IDEAS home Printed from https://ideas.repec.org/a/nat/natcom/v15y2024i1d10.1038_s41467-024-46213-y.html
   My bibliography  Save this article

Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform

Author

Listed:
  • Alexander Sturm

    (Resistell AG, Hofackerstrasse 40)

  • Grzegorz Jóźwiak

    (Resistell AG, Hofackerstrasse 40)

  • Marta Pla Verge

    (Resistell AG, Hofackerstrasse 40)

  • Laura Munch

    (Resistell AG, Hofackerstrasse 40)

  • Gino Cathomen

    (Resistell AG, Hofackerstrasse 40)

  • Anthony Vocat

    (Resistell AG, Hofackerstrasse 40)

  • Amanda Luraschi-Eggemann

    (Resistell AG, Hofackerstrasse 40)

  • Clara Orlando

    (Resistell AG, Hofackerstrasse 40)

  • Katja Fromm

    (Resistell AG, Hofackerstrasse 40)

  • Eric Delarze

    (Resistell AG, Hofackerstrasse 40)

  • Michał Świątkowski

    (Resistell AG, Hofackerstrasse 40)

  • Grzegorz Wielgoszewski

    (Resistell AG, Hofackerstrasse 40)

  • Roxana M. Totu

    (Resistell AG, Hofackerstrasse 40)

  • María García-Castillo

    (Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Carretera de Colmenar Km 9,1)

  • Alexandre Delfino

    (Lausanne University Hospital (CHUV) & University of Lausanne (UNIL))

  • Florian Tagini

    (Lausanne University Hospital (CHUV) & University of Lausanne (UNIL))

  • Sandor Kasas

    (École Polytechnique Fédérale de Lausanne (EPFL) and University of Lausanne (UNIL)
    Centre Universitaire Romand de Médecine Légale (UFAM) & Université de Lausanne (UNIL))

  • Cornelia Lass-Flörl

    (Medizinische Universität Innsbruck, Schöpfstraße 41)

  • Ronald Gstir

    (Medizinische Universität Innsbruck, Schöpfstraße 41)

  • Rafael Cantón

    (Instituto Ramón y Cajal de Investigación Sanitaria (IRYCIS), Carretera de Colmenar Km 9,1
    CIBER de Enfermedades Infecciosas (CIBERINFEC). Instituto de Salud Carlos III. Sinesio Delgado 4)

  • Gilbert Greub

    (Lausanne University Hospital (CHUV) & University of Lausanne (UNIL))

  • Danuta Cichocka

    (Resistell AG, Hofackerstrasse 40)

Abstract

Antimicrobial resistance (AMR) is a major public health threat, reducing treatment options for infected patients. AMR is promoted by a lack of access to rapid antibiotic susceptibility tests (ASTs). Accelerated ASTs can identify effective antibiotics for treatment in a timely and informed manner. We describe a rapid growth-independent phenotypic AST that uses a nanomotion technology platform to measure bacterial vibrations. Machine learning techniques are applied to analyze a large dataset encompassing 2762 individual nanomotion recordings from 1180 spiked positive blood culture samples covering 364 Escherichia coli and Klebsiella pneumoniae isolates exposed to cephalosporins and fluoroquinolones. The training performances of the different classification models achieve between 90.5 and 100% accuracy. Independent testing of the AST on 223 strains, including in clinical setting, correctly predict susceptibility and resistance with accuracies between 89.5% and 98.9%. The study shows the potential of this nanomotion platform for future bacterial phenotype delineation.

Suggested Citation

  • Alexander Sturm & Grzegorz Jóźwiak & Marta Pla Verge & Laura Munch & Gino Cathomen & Anthony Vocat & Amanda Luraschi-Eggemann & Clara Orlando & Katja Fromm & Eric Delarze & Michał Świątkowski & Grzego, 2024. "Accurate and rapid antibiotic susceptibility testing using a machine learning-assisted nanomotion technology platform," Nature Communications, Nature, vol. 15(1), pages 1-14, December.
  • Handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46213-y
    DOI: 10.1038/s41467-024-46213-y
    as

    Download full text from publisher

    File URL: https://www.nature.com/articles/s41467-024-46213-y
    File Function: Abstract
    Download Restriction: no

    File URL: https://libkey.io/10.1038/s41467-024-46213-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Vinodh Kandavalli & Praneeth Karempudi & Jimmy Larsson & Johan Elf, 2022. "Rapid antibiotic susceptibility testing and species identification for mixed samples," Nature Communications, Nature, vol. 13(1), pages 1-8, December.
    2. Ofer Fridman & Amir Goldberg & Irine Ronin & Noam Shoresh & Nathalie Q. Balaban, 2014. "Optimization of lag time underlies antibiotic tolerance in evolved bacterial populations," Nature, Nature, vol. 513(7518), pages 418-421, September.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marianne Bauer & Isabella R Graf & Vudtiwat Ngampruetikorn & Greg J Stephens & Erwin Frey, 2017. "Exploiting ecology in drug pulse sequences in favour of population reduction," PLOS Computational Biology, Public Library of Science, vol. 13(9), pages 1-17, September.
    2. Sourav Chowdhury & Daniel C. Zielinski & Christopher Dalldorf & Joao V. Rodrigues & Bernhard O. Palsson & Eugene I. Shakhnovich, 2023. "Empowering drug off-target discovery with metabolic and structural analysis," Nature Communications, Nature, vol. 14(1), pages 1-14, December.
    3. Jessica A Lee & Siavash Riazi & Shahla Nemati & Jannell V Bazurto & Andreas E Vasdekis & Benjamin J Ridenhour & Christopher H Remien & Christopher J Marx, 2019. "Microbial phenotypic heterogeneity in response to a metabolic toxin: Continuous, dynamically shifting distribution of formaldehyde tolerance in Methylobacterium extorquens populations," PLOS Genetics, Public Library of Science, vol. 15(11), pages 1-38, November.
    4. Niclas Nordholt & Orestis Kanaris & Selina B. I. Schmidt & Frank Schreiber, 2021. "Persistence against benzalkonium chloride promotes rapid evolution of tolerance during periodic disinfection," Nature Communications, Nature, vol. 12(1), pages 1-13, December.
    5. José Camacho Mateu & Matteo Sireci & Miguel A Muñoz, 2021. "Phenotypic-dependent variability and the emergence of tolerance in bacterial populations," PLOS Computational Biology, Public Library of Science, vol. 17(9), pages 1-28, September.
    6. Elwood A. Mullins & Jonathan Dorival & Gong-Li Tang & Dale L. Boger & Brandt F. Eichman, 2021. "Structural evolution of a DNA repair self-resistance mechanism targeting genotoxic secondary metabolites," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    7. Erica J. Zheng & Ian W. Andrews & Alexandra T. Grote & Abigail L. Manson & Miguel A. Alcantar & Ashlee M. Earl & James J. Collins, 2022. "Modulating the evolutionary trajectory of tolerance using antibiotics with different metabolic dependencies," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    8. Horvath, Denis & Brutovsky, Branislav, 2016. "Etiology of phenotype switching strategy in time varying stochastic environment," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 455-468.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:nat:natcom:v:15:y:2024:i:1:d:10.1038_s41467-024-46213-y. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.nature.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.