Moment-based metrics for molecules computable from cryogenic electron microscopy images.

Single-particle cryogenic electron microscopy (cryo-EM) is an imaging technique capable of recovering the high-resolution three-dimensional (3D) structure of biological macromolecules from many noisy and randomly oriented projection images. One notable approach to 3D reconstruction, known as Kam's method, relies on the moments of the two-dimensional (2D) images. Inspired by Kam's method, we introduce a rotationally invariant metric between two molecular structures, which does not require 3D alignment. Further, we introduce a metric between a stack of projection images and a molecular structure, which is invariant to rotations and reflections and does not require performing 3D reconstruction. Additionally, the latter metric does not assume a uniform distribution of viewing angles. We demonstrate the uses of the new metrics on synthetic and experimental datasets, highlighting their ability to measure structural similarity.

Self Fourier shell correlation: properties and application to cryo-ET.

The Fourier shell correlation (FSC) is a measure of the similarity between two signals computed over corresponding shells in the frequency domain and has broad applications in microscopy. In structural biology, the FSC is ubiquitous in methods for validation, resolution determination, and signal enhancement. Computing the FSC usually requires two independent measurements of the same underlying signal, which can be limiting for some applications. Here, we analyze and extend on an approach to estimate the FSC from a single measurement. In particular, we derive the necessary conditions required to estimate the FSC from downsampled versions of a single noisy measurement. These conditions reveal additional corrections which we implement to increase the applicability of the method. We then illustrate two applications of our approach, first as an estimate of the global resolution from a single 3-D structure and second as a data-driven method for denoising tomographic reconstructions in electron cryo-tomography. These results provide general guidelines for computing the FSC from a single measurement and suggest new applications of the FSC in microscopy.

Self Fourier shell correlation: properties and application to cryo-ET.

The Fourier shell correlation (FSC) is a measure of the similarity between two signals computed over corresponding shells in the frequency domain and has broad applications in microscopy. In structural biology, the FSC is ubiquitous in methods for validation, resolution determination, and signal enhancement. Computing the FSC usually requires two independent measurements of the same underlying signal, which can be limiting for some applications. Here, we analyze and extend on an approach proposed by Koho et al. [1] to estimate the FSC from a single measurement. In particular, we derive the necessary conditions required to estimate the FSC from downsampled versions of a single noisy measurement. These conditions reveal additional corrections which we implement to increase the applicability of the method. We then illustrate two applications of our approach, first as an estimate of the global resolution from a single 3-D structure and second as a data-driven method for denoising tomographic reconstructions in electron cryo-tomography. These results provide general guidelines for computing the FSC from a single measurement and suggest new applications of the FSC in microscopy.

The protein organization of a red blood cell.

Red blood cells (RBCs) (erythrocytes) are the simplest primary human cells, lacking nuclei and major organelles and instead employing about a thousand proteins to dynamically control cellular function and morphology in response to physiological cues. In this study, we define a canonical RBC proteome and interactome using quantitative mass spectrometry and machine learning. Our data reveal an RBC interactome dominated by protein homeostasis, redox biology, cytoskeletal dynamics, and carbon metabolism. We validate protein complexes through electron microscopy and chemical crosslinking and, with these data, build 3D structural models of the ankyrin/Band 3/Band 4.2 complex that bridges the spectrin cytoskeleton to the RBC membrane. The model suggests spring-like compression of ankyrin may contribute to the characteristic RBC cell shape and flexibility. Taken together, our study provides an in-depth view of the global protein organization of human RBCs and serves as a comprehensive resource for future research.

Cross-Seeding Controls Aß Fibril Populations and Resulting Functions.

Amyloid peptides nucleate from monomers to aggregate into fibrils through primary nucleation. Pre-existing fibrils can then act as seeds for additional monomers to fibrillize through secondary nucleation. Both nucleation processes occur simultaneously, yielding a distribution of fibril polymorphs that can generate a spectrum of neurodegenerative effects. Understanding the mechanisms driving polymorph structural distribution during both nucleation processes is important for uncovering fibril structure-function relationships, as well as for creating polymorph distributions in vitro that better match fibril structures found in vivo. Here, we explore how cross-seeding wild-type (WT) Aß1-40 with Aß1-40 mutants E22G (Arctic) and E22Δ (Osaka), as well as with WT Aß1-42, affects the distribution of fibril structural polymorphs and how changes in structural distribution impact toxicity. Transmission electron microscopy analysis revealed that fibril seeds derived from mutants of Aß1-40 imparted their structure to WT Aß1-40 monomers during secondary nucleation, but WT Aß1-40 fibril seeds do not affect the structure of fibrils assembled from mutant Aß1-40 monomers, despite the kinetic data indicating accelerated aggregation when cross-seeding of any combination of mutants. Additionally, WT Aß1-40 fibrils seeded with mutant fibrils produced similar structural distributions to the mutant seeds with similar cytotoxicity profiles. This indicates that mutant fibril seeds not only impart their structure to growing WT Aß1-40 aggregates but also impart cytotoxic properties. Our findings establish a relationship between the fibril structure and the phenotype on a polymorph population level and that these properties can be passed on through secondary nucleation to the succeeding generations of fibrils.

Functionalized Mesoporous Silicas Direct Structural Polymorphism of Amyloid-ß Fibrils.

The aggregation of amyloid-ß (Aß) is associated with the onset of Alzheimer's disease (AD) and involves a complex kinetic pathway as monomers self-assemble into fibrils. A central feature of amyloid fibrils is the existence of multiple structural polymorphs, which complicates the development of disease-relevant structure-function relationships. Developing these relationships requires new methods to control fibril structure. In this work, we evaluated the effect that mesoporous silicas (SBA-15) functionalized with hydrophobic (SBA-PFDTS) and hydrophilic groups (SBA-PEG) have on the aggregation kinetics and resulting structure of Aß1-40 fibrils. The hydrophilic SBA-PEG had little effect on amyloid kinetics, while as-synthesized and hydrophobic SBA-PFDTS accelerated aggregation kinetics. Subsequently, we quantified the relative population of fibril structures formed in the presence of each material using electron microscopy. Fibrils formed from Aß1-40 exposed to SBA-PEG were structurally similar to control fibrils. In contrast, Aß1-40 incubated with SBA-15 or SBA-PFDTS formed fibrils with shorter crossover distances that were more structurally representative of fibrils found in AD patient derived samples. Overall, our results suggest that mesoporous silicas and other exogenous materials are promising scaffolds for the de novo production of specific fibril polymorphs of Aß1-40 and other amyloidogenic proteins.

Structural Biology in the Multi-Omics Era.

Rapid developments in cryogenic electron microscopy have opened new avenues to probe the structures of protein assemblies in their near native states. Recent studies have begun applying single -particle analysis to heterogeneous mixtures, revealing the potential of structural-omics approaches that combine the power of mass spectrometry and electron microscopy. Here we highlight advances and challenges in sample preparation, data processing, and molecular modeling for handling increasingly complex mixtures. Such advances will help structural-omics methods extend to cellular-level models of structural biology.

Separating distinct structures of multiple macromolecular assemblies from cryo-EM projections.

Single particle analysis for structure determination in cryo-electron microscopy is traditionally applied to samples purified to near homogeneity as current reconstruction algorithms are not designed to handle heterogeneous mixtures of structures from many distinct macromolecular complexes. We extend on long established methods and demonstrate that relating two-dimensional projection images by their common lines in a graphical framework is sufficient for partitioning distinct protein and multiprotein complexes within the same data set. The feasibility of this approach is first demonstrated on a large set of synthetic reprojections from 35 unique macromolecular structures spanning a mass range of hundreds to thousands of kilodaltons. We then apply our algorithm on cryo-EM data collected from a mixture of five protein complexes and use existing methods to solve multiple three-dimensional structures ab initio. Incorporating methods to sort single particle cryo-EM data from extremely heterogeneous mixtures will alleviate the need for stringent purification and pave the way toward investigation of samples containing many unique structures.

Electron microscopy snapshots of single particles from single cells.

Cryo-electron microscopy (cryo-EM) has become an indispensable tool for structural studies of biological macromolecules. Two additional predominant methods are available for studying the architectures of multiprotein complexes: 1) single-particle analysis of purified samples and 2) tomography of whole cells or cell sections. The former can produce high-resolution structures but is limited to highly purified samples, whereas the latter can capture proteins in their native state but has a low signal-to-noise ratio and yields lower-resolution structures. Here, we present a simple, adaptable method combining microfluidic single-cell extraction with single-particle analysis by EM to characterize protein complexes from individual Caenorhabditis elegans embryos. Using this approach, we uncover 3D structures of ribosomes directly from single embryo extracts. Moreover, we investigated structural dynamics during development by counting the number of ribosomes per polysome in early and late embryos. This approach has significant potential applications for counting protein complexes and studying protein architectures from single cells in developmental, evolutionary, and disease contexts.

Classification of Single Particles from Human Cell Extract Reveals Distinct Structures.

Multi-protein complexes are necessary for nearly all cellular processes, and understanding their structure is required for elucidating their function. Current high-resolution strategies in structural biology are effective but lag behind other fields (e.g., genomics and proteomics) due to their reliance on purified samples rather than heterogeneous mixtures. Here, we present a method combining single-particle analysis by electron microscopy with protein identification by mass spectrometry to structurally characterize macromolecular complexes from human cell extract. We identify HSP60 through two-dimensional classification and obtain three-dimensional structures of native proteasomes directly from ab initio classification of a heterogeneous mixture of protein complexes. In addition, we reveal an ∼1-MDa-size structure of unknown composition and reference our proteomics data to suggest possible identities. Our study shows the power of using a shotgun approach to electron microscopy (shotgun EM) when coupled with mass spectrometry as a tool to uncover the structures of macromolecular machines.