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

Abstract

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.

Automation in the Life Science Research Laboratory

“…The number of automation development tools, components and virtual training options available to research laboratories continues to broaden, increasing their capability to develop low-cost solutions to labour intensive processes. The advent of affordable 3D printing modalities (Jones et al, 2011;Zluhan et al, 2016;Capel et al, 2018), off the shelf actuators and readily programable microcontrollers (Mabbott, 2014;Kim et al, 2015;Wong et al, 2018) has given research laboratories the ability to produce componentry that can then be assembled, controlled and automated all for a relatively low cost (Courtemanche et al, 2018;Needs et al, 2019;Barthels et al, 2020). Open source designs and software have an important enabling effect for researchers who may not have engineering or programming expertise.…”

Affordable mobile microfluidic diagnostics: minimum requirements for smartphones and digital imaging for colorimetric and fluorometric anti-dengue and anti-SARS-CoV-2 antibody detection

“…The MCF was manufactured by Lamina Dielectrics Ltd (Billingshurst, West Sussex, UK) and consisted of an array of 10 micro-capillaries produced from Teflon®-FEP FEP (fluorinated ethylene propylene) (Dow, USA) using a continuous melt-extrusion process 22,23 . The MCF had a width of 4.3mm and the mean internal diameter of the microcapillaries was 206µm.…”

“…We developed a simple and lowcost microfluidic platform that exploits the optical transparency of melt-extruded fluoropolymer microcapillary film (MCF). We previously showed both smartphone and consumer digital cameras, as well as the Raspberry Pi camera, can quantify immunoassay and analytical microbiology assays within affordable microfluidic devices made from MCF 3,[20][21][22][23][24] . The low cost of the devices and the optical transparency achieved through refractive index matching makes this simple platform ideally suited to systematic comparison of imaging performance.…”

High-throughput, multiplex microfluidic test strip for the determination of antibiotic susceptibility in uropathogenic E. coli with smartphone detection

“…Once all capillaries were filled (approximately 3 seconds) end covers filled with silicone grease were placed on each end to stop sample evaporation. Samples were incubated overnight at 37 °C and color change monitored using an in-house automated raspberry pi camera imaging system (Needs et al, 2019). MIC measurements were taken in duplicate with two wells used for each measurement (Fig 1a).…”

“…For time-lapse imaging, resazurin conversion was recorded every 15 minutes using the POLIR robot (Needs et al, 2019), with 3280 x 2464 resolution images taken with a Raspberry Pi v2 camera. MatLab scripts were used to analyse time-lapse image series of bacterial growth in MCF, and the code can be accessed here: https://gitlab.com/sneeds/code-repository.…”