Mercat, B. | Search bioRxiv

bioRxiv2024

The Roboscope: Smart and Fast Microscopy for Generic Event-Driven Acquisition

Automation of fluorescence microscopy is a challenge for capturing rare or transient events in biology and medicine. It relies on smart devices that integrate and interpret the observed data, and react to the targeted biological event. We report on the Roboscope, a novel autonomous microscope combining sequence interruption and deep learning integration, allowing generic event-driven acquisitions. This system distinguishes itself by its adaptability to various experiments, quick capture of dynamic events, and minimal data greediness - training with less than 100 images per class. The Roboscopes capability is demonstrated in non-synchronized cells by capturing the metaphase, a 20-minute event happening once per day or less. Conversely, double thymidine-block synchronisation, despite occurring during DNA replication, may perturb mitotic-spindle mechanics. The Roboscopes versatility and efficiency offer significant advancements to tackle the current challenges of cell biology, spreading out advanced microscopy methods to fundamental research as well as high content screening and precision medicine.

bioengineering↗

bioRxiv2023

Only three principal components account for inter-embryo variability of the spindle length over time.

How to quantify inter-individual variability? When measuring many features per experiment/individual, this question becomes non-trivial. One challenge lies in choosing features to recapitulate high-dimensional data. This paper focuses on spindle elongation phenotypes to highlight how a data-driven approach can help tackle this challenge. We showed that only three typical elongation patterns describe spindle elongation in C. elegans one-cell embryo. We called them archetypes. These archetypes were automatically extracted from the experimental data using principal component analysis (PCA) rather than defined a priori. They accounted for more than 95% of inter-individual variability in a dataset of more than 1600 experiments across more than 100 different experimental conditions (RNAi, mutants, changes in temperature, etc.). The two first archetypes were consistent with standard measures in the field, namely the average spindle length and the spindle elongation rate in late metaphase and anaphase. However, our archetypes were not strictly corresponding to these classic, manually-set, features. The third archetype, accounting for 6% of the variability, was novel and corresponded to a transient spindle shortening in late metaphase. We revealed that it is part of spindle elongation dynamics in all conditions. It is reminiscent of the spindle elongation pattern observed upon kinetochore function defects. Interestingly, because these archetypes were all three present from metaphase on, it implied that spindle elongation around the anaphase onset is sufficient to predict its late anaphase length. We validated this idea using a machine-learning approach. The inter-individual differences between embryos depleted from cell division-related proteins have the same underlying nature as inter-individual differences naturally arising between wild-type embryos. The same conclusion holds also when analysing embryos dividing at various temperatures. We thus propose that beyond the apparent complexity of the spindle and variability in the phenotypes of various gene depletions, only three independent mechanisms account for spindle elongation, weighted differently in the various conditions; meanwhile, no mechanism is specific to any condition. As such, given amounts of these three archetypes could represent a quantitative phenotype.

bioinformatics↗