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.

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 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.

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.

An anti-CRISPR that pulls apart a CRISPR-Cas complex.

In biological systems, the activities of macromolecular complexes must sometimes be turned off. Thus, a wide variety of protein inhibitors has evolved for this purpose. These inhibitors function through diverse mechanisms, including steric blocking of crucial interactions, enzymatic modification of key residues or substrates, and perturbation of post-translational modifications1. Anti-CRISPRs-proteins that block the activity of CRISPR-Cas systems-are one of the largest groups of inhibitors described, with more than 90 families that function through diverse mechanisms2-4. Here, we characterize the anti-CRISPR AcrIF25, and we show that it inhibits the type I-F CRISPR-Cas system by pulling apart the fully assembled effector complex. AcrIF25 binds to the predominant CRISPR RNA-binding components of this complex, comprising six Cas7 subunits, and strips them from the RNA. Structural and biochemical studies indicate that AcrIF25 removes one Cas7 subunit at a time, starting at one end of the complex. Notably, this feat is achieved with no apparent enzymatic activity. To our knowledge, AcrIF25 is the first example of a protein that disassembles a large and stable macromolecular complex in the absence of an external energy source. As such, AcrIF25 establishes a paradigm for macromolecular complex inhibitors that may be used for biotechnological applications.

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.

Data-driven regularization lowers the size barrier of cryo-EM structure determination.

Macromolecular structure determination by electron cryo-microscopy (cryo-EM) is limited by the alignment of noisy images of individual particles. Because smaller particles have weaker signals, alignment errors impose size limitations on its applicability. Here, we explore how image alignment is improved by the application of deep learning to exploit prior knowledge about biological macromolecular structures that would otherwise be difficult to express mathematically. We train a denoising convolutional neural network on pairs of half-set reconstructions from the electron microscopy data bank (EMDB) and use this denoiser as an alternative to a commonly used smoothness prior. We demonstrate that this approach, which we call Blush regularization, yields better reconstructions than do existing algorithms, in particular for data with low signal-to-noise ratios. The reconstruction of a protein-nucleic acid complex with a molecular weight of 40 kDa, which was previously intractable, illustrates that denoising neural networks will expand the applicability of cryo-EM structure determination for a wide range of biological macromolecules.

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.

Fluorinated macromolecular amphiphiles as prototypic molecular drones.

The advent of drones has revolutionized various aspects of our lives, and in the realm of biological systems, molecular drones hold immense promise as "magic bullets" for major diseases. Herein, we introduce a unique class of fluorinated macromolecular amphiphiles, designed in the shape of jellyfish, serving as exemplary molecular drones for fluorine-19 MRI (19F MRI) and fluorescence imaging (FLI)-guided drug delivery, status reporting, and targeted cancer therapy. Functioning akin to their mechanical counterparts, these biocompatible molecular drones autonomously assemble with hydrophobic drugs to form uniform nanoparticles, facilitating efficient drug delivery into cells. The status of drug delivery can be tracked through aggregation-induced emission (AIE) of FLI and 19F MRI. Furthermore, when loaded with a heptamethine cyanine fluorescent dye IR-780, these molecular drones enable near-infrared (NIR) FL detection of tumors and precise delivery of the photosensitizer. Similarly, when loaded with doxorubicin (DOX), they enable targeted chemotherapy with fluorescence resonance energy transfer (FRET) FL for real-time status updates, resulting in enhanced therapeutic efficacy. Compared to conventional drug delivery systems, molecular drones stand out for their simplicity, precise structure, versatility, and ability to provide instantaneous status updates. This study presents prototype molecular drones capable of executing fundamental drone functions, laying the groundwork for the development of more sophisticated molecular machines with significant biomedical implications.

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.