The electron cryomicroscopy (cryo-EM) resolution revolution has shifted structural biology into a new era, enabling the routine structure determination of macromolecular complexes at an unprecedented rate. Building on this, electron cryotomography (cryo-ET) offers the potential to visualise the native three-dimensional organisation of biological specimens, from cells to tissues and even entire organisms. Despite this huge potential, the study of tissue-like multicellular specimens via cryo-ET still presents numerous challenges, wherein many steps in the workflow are being developed or in urgent need of improvement. In this review, we outline the latest techniques currently utilised for in situ imaging of multicellular specimens, while clearly enumerating their associated limitations. We consider every step in typical workflows employed by various laboratories, including sample preparation, data collection and image analysis, to highlight recent progress and showcase prominent success stories. By considering the entire structural biology workflow for multicellular specimens, we identify which future exciting developments in hardware and software could enable comprehensive in situ structural biology investigations, bringing forth a new age of discovery in molecular structural and cell biology.

The TRiC/CCT complex assists in the folding of approximately 10% of cytosolic proteins through an ATP-driven conformational cycle, playing a crucial role in maintaining protein homeostasis. Despite our understanding of ATP-driven TRiC ring closing and substrate folding, the process and mechanisms underlying TRiC ring-opening and substrate release remain largely unexplored. In this study, by determining an ensemble of cryo-EM structures of yeast TRiC in the presence of ADP, including three intermediate transition states, we present a comprehensive picture of the TRiC ring-opening process. During this process, CCT3 detects the loss of γ-phosphate and initiates with the dynamics of its apical protrusion, and expands to the outward leaning of the consecutive CCT6/8/7/5 subunits. This is followed by significant movements of CCT2, CCT4, and especially CCT1 subunits, resulting in the opening of the TRiC rings. We also observed an unforeseen temporary separation between the two rings in the CCT2 side, coordinating the release of the originally locked CCT4 N-terminus, which potentially participates in the ring-opening process. Collectively, our study reveals a stepwise TRiC ring-opening mechanism, provides a comprehensive view of the TRiC conformational landscape, and sheds lights on its subunit specificity in sensing nucleotide status and substrate release. Our findings deepen our understanding of protein folding assisted by TRiC and may inspire new strategies for the diagnosis and treatment of related diseases.

Image-processing pipelines require the design of complex workflows combining many different steps that bring the raw acquired data to a final result with biological meaning. In the image-processing domain of cryo-electron microscopy single-particle analysis (cryo-EM SPA), hundreds of steps must be performed to obtain the three-dimensional structure of a biological macromolecule by integrating data spread over thousands of micrographs containing millions of copies of allegedly the same macromolecule. The execution of such complicated workflows demands a specific tool to keep track of all these steps performed. Additionally, due to the extremely low signal-to-noise ratio (SNR), the estimation of any image parameter is heavily affected by noise resulting in a significant fraction of incorrect estimates. Although low SNR and processing millions of images by hundreds of sequential steps requiring substantial computational resources are specific to cryo-EM, these characteristics may be shared by other biological imaging domains. Here, we present Scipion, a Python generic open-source workflow engine specifically adapted for image processing. Its main characteristics are: (a) interoperability, (b) smart object model, (c) gluing operations, (d) comparison operations, (e) wide set of domain-specific operations, (f) execution in streaming, (g) smooth integration in high-performance computing environments, (h) execution with and without graphical capabilities, (i) flexible visualization, (j) user authentication and private access to private data, (k) scripting capabilities, (l) high performance, (m) traceability, (n) reproducibility, (o) self-reporting, (p) reusability, (q) extensibility, (r) software updates, and (s) non-restrictive software licensing.

Principal component analysis (PCA) plays an important role in the analysis of cryo-electron microscopy (cryo-EM) images for various tasks such as classification, denoising, compression, and ab initio modeling. We introduce a fast method for estimating a compressed representation of the 2-D covariance matrix of noisy cryo-EM projection images affected by radial point spread functions that enables fast PCA computation. Our method is based on a new algorithm for expanding images in the Fourier–Bessel basis (the harmonics on the disk), which provides a convenient way to handle the effect of the contrast transfer functions. For $ N $ images of size $ L\times L $ , our method has time complexity $ O\left({NL}^3+{L}^4\right) $ and space complexity $ O\left({NL}^2+{L}^3\right) $ . In contrast to previous work, these complexities are independent of the number of different contrast transfer functions of the images. We demonstrate our approach on synthetic and experimental data and show acceleration by factors of up to two orders of magnitude.

Synthetic peptide and peptido-mimetic filaments and tubes represent a diverse class of nanomaterials with a broad range of potential applications, such as drug delivery, vaccine development, synthetic catalyst design, encapsulation, and energy transduction. The structures of these filaments comprise supramolecular polymers based on helical arrangements of subunits that can be derived from self-assembly of monomers based on diverse structural motifs. In recent years, structural analyses of these materials at near-atomic resolution (NAR) have yielded critical insights into the relationship between sequence, local conformation, and higher-order structure and morphology. This structural information offers the opportunity for development of new tools to facilitate the predictable and reproducible de novo design of synthetic helical filaments. However, these studies have also revealed several significant impediments to the latter process – most notably, the common occurrence of structural polymorphism due to the lability of helical symmetry in structural space. This article summarizes the current state of knowledge on the structures of designed peptide and peptido-mimetic filamentous assemblies, with a focus on structures that have been solved to NAR for which reliable atomic models are available.

Recent breakthroughs in deep learning-based protein structure prediction show that it is possible to obtain highly accurate models for a wide range of difficult protein targets for which only the amino acid sequence is known. The availability of accurately predicted models from sequences can potentially revolutionise many modelling approaches in structural biology, including the interpretation of cryo-EM density maps. Although atomic structures can be readily solved from cryo-EM maps of better than 4 Å resolution, it is still challenging to determine accurate models from lower-resolution density maps. Here, we report on the benefits of models predicted by AlphaFold2 (the best-performing structure prediction method at CASP14) on cryo-EM refinement using the Phenix refinement suite for AlphaFold2 models. To study the robustness of model refinement at a lower resolution of interest, we introduced hybrid maps (i.e. experimental cryo-EM maps) filtered to lower resolutions by real-space convolution. The AlphaFold2 models were refined to attain good accuracies above 0.8 TM scores for 9 of the 13 cryo-EM maps. TM scores improved for AlphaFold2 models refined against all 13 cryo-EM maps of better than 4.5 Å resolution, 8 hybrid maps of 6 Å resolution, and 3 hybrid maps of 8 Å resolution. The results show that it is possible (at least with the Phenix protocol) to extend the refinement success below 4.5 Å resolution. We even found isolated cases in which resolution lowering was slightly beneficial for refinement, suggesting that high-resolution cryo-EM maps might sometimes trap AlphaFold2 models in local optima.

Mitochondrial F-type adenosine triphosphate (ATP) synthases are commonly introduced as highly conserved membrane-embedded rotary machines generating the majority of cellular ATP. This simplified view neglects recently revealed striking compositional diversity of the enzyme and the fact that in specific life stages of some parasites, the physiological role of the enzyme is to maintain the mitochondrial membrane potential at the expense of ATP rather than to produce ATP. In addition, mitochondrial ATP synthases contribute indirectly to the organelle's other functions because they belong to major determinants of submitochondrial morphology. Here, we review current knowledge about the trypanosomal ATP synthase composition and architecture in the context of recent advances in the structural characterization of counterpart enzymes from several eukaryotic supergroups. We also discuss the physiological function of mitochondrial ATP synthases in three trypanosomatid parasites, Trypanosoma cruzi, Trypanosoma brucei and Leishmania, with a focus on their disease-causing life cycle stages. We highlight the reversed proton-pumping role of the ATP synthase in the T. brucei bloodstream form, the enzyme's potential link to the regulation of parasite's glycolysis and its role in generating mitochondrial membrane potential in the absence of mitochondrial DNA.

Human coronavirus NL63 (HCoV-NL63) is an enveloped pathogen of the family Coronaviridae that spreads worldwide and causes up to 10% of all annual respiratory diseases. HCoV-NL63 is typically associated with mild upper respiratory symptoms in children, elderly and immunocompromised individuals. It has also been shown to cause severe lower respiratory illness. NL63 shares ACE2 as a receptor for viral entry with SARS-CoV-1 and SARS-CoV-2. Here, we present the in situ structure of HCoV-NL63 spike (S) trimer at 3.4-Å resolution by single-particle cryo-EM imaging of vitrified virions without chemical fixative. It is structurally homologous to that obtained previously from the biochemically purified ectodomain of HCoV-NL63 S trimer, which displays a three-fold symmetric trimer in a single conformation. In addition to previously proposed and observed glycosylation sites, our map shows density at other sites, as well as different glycan structures. The domain arrangement within a protomer is strikingly different from that of the SARS-CoV-2 S and may explain their different requirements for activating binding to the receptor. This structure provides the basis for future studies of spike proteins with receptors, antibodies or drugs, in the native state of the coronavirus particles.