The female meiotic spindles of most animals are acentrosomal and undergo striking morphological changes while transitioning from metaphase to anaphase. The ultra-structure of acentrosomal spindles, and how changes to this structure correlate with such dramatic spindle rearrangements remains largely unknown. To address this, we applied light microscopy, large-scale electron tomography and mathematical modeling of female meiotic C. elegans spindles undergoing the transition from metaphase to anaphase. Combining these approaches, we find that meiotic spindles are dynamic arrays of short microtubules that turn over on second time scales. The results show that the transition from metaphase to anaphase correlates with an increase in the number of microtubules and a decrease in their average length. Detailed analysis of the tomographic data revealed that the length of microtubules changes significantly during the metaphase-to-anaphase transition. This effect is most pronounced for those microtubules located within 150 nm of the chromosome surface. To understand the mechanisms that drive this transition, we developed a mathematical model for the microtubule length distribution that considers microtubule growth, catastrophe, and severing. Using Bayesian inference to compare model predictions and data, we find that microtubule turn-over is the major driver of the observed large-scale reorganizations. Our data suggest that in metaphase only a minor fraction of microtubules, those that are closest to the chromosomes, are severed. The large majority of microtubules, which are not in close contact with chromosomes, do not undergo severing. Instead, their length distribution is fully explained by growth and catastrophe alone. In anaphase, even microtubules close to the chromosomes show no signs of cutting. This suggests that the most prominent drivers of spindle rearrangements from metaphase to anaphase are changes in nucleation and catastrophe rate. In addition, we provide evidence that microtubule severing is dependent on the presence of katanin.
Electron microscopy models of microtubules and chromosome surfaces will be made available on Dryad under doi.org/10.5061/dryad.x3ffbg7k5. Example data and analysis code is available at https://github.com/SebastianFuerthauer/SpindleRerrangement
C. elegans meiotic spindlesDryad Digital Repository, doi.org/10.5061/dryad.x3ffbg7k5.
Meiosis I spindles of Metaphase, early Anaphase and Anaphasehttps://www.cell.com/current-biology/fulltext/S0960-9822(18)30911-4?_returnURL=https%3A%2F%2Flinkinghub.elsevier.com%2Fretrieve%2Fpii%2FS0960982218309114%3Fshowall%3Dtrue.
- Ina Lantzsch
- Ina Lantzsch
- Erik Szentgyoergyi
- Stefanie Redemann
- Martin Srayko
- Che-Hang Yu
- Che-Hang Yu
- Che-Hang Yu
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
- Thomas Surrey, Centre for Genomic Regulation (CRG), Spain
© 2021, Lantzsch et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
mTORC1 senses nutrients and growth factors and phosphorylates downstream targets, including the transcription factor TFEB, to coordinate metabolic supply and demand. These functions position mTORC1 as a central controller of cellular homeostasis, but the behavior of this system in individual cells has not been well characterized. Here, we provide measurements necessary to refine quantitative models for mTORC1 as a metabolic controller. We developed a series of fluorescent protein-TFEB fusions and a multiplexed immunofluorescence approach to investigate how combinations of stimuli jointly regulate mTORC1 signaling at the single-cell level. Live imaging of individual MCF10A cells confirmed that mTORC1-TFEB signaling responds continuously to individual, sequential, or simultaneous treatment with amino acids and the growth factor insulin. Under physiologically relevant concentrations of amino acids, we observe correlated fluctuations in TFEB, AMPK, and AKT signaling that indicate continuous activity adjustments to nutrient availability. Using partial least squares regression modeling, we show that these continuous gradations are connected to protein synthesis rate via a distributed network of mTORC1 effectors, providing quantitative support for the qualitative model of mTORC1 as a homeostatic controller and clarifying its functional behavior within individual cells.