Antibiotic Resistance Protocols (Methods in Molecular Biology)

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Stephen H. Gillespie (ed.), Antibiotic Resistance Protocols, Methods in Molecular Biology, vol. 1736,
https://doi.org/10.1007/978-1-4939-7638-6_7, © Springer Science+Business Media, LLC 2018

Chapter 7

Real-Time Digital Bright Field Technology for Rapid

Antibiotic Susceptibility Testing

Chiara Canali, Erik Spillum, Martin Valvik, Niels Agersnap,

and Tom Olesen

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 anti-
microbial agents. Here, we describe an automated digital, time-lapse, bright field imaging system (oCel-
loScope, 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 oCello-
Scope 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

1 Introduction

As consequence of the dramatic increase in microbial resistance

and the recurrent need for treatment with newer and often more

expensive antibiotics, the ability to develop cost-effective, fast and

accurate antimicrobial susceptibility testing (AST) methods is cur-

rently in the spotlight [ 1 , 2 ]. The most widely used AST methods

include manual tests such as disk diffusion and broth microdilution

[ 3 – 5 ], as well as phenotypic [ 6 – 9 ] and genotypic [ 10 – 12 ]

techniques. Manual tests provide flexibility, possible cost saving