A minority of final stacks yields superior amplitude in single-particle cryo-EM

Cryo-EM structure of small-molecule agonist bound delta opioid receptor-Gi complex enables discovery of biased compound

Delta opioid receptor (δOR) plays a pivotal role in modulating human sensation and emotion. It is an attractive target for drug discovery since, unlike Mu opioid receptor, it is associated with low risk of drug dependence. Despite its potential applications, the pharmacological properties of δOR, including the mechanisms of activation by small-molecule agonists and the complex signaling pathways it engages, as well as their relation to the potential side effects, remain poorly understood. In this study, we use cryo-electron microscopy (cryo-EM) to determine the structure of the δOR-Gi complex when bound to a small-molecule agonist (ADL5859). Moreover, we design a series of probes to examine the key receptor-ligand interaction site and identify a region involved in signaling bias. Using ADL06 as a chemical tool, we elucidate the relationship between the β-arrestin pathway of the δOR and its biological functions, such as analgesic tolerance and convulsion activities. Notably, we discover that the β-arrestin recruitment of δOR might be linked to reduced gastrointestinal motility. These insights enhance our understanding of δOR's structure, signaling pathways, and biological functions, paving the way for the structure-based drug discovery.

CryoTRANS: predicting high-resolution maps of rare conformations from self-supervised trajectories in cryo-EM

Cryogenic electron microscopy (cryo-EM) has revolutionized structural biology, enabling efficient determination of structures at near-atomic resolutions. However, a common challenge arises from the severe imbalance among various conformations of vitrified particles, leading to low-resolution reconstructions in rare conformations due to a lack of particle images in these quasi-stable states. We introduce CryoTRANS, a method that predicts high-resolution maps of rare conformations by constructing a self-supervised pseudo-trajectory between density maps of varying resolutions. This trajectory is represented by an ordinary differential equation parameterized by a deep neural network, ensuring retention of detailed structures from high-resolution density maps. By leveraging a single high-resolution density map, CryoTRANS significantly improves the reconstruction of rare conformations and has been validated on four real-world datasets: alpha-2-macroglobulin, actin-binding protein complexes, SARS-CoV-2 spike glycoprotein, and the 70S ribosome. CryoTRANS can also predict high-resolution structures in cryogenic electron tomography maps using a high-resolution cryo-EM map.

Structural basis for the transport and substrate selection of human urate transporter 1

High serum urate levels are the major risk factor for gout. URAT1, the primary transporter for urate absorption in the kidneys, is well known as an anti-hyperuricemia drug target. However, the clinical application of URAT1-targeted drugs is limited because of their low specificity and severe side effects. The lack of structural information impedes elucidation of the transport mechanism and the development of new drugs. Here, we present the cryoelectron microscopy (cryo-EM) structures of human URAT1(R477S), its complex with urate, and its closely related homolog OAT4. URAT1(R477S) and OAT4 exhibit major facilitator superfamily (MFS) folds with outward- and inward-open conformations, respectively. Structural comparison reveals a 30° rotation between the N-terminal and C-terminal domains, supporting an alternating access mechanism. A conserved arginine (OAT4-Arg473/URAT1-Arg477) is found to be essential for chloride-mediated inhibition. The URAT1(R477S)-urate complex reveals the specificity of urate recognition. Taken together, our study promotes our understanding of the transport mechanism and substrate selection of URAT1.

Cryo-EM phase-plate images reveal unexpected levels of apparent specimen damage

Apoferritin (apoF) is commonly used as a test specimen in single-particle electron cryo-microscopy (cryo-EM), since it consistently produces density maps that go to 3 Å resolution or higher. When we imaged apoF with a laser phase plate (LPP), however, we observed more severe particle-to-particle variation in the images than we had previously thought to exist. Similarly, we found that images of ribulose bisphosphate carboxylase/oxygenase (rubisco) also exhibited a much greater amount of heterogeneity than expected. By comparison to simulations of images, we verified that the heterogeneity is not explained by the known features of the LPP, shot noise, or differences in particle orientation. We also demonstrate that our specimens are comparable to those previously used in the literature, based on using the final-reconstruction resolution as the metric for evaluation. All of this leads us to the hypothesis that the heterogeneity is due to damage that has occurred either during purification of the specimen or during preparation of the grids. It is not, however, our goal to explain the causes of heterogeneity; rather, we report that using the LPP has made the apparent damage too obvious to be ignored. In hindsight, similar heterogeneity can be seen in images of apoF and the 20S proteasome which others had recorded with a Volta phase plate. We therefore conclude that the increased contrast of phase-plate images (at low spatial frequencies) should also make it possible to visualize, on a single-particle basis, various forms of biologically functional heterogeneity in structure that had previously gone unnoticed.

A minority of final stacks yields superior amplitude in single-particle cryo-EM

Cryogenic electron microscopy (cryo-EM) is widely used to determine near-atomic resolution structures of biological macromolecules. Due to the low signal-to-noise ratio, cryo-EM relies on averaging many images. However, a crucial question in the field of cryo-EM remains unanswered: how close can we get to the minimum number of particles required to reach a specific resolution in practice? The absence of an answer to this question has impeded progress in understanding sample behavior and the performance of sample preparation methods. To address this issue, we develop an iterative particle sorting and/or sieving method called CryoSieve. Extensive experiments demonstrate that CryoSieve outperforms other cryo-EM particle sorting algorithms, revealing that most particles are unnecessary in final stacks. The minority of particles remaining in the final stacks yield superior high-resolution amplitude in reconstructed density maps. For some datasets, the size of the finest subset approaches the theoretical limit.