more areas of discovery and create an environment where it can be embraced. The public must also become aware of both the power and limitations of computing, particularly with respect to their health and personal data.

Imaging cell morphology and physiology using X-rays

Morphometric measurements, such as quantifying cell shape, characterizing sub-cellular organization, and probing cell-cell interactions, are fundamental in cell biology and clinical medicine. Until quite recently, the main source of morphometric data on cells has been light- and electron-based microscope images. However, many technological advances have propelled X-ray microscopy into becoming another source of high-quality morphometric information. Here, we review the status of X-ray microscopy as a quantitative biological imaging modality. We also describe the combination of X-ray microscopy data with information from other modalities to generate polychromatic views of biological systems. For example, the amalgamation of molecular localization data, from fluorescence microscopy or spectromicroscopy, with structural information from X-ray tomography. This combination of data from the same specimen generates a more complete picture of the system than that can be obtained by a single microscopy method. Such multimodal combinations greatly enhance our understanding of biology by combining physiological and morphological data to create models that more accurately reflect the complexities of life.

Cryo-soft X-ray tomography: using soft X-rays to explore the ultrastructure of whole cells

Cryo-soft X-ray tomography is an imaging technique that addresses the need for mesoscale imaging of cellular ultrastructure of relatively thick samples without the need for staining or chemical modification. It allows the imaging of cellular ultrastructure to a resolution of 25–40 nm and can be used in correlation with other imaging modalities, such as electron tomography and fluorescence microscopy, to further enhance the information content derived from biological samples. An overview of the technique, discussion of sample suitability and information about sample preparation, data collection and data analysis is presented here. Recent developments and future outlook are also discussed.

Opportunities and Challenges in Building a Spatiotemporal Multi-scale Model of the Human Pancreatic β Cell

The construction of a predictive model of an entire eukaryotic cell that describes its dynamic structure from atomic to cellular scales is a grand challenge at the intersection of biology, chemistry, physics, and computer science. Having such a model will open new dimensions in biological research and accelerate healthcare advancements. Developing the necessary experimental and modeling methods presents abundant opportunities for a community effort to realize this goal. Here, we present a vision for creation of a spatiotemporal multi-scale model of the pancreatic β-cell, a relevant target for understanding and modulating the pathogenesis of diabetes.