bioRxiv Science⌕ Search

bioRxiv · 10.1101/2022.07.27.501771

MEPSi: A tool for simulating tomograms of membrane-embedded proteins

Abstract

The throughput and fidelity of cryogenic cellular electron tomography (cryo-ET) is constantly increasing through advances in cryogenic electron microscope hardware, direct electron detection devices, and powerful image processing algorithms. However, the need for careful optimization of sample preparations and for access to expensive, high-end equipment, make cryo-ET a costly and time-consuming technique. Generally, only after the last step of the cryo-ET workflow, when reconstructed tomograms are available, it becomes clear whether the chosen imaging parameters were suitable for a specific type of sample in order to answer a specific biological question. Tools for a-priory assessment of the feasibility of samples to answer biological questions and how to optimize imaging parameters to do so would be a major advantage. Here we describe MEPSi (Membrane Embedded Protein Simulator), a simulation tool aimed at rapid and convenient evaluation and optimization of cryo-ET data acquisition parameters for studies of transmembrane proteins in their native environment. We demonstrate the utility of MEPSi by showing how to detangle the influence of different data collection parameters and different orientations in respect to tilt axis and electron beam for two examples: (1) simulated plasma membranes with embedded single-pass transmembrane IIb{beta}3 integrin receptors and (2) simulated virus membranes with embedded SARS-CoV-2 spike proteins. HIGHLIGHTSO_LITool to simulate tomograms of membrane-embedded proteins C_LIO_LIDetangles influence of data acquisition parameters from sample quality issues C_LIO_LIRapid evaluation and optimization of cryo-ET data acquisition parameters C_LIO_LIProof-of-concept provided with integrins and SARS-CoV-2 spike simulations C_LI GRAPHICAL ABSTRACT O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/501771v1_ufig1.gif" ALT="Figure 1"> View larger version (27K): org.highwire.dtl.DTLVardef@120b44eorg.highwire.dtl.DTLVardef@1d9056org.highwire.dtl.DTLVardef@ef327aorg.highwire.dtl.DTLVardef@1daf773_HPS_FORMAT_FIGEXP M_FIG C_FIG

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Rodriguez de Francisco, B., Bezault, A., Xu, X.-P., Hanein, D., Volkmann, N.. 2022-07-29. MEPSi: A tool for simulating tomograms of membrane-embedded proteins. https://doi.org/10.1101/2022.07.27.501771

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

RCDome: A Multi-Database Human Gene Atlas of Regulated Cell Death

Introduction: Regulated cell death (RCD) governs tissue homeostasis, development, and disease, and is executed or regulated by specific genes. Yet for the researcher asking which genes execute or regulate a given RCD form, the answer is rarely simple: gene lists for the same form rarely agree across databases, many associations carry no traceable source, and most have never been systematically checked against primary literature. We built RCDome to answer the most basic question a researcher can ask: where did this gene-RCD association come from, and what is the evidence? Methods: RCDome is a multi-database human gene atlas built through a staged architecture integrating multi-source compilation, literature validation and evidence recovery, mechanistic classification, human-governed ontological adjudication, and web deployment. Five complementary evidence channels (PubMed Boolean search, curated databases, AI-assisted screening, manual curation, and Elicit systematic review) were integrated from 20 public databases into a unified matrix. Sixty-two original name strings were canonicalized into 53 RCD-related entities with curator-adjudicated operational definitions and ontological levels. Gene-RCD associations were systematically evaluated through an independent DeepSeek two-call LLM validation, Europe PMC full-text recovery and deep evidence extraction, an independent Consensus literature-search channel, and GPT-4o arbitration of disagreements. Source-grounding controls rejected extracted evidence not found verbatim in the source document, while the governance contract was enforced as executable code. Results: The compendium holds 22,473 association rows spanning 9,265 unique HGNC-validated genes (21,568 unique gene-RCD pairs). Evidence-first adjudication resolved 5,138 pairs (23.8%) as mechanistically involved; across the 4,775 role-resolved pairs, 225 (4.7%) are executors, 4,455 (93.3%) are regulators, and 95 are markers, revealing a small death-executing core embedded in a vast regulatory network. Under a separate seven-class mechanistic criterion applied to all 22,473 rows, only 3,063 (13.6%) were mechanistically confirmed and 286 (1.3%) were database-only with no verifiable paper trail. Conclusion: RCDome makes the RCD evidence landscape measurable and traceable, showing that AI-assisted curation can be verifiable, human-governed, and explicit about uncertainty. It is delivered as a Shiny web application that lets any researcher query the atlas and inspect the evidence behind each association. Availability: RCDome is freely available at https://rcdome.org/ (source code and data at https://github.com/BioCancerInformatics/RCDome).

cell biology↗

Circadian Clock Coordination of the Notch-to-Wnt Signaling Switch Promotes Regenerative Myogenesis

Regenerative deficits of muscle stem cells (MuSCs) contribute to progressive muscle loss in muscular dystrophy. Successful regenerative repair requires a Notch to Wnt switch to allow MuSC expansion and myogenic differentiation, yet the underlying mechanisms remain poorly understood. Leveraging complementary genetic and pharmacological approaches, here we identify the circadian clock as a key regulator of the Notch to Wnt signaling transition to promote regeneration with therapeutic potential for dystrophic disease. Circadian clock activity marks cycling myogenic progenitors during muscle regeneration, and clock induction occurs in concert with Notch activation. We identify that key components of the Notch pathway are direct transcriptional targets of the clock that were induced by clock activation. Mechanistically, clock coordination of Notch and Wnt signaling promoted MuSC proliferative expansion while facilitating myogenic progression during regeneration. Importantly, this clock-regulated mechanism was preserved in dystrophin-deficient mouse and human myoblasts, and clock-activating compounds enhanced regenerative myogenesis in dystrophic muscle. Collectively, our findings uncover a circadian clock-controlled mechanism that orchestrates regenerative signaling transition with potential for therapeutic targeting to restore regenerative capacity in dystrophic disease.

cell biology↗

The yeast Gcn2 protein kinase mediates P-body formation both through its activity with eIF2α and with non-canonical substrates

P-bodies (PBs) are control hubs for RNA processing and storage that form when translation initiation is inhibited, including during stress. In yeast, Gcn2 is the sole eIF2 alpha kinase that inhibits translation initiation in response to diverse stresses. We show that PB formation depends strongly on Gcn2 during amino acid starvation but only partially during oxidative stress. Constitutively active Gcn2 also induces PB formation in unstressed cells. Surprisingly, PBs are still constitutively formed in a gcn3 mutant strain that is insensitive to eIF2 alpha phosphorylation suggesting that Gcn2 also promotes PB formation independently of eIF2 alpha phosphorylation. Analysis of several putative Gcn2-substrates involved in RNA metabolism identified several proteins required for Gcn2-mediated PB formation. Among these, Smu2, which was not previously implicated in PB formation, localises to PBs and is required for stress-induced coalescence of mRNA granules into PBs. Together, our findings indicate that Gcn2 promotes PB formation via two complementary routes: eIF2 alpha phosphorylation, which generates untranslated mRNAs, and Smu2-dependent maturation of mRNA granules into PBs.

cell biology↗