Understanding the cell: Future views of structural biology.

Determining the structure and mechanisms of all individual functional modules of cells at high molecular detail has often been seen as equal to understanding how cells work. Recent technical advances have led to a flush of high-resolution structures of various macromolecular machines, but despite this wealth of detailed information, our understanding of cellular function remains incomplete. Here, we discuss present-day limitations of structural biology and highlight novel technologies that may enable us to analyze molecular functions directly inside cells. We predict that the progression toward structural cell biology will involve a shift toward conceptualizing a 4D virtual reality of cells using digital twins. These will capture cellular segments in a highly enriched molecular detail, include dynamic changes, and facilitate simulations of molecular processes, leading to novel and experimentally testable predictions. Transferring biological questions into algorithms that learn from the existing wealth of data and explore novel solutions may ultimately unveil how cells work.

Head-to-Tail Polymerization in the Assembly of Biomolecular Condensates.

Clustering of macromolecules is a fundamental cellular device underlying diverse biological processes that require high-avidity binding to effectors and substrates. Often, this involves a transition between diffuse and locally concentrated molecules akin to biophysical phase separation observable in vitro. One simple mechanistic paradigm underlying physiologically relevant phase transitions in cells is the reversible head-to-tail polymerization of hub proteins into filaments that are cross-linked by dimerization into dynamic three-dimensional molecular condensates. While many diverse folds and motifs can mediate dimerization, only two structurally distinct domains have been discovered so far to undergo head-to-tail polymerization, though these are widespread among all living kingdoms.

Biomolecular condensates at the nexus of cellular stress, protein aggregation disease and ageing.

Biomolecular condensates are membraneless intracellular assemblies that often form via liquid-liquid phase separation and have the ability to concentrate biopolymers. Research over the past 10 years has revealed that condensates play fundamental roles in cellular organization and physiology, and our understanding of the molecular principles, components and forces underlying their formation has substantially increased. Condensate assembly is tightly regulated in the intracellular environment, and failure to control condensate properties, formation and dissolution can lead to protein misfolding and aggregation, which are often the cause of ageing-associated diseases. In this Review, we describe the mechanisms and regulation of condensate assembly and dissolution, highlight recent advances in understanding the role of biomolecular condensates in ageing and disease, and discuss how cellular stress, ageing-related loss of homeostasis and a decline in protein quality control may contribute to the formation of aberrant, disease-causing condensates. Our improved understanding of condensate pathology provides a promising path for the treatment of protein aggregation diseases.

A framework for understanding the functions of biomolecular condensates across scales.

Biomolecular condensates are found throughout eukaryotic cells, including in the nucleus, in the cytoplasm and on membranes. They are also implicated in a wide range of cellular functions, organizing molecules that act in processes ranging from RNA metabolism to signalling to gene regulation. Early work in the field focused on identifying condensates and understanding how their physical properties and regulation arise from molecular constituents. Recent years have brought a focus on understanding condensate functions. Studies have revealed functions that span different length scales: from molecular (modulating the rates of chemical reactions) to mesoscale (organizing large structures within cells) to cellular (facilitating localization of cellular materials and homeostatic responses). In this Roadmap, we discuss representative examples of biochemical and cellular functions of biomolecular condensates from the recent literature and organize these functions into a series of non-exclusive classes across the different length scales. We conclude with a discussion of areas of current interest and challenges in the field, and thoughts about how progress may be made to further our understanding of the widespread roles of condensates in cell biology.

RNA contributions to the form and function of biomolecular condensates.

Biomolecular condensation partitions cellular contents and has important roles in stress responses, maintaining homeostasis, development and disease. Many nuclear and cytoplasmic condensates are rich in RNA and RNA-binding proteins (RBPs), which undergo liquid-liquid phase separation (LLPS). Whereas the role of RBPs in condensates has been well studied, less attention has been paid to the contribution of RNA to LLPS. In this Review, we discuss the role of RNA in biomolecular condensation and highlight considerations for designing condensate reconstitution experiments. We focus on RNA properties such as composition, length, structure, modifications and expression level. These properties can modulate the biophysical features of native condensates, including their size, shape, viscosity, liquidity, surface tension and composition. We also discuss the role of RNA-protein condensates in development, disease and homeostasis, emphasizing how their properties and function can be determined by RNA. Finally, we discuss the multifaceted cellular functions of biomolecular condensates, including cell compartmentalization through RNA transport and localization, supporting catalytic processes, storage and inheritance of specific molecules, and buffering noise and responding to stress.

A validation strategy to assess the role of phase separation as a determinant of macromolecular localization.

Liquid-liquid phase separation (LLPS) of putative assembly scaffolds has been proposed to drive the biogenesis of membraneless compartments. LLPS scaffolds are usually identified through in vitro LLPS assays with single macromolecules (homotypic), but the predictive value of these assays remains poorly characterized. Here, we apply a strategy to evaluate the robustness of homotypic LLPS assays. When applied to the chromosomal passenger complex (CPC), which undergoes LLPS in vitro and localizes to centromeres to promote chromosome biorientation, LLPS propensity in vitro emerged as an unreliable predictor of subcellular localization. In vitro CPC LLPS in aqueous buffers was enhanced by commonly used crowding agents. Conversely, diluted cytomimetic media dissolved condensates of the CPC and of several other proteins. We also show that centromeres do not seem to nucleate LLPS, nor do they promote local, spatially restrained LLPS of the CPC. Our strategy can be adapted to purported LLPS scaffolds of other membraneless compartments.

Bridging structural and cell biology with cryo-electron microscopy.

Most life scientists would agree that understanding how cellular processes work requires structural knowledge about the macromolecules involved. For example, deciphering the double-helical nature of DNA revealed essential aspects of how genetic information is stored, copied and repaired. Yet, being reductionist in nature, structural biology requires the purification of large amounts of macromolecules, often trimmed off larger functional units. The advent of cryogenic electron microscopy (cryo-EM) greatly facilitated the study of large, functional complexes and generally of samples that are hard to express, purify and/or crystallize. Nevertheless, cryo-EM still requires purification and thus visualization outside of the natural context in which macromolecules operate and coexist. Conversely, cell biologists have been imaging cells using a number of fast-evolving techniques that keep expanding their spatial and temporal reach, but always far from the resolution at which chemistry can be understood. Thus, structural and cell biology provide complementary, yet unconnected visions of the inner workings of cells. Here we discuss how the interplay between cryo-EM and cryo-electron tomography, as a connecting bridge to visualize macromolecules in situ, holds great promise to create comprehensive structural depictions of macromolecules as they interact in complex mixtures or, ultimately, inside the cell itself.

Bringing dynamic molecular machines into focus by methyl-TROSY NMR.

Large macromolecular assemblies, so-called molecular machines, are critical to ensuring proper cellular function. Understanding how proper function is achieved at the atomic level is crucial to advancing multiple avenues of biomedical research. Biophysical studies often include X-ray diffraction and cryo-electron microscopy, providing detailed structural descriptions of these machines. However, their inherent flexibility has complicated an understanding of the relation between structure and function. Solution NMR spectroscopy is well suited to the study of such dynamic complexes, and continued developments have increased size boundaries; insights into function have been obtained for complexes with masses as large as 1 MDa. We highlight methyl-TROSY (transverse relaxation optimized spectroscopy) NMR, which enables the study of such large systems, and include examples of applications to several cellular machines. We show how this emerging technique contributes to an understanding of cellular function and the role of molecular plasticity in regulating an array of biochemical activities.

Macromolecular condensation buffers intracellular water potential.

Optimum protein function and biochemical activity critically depends on water availability because solvent thermodynamics drive protein folding and macromolecular interactions1. Reciprocally, macromolecules restrict the movement of 'structured' water molecules within their hydration layers, reducing the available 'free' bulk solvent and therefore the total thermodynamic potential energy of water, or water potential. Here, within concentrated macromolecular solutions such as the cytosol, we found that modest changes in temperature greatly affect the water potential, and are counteracted by opposing changes in osmotic strength. This duality of temperature and osmotic strength enables simple manipulations of solvent thermodynamics to prevent cell death after extreme cold or heat shock. Physiologically, cells must sustain their activity against fluctuating temperature, pressure and osmotic strength, which impact water availability within seconds. Yet, established mechanisms of water homeostasis act over much slower timescales2,3; we therefore postulated the existence of a rapid compensatory response. We find that this function is performed by water potential-driven changes in macromolecular assembly, particularly biomolecular condensation of intrinsically disordered proteins. The formation and dissolution of biomolecular condensates liberates and captures free water, respectively, quickly counteracting thermal or osmotic perturbations of water potential, which is consequently robustly buffered in the cytoplasm. Our results indicate that biomolecular condensation constitutes an intrinsic biophysical feedback response that rapidly compensates for intracellular osmotic and thermal fluctuations. We suggest that preserving water availability within the concentrated cytosol is an overlooked evolutionary driver of protein (dis)order and function.

Electrospray-assisted cryo-EM sample preparation to mitigate interfacial effects.

Addressing interfacial effects during specimen preparation in cryogenic electron microscopy remains challenging. Here we introduce ESI-cryoPrep, a specimen preparation method based on electrospray ionization in native mass spectrometry, designed to alleviate issues associated with protein denaturation or preferred orientation induced by macromolecule adsorption at interfaces. Through fine-tuning spraying parameters, we optimized protein integrity preservation and achieved the desired ice thickness for analyzing target macromolecules. With ESI-cryoPrep, we prepared high-quality cryo-specimens of five proteins and obtained three-dimensional reconstructions at near-atomic resolution. Our findings demonstrate that ESI-cryoPrep effectively confines macromolecules within the middle of the thin layer of amorphous ice, facilitating the preparation of blotting-free vitreous samples. The protective mechanism, characterized by the uneven distribution of charged biomolecules of varying sizes within charged droplets, prevents the adsorption of target biomolecules at air-water or graphene-water interfaces, thereby avoiding structural damage to the protein particles or the introduction of dominant orientation issues.

Discovering optimal kinetic pathways for self-assembly using automatic differentiation.

Macromolecular complexes are often composed of diverse subunits. The self-assembly of these subunits is inherently nonequilibrium and must avoid kinetic traps to achieve high yield over feasible timescales. We show how the kinetics of self-assembly benefits from diversity in subunits because it generates an expansive parameter space that naturally improves the "expressivity" of self-assembly, much like a deeper neural network. By using automatic differentiation algorithms commonly used in deep learning, we searched the parameter spaces of mass-action kinetic models to identify classes of kinetic protocols that mimic biological solutions for productive self-assembly. Our results reveal how high-yield complexes that easily become kinetically trapped in incomplete intermediates can instead be steered by internal design of rate-constants or external and active control of subunits to efficiently assemble. Internal design of a hierarchy of subunit binding rates generates self-assembly that can robustly avoid kinetic traps for all concentrations and energetics, but it places strict constraints on selection of relative rates. External control via subunit titration is more versatile, avoiding kinetic traps for any system without requiring molecular engineering of binding rates, albeit less efficiently and robustly. We derive theoretical expressions for the timescales of kinetic traps, and we demonstrate our optimization method applies not just for design but inference, extracting intersubunit binding rates from observations of yield-vs.-time for a heterotetramer. Overall, we identify optimal kinetic protocols for self-assembly as a powerful mechanism to achieve efficient and high-yield assembly in synthetic systems whether robustness or ease of "designability" is preferred.

OPUS-DSD: deep structural disentanglement for cryo-EM single-particle analysis.

Cryo-electron microscopy (cryo-EM) captures snapshots of dynamic macromolecules, collectively illustrating the involved structural landscapes. This provides an exciting opportunity to explore the structural variations of macromolecules under study. However, traditional cryo-EM single-particle analysis often yields static structures. Here we describe OPUS-DSD, an algorithm capable of efficiently reconstructing the structural landscape embedded in cryo-EM data. OPUS-DSD uses a three-dimensional convolutional encoder-decoder architecture trained with cryo-EM images, thereby encoding structural variations into a smooth and easily analyzable low-dimension space. This space can be traversed to reconstruct continuous dynamics or clustered to identify distinct conformations. OPUS-DSD can offer meaningful insights into the structural variations of macromolecules, filling in the gaps left by traditional cryo-EM structural determination, and potentially improves the reconstruction resolution by reliably clustering similar particles within the dataset. These functionalities are especially relevant to the study of highly dynamic biological systems. OPUS-DSD is available at https://github.com/alncat/opusDSD .

Parallel cryo electron tomography on in situ lamellae.

In situ cryo electron tomography of cryo focused ion beam milled samples has emerged in recent years as a powerful technique for structural studies of macromolecular complexes in their native cellular environment. However, the possibilities for recording tomographic tilt series in a high-throughput manner are limited, in part by the lamella-shaped samples. Here we utilize a geometrical sample model and optical image shift to record tens of tilt series in parallel, thereby saving time and gaining access to sample areas conventionally used for tracking specimen movement. The parallel cryo electron tomography (PACE-tomo) method achieves a throughput faster than 5 min per tilt series and allows for the collection of sample areas that were previously unreachable, thus maximizing the amount of data from each lamella. Performance testing with ribosomes in vitro and in situ on state-of-the-art and general-purpose microscopes demonstrated the high throughput and quality of PACE-tomo.

Integrated multimodality microscope for accurate and efficient target-guided cryo-lamellae preparation.

Cryo-electron tomography (cryo-ET) is a revolutionary technique for resolving the structure of subcellular organelles and macromolecular complexes in their cellular context. However, the application of the cryo-ET is hampered by the sample preparation step. Performing cryo-focused ion beam milling at an arbitrary position on the sample is inefficient, and the target of interest is not guaranteed to be preserved when thinning the cell from several micrometers to less than 300 nm thick. Here, we report a cryogenic correlated light, ion and electron microscopy (cryo-CLIEM) technique that is capable of preparing cryo-lamellae under the guidance of three-dimensional confocal imaging. Moreover, we demonstrate a workflow to preselect and preserve nanoscale target regions inside the finished cryo-lamellae. By successfully preparing cryo-lamellae that contain a single centriole or contact sites between subcellular organelles, we show that this approach is generally applicable, and shall help in innovating more applications of cryo-ET.

TomoTwin: generalized 3D localization of macromolecules in cryo-electron tomograms with structural data mining.

Cryogenic-electron tomography enables the visualization of cellular environments in extreme detail, however, tools to analyze the full amount of information contained within these densely packed volumes are still needed. Detailed analysis of macromolecules through subtomogram averaging requires particles to first be localized within the tomogram volume, a task complicated by several factors including a low signal to noise ratio and crowding of the cellular space. Available methods for this task suffer either from being error prone or requiring manual annotation of training data. To assist in this crucial particle picking step, we present TomoTwin: an open source general picking model for cryogenic-electron tomograms based on deep metric learning. By embedding tomograms in an information-rich, high-dimensional space that separates macromolecules according to their three-dimensional structure, TomoTwin allows users to identify proteins in tomograms de novo without manually creating training data or retraining the network to locate new proteins.

RNA: The Unsuspected Conductor in the Orchestra of Macromolecular Crowding.

This comprehensive Review delves into the chemical principles governing RNA-mediated crowding events, commonly referred to as granules or biological condensates. We explore the pivotal role played by RNA sequence, structure, and chemical modifications in these processes, uncovering their correlation with crowding phenomena under physiological conditions. Additionally, we investigate instances where crowding deviates from its intended function, leading to pathological consequences. By deepening our understanding of the delicate balance that governs molecular crowding driven by RNA and its implications for cellular homeostasis, we aim to shed light on this intriguing area of research. Our exploration extends to the methodologies employed to decipher the composition and structural intricacies of RNA granules, offering a comprehensive overview of the techniques used to characterize them, including relevant computational approaches. Through two detailed examples highlighting the significance of noncoding RNAs, NEAT1 and XIST, in the formation of phase-separated assemblies and their influence on the cellular landscape, we emphasize their crucial role in cellular organization and function. By elucidating the chemical underpinnings of RNA-mediated molecular crowding, investigating the role of modifications, structures, and composition of RNA granules, and exploring both physiological and aberrant phase separation phenomena, this Review provides a multifaceted understanding of the intriguing world of RNA-mediated biological condensates.

High-throughput cryo-ET structural pattern mining by unsupervised deep iterative subtomogram clustering.

Cryoelectron tomography directly visualizes heterogeneous macromolecular structures in their native and complex cellular environments. However, existing computer-assisted structure sorting approaches are low throughput or inherently limited due to their dependency on available templates and manual labels. Here, we introduce a high-throughput template-and-label-free deep learning approach, Deep Iterative Subtomogram Clustering Approach (DISCA), that automatically detects subsets of homogeneous structures by learning and modeling 3D structural features and their distributions. Evaluation on five experimental cryo-ET datasets shows that an unsupervised deep learning based method can detect diverse structures with a wide range of molecular sizes. This unsupervised detection paves the way for systematic unbiased recognition of macromolecular complexes in situ.

Ab initio phasing macromolecular structures using electron-counted MicroED data.

Structures of two globular proteins were determined ab initio using microcrystal electron diffraction (MicroED) data that were collected on a direct electron detector in counting mode. Microcrystals were identified using a scanning electron microscope (SEM) and thinned with a focused ion beam (FIB) to produce crystalline lamellae of ideal thickness. Continuous-rotation data were collected using an ultra-low exposure rate to enable electron counting in diffraction. For the first sample, triclinic lysozyme extending to a resolution of 0.87 Å, an ideal helical fragment of only three alanine residues provided initial phases. These phases were improved using density modification, allowing the entire atomic structure to be built automatically. A similar approach was successful on a second macromolecular sample, proteinase K, which is much larger and diffracted to a resolution of 1.5 Å. These results demonstrate that macromolecules can be determined to sub-ångström resolution by MicroED and that ab initio phasing can be successfully applied to counting data.