Nerve cells can be injured by a variety of diseases and conditions.  Some types of injury damage the part of the cell known as dendrites, which are the structures in a nerve cell that act as the antennae to receive signals from the environment or from other nerve cells.  After injury, dendrite branches can regrow robustly, but the regenerated shape is very different from what you would see in an uninjured neuron.  Genetic mutants cause differences in a single feature of neuron shape, but dendrite injury and regeneration cause multiple changes to many aspects of dendrite shape all at once. These dramatic changes in cell shape after regeneration mean that automated software programs which work beautifully on images of uninjured neurons fall apart when working on images of regenerated neurons.

In order to address this bottleneck for the field, recent Dunlop School undergraduate student Carolee Nguyen, BS, and Dr Katherine Thompson-Peer, PhD, of the department of Developmental and Cell Biology, ran a huge dataset of images of neurons through various different software pipelines, to see which approaches worked best on these challenging cells.  Ms Nguyen presented an early version of this project at the 4th RIKEN Center for Computational Science High Performance Computing Youth Workshop on Feb 2020 in Kobe, Japan. She was one of only 5 international students to earn a full-ride travel fellowship, and the only undergraduate student to attend or present (the other domestic and international attendees and presenters were all graduate students and postdocs).  The authors found that, compared to other approaches, the Imaris image analysis platform which they were able to access at the UC Irvine Optical Biology Core, worked best.  Their findings have just been published in the journal Neuroinformatics (Aug 3, 2021).  This work was supported by the UC Irvine Undergraduate Research Opportunities Program (UROP) to CN and by the NIH’s National Institute of Neurological Disease and Stroke to KTP.  Ms Nguyen was awarded her bachelor’s degree from UC Irvine at the end of summer 2020, and is starting a graduate program in Bioinformatics at the NYU School of Engineering this coming fall 2021.