Electron microscopy has been an important method for visualising biological structures and processes since the 1940s. The discovery of a practical vitreous-ice specimen-preparation technique in the mid-1980s [Adrian 1984] led to modern-day Cryogenic Electron Microscopy (Cryo-EM) which in recent years has become a major technique for studying the architecture of biological macromolecules. Many further instrumental and data-analysis improvements were established in the decades after the introduction of the “vitreous-ice” state of water. Especially the advent of direct electron detectors boosted the quality of the recorded data, allowing atomic-resolution information of biological complexes to be harvested in the early 2010s, developments that truly revolutionized the use of Cryo-EM in structural biology. Single-Particle Analysis (SPA) of isolated molecules, prepared in a thin layer of vitreous water, has proven a most successful approach in structural biology and now often supplants the use of classical techniques like X-ray crystallography, especially for large biological complexes. The ever-increasing number of researchers using Cryo-EM is reflected by the growing number of depositions in the Electron Microscopy Data Bank (EMDB). Explaining this methodology to a new generation of researchers has now become a priority. In writing this review we were reminded of some persistent confusions that emerged in the early days of Cryo-EM but that continue to muddle the field. A new problem with the prolific use of Graphic User Interfaces (GUIs), is that the underlying methodology is often no longer transparent to the users of these “black boxes”. Complicated procedures, well hidden behind a GUI window, may contain methodological flaws that the user must be aware of. The conquering of markets in this booming Cryo-EM field – crucial for developing new pharmaceuticals – must not prevail over scientific integrity. We here describe and critically review the principles of single-particle Cryo-EM. We warn for procedures that have gone astray and could generate serious problems especially in the quality-control of Single-Particle Cryogenic Electron Microscopy.

Bifidobacteria are early colonizers of the human gut and play central roles in human health and metabolism. To thrive in this competitive niche, these bacteria evolved the capacity to use complex carbohydrates, including mammalian N -glycans. Herein, we elucidated pivotal biochemical steps involved in high-mannose N -glycan utilization by Bifidobacterium longum . After N -glycan release by an endo-β- N -acetylglucosaminidase, the mannosyl arms are trimmed by the cooperative action of three functionally distinct glycoside hydrolase 38 (GH38) α-mannosidases and a specific GH125 α-1,6-mannosidase. High-resolution cryo-electron microscopy structures revealed that bifidobacterial GH38 α-mannosidases form homotetramers, with the N-terminal jelly roll domain contributing to substrate selectivity. Additionally, an α-glucosidase enables the processing of monoglucosylated N -glycans. Notably, the main degradation product, mannose, is isomerized into fructose before phosphorylation, an unconventional metabolic route connecting it to the bifid shunt pathway. These findings shed light on key molecular mechanisms used by bifidobacteria to use high-mannose N -glycans, a perennial carbon and energy source in the intestinal lumen.

In order to form functional filaments, human septins must assemble into hetero-oligomeric rod-like particles which polymerize end-to-end. The rules governing the assembly of these particles and the subsequent filaments are incompletely understood. Although crystallographic approaches have been successful in studying the separate components of the system, there has been difficulty in obtaining high resolution structures of the full particle. Here we report a first cryo-EM structure for a hexameric rod composed of human septins 2, 6 and 7 with a global resolution of similar to 3.6 angstrom and a local resolution of between similar to 3.0 angstrom and similar to 5.0 angstrom. By fitting the previously determined high-resolution crystal structures of the component subunits into the cryo-EM map, we are able to provide an essentially complete model for the particle. This exposes SEPT2 NC-interfaces at the termini of the hexamer and leaves internal cavities between the SEPT6-SEPT7 pairs. The floor of the cavity is formed by the two alpha(0) helices including their polybasic regions. These are locked into place between the two subunits by interactions made with the alpha(5) and alpha(6) helices of the neighbouring monomer together with its polyacidic region. The cavity may serve to provide space allowing the subunits to move with respect to one another. The elongated particle shows a tendency to bend at its centre where two copies of SEPT7 form a homodimeric G-interface. Such bending is almost certainly related to the ability of septin filaments to recognize and even induce membrane curvature. (C) 2021 Elsevier Ltd. All rights reserved.

Haemocyanins (Hcs) are copper-containing, respiratory proteins that occur in the haemolymph of many arthropod species. Here, we report the presence of Hcs in the chilopode Myriapoda, demonstrating that these proteins are more widespread among the Arthropoda than previously thought. The analysis of transcriptome of S. subspinipes subpinipes reveals the presence of two distinct subunits of Hc, where the signal peptide is present, and six of prophenoloxidase (PPO), where the signal peptide is absent, in the 75 kDa range. Size exclusion chromatography profiles indicate different quaternary organization for Hc of both species, which was corroborated by TEM analysis: S. viridicornis Hc is a 6 × 6-mer and S. subspinipes Hc is a 3 × 6-mer, which resembles the half-structure of the 6 × 6-mer but also includes the presence of phenoloxidases, since the 1 × 6-mer quaternary organization is commonly associated with hexamers of PPO. Studies with Chelicerata showed that PPO activity are exclusively associated with the Hcs. This study indicates that Scolopendra may have different proteins playing oxygen transport (Hc) and PO function, both following the hexameric oligomerization observed in Hcs.

In recent years, cryogenic electron microscopy (Cryo-EM) has revolutionized the structure determination of wet samples and especially that of biological macromolecules. The glassy-water medium in which the molecules are embedded is considered an almost in vivo environment for biological samples. The local structure of amorphous ice is known from neutron- and X-ray-diffraction studies, techniques appropriate for much larger volumes than those used in cryo-EM. We here present a first study of the pair-distribution function g(r) of glassy water under cryo-EM conditions using electron diffraction data. We found g(r) to be between that of low-density amorphous ice and that of supercooled water. Under electron exposure, cubic-ice regions were found to nucleate in thicker glassy-water samples. Our work enables to obtain quantitative structural information using g(r) from cryo-EM.

We are currently facing an avalanche of cryo-EM (cryogenic Electron Microscopy) publications presenting beautiful structures at resolution levels of ~3Å: a true “resolution revolution” [Kühlbrandt, Science 343(2014)1443-1444]. Impressive as these results may be, a fundamental statistical error has persisted in the literature that affects the numerical resolution values for practically all published structures. The error goes back to a misinterpretation of basic statistics and pervades virtually all popular cryo-EM quality metrics . The resolution in cryo-EM is typically assessed by the Fourier Shell Correlation “FSC” [Harauz & van Heel: Optik 73 (1986)146-156] using a fixed threshold value of 0.143 (“FSC0.143”) [Rosenthal, Henderson, J. Mol. Biol. 333 (2003)721–745]. Using a simple model experiment we illustrate why this fixed threshold is flawed and we pinpoint the source of the resolution confusion. When two vectors are uncorrelated the expectation value of their inner-product is zero. That, however, does not imply that each individual inner-product of the vectors is zero (the vectors are not orthogonal ). This error was introduced to electron microscopy in [Frank & Al-Ali, Nature 256 (1975)376-379] and has since proliferated into virtually all quality and resolution-related metrics in EM. One criterion not affected by this error is the information-based ½-bit FSC threshold [van Heel & Schatz: J. Struct. Biol. 151 (2005)250-262].

Single-particle cryogenic electron microscopy (cryo-EM) can now yield near-atomic resolution structures of biological complexes. However, the reference-based alignment algorithms commonly used in cryo-EM suffer from reference bias, limiting their applicability (also known as the `Einstein from random noise' problem). Low-dose cryo-EM therefore requires robust and objective approaches to reveal the structural information contained in the extremely noisy data, especially when dealing with small structures. A reference-free pipeline is presented for obtaining near-atomic resolution three-dimensional reconstructions from heterogeneous (`four-dimensional') cryo-EM data sets. The methodologies integrated in this pipeline include a posteriori camera correction, movie-based full-data-set contrast transfer function determination, movie-alignment algorithms, (Fourier-space) multivariate statistical data compression and unsupervised classification, `random-startup' three-dimensional reconstructions, four-dimensional structural refinements and Fourier shell correlation criteria for evaluating anisotropic resolution. The procedures exclusively use information emerging from the data set itself, without external `starting models'. Euler-angle assignments are performed by angular reconstitution rather than by the inherently slower projection-matching approaches. The comprehensive `ABC-4D' pipeline is based on the two-dimensional reference-free `alignment by classification' (ABC) approach, where similar images in similar orientations are grouped by unsupervised classification. Some fundamental differences between X-ray crystallography versus single-particle cryo-EM data collection and data processing are discussed. The structure of the giant haemoglobin from Lumbricus terrestris at a global resolution of ∼3.8 Å is presented as an example of the use of the ABC-4D procedure.

The structure of the infectious prion protein (PrPSc), which is responsible for Creutzfeldt-Jakob disease in humans and bovine spongiform encephalopathy, has escaped all attempts at elucidation due to its insolubility and propensity to aggregate. PrPSc replicates by converting the non-infectious, cellular prion protein (PrPC) into the misfolded, infectious conformer through an unknown mechanism. PrPSc and its N-terminally truncated variant, PrP 27-30, aggregate into amorphous aggregates, 2D crystals, and amyloid fibrils. The structure of these infectious conformers is essential to understanding prion replication and the development of structure-based therapeutic interventions. Here we used the repetitive organization inherent to GPI-anchorless PrP 27-30 amyloid fibrils to analyze their structure via electron cryomicroscopy. Fourier-transform analyses of averaged fibril segments indicate a repeating unit of 19.1 Å. 3D reconstructions of these fibrils revealed two distinct protofilaments, and, together with a molecular volume of 18,990 Å3, predicted the height of each PrP 27-30 molecule as ~17.7 Å. Together, the data indicate a four-rung β-solenoid structure as a key feature for the architecture of infectious mammalian prions. Furthermore, they allow to formulate a molecular mechanism for the replication of prions. Knowledge of the prion structure will provide important insights into the self-propagation mechanisms of protein misfolding.

Biology is a challenging and complicated mess. Understanding this challenging complexity is the realm of the biological sciences: Trying to make sense of the massive, messy data in terms of discovering patterns and revealing its underlying general rules. Among the most powerful mathematical tools for organizing and helping to structure complex, heterogeneous and noisy data are the tools provided by multivariate statistical analysis (MSA) approaches. These eigenvector/eigenvalue data-compression approaches were first introduced to electron microscopy (EM) in 1980 to help sort out different views of macromolecules in a micrograph. After 35 years of continuous use and developments, new MSA applications are still being proposed regularly. The speed of computing has increased dramatically in the decades since their first use in electron microscopy. However, we have also seen a possibly even more rapid increase in the size and complexity of the EM data sets to be studied. MSA computations had thus become a very serious bottleneck limiting its general use. The parallelization of our programs—speeding up the process by orders of magnitude—has opened whole new avenues of research. The speed of the automatic classification in the compressed eigenvector space had also become a bottleneck which needed to be removed. In this paper we explain the basic principles of multivariate statistical eigenvector-eigenvalue data compression; we provide practical tips and application examples for those working in structural biology, and we provide the more experienced researcher in this and other fields with the formulas associated with these powerful MSA approaches.