PT  - JOURNAL ARTICLE
AU  - Martin Hailstone
AU  - Lu Yang
AU  - Dominic Waithe
AU  - Tamsin J Samuels
AU  - Yoav Arava
AU  - Tomasz Dobrzycki
AU  - Richard M Parton
AU  - Ilan Davis
TI  - Brain development: machine learning analysis of individual stem cells in live 3D tissue
AID  - 10.1101/137406
DP  - 2017 Jan 01
TA  - bioRxiv
PG  - 137406
4099  - http://biorxiv.org/content/early/2017/05/14/137406.short
4100  - http://biorxiv.org/content/early/2017/05/14/137406.full
AB  - We have optimised imaging of explanted Drosophila brains and developed novel 4D machine learning image analysis software that out performs existing methods in characterising brain malformation mutants. Our new techniques can be applied widely to analyse the development of complex tissues in terms of the behaviour of individual cells.HighlightsTime-lapse imaging of developing ex-vivo cultured brains in excess of 30 hoursQBrain: machine learning quantitation of cell types and division in complex tissueOutperforms other state-of-the-art machine learning image analysis toolsAutomated characterisation of cause of a complex enlarged mutant brain phenotypeSUMMARY Brain malformations often result from subtle changes in neural stem cell behaviour, which are difficult to characterise using current methods on fixed material. Here, we tackle this issue by establishing optimised approaches for extended 3D time-lapse imaging of living explanted Drosophila brains and developing QBrain image analysis software, a novel implementation of supervised machine learning. We combined these tools to investigate brain enlargement of a previously difficult to characterise mutant phenotype, identifying a defect in developmental timing. QBrain significantly outperforms existing freely available state-of-the-art image analysis approaches in accuracy and speed of cell identification, determining cell number, location, density and division rate from large 3D time-lapse datasets. Our use of QBrain illustrates its wide applicability to characterise development in complex tissue, such as tumours or organoids, in terms of the behaviour in 3D of individual cells in their native environment.