MEDUSA: A cloud-based tool for the analysis of X-ray diffuse scattering to obtain the bending modulus from oriented membrane stacks

  • Sebastian Himbert
  • , Dorian Gaboo
  • , Emre Brookes
  • , John F. Nagle
  • , Maikel C. Rheinstädter

Research output: Contribution to journalArticlepeer-review

Abstract

An important mechanical property of cells is their membrane bending modulus, κ. Here, we introduce MEDUSA (MEmbrane DiffUse Scattering Analysis), a cloud-based analysis tool to determine the bending modulus, κ, from the analysis of X-ray diffuse scattering. MEDUSA uses GPU (graphics processing unit) accelerated hardware and a parallelized algorithm to run the calculations efficiently in a few seconds. MEDUSA’s graphical user interface allows the user to upload 2-dimensional data collected from different sources, perform background subtraction and distortion corrections, select regions of interest, run the fitting procedure and output the fitted parameters, the membranes’ bending modulus κ, and compressional modulus B.

Original languageEnglish
Article numbere1011749
Pages (from-to)e1011749
JournalPLoS Computational Biology
Volume20
Issue number1
DOIs
StatePublished - Jan 8 2024

Funding

This research was funded by the Natural Sciences and Engineering Research Council of Canada (NSERC), the Canada Foundation for Innovation (CFI) and the Ontario Ministry of Economic Development and Innovation awarded to M.C.R. S.H. is the recipient of the H.G. Thode Postdoctoral Fellowship at McMaster University. M.C.R. is the recipient of an Early Researcher Award of the Province of Ontario and a University Scholar of McMaster University. Research reported in this publication was supported by the National Institute of General Medical Sciences of the National Institutes of Health under award number R01GM120600 to EB. This work used the Extreme Science and Engineering Discovery Environment (XSEDE), which is supported by the National Science Foundation Grant Number ACI-1548562, the National Science Foundation award OAC-1912444 and the Advanced Cyberinfrastructure Coordination Ecosystem: Services & Support (ACCESS) program, which is supported by National Science Foundation grants 2138259, 2138286, 2138307, 2137603, and 2138296. The work utilizes Jetstream2 at Indiana University through allocation MCB170057 to EB. This work benefited from CCP-SAS software developed through a joint EPSRC (EP/K039121/1) and NSF (CHE-1265821) grant. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. M.C.R.istherecipientofanEarlyResearcher AwardoftheProvinceofOntarioandaUniversity ScholarofMcMasterUniversity.Researchreported inthispublicationwassupportedbytheNational InstituteofGeneralMedicalSciencesofthe NationalInstitutesofHealthunderawardnumber R01GM120600toEB.ThisworkusedtheExtreme ScienceandEngineeringDiscoveryEnvironment (XSEDE),whichissupportedbytheNational ScienceFoundationGrantNumberACI-1548562, theNationalScienceFoundationawardOAC-1912444andtheAdvancedCyberinfrastructure CoordinationEcosystem:Services&Support (ACCESS)program,whichissupportedbyNational ScienceFoundationgrants2138259,2138286, 2138307,2137603,and2138296.Thework utilizesJetstream2atIndianaUniversitythrough allocationMCB170057toEB.Thisworkbenefited fromCCP-SASsoftwaredevelopedthroughajoint EPSRC(EP/K039121/1)andNSF(CHE-1265821) grant.Thefundershadnoroleinstudydesign, datacollectionandanalysis,decisiontopublish,or preparationofthemanuscript.

FundersFunder number
2138286, 2138296, ACI-1548562, OAC-1912444, 2137603, 2138307, 2138259
R01GM120600
MCB170057
McMaster University
Canada Foundation for Innovation
Engineering and Physical Sciences Research CouncilCHE-1265821, EP/K039121/1

    Keywords

    • Algorithms
    • Cloud Computing
    • Radiography
    • X-Rays

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