Rapid antimicrobial susceptibility testing (AST) is essential for early and appropriate therapy. Methods with short detection time enabling same-day treatment optimisation are highly favourable. In this study, we evaluated the potential of a digital time-lapse microscope system, the oCelloScope system, to perform rapid AST. The oCelloScope system demonstrated a very high accuracy (96 % overall agreement) when determining the resistance profiles of four reference strains, nine clinical isolates, including multi-drug-resistant isolates, and three positive blood cultures. AST of clinical isolates (168 antimicrobial agent–organism combinations) demonstrated 3.6 % minor, no major and 1.2 % very major errors of the oCelloScope system compared to conventional susceptibility testing, as well as a rapid and correct phenotypic detection of strains with methicillin-resistant Staphylococcus aureus (MRSA) and extended-spectrum β-lactamase (ESBL) profiles. The net average time-to-result was 108 min, with 95 % of the results being available within 180 min. In conclusion, this study strongly indicates that the oCelloScope system holds considerable potential as an accurate and sensitive AST method with short time-to-result, enabling same-day targeted antimicrobial therapy, facilitating antibiotic stewardship and better patient management. A full-scale validation of the oCelloScope system including more isolates is necessary to assess the impact of using it for AST.

BackgroundAntibiotics of the β-lactam group are able to alter the shape of the bacterial cell wall, e.g. filamentation or a spheroplast formation. Early determination of antimicrobial susceptibility may be complicated by filamentation of bacteria as this can be falsely interpreted as growth in systems relying on colorimetry or turbidometry (such as Vitek-2, Phoenix, MicroScan WalkAway). The objective was to examine an automated image analysis algorithm for quantification of filamentous bacteria using the 3D digital microscopy imaging system, oCelloScope.ResultsThree E. coli strains displaying different resistant profiles and differences in filamentation kinetics were used to study a novel image analysis algorithm to quantify length of bacteria and bacterial filamentation. A total of 12 β-lactam antibiotics or β-lactam–β-lactamase inhibitor combinations were analyzed for their ability to induce filamentation. Filamentation peaked at approximately 120 min with an average cell length of 30 μm.ConclusionThe automated image analysis algorithm showed a clear ability to rapidly detect and quantify β-lactam-induced filamentation in E. coli. This rapid determination of β-lactam-mediated morphological alterations may facilitate future development of fast and accurate AST systems, which in turn will enable early targeted antimicrobial therapy. Therefore, rapid detection of β-lactam-mediated morphological changes may have important clinical implications.Electronic supplementary materialThe online version of this article (doi:10.1186/s12866-015-0583-5) contains supplementary material, which is available to authorized users.

The treatment response to anti-angiogenic agents varies among cancer patients and predictive biomarkers are needed to identify patients with resistant cancer or guide the choice of anti-angiogenic treatment. We present “the Cancer Angiogenesis Co-Culture (CACC) assay”, an in vitro Functional Precision Medicine assay which enables the study of tumouroid induced angiogenesis. This assay can quantify the ability of a patient-derived tumouroid to induce vascularization by measuring the induction of tube formation in a co-culture of vascular cells and tumoroids established from the primary colorectal tumour or a metastasis. Furthermore, the assay can quantify the sensitivity of patient-derived tumoroids to anti-angiogenic therapies. We observed that tube formation increased in a dose-dependent manner upon treatment with the pro-angiogenic factor vascular endothelial growth factor A (VEGF-A). When investigating the angiogenic potential of tumoroids from 12 patients we found that 9 tumoroid cultures induced a significant increase in tube formation compared to controls without tumoroids. In these 9 angiogenic tumoroid cultures the tube formation could be abolished by treatment with one or more of the investigated anti-angiogenic agents. The 3 non-angiogenic tumoroid cultures secreted VEGF-A but we observed no correlation between the amount of tube formation and tumoroid-secreted VEGF-A. Our data suggests that the CACC assay recapitulates the complexity of tumour angiogenesis, and when clinically verified, could prove a valuable tool to quantify sensitivity towards different anti-angiogenic agents.

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.

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