New measures of anisotropy of cryo-EM maps

Overcoming the preferred orientation problem in cryoEM with self-supervised deep-learning

While advances in single-particle cryoEM have enabled the structural determination of macromolecular complexes at atomic resolution, particle orientation bias (the so-called "preferred" orientation problem) remains a complication for most specimens. Existing solutions have relied on biochemical and physical strategies applied to the specimen and are often complex and challenging. Here, we develop spIsoNet, an end-to-end self-supervised deep-learning-based software to address the preferred orientation problem. Using preferred-orientation views to recover molecular information in under-sampled views, spIsoNet improves both angular isotropy and particle alignment accuracy during 3D reconstruction. We demonstrate spIsoNet's capability of generating near-isotropic reconstructions from representative biological systems with limited views, including ribosomes, β-galactosidases, and a previously intractable hemagglutinin trimer dataset. spIsoNet can also be generalized to improve map isotropy and particle alignment of preferentially oriented molecules in subtomogram averaging. Therefore, without additional specimen-preparation procedures, spIsoNet provides a general computational solution to the preferred orientation problem.

Cryo-EM Map Anisotropy Can Be Attenuated by Map Post-Processing and a New Method for Its Estimation

One of the most important challenges in cryogenic electron microscopy (cryo-EM) is the substantial number of samples that exhibit preferred orientations, which leads to an uneven coverage of the projection sphere. As a result, the overall quality of the reconstructed maps can be severely affected, as manifested by the presence of anisotropy in the map resolution. Several methods have been proposed to measure the directional resolution of maps in tandem with experimental protocols to address the problem of preferential orientations in cryo-EM. Following these works, in this manuscript we identified one potential limitation that may affect most of the existing methods and we proposed an alternative approach to evaluate the presence of preferential orientations in cryo-EM reconstructions. In addition, we also showed that some of the most recently proposed cryo-EM map post-processing algorithms can attenuate map anisotropy, thus offering alternative visualization opportunities for cases affected by moderate levels of preferential orientations.

Optimizing cryo-EM structural analysis of Gi-coupling receptors via engineered Gt and Nb35 application

Cryo-EM single particle analysis has recently facilitated the high-resolution structural determination of numerous GPCR-G complexes. Diverse methodologies have been devised with this trend, and in the case of GPCR-Gi complexes, scFv16, an antibody that recognizes the intricate interface of the complex, has been mainly implemented to stabilize the complex. However, owing to their flexibility and heterogeneity, structural determinations of GPCR-Gi complexes remain both challenging and resource-intensive. By employing eGαt, which exhibits binding affinity to modified nanobody Nb35, the cryo-EM structure of Rhodopsin-eGαt complex was previously reported. Using this modified G protein, we determined the structure of the ETB-eGt complex bound to the modified Nb35. The determined structure of ETB receptor was the same as the previously reported ETB-Gi complex, and the resulting dataset demonstrated significantly improved anisotropy. This modified G protein will be utilized for the structural determination of other GPCR-Gi complexes.

The PfRCR complex bridges malaria parasite and erythrocyte during invasion

The symptoms of malaria occur during the blood stage of infection, when parasites invade and replicate within human erythrocytes. The PfPCRCR complex1, containing PfRH5 (refs. 2,3), PfCyRPA, PfRIPR, PfCSS and PfPTRAMP, is essential for erythrocyte invasion by the deadliest human malaria parasite, Plasmodium falciparum. Invasion can be prevented by antibodies3-6 or nanobodies1 against each of these conserved proteins, making them the leading blood-stage malaria vaccine candidates. However, little is known about how PfPCRCR functions during invasion. Here we present the structure of the PfRCR complex7,8, containing PfRH5, PfCyRPA and PfRIPR, determined by cryogenic-electron microscopy. We test the hypothesis that PfRH5 opens to insert into the membrane9, instead showing that a rigid, disulfide-locked PfRH5 can mediate efficient erythrocyte invasion. We show, through modelling and an erythrocyte-binding assay, that PfCyRPA-binding antibodies5 neutralize invasion through a steric mechanism. We determine the structure of PfRIPR, showing that it consists of an ordered, multidomain core flexibly linked to an elongated tail. We also show that the elongated tail of PfRIPR, which is the target of growth-neutralizing antibodies6, binds to the PfCSS-PfPTRAMP complex on the parasite membrane. A modular PfRIPR is therefore linked to the merozoite membrane through an elongated tail, and its structured core presents PfCyRPA and PfRH5 to interact with erythrocyte receptors. This provides fresh insight into the molecular mechanism of erythrocyte invasion and opens the way to new approaches in rational vaccine design.

Quantitatively mapping local quality of super-resolution microscopy by rolling Fourier ring correlation

In fluorescence microscopy, computational algorithms have been developed to suppress noise, enhance contrast, and even enable super-resolution (SR). However, the local quality of the images may vary on multiple scales, and these differences can lead to misconceptions. Current mapping methods fail to finely estimate the local quality, challenging to associate the SR scale content. Here, we develop a rolling Fourier ring correlation (rFRC) method to evaluate the reconstruction uncertainties down to SR scale. To visually pinpoint regions with low reliability, a filtered rFRC is combined with a modified resolution-scaled error map (RSM), offering a comprehensive and concise map for further examination. We demonstrate their performances on various SR imaging modalities, and the resulting quantitative maps enable better SR images integrated from different reconstructions. Overall, we expect that our framework can become a routinely used tool for biologists in assessing their image datasets in general and inspire further advances in the rapidly developing field of computational imaging.