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.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsSpringer Nature is developing a new tool to find and evaluate Protocols. Learn more
References
Jorgensen JH, Ferraro MJ (2009) Antimicrobial susceptibility testing: a review of general principles and contemporary practices. Clin Infect Dis 49:1749–1755
Jenkins SG, Schuetz AN (2012) Current concepts in laboratory testing to guide antimicrobial therapy. Mayo Clin Proc 87:290–308
Ge B, Wang F, Sjölund-Karlsson M et al (2013) Antimicrobial resistance in Campylobacter: susceptibility testing methods and resistance trends. J Microbiol Methods 95:57–67
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 53:314–318
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 29:533–538
Dortet L, Poirel L, Nordmann P (2015) Rapid detection of ESBL-producing enterobacteriaceae in blood cultures. Emerg Infect Dis 21:504–507
Van Belkum A, Dunne WM (2013) Next-generation antimicrobial susceptibility testing. J Clin Microbiol 51:2018–2024
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 11:1–6
Mohan R, Mukherjee A, Sevgen SE et al (2013) A multiplexed microfluidic platform for rapid antibiotic susceptibility testing. Biosens Bioelectron 49:118–125
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 42:2314–2321
Celandroni F, Salvetti S, Gueye SA et al (2016) Identification and pathogenic potential of clinical bacillus and paenibacillus isolates. PLoS One 11:0152831
Waldeisen JR, Wang T, Mitra D et al (2011) A real-time PCR antibiogram for drug-resistant sepsis. PLoS One 6:e28528
Wiegand I, Hilpert K, Hancock REW (2008) Agar and broth dilution methods to determine the minimal inhibitory concentration (MIC) of antimicrobial substances. Nat Protoc 3:163–175
Doern GV (2011) Antimicrobial susceptibility testing. J Clin Microbiol 49:S4
Turnidge J, Paterson DL (2007) Setting and revising antibacterial susceptibility breakpoints. Clin Microbiol Rev 20:391–408
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
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 34:2385–2394
Fredborg M, Rosenvinge FS, Spillum E et al (2015) Automated image analysis for quantification of filamentous bacteria. BMC Microbiol 15:1–8
Fredborg M, Andersen KR, Jorgensen E et al (2013) Real-time optical antimicrobial susceptibility testing. J Clin Microbiol 51:2047–2053
Aunsbjerg SD, Andersen KR, Knøchel S (2015) Real-time monitoring of fungal inhibition and morphological changes. J Microbiol Methods 119:196–202
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 15:1–6
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 84:2076–2085
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 70:3051–3060
Uggerhøj LE, Poulsen TJ, Munk JK et al (2015) Rational design of alpha-helical antimicrobial peptides: do’s and don’ts. Chembiochem 16:242–253
Yao Z, Kahne D, Kishony R (2012) Distinct single-cell morphological dynamics under beta-lactam antibiotics. Mol Cell 48:705–712
Periti P, Nicoletti P (1999) Classification of betalactam antibiotics according to their pharmacodynamics. J Chemother 11:323–330
Greenwood D, O’Grady F (1973) Comparison of the responses of Escherichia coli and Proteus mirabilis to seven β-lactam antibiotics. J Infect Dis 128:211–222
Goldman E, Green LH (2015) Practical handbook of microbiology. CRC Press, Boca Raton, FL
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer Science+Business Media, LLC
About this protocol
Cite this protocol
Canali, C., Spillum, E., Valvik, M., Agersnap, N., Olesen, T. (2018). Real-Time Digital Bright Field Technology for Rapid Antibiotic Susceptibility Testing. In: Gillespie, S. (eds) Antibiotic Resistance Protocols. Methods in Molecular Biology, vol 1736. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7638-6_7
Download citation
DOI: https://doi.org/10.1007/978-1-4939-7638-6_7
Published:
Publisher Name: Humana Press, New York, NY
Print ISBN: 978-1-4939-7636-2
Online ISBN: 978-1-4939-7638-6
eBook Packages: Springer Protocols