Cytoplasmic fluidization contributes to breaking spore dormancy in fission yeast.

The cytoplasm is a complex, crowded environment that influences myriad cellular processes including protein folding and metabolic reactions. Recent studies have suggested that changes in the biophysical properties of the cytoplasm play a key role in cellular homeostasis and adaptation. However, it still remains unclear how cells control their cytoplasmic properties in response to environmental cues. Here, we used fission yeast spores as a model system of dormant cells to elucidate the mechanisms underlying regulation of the cytoplasmic properties. By tracking fluorescent tracer particles, we found that particle mobility decreased in spores compared to vegetative cells and rapidly increased at the onset of dormancy breaking upon glucose addition. This cytoplasmic fluidization depended on glucose-sensing via the cyclic adenosine monophosphate-protein kinase A pathway. PKA activation led to trehalose degradation through trehalase Ntp1, thereby increasing particle mobility as the amount of trehalose decreased. In contrast, the rapid cytoplasmic fluidization did not require de novo protein synthesis, cytoskeletal dynamics, or cell volume increase. Furthermore, the measurement of diffusion coefficients with tracer particles of different sizes suggests that the spore cytoplasm impedes the movement of larger protein complexes (40 to 150 nm) such as ribosomes, while allowing free diffusion of smaller molecules (~3 nm) such as second messengers and signaling proteins. Our experiments have thus uncovered a series of signaling events that enable cells to quickly fluidize the cytoplasm at the onset of dormancy breaking.

A transcriptional program underlying the circannual rhythms of gonadal development in medaka.

To cope with seasonal environmental changes, organisms have evolved approximately 1-y endogenous circannual clocks. These circannual clocks regulate various physiological properties and behaviors such as reproduction, hibernation, migration, and molting, thus providing organisms with adaptive advantages. Although several hypotheses have been proposed, the genes that regulate circannual rhythms and the underlying mechanisms controlling long-term circannual clocks remain unknown in any organism. Here, we show a transcriptional program underlying the circannual clock in medaka fish (Oryzias latipes). We monitored the seasonal reproductive rhythms of medaka kept under natural outdoor conditions for 2 y. Linear regression analysis suggested that seasonal changes in reproductive activity were predominantly determined by an endogenous program. Medaka hypothalamic and pituitary transcriptomes were obtained monthly over 2 y and daily on all equinoxes and solstices. Analysis identified 3,341 seasonally oscillating genes and 1,381 daily oscillating genes. We then examined the existence of circannual rhythms in medaka via maintaining them under constant photoperiodic conditions. Medaka exhibited approximately 6-mo free-running circannual rhythms under constant conditions, and monthly transcriptomes under constant conditions identified 518 circannual genes. Gene ontology analysis of circannual genes highlighted the enrichment of genes related to cell proliferation and differentiation. Altogether, our findings support the "histogenesis hypothesis" that postulates the involvement of tissue remodeling in circannual time-keeping.

FGF signaling induces the regeneration of collagen fiber structure during skin wound healing in axolotls.

Axolotls have been considered to be able to regenerate their skin completely. Our recent study updated this theory with the finding that the lattice structure of dermal collagen fibers was not fully regenerated after skin injury. We also discovered that nerves induce the regeneration of collagen fibers. The mechanism of collagen fiber regeneration remains unknown, however. In this study, we focused on the structure of collagen fibers with collagen braiding cells, and cell origin in axolotl skin regeneration. In the wounded dermis, cells involved in skin repair/regeneration were derived from both the surrounding dermis and the subcutaneous tissue. Regardless of cell origin, cells acquired the proper cell morphology to braid collagen fiber with nerve presence. We also found that FGF signaling could substitute for the nerve roles in the conversion of subcutaneous fibroblasts to lattice-shaped dermal fibroblasts. Our findings contribute to the elucidation of the fundamental mechanisms of true skin regeneration and provide useful insights for pioneering new skin treatments.

Shedding light on developmental ERK signaling with genetically encoded biosensors.

The extracellular signal-regulated kinase (ERK) pathway governs cell proliferation, differentiation and migration, and therefore plays key roles in various developmental and regenerative processes. Recent advances in genetically encoded fluorescent biosensors have unveiled hitherto unrecognized ERK activation dynamics in space and time and their functional importance mainly in cultured cells. However, ERK dynamics during embryonic development have still only been visualized in limited numbers of model organisms, and we are far from a sufficient understanding of the roles played by developmental ERK dynamics. In this Review, we first provide an overview of the biosensors used for visualization of ERK activity in live cells. Second, we highlight the applications of the biosensors to developmental studies of model organisms and discuss the current understanding of how ERK dynamics are encoded and decoded for cell fate decision-making.

Circadian Clock Controls Root Hair Elongation through Long-Distance Communication.

Plants adapt to periodic environmental changes, such as day and night, by using circadian clocks. Cell division and elongation are primary steps to adjust plant development according to their environments. In Arabidopsis, hypocotyl elongation has been studied as a representative model to understand how the circadian clock regulates cell elongation. However, it remains unknown whether similar phenomena exist in other organs, such as roots, where circadian clocks regulate physiological responses. Here, we show that root hair elongation is controlled by both light and the circadian clock. By developing machine-learning models to automatically analyze the images of root hairs, we found that genes encoding major components of the central oscillator, such as TIMING OF CAB EXPRESSION1 (TOC1) or CIRCADIAN CLOCK ASSOCIATED1 (CCA1), regulate the rhythmicity of root hair length. The partial illumination of light to either shoots or roots suggested that light received in shoots is mainly responsible for the generation of root hair rhythmicity. Furthermore, grafting experiments between wild-type (WT) and toc1 plants demonstrated that TOC1 in shoots is responsible for the generation of root hair rhythmicity. Our results illustrate the combinational effects of long-distance signaling and the circadian clock on the regulation of root hair length.

Analysis of Plant-Specific ANTH Domain-Containing Protein in Marchantia polymorpha.

Membrane trafficking is a fundamental mechanism for protein and lipid transport in eukaryotic cells and exhibits marked diversity among eukaryotic lineages with distinctive body plans and lifestyles. Diversification of the membrane trafficking system is associated with the expansion and secondary loss of key machinery components, including RAB GTPases, soluble N-ethylmaleimide-sensitive factor attachment protein receptors (SNAREs) and adaptor proteins, during plant evolution. The number of AP180 N-terminal homology (ANTH) proteins, an adaptor family that regulates vesicle formation and cargo sorting during clathrin-mediated endocytosis, increases during plant evolution. In the genome of Arabidopsis thaliana, 18 genes for ANTH proteins have been identified, a higher number than that in yeast and animals, suggesting a distinctive diversification of ANTH proteins. Conversely, the liverwort Marchantia polymorpha possesses a simpler repertoire; only two genes encoding canonical ANTH proteins have been identified in its genome. Intriguingly, a non-canonical ANTH protein is encoded in the genome of M. polymorpha, which also harbors a putative kinase domain. Similar proteins have been detected in sporadic lineages of plants, suggesting their ancient origin and multiple secondary losses during evolution. We named this unique ANTH group phosphatidylinositol-binding clathrin assembly protein-K (PICALM-K) and characterized it in M. polymorpha using genetic, cell biology-based and artificial intelligence (AI)-based approaches. Our results indicate a flagella-related function of MpPICALM-K in spermatozoids, which is distinct from that of canonical ANTH proteins. Therefore, ANTH proteins have undergone significant functional diversification during evolution, and PICALM-K represents a plant-unique ANTH protein that is delivered by neofunctionalization through exon shuffling.

Harnessing Deep Learning to Analyze Cryptic Morphological Variability of Marchantia polymorpha.

Characterizing phenotypes is a fundamental aspect of biological sciences, although it can be challenging due to various factors. For instance, the liverwort Marchantia polymorpha is a model system for plant biology and exhibits morphological variability, making it difficult to identify and quantify distinct phenotypic features using objective measures. To address this issue, we utilized a deep-learning-based image classifier that can handle plant images directly without manual extraction of phenotypic features and analyzed pictures of M. polymorpha. This dioicous plant species exhibits morphological differences between male and female wild accessions at an early stage of gemmaling growth, although it remains elusive whether the differences are attributable to sex chromosomes. To isolate the effects of sex chromosomes from autosomal polymorphisms, we established a male and female set of recombinant inbred lines (RILs) from a set of male and female wild accessions. We then trained deep learning models to classify the sexes of the RILs and the wild accessions. Our results showed that the trained classifiers accurately classified male and female gemmalings of wild accessions in the first week of growth, confirming the intuition of researchers in a reproducible and objective manner. In contrast, the RILs were less distinguishable, indicating that the differences between the parental wild accessions arose from autosomal variations. Furthermore, we validated our trained models by an 'eXplainable AI' technique that highlights image regions relevant to the classification. Our findings demonstrate that the classifier-based approach provides a powerful tool for analyzing plant species that lack standardized phenotyping metrics.

In-Depth Quantification of Cell Division and Elongation Dynamics at the Tip of Growing Arabidopsis Roots Using 4D Microscopy, AI-Assisted Image Processing and Data Sonification.

One of the fundamental questions in plant developmental biology is how cell proliferation and cell expansion coordinately determine organ growth and morphology. An amenable system to address this question is the Arabidopsis root tip, where cell proliferation and elongation occur in spatially separated domains, and cell morphologies can easily be observed using a confocal microscope. While past studies revealed numerous elements of root growth regulation including gene regulatory networks, hormone transport and signaling, cell mechanics and environmental perception, how cells divide and elongate under possible constraints from cell lineages and neighboring cell files has not been analyzed quantitatively. This is mainly due to the technical difficulties in capturing cell division and elongation dynamics at the tip of growing roots, as well as an extremely labor-intensive task of tracing the lineages of frequently dividing cells. Here, we developed a motion-tracking confocal microscope and an Artificial Intelligence (AI)-assisted image-processing pipeline that enables semi-automated quantification of cell division and elongation dynamics at the tip of vertically growing Arabidopsis roots. We also implemented a data sonification tool that facilitates human recognition of cell division synchrony. Using these tools, we revealed previously unnoted lineage-constrained dynamics of cell division and elongation, and their contribution to the root zonation boundaries.

Near-infrared imaging in fission yeast using a genetically encoded phycocyanobilin biosynthesis system.

Near-infrared fluorescent protein (iRFP) is a bright and stable fluorescent protein with near-infrared excitation and emission maxima. Unlike the other conventional fluorescent proteins, iRFP requires biliverdin (BV) as a chromophore. Here, we report that phycocyanobilin (PCB) functions as a brighter chromophore for iRFP than BV, and that biosynthesis of PCB allows live-cell imaging with iRFP in the fission yeast Schizosaccharomyces pombe. We initially found that fission yeast cells did not produce BV and therefore did not show any iRFP fluorescence. The brightness of iRFP-PCB was higher than that of iRFP-BV both in vitro and in fission yeast. We introduced SynPCB2.1, a PCB biosynthesis system, into fission yeast, resulting in the brightest iRFP fluorescence. To make iRFP readily available in fission yeast, we developed an endogenous gene tagging system with iRFP and all-in-one integration plasmids carrying the iRFP-fused marker proteins together with SynPCB2.1. These tools not only enable the easy use of multiplexed live-cell imaging in fission yeast with a broader color palette, but also open the door to new opportunities for near-infrared fluorescence imaging in a wider range of living organisms. This article has an associated First Person interview with the first author of the paper.

Quantitative live-cell imaging of GPCR downstream signaling dynamics.

G-protein-coupled receptors (GPCRs) play an important role in sensing various extracellular stimuli, such as neurotransmitters, hormones, and tastants, and transducing the input information into the cell. While the human genome encodes more than 800 GPCR genes, only four Gα-proteins (Gαs, Gαi/o, Gαq/11, and Gα12/13) are known to couple with GPCRs. It remains unclear how such divergent GPCR information is translated into the downstream G-protein signaling dynamics. To answer this question, we report a live-cell fluorescence imaging system for monitoring GPCR downstream signaling dynamics. Genetically encoded biosensors for cAMP, Ca2+, RhoA, and ERK were selected as markers for GPCR downstream signaling, and were stably expressed in HeLa cells. GPCR was further transiently overexpressed in the cells. As a proof-of-concept, we visualized GPCR signaling dynamics of five dopamine receptors and 12 serotonin receptors, and found heterogeneity between GPCRs and between cells. Even when the same Gα proteins were known to be coupled, the patterns of dynamics in GPCR downstream signaling, including the signal strength and duration, were substantially distinct among GPCRs. These results suggest the importance of dynamical encoding in GPCR signaling.

Visualization and Manipulation of Intracellular Signaling.

Cells respond to a wide range of extracellular stimuli, and process the input information through an intracellular signaling system comprised of biochemical and biophysical reactions, including enzymatic and protein-protein interactions. It is essential to understand the molecular mechanisms underlying intracellular signal transduction in order to clarify not only physiological cellular functions but also pathological processes such as tumorigenesis. Fluorescent proteins have revolutionized the field of life science, and brought the study of intracellular signaling to the single-cell and subcellular levels. Much effort has been devoted to developing genetically encoded fluorescent biosensors based on fluorescent proteins, which enable us to visualize the spatiotemporal dynamics of cell signaling. In addition, optogenetic techniques for controlling intracellular signal transduction systems have been developed and applied in recent years by regulating intracellular signaling in a light-dependent manner. Here, we outline the principles of biosensors for probing intracellular signaling and the optogenetic tools for manipulating them.

Design of Nuclear Magnetic Resonance Molecular Probes for Hyperpolarized Bioimaging.

Nuclear hyperpolarization has emerged as a method to dramatically enhance the sensitivity of NMR spectroscopy. By application of this powerful tool, small molecules with stable isotopes have been used for highly sensitive biomedical molecular imaging. The recent development of molecular probes for hyperpolarized in vivo analysis has demonstrated the ability of this technique to provide unique metabolic and physiological information. This review presents a brief introduction of hyperpolarization technology, approaches to the rational design of molecular probes for hyperpolarized analysis, and examples of molecules that have met with success in vitro or in vivo.

Single-cell quantification of the concentrations and dissociation constants of endogenous proteins.

Kinetic simulation is a useful approach for elucidating complex cell-signaling systems. The numerical simulations required for kinetic modeling in live cells critically require parameters such as protein concentrations and dissociation constants (Kd ). However, only a limited number of parameters have been measured experimentally in living cells. Here we describe an approach for quantifying the concentration and Kd of endogenous proteins at the single-cell level with CRISPR/Cas9-mediated knock-in and fluorescence cross-correlation spectroscopy. First, the mEGFP gene was knocked in at the end of the mitogen-activated protein kinase 1 (MAPK1) gene, encoding extracellular signal-regulated kinase 2 (ERK2), through homology-directed repair or microhomology-mediated end joining. Next, the HaloTag gene was knocked in at the end of the ribosomal S6 kinase 2 (RSK2) gene. We then used fluorescence correlation spectroscopy to measure the protein concentrations of endogenous ERK2-mEGFP and RSK2-HaloTag fusion constructs in living cells, revealing substantial heterogeneities. Moreover, fluorescence cross-correlation spectroscopy analyses revealed temporal changes in the apparent Kd values of the binding between ERK2-mEGFP and RSK2-HaloTag in response to epidermal growth factor stimulation. Our approach presented here provides a robust and efficient method for quantifying endogenous protein concentrations and dissociation constants in living cells.

Fold-change detection and scale invariance of cell-cell signaling in social amoeba.

Cell-cell signaling is subject to variability in the extracellular volume, cell number, and dilution that potentially increase uncertainty in the absolute concentrations of the extracellular signaling molecules. To direct cell aggregation, the social amoebae Dictyostelium discoideum collectively give rise to oscillations and waves of cyclic adenosine 3',5'-monophosphate (cAMP) under a wide range of cell density. To date, the systems-level mechanism underlying the robustness is unclear. By using quantitative live-cell imaging, here we show that the magnitude of the cAMP relay response of individual cells is determined by fold change in the extracellular cAMP concentrations. The range of cell density and exogenous cAMP concentrations that support oscillations at the population level agrees well with conditions that support a large fold-change-dependent response at the single-cell level. Mathematical analysis suggests that invariance of the oscillations to density transformation is a natural outcome of combining secrete-and-sense systems with a fold-change detection mechanism.

Inverse tissue mechanics of cell monolayer expansion.

Living tissues undergo deformation during morphogenesis. In this process, cells generate mechanical forces that drive the coordinated cell motion and shape changes. Recent advances in experimental and theoretical techniques have enabled in situ measurement of the mechanical forces, but the characterization of mechanical properties that determine how these forces quantitatively affect tissue deformation remains challenging, and this represents a major obstacle for the complete understanding of morphogenesis. Here, we proposed a non-invasive reverse-engineering approach for the estimation of the mechanical properties, by combining tissue mechanics modeling and statistical machine learning. Our strategy is to model the tissue as a continuum mechanical system and to use passive observations of spontaneous tissue deformation and force fields to statistically estimate the model parameters. This method was applied to the analysis of the collective migration of Madin-Darby canine kidney cells, and the tissue flow and force were simultaneously observed by the phase contrast imaging and traction force microscopy. We found that our monolayer elastic model, whose elastic moduli were reverse-engineered, enabled a long-term forecast of the traction force fields when given the tissue flow fields, indicating that the elasticity contributes to the evolution of the tissue stress. Furthermore, we investigated the tissues in which myosin was inhibited by blebbistatin treatment, and observed a several-fold reduction in the elastic moduli. The obtained results validate our framework, which paves the way to the estimation of mechanical properties of living tissues during morphogenesis.

Temporal relation between neural activity and neurite pruning on a numerical model and a microchannel device with micro electrode array.

Synapse elimination and neurite pruning are essential processes for the formation of neuronal circuits. These regressive events depend on neural activity and occur in the early postnatal days known as the critical period, but what makes this temporal specificity is not well understood. One possibility is that the neural activities during the developmentally regulated shift of action of GABA inhibitory transmission lead to the critical period. Moreover, it has been reported that the shifting action of the inhibitory transmission on immature neurons overlaps with synapse elimination and neurite pruning and that increased inhibitory transmission by drug treatment could induce temporal shift of the critical period. However, the relationship among these phenomena remains unclear because it is difficult to experimentally show how the developmental shift of inhibitory transmission influences neural activities and whether the activities promote synapse elimination and neurite pruning. In this study, we modeled synapse elimination in neuronal circuits using the modified Izhikevich's model with functional shifting of GABAergic transmission. The simulation results show that synaptic pruning within a specified period like the critical period is spontaneously generated as a function of the developmentally shifting inhibitory transmission and that the specific firing rate and increasing synchronization of neural circuits are seen at the initial stage of the critical period. This temporal relationship was experimentally supported by an in vitro primary culture of rat cortical neurons in a microchannel on a multi-electrode array (MEA). The firing rate decreased remarkably between the 18-25 days in vitro (DIV), and following these changes in the firing rate, the neurite density was slightly reduced. Our simulation and experimental results suggest that decreasing neural activity due to developing inhibitory synaptic transmission could induce synapse elimination and neurite pruning at particular time such as the critical period. Additionally, these findings indicate that we can estimate the maturity level of inhibitory transmission and the critical period by measuring the firing rate and the degree of synchronization in engineered neural networks.

Revisiting the evolution of bow-tie architecture in signaling networks.

Bow-tie architecture is a layered network structure that has a narrow middle layer with multiple inputs and outputs. Such structures are widely seen in the molecular networks in cells, suggesting that a universal evolutionary mechanism underlies the emergence of bow-tie architecture. The previous theoretical studies have implemented evolutionary simulations of the feedforward network to satisfy a given input-output goal and proposed that the bow-tie architecture emerges when the ideal input-output relation is given as a rank-deficient matrix with mutations in network link intensities in a multiplicative manner. Here, we report that the bow-tie network inevitably appears when the link intensities representing molecular interactions are small at the initial condition of the evolutionary simulation, regardless of the rank of the goal matrix. Our dynamical system analysis clarifies the mechanisms underlying the emergence of the bow-tie structure. Further, we demonstrate that the increase in the input-output matrix reduces the width of the middle layer, resulting in the emergence of bow-tie architecture, even when evolution starts from large link intensities. Our data suggest that bow-tie architecture emerges as a side effect of evolution rather than as a result of evolutionary adaptation.

Live-cell imaging defines a threshold in CDK activity at the G2/M transition.

Cyclin-dependent kinase (CDK) determines the temporal ordering of the cell cycle phases. However, despite significant progress in studying regulators of CDK and phosphorylation patterns of CDK substrates at the population level, it remains elusive how CDK regulators coordinately affect CDK activity at the single-cell level and how CDK controls the temporal order of cell cycle events. Here, we elucidate the dynamics of CDK activity in fission yeast and mammalian cells by developing a CDK activity biosensor, Eevee-spCDK. We find that although CDK activity does not necessarily correlate with cyclin levels, it converges to the same level around mitotic onset in several mutant backgrounds, including pom1Δ cells and wee1 or cdc25 overexpressing cells. These data provide direct evidence that cells enter the M phase when CDK activity reaches a high threshold, consistent with the quantitative model of cell cycle progression in fission yeast.

Microtubule-associated phase separation of MIDD1 tunes cell wall spacing in xylem vessels in Arabidopsis thaliana.

Properly patterned cell walls specify cellular functions in plants. Differentiating protoxylem and metaxylem vessel cells exhibit thick secondary cell walls in striped and pitted patterns, respectively. Cortical microtubules are arranged in distinct patterns to direct cell wall deposition. The scaffold protein MIDD1 promotes microtubule depletion by interacting with ROP GTPases and KINESIN-13A in metaxylem vessels. Here we show that the phase separation of MIDD1 fine-tunes cell wall spacing in protoxylem vessels in Arabidopsis thaliana. Compared with wild-type, midd1 mutants exhibited narrower gaps and smaller pits in the secondary cell walls of protoxylem and metaxylem vessel cells, respectively. Live imaging of ectopically induced protoxylem vessels revealed that MIDD1 forms condensations along the depolymerizing microtubules, which in turn caused massive catastrophe of microtubules. The MIDD1 condensates exhibited rapid turnover and were susceptible to 1,6-hexanediol. Loss of ROP abolished the condensation of MIDD1 and resulted in narrow cell wall gaps in protoxylem vessels. These results suggest that the microtubule-associated phase separation of MIDD1 facilitates microtubule arrangement to regulate the size of gaps in secondary cell walls. This study reveals a new biological role of phase separation in the fine-tuning of cell wall patterning.

LIM Tracker: a software package for cell tracking and analysis with advanced interactivity.

Cell tracking is one of the most critical tools for time-lapse image analysis to observe cell behavior and cell lineages over a long period of time. However, the accompanying graphical user interfaces are often difficult to use and do not incorporate seamless manual correction, data analysis tools, or simple training set design tools if it is machine learning based. In this paper, we introduce our cell tracking software "LIM Tracker". This software has a conventional tracking function consisting of recognition processing and link processing, a sequential search-type tracking function based on pattern matching, and a manual tracking function. LIM Tracker enables the seamless use of these functions. In addition, the system incorporates a highly interactive and interlocking data visualization method, which displays analysis result in real time, making it possible to flexibly correct the data and reduce the burden of tracking work. Moreover, recognition functions with deep learning (DL) are also available, which can be used for a wide range of targets including stain-free images. LIM Tracker allows researchers to track living objects with good usability and high versatility for various targets. We present a tracking case study based on fluorescence microscopy images (NRK-52E/EKAREV-NLS cells or MCF-10A/H2B-iRFP-P2A-mScarlet-I-hGem-P2A-PIP-NLS-mNeonGreen cells) and phase contrast microscopy images (Glioblastoma-astrocytoma U373 cells). LIM Tracker is implemented as a plugin for ImageJ/Fiji. The software can be downloaded from https://github.com/LIMT34/LIM-Tracker .