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The bacterial chaperonin GroEL-GroES promotes protein folding through ATP-regulated cycles of substrate protein binding, encapsulation, and release. Here, we have used cryoEM to determine structures of GroEL, GroEL-ADP.BeF3, and GroEL-ADP.AlF3-GroES all complexed with the model substrate Rubisco. Our structures provide a series of snapshots that show how the conformation and interactions of non-native Rubisco change as it proceeds through the GroEL-GroES reaction cycle. We observe specific charged and hydrophobic GroEL residues forming strong initial contacts with non-native Rubisco. Binding of ATP or ADP.BeF3 to GroEL-Rubisco results in the formation of an intermediate GroEL complex displaying striking asymmetry in the ATP/ADP.BeF3-bound ring. In this ring, four GroEL subunits bind Rubisco and the other three are in the GroES-accepting conformation, explaining how GroEL can recruit GroES without releasing bound substrate. Our cryoEM structures of stalled GroEL-ADP.AlF3-Rubisco-GroES complexes show Rubisco folding intermediates interacting with GroEL-GroES via different sets of residues.

Volume electron microscopy (vEM) is a group of techniques that reveal the 3D ultrastructure of cells and tissues through continuous depths of at least 1 micrometer. A burgeoning grassroots community effort is fast building the profile and revealing the impact of vEM technology in the life sciences and clinical research.

Public participation in research, also known as citizen science, is being increasingly adopted for the analysis of biological volumetric data. Researchers working in this domain are applying online citizen science as a scalable distributed data analysis approach, with recent research demonstrating that non-experts can productively contribute to tasks such as the segmentation of organelles in volume electron microscopy data. This, alongside the growing challenge to rapidly process the large amounts of biological volumetric data now routinely produced, means there is increasing interest within the research community to apply online citizen science for the analysis of data in this context. Here, we synthesise core methodological principles and practices for applying citizen science for analysis of biological volumetric data. We collate and share the knowledge and experience of multiple research teams who have applied online citizen science for the analysis of volumetric biological data using the Zooniverse platform (www.zooniverse.org). We hope this provides inspiration and practical guidance regarding how contributor effort via online citizen science may be usefully applied in this domain.

Serial focussed ion beam scanning electron microscopy (FIB/SEM) enables imaging and assessment of subcellular structures on the mesoscale (10 nm to 10 µm). When applied to vitrified samples, serial FIB/SEM is also a means to target specific structures in cells and tissues while maintaining constituents’ hydration shells for in situ structural biology downstream. However, the application of serial FIB/SEM imaging of non-stained cryogenic biological samples is limited due to low contrast, curtaining, and charging artefacts. We address these challenges using a cryogenic plasma FIB/SEM. We evaluated the choice of plasma ion source and imaging regimes to produce high-quality SEM images of a range of different biological samples. Using an automated workflow we produced three-dimensional volumes of bacteria, human cells, and tissue, and calculated estimates for their resolution, typically achieving 20–50 nm. Additionally, a tag-free localisation tool for regions of interest is needed to drive the application of in situ structural biology towards tissue. The combination of serial FIB/SEM with plasma-based ion sources promises a framework for targeting specific features in bulk-frozen samples (>100 µm) to produce lamellae for cryogenic electron tomography.

Cryo-electron microscopy (cryoEM) has been transformed over the last decade, with continual new hardware and software tools coming online, pushing the boundaries of what is possible and the nature and complexity of projects that can be undertaken. Here we discuss some recent trends and new tools which are creating opportunities to make more effective use of the resources available within facilities (both staff and equipment). We present approaches for the stratification of projects based on risk and known information about the projects, and the impacts this might have on the allocation of microscope time. We show that allocating different resources (microscope time) based on this information can lead to a significant increase in 'successful' use of the microscope, and reduce lead time by enabling projects to 'fail faster'. This model results in more efficient and sustainable cryoEM facility operation.

An emergent volume electron microscopy (vEM) technique called cryogenic serial plasma focused ion beam milling scanning electron microscopy (pFIB/SEM) can decipher complex biological structures by building a three-dimensional picture of biological samples at mesoscale resolution. This is achieved by collecting consecutive SEM images after successive rounds of FIB milling that expose a new surface after each milling step. Due to instrumental limitations, some image processing is necessary before 3D visualisation and analysis of the data is possible. SEM images are affected by noise, drift, and charging effects, that can make precise 3D reconstruction of biological features difficult. This paper presents Okapi-EM, an open-source Napari plugin(1)developed to process and analyse cryogenic serial FIB/SEM images. Okapi-EM enables automated image registration of slices, evaluation of image quality metrics specific to FIB-SEM imaging, and mitigation of charging artefacts. Implementation of Okapi-EM within the Napari framework ensures that the tools are both user- and developer-friendly, through provision of a graphical user interface and access to Python programming. Napari also hosts a variety of other image processing plugins so Okapi-EM tools can be integrated into and combined with other workflows. Okapi-EM can be downloaded freely athttps://github.com/rosalindfranklininstitute/okapi-em, or installed from Python package index (PyPI).Impact statementCryogenic serial pFIB/SEM is an emerging microscopy technique that is used to visualise 3D structures of biological features at mesoscale resolutions(2). This technique requires common post processing of data such as alignment and charge mitigation to enable robust segmentation and analysis. In addition, approaches are needed to quantify data quality to enable an assessment of features and tune data acquisition parameters to enable optimal image acquisition. This article presents Okapi-EM, a combination of software tools designed to facilitate these important initial steps in assessing and processing images from these experiments. These tools have been assembled as a plugin for a popular 3D biological image visualiser called Napari, making their usage user-friendly and readily accessible.

Electron cryo-tomography (cryo-ET) is an imaging technique for probing 3D structures with at the nanometre scale. This technique has been used extensively in the biomedical field to study the complex structures of proteins and other macromolecules. With the advancement in technology, microscopes are currently capable of producing images amounting to terabytes of data per day, posing great challenges for scientists as the speed of processing of the images cannot keep up with the ever-higher throughput of the microscopes. Therefore, automation is an essential and natural pathway on which image processing – from individual micrographs to full tomograms – is developing. In this paper, we present Ot2Rec, an open-source pipelining tool which aims to enable scientists to build their own processing workflows in a flexible and automatic manner. The basic building blocks of Ot2Rec are plugins which follow a unified API structure, making it simple for scientists to contribute to Ot2Rec by adding features which are not already available. In this paper, we also present three case studies of image processing using Ot2Rec, through which we demonstrate the speedup of using a semi-automatic workflow over a manual one, the possibility of writing and using custom (prototype) plugins, and the flexibility of Ot2Rec which enables the mix-and-match of plugins. We also demonstrate, in the supplementary information, a built-in reporting feature in Ot2Rec which aggregates the metadata from all process being run, and output them in the Jupyter Notebook and/or HTML formats for quick review of image processing quality. Ot2Rec can be found athttps://github.com/rosalindfranklininstitute/ot2rec.Impact StatementThe field of cryo electron tomography has grown substantially in recent years, bringing about new advances in hardware and software which enable visualisation of cell and tissue architecture and proteins found in their native context. These same advances have, in some ways, stratified the field into those with access and those without. On the software side, this has emphasised the need for open-source options that do not require high levels of computational literacy to access. Additionally, it has highlighted the need for ways to both mix-and-match software for easy prototyping and comparisons between parameters and methods. Ot2Rec addresses these needs through a simple, unified plugin structure allowing the addition of existing software or the development of new and does so in a way which democratises access.

Protein misfolding is common to neurodegenerative diseases (NDs) including Alzheimer’s disease (AD), which is characterized by self-assembly and accumulation of Amyloid-beta in the brain. Furthermore, impaired proteostatic mechanisms have been implicated in NDs. Lysosomes are a critical component of the proteostasis network required to degrade and recycle material from outside and within the cell. Using a model of AD neurodegeneration where toxic amyloid beta oligomers are applied exogenously to primary hippocampal neurons, we have previously established that oligomers are endocytosed and trafficked to lysosomes where they accumulate and prevent further endocytosis. Here, we use pioneering correlative cryo-structured illumination microscopy and cryo-soft X-ray tomography imaging techniques to reconstruct 3D cellular architecture in the native state. We demonstrate that lysosomes in oligomer treated neurons are less X-ray dense suggesting they contain less carbon-rich material than untreated cells. Furthermore, we observe an increase in carbon dense lipid vesicles in oligomer treated cells. This work provides unprecedented and critical visual information on the changes to neuronal architecture inflicted by amyloid beta oligomers using advanced methods in structural cell biology.

Serial focussed ion beam scanning electron microscopy (FIB/SEM) enables imaging and assessment of sub-cellular structures on the mesoscale (10 nm to 10 μm). When applied to vitrified samples, serial FIB/SEM is also a means to target specific structures in cells and tissues while maintaining constituents’ hydration shells for in-situ structural biology downstream. However, the application of serial FIB/SEM imaging of non-stained cryogenic biological samples is limited due to low contrast, curtaining and charging artefacts. We address these challenges using a cryogenic plasma FIB/SEM (cryo-pFIB/SEM). We evaluated the choice of plasma ion source and imaging regimes to produce high quality SEM images of a range of different biological samples. Using an automated workflow we produced three dimensional volumes of bacteria, human cells, and tissue, and calculated estimates for their resolution, typically achieving 20 to 50 nm. Additionally, a tag-free tool is needed to drive the application of in situ structural biology towards tissue. The combination of serial FIB/SEM with plasmabased ion sources promises a framework for targeting specific features in bulk-frozen samples (>100 μm) to produce lamella for cryogenic electron tomography.

As sample preparation and imaging techniques have expanded and improved to include a variety of options for larger sized and numbers of samples, the bottleneck in volumetric imaging is now data analysis. Annotation and segmentation are both common, yet difficult, data analysis tasks which are required to bring meaning to the volumetric data. The SuRVoS application has been updated and redesigned to provide access to both manual and machine learning-based segmentation and annotation techniques, including support for crowd sourced data. Combining adjacent, similar voxels (supervoxels) provides a mechanism for speeding up segmentation both in the painting of annotation and by training a segmentation model on a small amount of annotation. The support for layers allows multiple datasets to be viewed and annotated together which, for example, enables the use of correlative data (e.g. crowd-sourced annotations or secondary imaging techniques) to guide segmentation. The ability to work with larger data on high-performance servers with GPUs has been added through a client-server architecture and the Pytorch-based image processing and segmentation server is flexible and extensible, and allows the implementation of deep learning-based segmentation modules. The client side has been built around Napari allowing integration of SuRVoS into an ecosystem for open-source image analysis while the server side has been built with cloud computing and extensibility through plugins in mind. Together these improvements to SuRVoS provide a platform for accelerating the annotation and segmentation of volumetric and correlative imaging data across modalities and scales.

Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.

Ribonucleotide reductase (RNR) is an essential enzyme that converts ribonucleotides to deoxyribonucleotides and is a promising antibiotic target, but few RNRs have been structurally characterized. We present the use of the chameleon, a commercially-available piezoelectric cryogenic electron microscopy plunger, to address complex denaturation in the Neisseria gonorrhoeae class Ia RNR. Here, we characterize the extent of denaturation of the ring-shaped complex following grid preparation using a traditional plunger and using a chameleon with varying dispense-to-plunge times. We also characterize how dispense-to-plunge time influences the amount of protein sample required for grid preparation and preferred orientation of the sample. We demonstrate that the fastest dispense-to-plunge time of 54 ms is sufficient for generation of a data set that produces a high quality structure, and that a traditional plunging technique or slow chameleon dispense-to-plunge times generate data sets limited in resolution by complex denaturation. The 4.3 Å resolution structure of Neisseria gonorrhoeae class Ia RNR in the inactive α4β4 oligomeric state solved using the chameleon with a fast dispense-to-plunge time yields molecular information regarding similarities and differences to the well studied Escherichia coli class Ia RNR α4β4 ring.

Multi-scale structural assessment of biological soft tissue is challenging but essential to gain insight into structure-function relationships of tissue/organ. Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced imaging, and robust, validated machine-learning segmentation techniques to provide the first massively multi-scale and multi-domain information that enables detailed morphological and functional analyses of both maternal and fetal placental domains. Finally, we quantify the scale-dependent error in morphological metrics of heterogeneous placental tissue, estimating the minimal tissue scale needed in extracting meaningful biological data. The developed protocol is beneficial for high-throughput investigation of structure-function relationships in both normal and diseased placentas, allowing us to optimise therapeutic approaches for pathological pregnancies. In addition, the methodology presented is applicable in characterisation of tissue architecture and physiological behaviours of other complex organs with similarity to the placenta, where an exchange barrier possesses circulating vascular and avascular fluid spaces. Summary Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced 3D X-ray imaging, and robust, validated machine-learning segmentation techniques to provide massively multi-scale and multi-domain insights on vascular-rich organ morphology and function.

A host of new technologies are under development to improve the quality and reproducibility of cryoEM grid preparation. Here we have systematically investigated the preparation of three macromolecular complexes using three different vitrification devices (Vitrobot™, chameleon and a time-resolved cryoEM device) on various timescales, including grids made within 6 ms, (the fastest reported to date), to interrogate particle behaviour at the air-water interface for different timepoints. Results demonstrate that different macromolecular complexes can respond to the thin film environment formed during cryoEM sample preparation in highly variable ways, shedding light on why cryoEM sample preparation can be difficult to optimise. We demonstrate that reducing time between sample application and vitrification is just one tool to improve cryoEM grid quality, but that it is unlikely to be a generic ‘silver bullet’ for improving the quality of every cryoEM sample preparation.

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.

Summary A host of new technologies are under development to improve the quality and reproducibility of cryoelectron microscopy (cryoEM) grid preparation. Here we have systematically investigated the preparation of three macromolecular complexes using three different vitrification devices (Vitrobot, chameleon, and a time-resolved cryoEM device) on various timescales, including grids made within 6 ms (the fastest reported to date), to interrogate particle behavior at the air-water interface for different timepoints. Results demonstrate that different macromolecular complexes can respond to the thin-film environment formed during cryoEM sample preparation in highly variable ways, shedding light on why cryoEM sample preparation can be difficult to optimize. We demonstrate that reducing time between sample application and vitrification is just one tool to improve cryoEM grid quality, but that it is unlikely to be a generic “silver bullet” for improving the quality of every cryoEM sample preparation., Graphical Abstract, Highlights • Particles partition to the air-water-interface even during fast (ms) grid making • Higher grid-making speeds can result in greater angular spread of the specimen • Higher grid-making speeds may reduce particle damage and subunit dissociation • Different grid-making apparatus can affect sample concentration in the ice, Here, we take advantage of new grid-making procedures to investigate the effect of speed in cryoEM grid production on protein particle behavior. These results allow us to better understand how different grid-making approaches can affect the resultant grid with respect to particle damage, preferred orientation, and resultant concentration.

Super-resolution fluorescence microscopy plays a crucial role in our understanding of cell structure and function by reporting cellular ultrastructure with 20–30 nm resolution. However, this resolution is insufficient to image macro-molecular machinery at work. A path to improve resolution is to image under cryogenic conditions. This substantially increases the brightness of most fluorophores and preserves native ultrastructure much better than chemical fixation. Cryogenic conditions are, however, underutilised because of the lack of compatible high numerical aperture objectives. Here, using a low-cost super-hemispherical solid immersion lens (superSIL) and a basic set-up we achieve 12 nm resolution under cryogenic conditions, to our knowledge the best yet attained in cells using simple set-ups and/or commercial systems. By also allowing multicolour imaging, and by paving the way to total-internal-reflection fluorescence imaging of mammalian cells under cryogenic conditions, superSIL microscopy opens a straightforward route to achieve unmatched resolution on bacterial and mammalian cell samples., Lin Wang et al. present a new super-resolution modality using a super-hemispherical immersion lens. They achieve a 12 nm spatial resolution in cells under cryogenic conditions, which offers the technical means to study bacterial and mammalian cell samples at molecule localisation length-scales.

Super-resolution fluorescence microscopy achieves 20-30 nm resolution by using liquid-immersion objectives to optimize light collection and chemical sample fixation to minimize image blurring. It is known that fluorophore brightness increases substantially under cryogenic conditions and that cryo-fixation is far superior in preserving ultrastructure. However, cryogenic conditions have not been exploited to improve resolution or sample quality because liquid immersion media freezes at the objective, losing its optical properties. Here, simply by replacing the immersion fluid with a low-cost super-hemispherical solid immersion lens (superSIL), we effortlessly achieve uperSIL microscopy delivers a straightforward route to achieve unmatched nanoscale resolution on both bacterial and mammalian cell samples, which any laboratory can effortlessly and inexpensively implement.

Segmentation is the process of isolating specific regions or objects within an imaged volume, so that further study can be undertaken on these areas of interest. When considering the analysis of complex biological systems, the segmentation of three-dimensional image data is a time consuming and labor intensive step. With the increased availability of many imaging modalities and with automated data collection schemes, this poses an increased challenge for the modern experimental biologist to move from data to knowledge. This publication describes the use of SuRVoS Workbench, a program designed to address these issues by providing methods to semi-automatically segment complex biological volumetric data. Three datasets of differing magnification and imaging modalities are presented here, each highlighting different strategies of segmenting with SuRVoS. Phase contrast X-ray tomography (microCT) of the fruiting body of a plant is used to demonstrate segmentation using model training, cryo electron tomography (cryoET) of human platelets is used to demonstrate segmentation using super- and megavoxels, and cryo soft X-ray tomography (cryoSXT) of a mammalian cell line is used to demonstrate the label splitting tools. Strategies and parameters for each datatype are also presented. By blending a selection of semi-automatic processes into a single interactive tool, SuRVoS provides several benefits. Overall time to segment volumetric data is reduced by a factor of five when compared to manual segmentation, a mainstay in many image processing fields. This is a significant savings when full manual segmentation can take weeks of effort. Additionally, subjectivity is addressed through the use of computationally identified boundaries, and splitting complex collections of objects by their calculated properties rather than on a case-by-case basis.

Segmentation of biological volumes is a crucial step needed to fully analyse their scientific content. Not having access to convenient tools with which to segment or annotate the data means many biological volumes remain under-utilised. Automatic segmentation of biological volumes is still a very challenging research field, and current methods usually require a large amount of manually-produced training data to deliver a high-quality segmentation. However, the complex appearance of cellular features and the high variance from one sample to another, along with the time-consuming work of manually labelling complete volumes, makes the required training data very scarce or non-existent. Thus, fully automatic approaches are often infeasible for many practical applications. With the aim of unifying the segmentation power of automatic approaches with the user expertise and ability to manually annotate biological samples, we present a new workbench named SuRVoS (Super-Region Volume Segmentation). Within this software, a volume to be segmented is first partitioned into hierarchical segmentation layers (named Super-Regions) and is then interactively segmented with the user's knowledge input in the form of training annotations. SuRVoS first learns from and then extends user inputs to the rest of the volume, while using Super-Regions for quicker and easier segmentation than when using a voxel grid. These benefits are especially noticeable on noisy, low-dose, biological datasets.

© 2016. Published by The Company of Biologists Ltd. Sickle cell disease is a destructive genetic disorder characterized by the formation of fibrils of deoxygenated hemoglobin, leading to the red blood cell (RBC) morphology changes that underlie the clinical manifestations of this disease. Using cryogenic soft X-ray tomography (SXT), we characterized the morphology of sickled RBCs in terms of volume and the number of protrusions per cell. We were able to identify statistically a relationship between the number of protrusions and the volume of the cell, which is known to correlate to the severity of sickling. This structural polymorphism allows for the classification of the stages of the sickling process. Recent studies have shown that elevated sphingosine kinase 1 (Sphk1)-mediated sphingosine 1-phosphate production contributes to sickling. Here, we further demonstrate that compound 5C, an inhibitor of Sphk1, has anti-sickling properties. Additionally, the variation in cellular morphology upon treatment suggests that this drug acts to delay the sickling process. SXT is an effective tool that can be used to identify the morphology of the sickling process and assess the effectiveness of potential therapeutics.

Although acknowledged to be variable and subjective, manual annotation of cryo-electron tomography data is commonly used to answer structural questions and to create a “ground truth” for evaluation of automated segmentation algorithms. Validation of such annotation is lacking, but is critical for understanding the reproducibility of manual annotations. Here, we used voxel-based similarity scores for a variety of specimens, ranging in complexity and segmented by several annotators, to quantify the variation among their annotations. In addition, we have identified procedures for merging annotations to reduce variability, thereby increasing the reliability of manual annotation. Based on our analyses, we find that it is necessary to combine multiple manual annotations to increase the confidence level for answering structural questions. We also make recommendations to guide algorithm development for automated annotation of features of interest.

Huntington disease, a neurodegenerative disorder characterized by functional deficits and loss of striatal neurons, is linked to an expanded and unstable CAG trinucleotide repeat in the huntingtin gene (HTT). This DNA sequence translates to a polyglutamine repeat in the protein product, leading to mutant huntingtin (mHTT) protein aggregation. The aggregation of mHTT is inhibited in vitro and in vivo by the TCP-1 ring complex (TRiC) chaperonin. Recently, a novel complex comprised of a single type of TRiC subunit has been reported to inhibit mHTT aggregation. Specifically, the purified CCT5 homo-oligomer complex, when compared with TRiC, has a similar structure, ATP use, and substrate refolding activity, and, importantly, it also inhibits mHTT aggregation. Using an aggregation suppression assay and cryoelectron tomography coupled with a novel computational classification method, we uncover the interactions between the synthetic CCT5 complex (∼1 MDa) and aggregates of mutant huntingtin exon 1 containing 46 glutamines (mHTTQ46-Ex1). We find that, in a similar fashion to TRiC, synthetic CCT5 complex caps mHTT fibrils at their tips and encapsulates mHTT oligomers, providing a structural description of the inhibition of mHTTQ46-Ex1 by CCT5 complex and a shared mechanism of mHTT inhibition between TRiC chaperonin and the CCT5 complex: cap and contain. Background: Huntington disease patients show an accumulation of oligomers and fibrillar species of mutant huntingtin (mHTT). Results: Cryoelectron tomography and subvolume averaging visualizes heterogeneous mHTT oligomeric species inside the chaperonin-like CCT5 cavity. Conclusion: The structural basis of mHTT aggregation inhibition by CCT5 is through capping of fibrils and encapsulation of oligomers. Significance: These structural mechanisms inspire the development of new strategies for inhibiting mHTT aggregation.

Basic ideas about the constancy and randomness of mutagenesis that drives evolution were challenged by the discovery of mutation pathways activated by stress responses. These pathways could promote evolution specifically when cells are maladapted to their environment (i.e., are stressed). However, the clearest example—a general stress-response–controlled switch to error-prone DNA break (double-strand break, DSB) repair—was suggested to be peculiar to an Escherichia coli F′ conjugative plasmid, not generally significant, and to occur by an alternative stress-independent mechanism. Moreover, mechanisms of spontaneous mutation in E. coli remain obscure. First, we demonstrate that this same mechanism occurs in chromosomes of starving F − E. coli . I-SceI endonuclease-induced chromosomal DSBs increase mutation 50-fold, dependent upon general/starvation- and DNA-damage-stress responses, DinB error-prone DNA polymerase, and DSB-repair proteins. Second, DSB repair is also mutagenic if the RpoS general-stress-response activator is expressed in unstressed cells, illustrating a stress-response–controlled switch to mutagenic repair. Third, DSB survival is not improved by RpoS or DinB, indicating that mutagenesis is not an inescapable byproduct of repair. Importantly, fourth, fully half of spontaneous frame-shift and base-substitution mutation during starvation also requires the same stress-response, DSB-repair, and DinB proteins. These data indicate that DSB-repair-dependent stress-induced mutation, driven by spontaneous DNA breaks, is a pathway that cells usually use and a major source of spontaneous mutation. These data also rule out major alternative models for the mechanism. Mechanisms that couple mutagenesis to stress responses can allow cells to evolve rapidly and responsively to their environment.