For a better understanding of the mechanisms behind cellular functions, quantification of the heterogeneity in an organism or cells is essential. Recently, the importance of quantifying temperature has been highlighted, as it correlates with biochemical reaction rates. Several methods for detecting intracellular temperature have recently been established. Here we develop a novel method for sensing temperature in living cells based on the imaging technique of fluorescence of quantum dots. We apply the method to quantify the temperature difference in a human derived neuronal cell line, SH-SY5Y. Our results show that temperatures in the cell body and neurites are different and thus suggest that inhomogeneous heat production and dissipation happen in a cell. We estimate that heterogeneous heat dissipation results from the characteristic shape of neuronal cells, which consist of several compartments formed with different surface-volume ratios. Inhomogeneous heat production is attributable to the localization of specific organelles as the heat source.

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS‐CoV‐2 infection, improving data interpretation and predicting key targets of intervention. Here, we describe a large‐scale community effort to build an open access, interoperable and computable repository of COVID‐19 molecular mechanisms. The COVID‐19 Disease Map (C19DMap) is a graphical, interactive representation of disease‐relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph‐based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS‐CoV‐2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID‐19 or similar pandemics in the long‐term perspective.

Microtubules execute diverse mitotic events that are spatially and temporally separated; the underlying regulation is poorly understood. By combining drug treatments, large-scale immunoprecipitation and mass spectrometry, we report the first comprehensive map of mitotic phase-specific protein interactions of the microtubule-end binding protein, EB1. EB1 interacts with some, but not all, of its partners throughout mitosis. We show that the interaction of EB1 with Astrin-SKAP complex, a key regulator of chromosome segregation, is enhanced during prometaphase, compared to anaphase. We find that EB1 and EB3, another EB family member, can interact directly with SKAP, in an SXIP-motif dependent manner. Using an SXIP defective mutant that cannot interact with EB, we uncover two distinct pools of SKAP at spindle microtubules and kinetochores. We demonstrate the importance of SKAP's SXIP-motif in controlling microtubule growth rates and anaphase onset, without grossly disrupting spindle function. Thus, we provide the first comprehensive map of temporal changes in EB1 interactors during mitosis and highlight the importance of EB protein interactions in ensuring normal mitosis.

We provide an evaluation for an electrically tunable lens (ETL), combined with a microscope system, from the viewpoint of tracking intracellular protein complexes. We measured the correlation between the quantitative axial focus shift and the control current for ETL, and determined the stabilization time for refocusing to evaluate the electrical focusing behaviour of our system. We also confirmed that the change of relative magnification by the lens and associated resolution does not influence the ability to find intracellular targets. By applying the ETL system to observe intracellular structures and protein complexes, we confirmed that this system can obtain 10 nm order z-stacks, within video rate, while maintaining the quality of images and that this system has sufficient optical performance to detect the molecules.

During embryogenesis, cells repeatedly divide and dynamically change their positions in three-dimensional (3D) space. A robust and accurate algorithm to acquire the 3D positions of the cells would help to reveal the mechanisms of embryogenesis. To acquire quantitative criteria of embryogenesis from time-series 3D microscopic images, image processing algorithms such as segmentation have been applied. Because the cells in embryos are considerably crowded, an algorithm to segment individual cells in detail and accurately is needed. To quantify the nuclear region of every cell from a time-series 3D fluorescence microscopic image of living cells, we developed QCANet, a convolutional neural network-based segmentation algorithm for 3D fluorescence bioimages. We demonstrated that QCANet outperformed 3D Mask R-CNN, which is currently considered as the best algorithm of instance segmentation. We showed that QCANet can be applied not only to developing mouse embryos but also to developing embryos of two other model species. Using QCANet, we were able to extract several quantitative criteria of embryogenesis from 11 early mouse embryos. We showed that the extracted criteria could be used to evaluate the differences between individual embryos. This study contributes to the development of fundamental approaches for assessing embryogenesis on the basis of extracted quantitative criteria.

Rcd1, initially identified as a factor essential for the commitment to nitrogen starvation‐invoked differentiation in fission yeast, is one of the most conserved proteins found across eukaryotes, and its mammalian homolog is expressed in a variety of differentiating tissues. Here we show that mammalian Rcd1 is a novel transcriptional cofactor and is critically involved in the commitment step in the retinoic acid‐induced differentiation of F9 mouse teratocarcinoma cells, at least in part, via forming complexes with retinoic acid receptor and activation transcription factor‐2 (ATF‐2). In addition, antisense oligonucleotide treatment of embryonic mouse lung explants suggests that Rcd1 also plays a role in retinoic acid‐controlled lung development.