Exploiting open source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology

Needs, S. H. ORCID: https://orcid.org/0000-0003-3407-9637, Diep, T. T., Bull, S. P. ORCID: https://orcid.org/0000-0001-5129-1731, Lindley-Decaire, A., Ray, P. ORCID: https://orcid.org/0000-0001-8375-8279 and Edwards, A. D. ORCID: https://orcid.org/0000-0003-2369-989X (2019) Exploiting open source 3D printer architecture for laboratory robotics to automate high-throughput time-lapse imaging for analytical microbiology. PLOS ONE, 14 (11). e0224878. ISSN 1932-6203 doi: 10.1371/journal.pone.0224878

Abstract/Summary

Growth in open-source hardware designs combined with the low-cost of high performance optoelectronic and robotics components has supported a resurgence of in-house custom lab equipment development. We describe a low cost (below $700), open-source, fully customizable high-throughput imaging system for analytical microbiology applications. The system comprises a Raspberry Pi camera mounted on an aluminium extrusion frame with 3D-printed joints controlled by an Arduino microcontroller running open-source Repetier Host Firmware. The camera position is controlled by simple G-code scripts supplied from a Raspberry Pi singleboard computer and allow customized time-lapse imaging of microdevices over a large imaging area. Open-source OctoPrint software allows remote access and control. This simple yet effective design allows high-throughput microbiology testing in multiple formats including formats for bacterial motility, colony growth, microtitre plates and microfluidic devices termed ‘lab-on-a-comb’ to screen the effects of different culture media components and antibiotics on bacterial growth. The open-source robot design allows customization of the size of the imaging area; the current design has an imaging area of ~420 × 300mm, which allows 29 ‘lab-on-a-comb’ devices to be imaged which is equivalent 3480 individual 1µl samples. The system can also be modified for fluorescence detection using LED and emission filters embedded on the PiCam for more sensitive detection of bacterial growth using fluorescent dyes.

Item Type	Article
URI	https://reading-clone.eprints-hosting.org/id/eprint/87413
Item Type	Article
Refereed	Yes
Divisions	Life Sciences > School of Chemistry, Food and Pharmacy > School of Pharmacy > Pharmaceutics Research Group
Publisher	PLOS
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