Measuring and modeling the dynamics of mitotic error correction.

Error correction is central to many biological systems and is critical for protein function and cell health. During mitosis, error correction is required for the faithful inheritance of genetic material. When functioning properly, the mitotic spindle segregates an equal number of chromosomes to daughter cells with high fidelity. Over the course of spindle assembly, many initially erroneous attachments between kinetochores and microtubules are fixed through the process of error correction. Despite the importance of chromosome segregation errors in cancer and other diseases, there is a lack of methods to characterize the dynamics of error correction and how it can go wrong. Here, we present an experimental method and analysis framework to quantify chromosome segregation error correction in human tissue culture cells with live cell confocal imaging, timed premature anaphase, and automated counting of kinetochores after cell division. We find that errors decrease exponentially over time during spindle assembly. A coarse-grained model, in which errors are corrected in a chromosome-autonomous manner at a constant rate, can quantitatively explain both the measured error correction dynamics and the distribution of anaphase onset times. We further validated our model using perturbations that destabilized microtubules and changed the initial configuration of chromosomal attachments. Taken together, this work provides a quantitative framework for understanding the dynamics of mitotic error correction.

A coarse-grained NADH redox model enables inference of subcellular metabolic fluxes from fluorescence lifetime imaging.

Mitochondrial metabolism is of central importance to diverse aspects of cell and developmental biology. Defects in mitochondria are associated with many diseases, including cancer, neuropathology, and infertility. Our understanding of mitochondrial metabolism in situ and dysfunction in diseases are limited by the lack of techniques to measure mitochondrial metabolic fluxes with sufficient spatiotemporal resolution. Herein, we developed a new method to infer mitochondrial metabolic fluxes in living cells with subcellular resolution from fluorescence lifetime imaging of NADH. This result is based on the use of a generic coarse-grained NADH redox model. We tested the model in mouse oocytes and human tissue culture cells subject to a wide variety of perturbations by comparing predicted fluxes through the electron transport chain (ETC) to direct measurements of oxygen consumption rate. Interpreting the fluorescence lifetime imaging microscopy measurements of NADH using this model, we discovered a homeostasis of ETC flux in mouse oocytes: perturbations of nutrient supply and energy demand of the cell do not change ETC flux despite significantly impacting NADH metabolic state. Furthermore, we observed a subcellular spatial gradient of ETC flux in mouse oocytes and found that this gradient is primarily a result of a spatially heterogeneous mitochondrial proton leak. We concluded from these observations that ETC flux in mouse oocytes is not controlled by energy demand or supply, but by the intrinsic rates of mitochondrial respiration.