ScipionTomo: Towards cryo-electron tomography software integration, reproducibility, and validation.

Image processing in cryogenic electron tomography (cryoET) is currently at a similar state as Single Particle Analysis (SPA) in cryogenic electron microscopy (cryoEM) was a few years ago. Its data processing workflows are far from being well defined and the user experience is still not smooth. Moreover, file formats of different software packages and their associated metadata are not standardized, mainly since different packages are developed by different groups, focusing on different steps of the data processing pipeline. The Scipion framework, originally developed for SPA (de la Rosa-Trevín et al., 2016), has a generic python workflow engine that gives it the versatility to be extended to other fields, as demonstrated for model building (Martínez et al., 2020). In this article, we provide an extension of Scipion based on a set of tomography plugins (referred to as ScipionTomo hereafter), with a similar purpose: to allow users to be focused on the data processing and analysis instead of having to deal with multiple software installation issues and the inconvenience of switching from one to another, converting metadata files, managing possible incompatibilities, scripting (writing a simple program in a language that the computer must convert to machine language each time the program is run), etcetera. Additionally, having all the software available in an integrated platform allows comparing the results of different algorithms trying to solve the same problem. In this way, the commonalities and differences between estimated parameters shed light on which results can be more trusted than others. ScipionTomo is developed by a collaborative multidisciplinary team composed of Scipion team engineers, structural biologists, and in some cases, the developers whose software packages have been integrated. It is open to anyone in the field willing to contribute to this project. The result is a framework extension that combines the acquired knowledge of Scipion developers in close collaboration with third-party developers, and the on-demand design of functionalities requested by beta testers applying this solution to actual biological problems.

Algorithmic robustness to preferred orientations in single particle analysis by CryoEM.

The presence of preferred orientations in single particle analysis (SPA) by cryo-Electron Microscopy (cryoEM) is currently one of the hurdles preventing many structural analyses from yielding high-resolution structures. Although the existence of preferred orientations is mostly related to the grid preparation, in this technical note, we show that some image processing algorithms used for angular assignment and three-dimensional (3D) reconstruction are more robust than others to these detrimental conditions. We exemplify this argument with three different data sets in which the presence of preferred orientations hindered achieving a 3D reconstruction without artifacts or, even worse, a 3D reconstruction could never be achieved.

Low Expression of ICAM-1 in Blood Eosinophils in Patients With Active Eosinophilic Esophagitis.

BACKGROUND AND OBJECTIVE: Eosinophilic esophagitis (EoE) is a chronic and isolated inflammation of the esophagus characterized by a marked infiltration of eosinophilic leukocytes. Diagnosis and course of the disease are based exclusively on histopathology. Therefore, patients must undergo several esophageal biopsies, implying a risk associated with the procedure and considerable use of resources. Objective: The presence of active circulating eosinophils, which are quantifiable through the expression of specific cellular activation proteins in their membrane, could be consistent with histopathological findings, which are currently the only valid parameters in studies on EoE. METHODS: The activity of peripheral blood eosinophils from patients with EoE was analyzed by identifying 5 surface molecules (CD69, IL- 5Rα, CD44, ICAM-1, CD63), which are seen to be expressed by the active eosinophils in flow cytometry. The results were compared with the infiltrate of eosinophils present in patients' esophageal biopsies. RESULTS: ICAM-1 levels decreased significantly in patients with active EoE compared with nonactive EoE patients, allergic patients, and healthy controls. In patients with EoE, an inverse correlation was observed between the number of eosinophils in the esophageal biopsy and the percentage of ICAM-1 expression in peripheral blood eosinophils. No differences were observed for the remaining molecules studied. CONCLUSION: Expression of ICAM-1 in blood eosinophils could be a useful noninvasive marker for the diagnosis and assessment of patients with EoE.

Re-examining the spectra of macromolecules. Current practice of spectral quasi B-factor flattening.

The analysis of structure factors in 3D cryo-EM Coulomb potential maps and their "enhancement" at the end of the reconstruction process is a well-established practice, normally referred to as sharpening. The aim is to increase contrast and, in this way, to help tracing the atomic model. The most common way to accomplish this enhancement is by means of the so-called B-factor correction, which applies a global filter to boost high frequencies with some dampening considerations related to noise amplification. The results are maps with a better visual aspect and a quasiflat spectrum at medium and high frequencies. This practice is so widespread that most map depositions in the Electron Microscopy Data Base (EMDB) only contain sharpened maps. Here, the use in cryoEM of global B-factor corrections is theoretically and experimentally analyzed. Results clearly illustrate that protein spectra present a falloff. Thus, spectral quasi-flattening may produce protein spectra with distortions when compared with experimental ones, this fact, combined with the practice of reporting only sharpened maps, generates a sub-optimal situation in terms of data preservation, reuse and reproducibility. Now that the field is more advanced, we put forward two suggestions: (1) to use methods which keep more faithfully the original experimental signal properties of macromolecules when "enhancing" the map, and (2) to further stress the need to deposit the original experimental maps without any postprocessing or sharpening, not only the enhanced maps. In the absence of access to these original maps data is lost, preventing their future analysis with new methods.

Integration of Cryo-EM Model Building Software in Scipion.

Advances in cryo-electron microscopy (cryo-EM) have made it possible to obtain structures of large biological macromolecules at near-atomic resolution. This "resolution revolution" has encouraged the use and development of modeling tools able to produce high-quality atomic models from cryo-EM density maps. Unfortunately, many practical problems appear when combining different packages in the same processing workflow, which make difficult the use of these tools by non-experts and, therefore, reduce their utility. We present here a major extension of the image processing framework Scipion that provides inter-package integration in the model building area and full tracking of the complete workflow, from image processing to structure validation.

Blind estimation of DED camera gain in Electron Microscopy.

The introduction of Direct Electron Detector (DED) videos in the Electron Microscope field has boosted Single Particle Analysis to a point in which it is currently considered to be a key technique in Structural Biology. In this article we introduce an approach to estimate the DED camera gain at each pixel from the movies themselves. This gain is needed to have the set of recorded frames into a coherent gray level range, homogeneous over the whole image. The algorithm does not need any other input than the DED movie itself, being capable of providing an estimate of the camera gain image, helping to identify dead pixels and cases of incorrectly calibrated cameras. We propose the algorithm to be used either to validate the experimentally acquired gain image (for instance, to follow its possible change over time) or to verify that there is no residual gain image after experimentally correcting for the camera gain. We show results for a number of DED camera models currently in use (DE, Falcon II, Falcon 3, and K2).

A new algorithm for high-resolution reconstruction of single particles by electron microscopy.

The Map Challenge organized by the Electron Microscopy Data Bank has prompted the development of an Xmipp high resolution reconstruction protocol (which we will refer to as highres) that is integrated in the software platform Scipion. In this work we describe the details of the image angular alignment and map reconstruction steps in our new method. This algorithm is similar to the standard projection matching approach with some important modifications, especially in the area of detecting significant features in the reconstructed volume. We show that the new method is able to produce higher resolution maps than the current de facto standard as measured by the Fourier Shell Correlation, the Monogenic Local Resolution and EMRinger.

Using Scipion for stream image processing at Cryo-EM facilities.

Three dimensional electron microscopy is becoming a very data-intensive field in which vast amounts of experimental images are acquired at high speed. To manage such large-scale projects, we had previously developed a modular workflow system called Scipion (de la Rosa-Trevín et al., 2016). We present here a major extension of Scipion that allows processing of EM images while the data is being acquired. This approach helps to detect problems at early stages, saves computing time and provides users with a detailed evaluation of the data quality before the acquisition is finished. At present, Scipion has been deployed and is in production mode in seven Cryo-EM facilities throughout the world.

Denoising of high-resolution single-particle electron-microscopy density maps by their approximation using three-dimensional Gaussian functions.

Cryo-electron microscopy (cryo-EM) of frozen-hydrated preparations of isolated macromolecular complexes is the method of choice to obtain the structure of complexes that cannot be easily studied by other experimental methods due to their flexibility or large size. An increasing number of macromolecular structures are currently being obtained at subnanometer resolution but the interpretation of structural details in such EM-derived maps is often difficult because of noise at these high-frequency signal components that reduces their contrast. In this paper, we show that the method for EM density-map approximation using Gaussian functions can be used for denoising of single-particle EM maps of high (typically subnanometer) resolution. We show its denoising performance using simulated and experimental EM density maps of several complexes.

Fast and automatic identification of particle tilt pairs based on Delaunay triangulation.

Random conical tilt (RCT) and orthogonal tilt reconstruction (OTR) are two remarkable methods for reconstructing the three-dimensional structure of macromolecules at low resolution. These techniques use two images at two different sample tilts. One of the most demanding steps in these methods at the image processing level is to identify corresponding particles on both micrographs, and manual or semiautomatic matching methods are usually used. Here we present an approach to solve this bottleneck with a fully automatic method for assigning particle tilt pairs. This new algorithm behaves correctly with a variety of samples, covering the range from small to large macromolecules and from sparse to densely populated fields of view. It is also more rapid than previous approaches. The roots of the method lie in a Delaunay triangulation of the set of independently picked coordinates on both the untilted and tilted micrographs. These triangulations are then used to search an affine transformation between the untilted and tilted triangles. The affine transformation that maximizes the number of correspondences between the two micrographs defines the coordinate matching.

Local analysis of strains and rotations for macromolecular electron microscopy maps.

Macromolecular complexes perform their physiological functions by local rearrangements of their constituents and biochemically interacting with their reaction partners. These rearrangements may involve local rotations and the induction of local strains causing different mechanical efforts and stretches at the different areas of the protein. The analysis of these local deformations may reveal important insight into the way proteins perform their tasks. In this paper we introduce a method to perform this kind of local analysis using Electron Microscopy volumes in a fully objective and automatic manner. For doing so, we exploit the continuous nature of the result of an elastic image registration using B-splines as its basis functions. We show that the results obtained by the new automatic method are consistent with previous observations on these macromolecules.

Characterization of hospitalized patients with acute kidney injury associated with COVID-19 in Spain: renal replacement therapy and mortality. FRA-COVID SEN Registry Data.

BACKGROUND: Acute kidney injury (AKI) is common among hospitalized patients with COVID-19 and associated with worse prognosis. The Spanish Society of Nephrology created the AKI- COVID Registry to characterize the population admitted for COVID-19 that developed AKI in Spanish hospitals. The need of renal replacement therapy (RRT) therapeutic modalities, and mortality in these patients were assessed MATERIAL AND METHOD: In a retrospective study, we analyzed data from the AKI-COVID Registry, which included patients hospitalized in 30 Spanish hospitals from May 2020 to November 2021. Clinical and demographic variables, factors related to the severity of COVID-19 and AKI, and survival data were recorded. A multivariate regression analysis was performed to study factors related to RRT and mortality. RESULTS: Data from 730 patients were recorded. A total of 71.9% were men, with a mean age of 70 years (60-78), 70.1% were hypertensive, 32.9% diabetic, 33.3% with cardiovascular disease and 23.9% had some degree of chronic kidney disease (CKD). Pneumonia was diagnosed in 94.6%, requiring ventilatory support in 54.2% and admission to the ICU in 44.1% of cases. The median time from the onset of COVID-19 symptoms to the appearance of AKI (37.1% KDIGO I, 18.3% KDIGO II, 44.6% KDIGO III) was 6 days (4-10). A total of 235 (33.9%) patients required RRT: 155 patients with continuous renal replacement therapy, 89 alternate-day dialysis, 36 daily dialysis, 24 extended hemodialysis and 17 patients with hemodiafiltration. Smoking habit (OR 3.41), ventilatory support (OR 20.2), maximum creatinine value (OR 2.41), and time to AKI onset (OR 1.13) were predictors of the need for RRT; age was a protective factor (0.95). The group without RRT was characterized by older age, less severe AKI, and shorter kidney injury onset and recovery time (p < 0.05). 38.6% of patients died during hospitalization; serious AKI and RRT were more frequent in the death group. In the multivariate analysis, age (OR 1.03), previous chronic kidney disease (OR 2.21), development of pneumonia (OR 2.89), ventilatory support (OR 3.34) and RRT (OR 2.28) were predictors of mortality while chronic treatment with ARBs was identified as a protective factor (OR 0.55). CONCLUSIONS: Patients with AKI during hospitalization for COVID-19 had a high mean age, comorbidities and severe infection. We defined two different clinical patterns: an AKI of early onset, in older patients that resolves in a few days without the need for RRT; and another more severe pattern, with greater need for RRT, and late onset, which was related to greater severity of the infectious disease. The severity of the infection, age and the presence of CKD prior to admission were identified as a risk factors for mortality in these patients. In addition chronic treatment with ARBs was identified as a protective factor for mortality.

Scipion Flexibility Hub: an integrative framework for advanced analysis of conformational heterogeneity in cryoEM.

Understanding how structure and function meet to drive biological processes is progressively shifting the cryoEM field towards a more advanced analysis of macromolecular flexibility. Thanks to techniques such as single-particle analysis and electron tomography, it is possible to image a macromolecule in different states, information that can subsequently be extracted through advanced image-processing methods to build a richer approximation of a conformational landscape. However, the interoperability of all of these algorithms remains a challenging task that is left to users, preventing them from defining a single flexible workflow in which conformational information can be addressed by different algorithms. Therefore, in this work, a new framework integrated into Scipion is proposed called the Flexibility Hub. This framework automatically handles intercommunication between different heterogeneity software, simplifying the task of combining the software into workflows in which the quality and the amount of information extracted from flexibility analysis is maximized.

On bias, variance, overfitting, gold standard and consensus in single-particle analysis by cryo-electron microscopy.

Cryo-electron microscopy (cryoEM) has become a well established technique to elucidate the 3D structures of biological macromolecules. Projection images from thousands of macromolecules that are assumed to be structurally identical are combined into a single 3D map representing the Coulomb potential of the macromolecule under study. This article discusses possible caveats along the image-processing path and how to avoid them to obtain a reliable 3D structure. Some of these problems are very well known in the community. These may be referred to as sample-related (such as specimen denaturation at interfaces or non-uniform projection geometry leading to underrepresented projection directions). The rest are related to the algorithms used. While some have been discussed in depth in the literature, such as the use of an incorrect initial volume, others have received much less attention. However, they are fundamental in any data-analysis approach. Chiefly among them, instabilities in estimating many of the key parameters that are required for a correct 3D reconstruction that occur all along the processing workflow are referred to, which may significantly affect the reliability of the whole process. In the field, the term overfitting has been coined to refer to some particular kinds of artifacts. It is argued that overfitting is a statistical bias in key parameter-estimation steps in the 3D reconstruction process, including intrinsic algorithmic bias. It is also shown that common tools (Fourier shell correlation) and strategies (gold standard) that are normally used to detect or prevent overfitting do not fully protect against it. Alternatively, it is proposed that detecting the bias that leads to overfitting is much easier when addressed at the level of parameter estimation, rather than detecting it once the particle images have been combined into a 3D map. Comparing the results from multiple algorithms (or at least, independent executions of the same algorithm) can detect parameter bias. These multiple executions could then be averaged to give a lower variance estimate of the underlying parameters.

Cryo-EM and Single-Particle Analysis with Scipion.

Cryo-electron microscopy has become one of the most important tools in biological research to reveal the structural information of macromolecules at near-atomic resolution. In single-particle analysis, the vitrified sample is imaged by an electron beam and the detectors at the end of the microscope column produce movies of that sample. These movies contain thousands of images of identical particles in random orientations. The data need to go through an image processing workflow with multiple steps to obtain the final 3D reconstructed volume. The goal of the image processing workflow is to identify the acquisition parameters to be able to reconstruct the specimen under study. Scipion provides all the tools to create this workflow using several image processing packages in an integrative framework, also allowing the traceability of the results. In this article the whole image processing workflow in Scipion is presented and discussed with data coming from a real test case, giving all the details necessary to go from the movies obtained by the microscope to a high resolution final 3D reconstruction. Also, the power of using consensus tools that allow combining methods, and confirming results along every step of the workflow, improving the accuracy of the obtained results, is discussed.

A clustering approach to multireference alignment of single-particle projections in electron microscopy.

Two-dimensional analysis of projections of single-particles acquired by an electron microscope is a useful tool to help identifying the different kinds of projections present in a dataset and their different projection directions. Such analysis is also useful to distinguish between different kinds of particles or different particle conformations. In this paper we introduce a new algorithm for performing two-dimensional multireference alignment and classification that is based on a Hierarchical clustering approach using correntropy (instead of the more traditional correlation) and a modified criterion for the definition of the clusters specially suited for cases in which the Signal-to-Noise Ratio of the differences between classes is low. We show that our algorithm offers an improved sensitivity over current methods in use for distinguishing between different projection orientations and different particle conformations. This algorithm is publicly available through the software package Xmipp.

Measurement of local resolution in electron tomography.

Resolution (global and local) is one of the most reported metrics of quality measurement in Single Particle Analysis (SPA). However, in electron tomography, the situation is different and its computation is not straightforward. Typically, resolution estimation is global and, therefore, reduces the assessment of a whole tomogram to a single number. However, it is known that tomogram quality is spatially variant. Still, up to our knowledge, a method to estimate local quality metrics in tomography is lacking. This work introduces MonoTomo, a method developed to estimate locally in a tomogram the highest reliable frequency component, expressed as a form of local resolution. The fundamentals lie in a local analysis of the density map via monogenic signals, which, in analogy to MonoRes, allows for local estimations. Results with experimental data show that the local resolution range that MonoTomo casts agrees with reported resolution values for experimental data sets, with the advantage of providing a local estimation. A range of applications of MonoTomo are suggested for further exploration.

Survey of the analysis of continuous conformational variability of biological macromolecules by electron microscopy.

Single-particle analysis by electron microscopy is a well established technique for analyzing the three-dimensional structures of biological macromolecules. Besides its ability to produce high-resolution structures, it also provides insights into the dynamic behavior of the structures by elucidating their conformational variability. Here, the different image-processing methods currently available to study continuous conformational changes are reviewed.

Flexible workflows for on-the-fly electron-microscopy single-particle image processing using Scipion.

Electron microscopy of macromolecular structures is an approach that is in increasing demand in the field of structural biology. The automation of image acquisition has greatly increased the potential throughput of electron microscopy. Here, the focus is on the possibilities in Scipion to implement flexible and robust image-processing workflows that allow the electron-microscope operator and the user to monitor the quality of image acquisition, assessing very simple acquisition measures or obtaining a first estimate of the initial volume, or the data resolution and heterogeneity, without any need for programming skills. These workflows can implement intelligent automatic decisions and they can warn the user of possible acquisition failures. These concepts are illustrated by analysis of the well known 2.2 Šresolution ß-galactosidase data set.