ABSTRACT
Time-lapse microscopy is the only method that can directly capture the dynamics and heterogeneity of fundamental cellular processes at the single-cell level with high temporal resolution. Successful application of single-cell time-lapse microscopy requires automated segmentation and tracking of hundreds of individual cells over several time points. However, segmentation and tracking of single cells remain challenging for the analysis of time-lapse microscopy images, in particular for widely available and non-toxic imaging modalities such as phase-contrast imaging. This work presents a versatile and trainable deep-learning model, termed DeepSea, that allows for both segmentation and tracking of single cells in sequences of phase-contrast live microscopy images with higher precision than existing models. We showcase the application of DeepSea by analyzing cell size regulation in embryonic stem cells.
Subject(s)
Deep Learning , Microscopy , Time-Lapse Imaging/methods , Microscopy, Phase-ContrastABSTRACT
Nonsense-mediated mRNA decay (NMD) protects cells from the toxic and potentially dominant effects of truncated proteins. Targeting of mRNAs with early stop codons is mediated by the ribosome and spatiotemporally aligned with translation termination. Previously we identified a novel NMD intermediate: ribosomes stalled on cleaved stop codons, raising the possibility that NMD begins even prior to ribosome removal from the stop codon. Here we show that this intermediate is the result of mRNA cleavage by the endonuclease SMG-6. Our work supports a model in which ribosomes stall secondary to SMG-6 mRNA cleavage in Caenorhabditis elegans and humans, i.e. that the novel NMD intermediate occurs after a prior ribosome elicits NMD. Our genetic analysis of C. elegans' SMG-6 supports a central role for SMG-6 in metazoan NMD, and provides a context for evaluating its function in other metazoans.