Sign in
Cell BiologybioRxiv
Preprint

An open-source experimental framework for automation of cell biology experiments

P. Katunin, A. J. Cadby, A. Nikolaev

Abstract

Modern data analysis methods, such as optimisation algorithms or machine and deep learning, have been successfully applied to a number of biological, biotechnological and medical questions. For these methods to be efficient, a large number of high quality experiments need to be conducted, which requires a high degree of automation. Here we report an open-source hardware that allows for automatic high-throughput generation of large amounts of cell biology data. The hardware consists of an automatic XY-stage for moving a multiwell plate containing growing cells; a perfusion manifold allowing application of up to 8 different solutions; and a small epifluorescent microscope. It is extremely cheap (approximately {pound}400 without and {pound}2500 with a fluorescent microscope) and is easily customizable for individual experimental needs. We demonstrate the usability of this platform with high-throughput Ca2+ imaging and large-scale labelling experiments. Key points- We present an open source framework for automation of cell biology experiments - The framework consists of an XY platform, application of up to 8 solutions and a small epifluorescent microscope with autofocusing - Very cheap ({pound}400 without a fluorescent microscope and {pound}2500 with a fluorescent microscope), customisable, - Can be used in a variety of biological applications such as imaging of fluorescent reporters, optimisation of treatment conditions and fluorescent labelling

PDFDOI

02 /Specification & Classification

Click any tag to browse matching papers

Reproducibility ledger

Nobody has reported trying to reproduce this paper yet. Did you replicate an experiment or run the code? Your report saves the next lab a week.

Sign in to file a reproducibility report.

Similarity Map
SelectedSame fieldCross-field
THISOuyang '21Zehrer '23Wiener '23Luo '21Courville '25Almada '18
71% semantic matchCell Biology
W. Ouyang, R. Bowman, H. Wang+5 more·bioRxiv·Jun 24, 2021