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By centralizing many of the tasks associated with the upkeep of scientific software, SBGrid allows researchers to spend more of their time on research.By centralizing many of the tasks associated with the upkeep of scientific software, SBGrid allows researchers to spend more of their time on research.

Single-cell transcriptomics data are analyzed using two popular tools, Seurat and Scanpy. Multiple separate tools are used downstream of Seurat and Scanpy cell annotation to study cell differentiation and communication, including cell proportion difference analysis between conditions, pseudotime and trajectory analyses to study cell transition, and cell–cell communication analysis. To automate the integrative cell differentiation and communication analyses of single-cell RNA-seq data, we developed a single-cell RNA-seq downstream analysis pipeline called “scDown”. This R package includes cell proportion difference analysis, cell–cell communication analysis, pseudotime analysis, and RNA velocity analysis. Both Seurat and Scanpy annotated single-cell RNA-seq data are accepted in this pipeline. We applied scDown to a published dataset and identified a unique, previously undiscovered signature of neuronal inflammatory signaling associated with a rare genetic neurodevelopmental disorder. These findings were not identified with a simple implementation of Seurat differential gene expression analysis, illustrating the value of our pipeline in biological discovery. scDown can be broadly utilized in downstream analyses of scRNA-seq data, particularly in rare diseases.

  [...]proprietary licenses are often very restrictive for end-users. [...]in our software-dependent information age, few laws are influencing our professional (and personal) pursuits more than these.

Lens-specific aquaporin-0 (AQP0) functions as a specific water pore and forms the thin junctions between fibre cells. Here we describe a 1.9 Å resolution structure of junctional AQP0, determined by electron crystallography of double-layered two-dimensional crystals. Comparison of junctional and non-junctional AQP0 structures shows that junction formation depends on a conformational switch in an extracellular loop, which may result from cleavage of the cytoplasmic amino and carboxy termini. In the centre of the water pathway, the closed pore in junctional AQP0 retains only three water molecules, which are too widely spaced to form hydrogen bonds with each other. Packing interactions between AQP0 tetramers in the crystalline array are mediated by lipid molecules, which assume preferred conformations. We were therefore able to build an atomic model for the lipid bilayer surrounding the AQP0 tetramers, and we describe lipid–protein interactions. Membrane organization Aquaporin-0 (AQP0) is the most abundant protein in the membranes of fibre cells in the lens of the mammalian eye, acting both as a water-conducting channel and as an adhesion molecule at cell junctions. The structure of AQP0 unbound (shown on the cover), and together with the lipids that surround it in the membrane, has now been determined at high resolution by electron microscopy — high enough to resolve single water molecules. The structure gives us the first close look at how a membrane protein is embedded in a lipid bilayer. When junctions form between lens fibre cells, the associated lipids, already partly immobilized by interaction with AQP0, mediate the lattice contacts. AQP0 mutations are known to cause cataracts; these mutations may be interfering with AQP0's interaction with the lipids, preventing the integration of AQP0 into a bilayer

Integral β-barrel proteins are found in the outer membranes of mitochondria, chloroplasts, and Gram-negative bacteria. The machine that assembles these proteins contains an integral membrane protein, called YaeT in Escherichia coli, which has one or more polypeptide transport-associated (POTRA) domains. The crystal structure of a periplasmic fragment of YaeT reveals the POTRA domain fold and suggests a model for how POTRA domains can bind different peptide sequences, as required for a machine that handles numerous β-barrel protein precursors. Analysis of POTRA domain deletions shows which are essential and provides a view of the spatial organization of this assembly machine.

Structural biology generates vast amounts of data, particularly in cryo-electron microscopy (cryo-EM), cryo-electron tomography (cryo-ET), and X- ray diffraction. Modern detectors produce many terabytes of data per day and require resource-intensive processing, often with specialized hardware. This data deluge creates significant challenges for storage and timely analysis. High-performance data storage systems are required for continuous data collection and processing, but are costly to purchase and maintain and thus may not be available to many research groups. Cloud computing offers a scalable alternative here, providing near-infinite storage and on-demand processing power without the requirements of maintaining local hardware. This can be advantageous for shared resource facilities and industry environments where eliminating bottlenecks in data collection pipelines is crucial. In response to the growing adoption of cloud-based data storage, SBGrid has developed a platform specifically designed for structural biology data management and analysis in the cloud. We will discuss the challenges of managing large datasets in structural biology and strategies we have implemented for throughput, processing and storage. We will explore effective use of cloud platforms for large datasets, cost management strategies, and the benefits and limitations of cloud infrastructure for macromolecular structure determination.

Structural dynamics research requires robust computational methods, reliable software, accessible data, and scalable infrastructure. Managing these components is complex and directly affects reproducibility and efficiency. The SBGrid Consortium addresses these challenges through a three-pillar approach that encompasses Software, Data, and Infrastructure, designed to foster a consistent and rigorous computational environment. At the core is the SBGrid software collection (>620 curated applications), supported by the Capsules Software Execution Environment, which ensures conflict-free, version-controlled execution. The SBGrid Data Bank supports open science by enabling the publication of primary experimental data. SBCloud, a fully managed cloud computing platform, provides scalable, on-demand infrastructure optimized for structural biology workloads. Together, they reduce computational friction, enabling researchers to focus on interpreting time-resolved data, modeling structural transitions, and managing large simulation datasets for advancing structural dynamics. This integrated platform delivers a reliable and accessible foundation for computationally intensive research across diverse scientific fields sharing common computational methods.

Parallel sequence and structure alignment tools have become ubiquitous and invaluable at all levels in the study of biological systems. We demonstrate the application and utility of this same parallel search paradigm to the process of protein structure determination, benefitting from the large and growing corpus of known structures. Such searches were previously computationally intractable. Through the method of Wide Search Molecular Replacement, developed here, they can be completed in a few hours with the aide of national-scale federated cyberinfrastructure. By dramatically expanding the range of models considered for structure determination, we show that small (less than 12% structural coverage) and low sequence identity (less than 20% identity) template structures can be identified through multidimensional template scoring metrics and used for structure determination. Many new macromolecular complexes can benefit significantly from such a technique due to the lack of known homologous protein folds or sequences. We demonstrate the effectiveness of the method by determining the structure of a full-length p97 homologue from Trichoplusia ni. Example cases with the MHC/T-cell receptor complex and the EmoB protein provide systematic estimates of minimum sequence identity, structure coverage, and structural similarity required for this method to succeed. We describe how this structure-search approach and other novel computationally intensive workflows are made tractable through integration with the US national computational cyberinfrastructure, allowing, for example, rapid processing of the entire Structural Classification of Proteins protein fragment database.

Peptidoglycan is an essential polymer that forms a protective shell around bacterial cell membranes. Peptidoglycan biosynthesis is the target of many clinically used antibiotics, including the β-lactams, imipenems, cephalosporins, and glycopeptides. Resistance to these and other antibiotics has prompted interest in an atomic-level understanding of the enzymes that make peptidoglycan. Representative structures have been reported for most of the enzymes in the pathway. Until now, however, there have been no structures of any peptidoglycan glycosyltransferases (also known as transglycosylases), which catalyze formation of the carbohydrate chains of peptidoglycan from disaccharide subunits on the bacterial cell surface. We report here the 2.1-Å crystal structure of the peptidoglycan glycosyltransferase (PGT) domain of Aquifex aeolicus PBP1A. The structure has a different fold from all other glycosyltransferase structures reported to date, but it bears some resemblance to λ-lysozyme, an enzyme that degrades the carbohydrate chains of peptidoglycan. An analysis of the structure, combined with biochemical information showing that these enzymes are processive, suggests a model for glycan chain polymerization.

Background SELENON -Congenital Myopathy ( SELENON- CM) is a rare congenital myopathy caused by mutations of the SELENON gene characterized by axial muscle weakness and progressive respiratory insufficiency. Muscle histopathology may be non-specific, but commonly includes multiminicores or a dystrophic pattern. The SELENON gene encodes selenoprotein N (SelN), a selenocysteine-containing redox enzyme located in the endo/sarcoplasmic reticulum membrane where it colocalizes with mitochondria-associated membranes. However, the molecular mechanism(s) by which SelN deficiency cause SELENON -CM remain poorly understood. A hurdle is the lack of cellular and animal models that show easily assayable phenotypes. Methods Using CRISPR-Cas9 we generated three zebrafish models of SELENON -CM, which were then studied by spontaneous coiling, hatching, and activity assays. We also performed selenon coexpression analysis using a single cell RNAseq zebrafish embryo-atlas. SelN-deficient myoblasts were generated and assayed for glutathione, reactive oxygen species, carbonylation, and nytrosylation levels. Finally, we tested Selenon- deficient myoblasts’ metabolism using a Seahorse cell respirometer. Results We report deep-phenotyping of SelN-deficient zebrafish and muscle cells. SelN-deficient zebrafish exhibit changes in embryonic muscle function and swimming activity in larvae. Analysis of single cell RNAseq data in a zebrafish embryo-atlas revealed coexpression of selenon and genes involved in the glutathione redox pathway. SelN-deficient zebrafish and mouse myoblasts exhibit altered glutathione and redox homeostasis, as well as abnormal patterns of energy metabolism, suggesting roles for SelN in these functions. Conclusions These data demonstrate a role for SelN in zebrafish early development and myoblast metabolism and provide a basis for cellular and animal model assays for SELENON -CM.