Switching from weak to strong cortical attachment of microtubules accounts for the transition from nuclear centration to spindle elongation in metazoans.

The centrosome is a major microtubule organizing center in animal cells. The position of the centrosomes inside the cell is important for cell functions such as cell cycle, and thus should be tightly regulated. Theoretical models based on the forces generated along the microtubules have been proposed to account for the dynamic movements of the centrosomes during the cell cycle. These models, however, often adopted inconsistent assumptions to explain distinct but successive movements, thus preventing a unified model for centrosome positioning. For the centration of the centrosomes, weak attachment of the astral microtubules to the cell cortex was assumed. In contrast, for the separation of the centrosomes during spindle elongation, strong attachment was assumed. Here, we mathematically analyzed these processes at steady state and found that the different assumptions are proper for each process. We experimentally validated our conclusion using nematode and sea urchin embryos by manipulating their shapes. Our results suggest the existence of a molecular mechanism that converts the cortical attachment from weak to strong during the transition from centrosome centration to spindle elongation.

Drug-target identification in COVID-19 disease mechanisms using computational systems biology approaches.

Introduction: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Methods: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. Results: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. Discussion: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Intercellular interaction mechanisms promote diversity in intracellular ATP concentration in Escherichia coli populations.

In fluctuating environments, many microorganisms acquire phenotypic heterogeneity as a survival tactic to increase the likelihood of survival of the overall population. One example of this interindividual heterogeneity is the diversity of ATP concentration among members of Escherichia coli populations under glucose deprivation. Despite the importance of such environmentally driven phenotypic heterogeneity, how the differences in intracellular ATP concentration emerge among individual E. coli organisms is unknown. In this study, we focused on the mechanism through which individual E. coli achieve high intracellular ATP concentrations. First, we measured the ATP retained by E. coli over time when cultured at low (0.1 mM) and control (22.2 mM) concentrations of glucose and obtained the chronological change in ATP concentrations. Then, by comparing these chronological change of ATP concentrations and analyzing whether stochastic state transitions, periodic oscillations, cellular age, and intercellular communication-which have been reported as molecular biological mechanisms for generating interindividual heterogeneity-are involved, we showed that the appearance of high ATP-holding individuals observed among E. coli can be explained only by intercellular transmission. By performing metabolomic analysis of post-culture medium, we revealed a significant increase in the ATP, especially at low glucose, and that the number of E. coli that retain significantly higher ATP can be controlled by adding large amounts of ATP to the medium, even in populations cultured under control glucose concentrations. These results reveal for the first time that ATP-mediated intercellular transmission enables some individuals in E. coli populations grown at low glucose to retain large amounts of ATP.

COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

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.

3D convolutional neural networks-based segmentation to acquire quantitative criteria of the nucleus during mouse embryogenesis.

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.

Cellular thermogenesis compensates environmental temperature fluctuations for maintaining intracellular temperature.

Temperature governs states and dynamics of all biological molecules, and several cellular processes are often heat sources and/or sinks. Technical achievement of intracellular thermometry enables us to measure intracellular temperature, and it can offer novel perspectives in biology and medicine. However, little is known that changes of intracellular temperature throughout the cell-cycle and the manner of which cells regulates their thermogenesis in response to fluctuation of the environmental temperature. Here, cell-cycle-dependent changes of intracellular temperature were reconstructed from the snapshots of cell population at single-cell resolution using ergodic analysis for asynchronously cultured HeLa cells expressing a genetically encoded thermometry. Intracellular temperature is highest at G1 phase, and it gradually decreases along cell-cycle progression and increases abruptly during mitosis. Cells easily heated up are harder to cool down and vice versa, especially at G1/S phases. Together, intracellular thermogenesis depends on cell-cycle phases and it maintains intracellular temperature through compensating environmental temperature fluctuations.

Identification of a master transcription factor and a regulatory mechanism for desiccation tolerance in the anhydrobiotic cell line Pv11.

Water is essential for living organisms. Terrestrial organisms are incessantly exposed to the stress of losing water, desiccation stress. Avoiding the mortality caused by desiccation stress, many organisms acquired molecular mechanisms to tolerate desiccation. Larvae of the African midge, Polypedilum vanderplanki, and its embryonic cell line Pv11 tolerate desiccation stress by entering an ametabolic state, anhydrobiosis, and return to active life after rehydration. The genes related to desiccation tolerance have been comprehensively analyzed, but transcriptional regulatory mechanisms to induce these genes after desiccation or rehydration remain unclear. Here, we comprehensively analyzed the gene regulatory network in Pv11 cells and compared it with that of Drosophila melanogaster, a desiccation sensitive species. We demonstrated that nuclear transcription factor Y subunit gamma-like, which is important for drought stress tolerance in plants, and its transcriptional regulation of downstream positive feedback loops have a pivotal role in regulating various anhydrobiosis-related genes. This study provides an initial insight into the systemic mechanism of desiccation tolerance.

XitoSBML: A Modeling Tool for Creating Spatial Systems Biology Markup Language Models From Microscopic Images.

XitoSBML is a software tool designed to create an SBML (Systems Biology Markup Language) Level 3 Version 1 document from microscopic cellular images. It is implemented as an ImageJ plug-in and is designed to create spatial models that reflect the three-dimensional cellular geometry. With XitoSBML, users can perform spatial model simulations based on realistic cellular geometry by using SBML-supported software tools, including simulators such as Virtual Cell and Spatial Simulator. XitoSBML is open-source and is available at https://github.com/spatialsimulator/XitoSBML/. XitoSBML is confirmed to run on most 32/64-bit operating systems: Windows, MacOS, and Linux.

Predicting the future direction of cell movement with convolutional neural networks.

Image-based deep learning systems, such as convolutional neural networks (CNNs), have recently been applied to cell classification, producing impressive results; however, application of CNNs has been confined to classification of the current cell state from the image. Here, we focused on cell movement where current and/or past cell shape can influence the future cell movement. We demonstrate that CNNs prospectively predicted the future direction of cell movement with high accuracy from a single image patch of a cell at a certain time. Furthermore, by visualizing the image features that were learned by the CNNs, we could identify morphological features, e.g., the protrusions and trailing edge that have been experimentally reported to determine the direction of cell movement. Our results indicate that CNNs have the potential to predict the future direction of cell movement from current cell shape, and can be used to automatically identify those morphological features that influence future cell movement.

Activation of cell migration via morphological changes in focal adhesions depends on shear stress in MYCN-amplified neuroblastoma cells.

Neuroblastoma is the most common solid tumour of childhood, and it metastasizes to distant organs. However, the mechanism of metastasis, which generally depends on the cell motility of the neuroblastoma, remains unclear. In many solid tumours, it has been reported that shear stress promotes metastasis. Here, we investigated the relationship between shear stress and cell motility in the MYCN-amplified human neuroblastoma cell line IMR32, using a microfluidic device. We confirmed that most of the cells migrated downstream, and cell motility increased dramatically when the cells were exposed to a shear stress of 0.4 Pa, equivalent to that expected in vivo. We observed that the morphological features of focal adhesion were changed under a shear stress of 0.4 Pa. We also investigated the relationship between malignancy and the motility of IMR32 cells under shear stress. Decreasing the expression of MYCN in IMR32 cells via siRNA transfection inhibited cell motility by a shear stress of 0.4 Pa. These results suggest that MYCN-amplified neuroblastoma cells under high shear stress migrate to distant organs due to high cell motility, allowing cell migration to lymphatic vessels and venules.

Quantitative analysis of sensitivity to a Wnt3a gradient in determination of the pole-to-pole axis of mitotic cells by using a microfluidic device.

Proper determination of the cell division axis is essential during development. Wnt3a is a known regulator of the cell division axis; however, the sensitivity of cells to Wnt3a signalling and its role in determining the cell division axis have not been measured to date. To address this gap, we took advantage of the asymmetric distribution of outer dense fibre 2 (ODF2/cenexin) proteins on centrosomes in dividing cells. To precisely quantify the sensitivity of cells to Wnt3a signalling, we developed a microfluidic cell culture device, which can produce a quantitative gradient of signalling molecules. We confirmed that mitotic SH-SY5Y neuroblastoma cells could detect a 2.5 ~ 5 × 10-3 nm·µm-1 Wnt3a concentration gradient and demonstrated that this gradient is sufficient to affect the determination of the pole-to-pole axis of cell division during the later stages of mitosis.

Transcriptome analysis of the anhydrobiotic cell line Pv11 infers the mechanism of desiccation tolerance and recovery.

The larvae of the African midge, Polypedilum vanderplanki, can enter an ametabolic state called anhydrobiosis to overcome fatal desiccation stress. The Pv11 cell line, derived from P. vanderplanki embryo, shows desiccation tolerance when treated with trehalose before desiccation and resumes proliferation after rehydration. However, the molecular mechanisms of this desiccation tolerance remain unknown. Here, we performed high-throughput CAGE-seq of mRNA and a differentially expressed gene analysis in trehalose-treated, desiccated, and rehydrated Pv11 cells, followed by gene ontology analysis of the identified differentially expressed genes. We detected differentially expressed genes after trehalose treatment involved in various stress responses, detoxification of harmful chemicals, and regulation of oxidoreduction that were upregulated. In the desiccation phase, L-isoaspartyl methyltransferase and heat shock proteins were upregulated and ribosomal proteins were downregulated. Analysis of differentially expressed genes during rehydration supported the notion that homologous recombination, nucleotide excision repair, and non-homologous recombination were involved in the recovery process. This study provides initial insights into the molecular mechanisms underlying the extreme desiccation tolerance of Pv11 cells.

Detection of Temperature Difference in Neuronal Cells.

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.

Acceleration of discrete stochastic biochemical simulation using GPGPU.

For systems made up of a small number of molecules, such as a biochemical network in a single cell, a simulation requires a stochastic approach, instead of a deterministic approach. The stochastic simulation algorithm (SSA) simulates the stochastic behavior of a spatially homogeneous system. Since stochastic approaches produce different results each time they are used, multiple runs are required in order to obtain statistical results; this results in a large computational cost. We have implemented a parallel method for using SSA to simulate a stochastic model; the method uses a graphics processing unit (GPU), which enables multiple realizations at the same time, and thus reduces the computational time and cost. During the simulation, for the purpose of analysis, each time course is recorded at each time step. A straightforward implementation of this method on a GPU is about 16 times faster than a sequential simulation on a CPU with hybrid parallelization; each of the multiple simulations is run simultaneously, and the computational tasks within each simulation are parallelized. We also implemented an improvement to the memory access and reduced the memory footprint, in order to optimize the computations on the GPU. We also implemented an asynchronous data transfer scheme to accelerate the time course recording function. To analyze the acceleration of our implementation on various sizes of model, we performed SSA simulations on different model sizes and compared these computation times to those for sequential simulations with a CPU. When used with the improved time course recording function, our method was shown to accelerate the SSA simulation by a factor of up to 130.

High-speed microscopy with an electrically tunable lens to image the dynamics of in vivo molecular complexes.

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.

A proteomic study of mitotic phase-specific interactors of EB1 reveals a role for SXIP-mediated protein interactions in anaphase onset.

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.

Assessing uncertainty in model parameters based on sparse and noisy experimental data.

To perform parametric identification of mathematical models of biological events, experimental data are rare to be sufficient to estimate target behaviors produced by complex non-linear systems. We performed parameter fitting to a cell cycle model with experimental data as an in silico experiment. We calibrated model parameters with the generalized least squares method with randomized initial values and checked local and global sensitivity of the model. Sensitivity analyses showed that parameter optimization induced less sensitivity except for those related to the metabolism of the transcription factors c-Myc and E2F, which are required to overcome a restriction point (R-point). We performed bifurcation analyses with the optimized parameters and found the bimodality was lost. This result suggests that accumulation of c-Myc and E2F induced dysfunction of R-point. We performed a second parameter optimization based on the results of sensitivity analyses and incorporating additional derived from recent in vivo data. This optimization returned the bimodal characteristics of the model with a narrower range of hysteresis than the original. This result suggests that the optimized model can more easily go through R-point and come back to the gap phase after once having overcome it. Two parameter space analyses showed metabolism of c-Myc is transformed as it can allow cell bimodal behavior with weak stimuli of growth factors. This result is compatible with the character of the cell line used in our experiments. At the same time, Rb, an inhibitor of E2F, can allow cell bimodal behavior with only a limited range of stimuli when it is activated, but with a wider range of stimuli when it is inactive. These results provide two insights; biologically, the two transcription factors play an essential role in malignant cells to overcome R-point with weaker growth factor stimuli, and theoretically, sparse time-course data can be used to change a model to a biologically expected state.