Low-Cost Motility Tracking System (LOCOMOTIS) for Time-Lapse Microscopy Applications and Cell Visualisation

Abstract

Direct visualisation of cells for the purpose of studying their motility has typically required expensive microscopy equipment. However, recent advances in digital sensors mean that it is now possible to image cells for a fraction of the price of a standard microscope. Along with low-cost imaging there has also been a large increase in the availability of high quality, open-source analysis programs. In this study we describe the development and performance of an expandable cell motility system employing inexpensive, commercially available digital USB microscopes to image various cell types using time-lapse and perform tracking assays in proof-of-concept experiments. With this system we were able to measure and record three separate assays simultaneously on one personal computer using identical microscopes, and obtained tracking results comparable in quality to those from other studies that used standard, more expensive, equipment. The microscopes used in our system were capable of a maximum magnification of 413.6×. Although resolution was lower than that of a standard inverted microscope we found this difference to be indistinguishable at the magnification chosen for cell tracking experiments (206.8×). In preliminary cell culture experiments using our system, velocities (mean µm/min ± SE) of 0.81±0.01 (Biomphalaria glabrata hemocytes on uncoated plates), 1.17±0.004 (MDA-MB-231 breast cancer cells), 1.24±0.006 (SC5 mouse Sertoli cells) and 2.21±0.01 (B. glabrata hemocytes on Poly-L-Lysine coated plates), were measured and are consistent with previous reports. We believe that this system, coupled with open-source analysis software, demonstrates that higher throughput time-lapse imaging of cells for the purpose of studying motility can be an affordable option for all researchers.

Experimental heatwaves compromise sperm function and cause transgenerational damage in a model insect

“…1.49k) 73 (Supplementary Figure 7 ). The macro subtracted background in each channel image using a rolling ball radius of 25 pixels for the smoothing algorithm 74 . To remove autofluorescence from the GFP-channel image so that only GFP sperm fluorescence was visible 75 , the macro corrected each GFP-channel image as follows: a region of interest (ROI) was created manually in the AF-channel in an area of the image displaying high fluorescence but no corresponding fluorescence in the GFP-channel image, the mean intensity was then measured in this ROI (Int Auto ).…”

Novel aspects of live intestinal epithelial cell function revealed using a custom time‐lapse video microscopy apparatus

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Mobile Diagnostics Based on Motion? A Close Look at Motility Patterns in the Schistosome Life Cycle

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