Czech National Centre of the European Research Infrastructure Consortium INSTRUCT ERIC

A gateway to realm of structural data for biochemists, biophysicists, molecular biologist, and all scientists whose research benefits from accurate structure determination of biological macromolecules, assemblies, and complex molecular machineries at atomic resolution.

Open access to 10 high-end core facilities and assisted expertise in NMR, X-ray crystallography and crystallization, cryo-electron microscopy and tomography, biophysical characterization of biomolecular interaction, nanobiotechnology, proteomics and structural mass spectrometry.

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Research Highlights

the best of science obtained using CIISB Core Facilities

Nucleic Acids Res. 2020

Structure of STAU1 dsRBD4 and dsRBD3/4 in complex with sARF1 SBS dsRNA. (A) Structural ensemble of the STAU1 dsRBD4–sARF1 SBS dsRNA complex. Heavy-atom superposition of the ensemble of the 20 lowest-energy structures. The protein backbone is shown in dark green and the RNA heavy atoms of the bases in orange and those of the ribose-phosphodiester backbone are shown in gold (omitting phosphate and 2-OH oxygens). (B) Schematic representation of sARF1 SBS dsRNA showing interactions of dsRBD3 as well as dsRBD4 as dotted lines. Interactions with the ribose-phosphodiester backbone are circled in dark green for dsRBD4 and light green for dsRBD3 while base interactions are shown as filled circles.

Peter J. Lukavsky Research Group

Significance

Staufen1 (STAU1) is a dsRNA binding protein mediating mRNA transport and localization, translational control and STAU1-mediated mRNA decay (SMD). The STAU1 binding site (SBS) within human ADP-ribosylation factor1 (ARF1) 3 UTR binds STAU1 and this downregulates ARF1 cytoplasmic mRNA levels by SMD. However, how STAU1 recognizes specific mRNA targets is still under debate. The structure of the ARF1 SBS–STAU1 complex, presented in this study, uncovers target recognition by STAU1. STAU1 dsRNA binding domain (dsRBD) 4 interacts with two pyrimidines and one purine from the minor groove side via helix a1, the b1–b 2 loop anchors the dsRBD at the end of the dsRNA and lysines in helix a2 bind to the phosphodiester backbone from the major groove side. STAU1 dsRBD3 displays the same binding mode with specific recognition of one guanine base. Mutants disrupting minor groove recognition of ARF1 SBS affect in vitrobinding and reduce SMD in vivo. Our data thus reveal how STAU1 recognizes minor groove features in dsRNA relevant for target selection.

 

Yadav, DP, Zigáčková, D., Zlobina, M.,  Klumpler, Beaumont, TC., Kubíčková, M., Vaňáčová, Š,  and Lukavsky, PJ.: Staufen1 reads out structure and sequence features in ARF1 dsRNA for target recognition,  Nucleic Acids Res.  2020, 48, 2091-2106, doi:10.1093/nar/gkz1163

 

J. Am. Chem. Soc. 2020

Nature Index Journal

Crystal structures of (A) PBD anthramycin covalently bound to DNA strands and (B) lincomycin targeting the peptidyl transferase center in the 50S ribosomal subunit of Staphylococcus aureus.

Jiří Janata Research Group

Significance

Antitumor pyrrolobenzodiazepines (PBDs), lincosamide antibiotics, quorumsensing molecule hormaomycin, and antimicrobial griselimycin are structurally and functionally diverse groups of actinobacterial metabolites. The common feature of these compounds is the incorporation of L -tyrosine- or L -leucine-derived 4-alkyl-L -proline derivatives (APDs) in their structures. In this study, the authors report that the last reaction in the biosynthetic pathway of APDs, catalyzed by F420 H2 -dependent Apd6 reductases, contributes to the structural diversity of APD precursors. Specifically, the heterologous overproduction of six Apd6 enzymes demonstrated that Apd6 from the biosynthesis of PBDs and hormaomycin can reduce only an endocyclic imine double bond, whereas Apd6 LmbY and partially GriH from the biosynthesis of lincomycin and griselimycin, respectively, also reduce the more inert exocyclic double bond of the same 4- substituted Δ 1-pyrroline-2-carboxylic acid substrate, making LmbY and GriH unusual, if not unique, among reductases. Furthermore, the differences in the reaction specificity of the Apd6 reductases determine the formation of the fully saturated APD moiety of lincomycin versus the unsaturated APD moiety of PBDs, providing molecules with optimal shapes to bind their distinct biological targets. Moreover, the Apd6 reductases establish the first F420 H2-dependent enzymes from the luciferase-like hydride transferase protein superfamily in the biosynthesis of bioactive molecules. Finally, bioinformatics analysis demonstrates that Apd6 and their homologues, widely distributed within several bacterial phyla, play a role in the formation of novel yet unknown natural products with incorporated L-proline-like precursors and likely in the microbial central metabolism.

Steiningerova, L. Kamenik, Z.*,  Gazak, R.,  Kadlcik, S.,  Bashiri, G.,  Man, P., Kuzma, M., Pavlikova, M., and Janata, J.: Different Reaction Specificities of F420H2Dependent Reductases Facilitate Pyrrolobenzodiazepines and Lincomycin To Fit Their Biological Targets, J. Am. Chem. Soc.  2020, 142, 3440-3448, https://dx.doi.org/10.1021/jacs.9b11234

 

 

 

 

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Reader’s Corner

literature to read, science to follow

In this section, a distinct selection of six highly stimulating research publications and reviews published during past 6 months is presented. It is our hope that links to exciting science, which deserves attention of the structural biology community, will help you to locate gems in the steadily expanding jungle of scientific literature. You are welcome to point out to any paper you found interesting by sending a link or citation to readerscorner@ciisb.org. The section is being updated regularly.


 

2 Jan

CLEM-Reg: An automated point cloud based registration algorithm for correlative light and volume electron microscopy

Correlative light and volume electron microscopy (vCLEM) is a powerful imaging technique that enables the visualisation of fluorescently labelled proteins within their ultrastructural context on a subcellular level. Currently, expert microscopists align vCLEM acquisitions using time-consuming and subjective manual methods. This paper presents CLEM-Reg, an algorithm that automates the 3D alignment of vCLEM datasets by leveraging probabilistic point cloud registration techniques. These point clouds are derived from segmentations of common structures in each modality, created by state-of-the-art open-source methods, with the option to leverage alternative tools from other plugins or platforms. CLEM-Reg drastically reduces the time required to register vCLEM datasets to a few minutes and achieves correlation of fluorescent signal to sub-micron target structures in EM on three newly acquired vCLEM benchmark datasets (fluorescence microscopy combined with FIB-SEM or SBF-SEM). CLEM-Reg was then used to automatically obtain vCLEM overlays to unambiguously identify TGN46-positive transport carriers involved in the trafficking of proteins between the trans-Golgi network and plasma membrane. The datasets are available in the EMPIAR and BioStudies public image archives for reuse in testing and developing multimodal registration algorithms by the wider community. A napari plugin integrating the algorithm is also provided to aid end-user adoption. DOI: 10.1101/2023.05.11.540445

26 Nov 2024

Large-Scale Quantitative Cross-Linking and Mass Spectrometry Provides New Insight on Protein Conformational Plasticity within Organelles, Cells, and Tissues (Biorxiv)

Many proteins can exist in multiple conformational states in vivo to achieve distinct functional roles. These states include alternative conformations, variable PTMs, and association with interacting protein, nucleotide, and ligand partners. Quantitative chemical cross-linking of live cells, organelles, or tissues together with mass spectrometry provides the relative abundance of cross-link levels formed in two or more compared samples, which depends both on the relative levels of existent protein conformational states in the compared samples as well as the relative likelihood of the cross-link originating from each. Because cross-link conformational state preferences can vary widely, one expects intra-protein cross-link levels from proteins with high conformational plasticity to display divergent quantitation among samples with differing conformational ensembles. Here we use the large volume of quantitative cross-linking data available on the public XLinkDB database to cluster intra-protein cross-links according to their quantitation in many diverse compared samples to provide the first widescale glimpse of cross-links grouped according to the protein conformational state(s) from which they predominantly originate. We further demonstrate how cluster cross-links can be aligned with any protein structure to assess the likelihood that they were derived from it.​

Reader’s Corner Archive

Quote of May

“I have learned much from my teachers, more from my colleagues, and the most from my students.”

Talmud

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