Advertisement

Real-Time Digital Bright Field Technology for Rapid Antibiotic Susceptibility Testing

  • Chiara CanaliEmail author
  • Erik Spillum
  • Martin Valvik
  • Niels Agersnap
  • Tom Olesen
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 1736)

Abstract

Optical scanning through bacterial samples and image-based analysis may provide a robust method for bacterial identification, fast estimation of growth rates and their modulation due to the presence of antimicrobial agents. Here, we describe an automated digital, time-lapse, bright field imaging system (oCelloScope, BioSense Solutions ApS, Farum, Denmark) for rapid and higher throughput antibiotic susceptibility testing (AST) of up to 96 bacteria–antibiotic combinations at a time. The imaging system consists of a digital camera, an illumination unit and a lens where the optical axis is tilted 6.25° relative to the horizontal plane of the stage. Such tilting grants more freedom of operation at both high and low concentrations of microorganisms. When considering a bacterial suspension in a microwell, the oCelloScope acquires a sequence of 6.25°-tilted images to form an image Z-stack. The stack contains the best-focus image, as well as the adjacent out-of-focus images (which contain progressively more out-of-focus bacteria, the further the distance from the best-focus position). The acquisition process is repeated over time, so that the time-lapse sequence of best-focus images is used to generate a video. The setting of the experiment, image analysis and generation of time-lapse videos can be performed through a dedicated software (UniExplorer, BioSense Solutions ApS). The acquired images can be processed for online and offline quantification of several morphological parameters, microbial growth, and inhibition over time.

Key words

Automated digital time-lapse bright field screening system oCelloScope Qualitative and quantitative image-based analysis Generation of time-lapse videos UniExplorer Bacterial cultures and clinical isolates Antibiotic resistance testing 

References

  1. 1.
    Jorgensen JH, Ferraro MJ (2009) Antimicrobial susceptibility testing: a review of general principles and contemporary practices. Clin Infect Dis 49:1749–1755CrossRefPubMedGoogle Scholar
  2. 2.
    Jenkins SG, Schuetz AN (2012) Current concepts in laboratory testing to guide antimicrobial therapy. Mayo Clin Proc 87:290–308CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Ge B, Wang F, Sjölund-Karlsson M et al (2013) Antimicrobial resistance in Campylobacter: susceptibility testing methods and resistance trends. J Microbiol Methods 95:57–67CrossRefPubMedGoogle Scholar
  4. 4.
    Berghaus LJ, Giguère S, Guldbech K et al (2015) Comparison of Etest, disk diffusion, and broth macrodilution for in vitro susceptibility testing of Rhodococcus equi. J Clin Microbiol 53:314–318CrossRefPubMedGoogle Scholar
  5. 5.
    Baker CN, Stocker SA, Culver DH et al (1991) Comparison of the E test to agar dilution, broth microdilution, and agar diffusion susceptibility testing techniques by using a special challenge set of bacteria. J Clin Microbiol 29:533–538PubMedPubMedCentralGoogle Scholar
  6. 6.
    Dortet L, Poirel L, Nordmann P (2015) Rapid detection of ESBL-producing enterobacteriaceae in blood cultures. Emerg Infect Dis 21:504–507CrossRefPubMedPubMedCentralGoogle Scholar
  7. 7.
    Van Belkum A, Dunne WM (2013) Next-generation antimicrobial susceptibility testing. J Clin Microbiol 51:2018–2024CrossRefPubMedPubMedCentralGoogle Scholar
  8. 8.
    Ahmed MAS, Bansal D, Acharya A et al (2016) Antimicrobial susceptibility and molecular epidemiology of extended-spectrum beta-lactamase-producing Enterobacteriaceae from intensive care units at Hamad Medical Corporation, Qatar. Antimicrob Resist Infect Control 11:1–6Google Scholar
  9. 9.
    Mohan R, Mukherjee A, Sevgen SE et al (2013) A multiplexed microfluidic platform for rapid antibiotic susceptibility testing. Biosens Bioelectron 49:118–125CrossRefPubMedGoogle Scholar
  10. 10.
    Liu T, Lu Y, Gau V et al (2014) Rapid antimicrobial susceptibility testing with electrokinetics enhanced biosensors for diagnosis of acute bacterial infections. Ann Biomed Eng 42:2314–2321CrossRefPubMedPubMedCentralGoogle Scholar
  11. 11.
    Celandroni F, Salvetti S, Gueye SA et al (2016) Identification and pathogenic potential of clinical bacillus and paenibacillus isolates. PLoS One 11:0152831CrossRefGoogle Scholar
  12. 12.
    Waldeisen JR, Wang T, Mitra D et al (2011) A real-time PCR antibiogram for drug-resistant sepsis. PLoS One 6:e28528CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Wiegand I, Hilpert K, Hancock REW (2008) Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat Protoc 3:163–175CrossRefPubMedGoogle Scholar
  14. 14.
    Doern GV (2011) Antimicrobial susceptibility testing. J Clin Microbiol 49:S4CrossRefPubMedCentralGoogle Scholar
  15. 15.
    Turnidge J, Paterson DL (2007) Setting and revising antibacterial susceptibility breakpoints. Clin Microbiol Rev 20:391–408CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Depalma G, Turnidge J, Craig BA (2016) Determination of disk diffusion susceptibility testing interpretive criteria using model-based analysis: development and implementation. Diagn Microbiol Infect Dis.  https://doi.org/10.1016/j.diagmicrobio.2016.03.004
  17. 17.
    Fredborg M, Rosenvinge FS, Spillum E et al (2015) Rapid antimicrobial susceptibility testing of clinical isolates by digital time-lapse microscopy. Eur J Clin Microbiol Infect Dis 34:2385–2394CrossRefPubMedPubMedCentralGoogle Scholar
  18. 18.
    Fredborg M, Rosenvinge FS, Spillum E et al (2015) Automated image analysis for quantification of filamentous bacteria. BMC Microbiol 15:1–8CrossRefGoogle Scholar
  19. 19.
    Fredborg M, Andersen KR, Jorgensen E et al (2013) Real-time optical antimicrobial susceptibility testing. J Clin Microbiol 51:2047–2053CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Aunsbjerg SD, Andersen KR, Knøchel S (2015) Real-time monitoring of fungal inhibition and morphological changes. J Microbiol Methods 119:196–202CrossRefPubMedGoogle Scholar
  21. 21.
    Kjeldsen T, Sommer M, Olsen JE (2015) Extended spectrum β-lactamase-producing Escherichia coli forms filaments as an initial response to cefotaxime treatment. BMC Microbiol 15:1–6CrossRefGoogle Scholar
  22. 22.
    Jelsbak L, Mortensen MIB, Kilstrup M et al (2016) The in vitro redundant enzymes PurN and PurT are both essential for systemic infection of mice in Salmonella enterica serovar Typhimurium. Infect Immun 84:2076–2085CrossRefPubMedPubMedCentralGoogle Scholar
  23. 23.
    Khan DD, Lagerbäck P, Cao S et al (2015) A mechanism-based pharmacokinetic/pharmacodynamic model allows prediction of antibiotic killing from MIC values for WT and mutants. J Antimicrob Chemother 70:3051–3060CrossRefPubMedGoogle Scholar
  24. 24.
    Uggerhøj LE, Poulsen TJ, Munk JK et al (2015) Rational design of alpha-helical antimicrobial peptides: do’s and don’ts. Chembiochem 16:242–253CrossRefPubMedGoogle Scholar
  25. 25.
    Yao Z, Kahne D, Kishony R (2012) Distinct single-cell morphological dynamics under beta-lactam antibiotics. Mol Cell 48:705–712CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Periti P, Nicoletti P (1999) Classification of betalactam antibiotics according to their pharmacodynamics. J Chemother 11:323–330CrossRefPubMedGoogle Scholar
  27. 27.
    Greenwood D, O’Grady F (1973) Comparison of the responses of Escherichia coli and Proteus mirabilis to seven β-lactam antibiotics. J Infect Dis 128:211–222CrossRefPubMedGoogle Scholar
  28. 28.
    Goldman E, Green LH (2015) Practical handbook of microbiology. CRC Press, Boca Raton, FLGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2018

Authors and Affiliations

  • Chiara Canali
    • 1
    Email author
  • Erik Spillum
    • 1
    • 2
  • Martin Valvik
    • 1
  • Niels Agersnap
    • 1
  • Tom Olesen
    • 1
    • 2
  1. 1.Philips BioCell A/SAllerødDenmark
  2. 2.BioSense Solutions ApSFarumDenmark

Personalised recommendations