Yuki Tsukada

Aurora B and Kif2A control microtubule length for assembly of a functional central spindle during anaphase

A gradient of Aurora B activity determines the distribution of the microtubule depolymerase Kif2A at the central spindle and specifies the subsequent spindle structure necessary for proper cytokinesis.

Quantification of Local Morphodynamics and Local GTPase Activity by Edge Evolution Tracking

Advances in time-lapse fluorescence microscopy have enabled us to directly observe dynamic cellular phenomena. Although the techniques themselves have promoted the understanding of dynamic cellular functions, the vast number of images acquired has generated a need for automated processing tools to extract statistical information. A problem underlying the analysis of time-lapse cell images is the lack of rigorous methods to extract morphodynamic properties. Here, we propose an algorithm called edge evolution tracking (EET) to quantify the relationship between local morphological changes and local fluorescence intensities around a cell edge using time-lapse microscopy images. This algorithm enables us to trace the local edge extension and contraction by defining subdivided edges and their corresponding positions in successive frames. Thus, this algorithm enables the investigation of cross-correlations between local morphological changes and local intensity of fluorescent signals by considering the time shifts. By applying EET to fluorescence resonance energy transfer images of the Rho-family GTPases Rac1, Cdc42, and RhoA, we examined the cross-correlation between the local area difference and GTPase activity. The calculated correlations changed with time-shifts as expected, but surprisingly, the peak of the correlation coefficients appeared with a 6–8 min time shift of morphological changes and preceded the Rac1 or Cdc42 activities. Our method enables the quantification of the dynamics of local morphological change and local protein activity and statistical investigation of the relationship between them by considering time shifts in the relationship. Thus, this algorithm extends the value of time-lapse imaging data to better understand dynamics of cellular function.

Sprouty4, an FGF Inhibitor, Displays Cyclic Gene Expression under the Control of the Notch Segmentation Clock in the Mouse PSM

Background During vertebrate embryogenesis, somites are generated at regular intervals, the temporal and spatial periodicity of which is governed by a gradient of fibroblast growth factor (FGF) and/or Wnt signaling activity in the presomitic mesoderm (PSM) in conjunction with oscillations of gene expression of components of the Notch, Wnt and FGF signaling pathways. Principal Findings Here, we show that the expression of Sprouty4, which encodes an FGF inhibitor, oscillates in 2-h cycles in the mouse PSM in synchrony with other oscillating genes from the Notch signaling pathway, such as lunatic fringe. Sprouty4 does not oscillate in Hes7-null mutant mouse embryos, and Hes7 can inhibit FGF-induced transcriptional activity of the Sprouty4 promoter. Conclusions Thus, periodic expression of Sprouty4 is controlled by the Notch segmentation clock and may work as a mediator that links the temporal periodicity of clock gene oscillations with the spatial periodicity of boundary formation which is regulated by the gradient of FGF/Wnt activity.

Reconstruction of Spatial Thermal Gradient Encoded in Thermosensory Neuron AFD in Caenorhabditis elegans.

During navigation, animals process temporal sequences of sensory inputs to evaluate the surrounding environment. Thermotaxis of Caenorhabditis elegans is a favorable sensory behavior to elucidate how navigating animals process sensory signals from the environment. Sensation and storage of temperature information by a bilaterally symmetric pair of thermosensory neurons, AFD, is essential for the animals to migrate toward the memorized temperature on a thermal gradient. However, the encoding mechanisms of the spatial environment with the temporal AFD activity during navigation remain to be elucidated. Here, we show how the AFD neuron encodes sequences of sensory inputs to perceive spatial thermal environment. We used simultaneous calcium imaging and tracking system for a freely moving animal and characterized the response property of AFD to the thermal stimulus during thermotaxis. We show that AFD neurons respond to shallow temperature increases with intermittent calcium pulses and detect temperature differences with a critical time window of 20 s, which is similar to the timescale of behavioral elements of C. elegans, such as turning. Convolution of a thermal stimulus and the identified response property successfully reconstructs AFD activity. Conversely, deconvolution of the identified response kernel and AFD activity reconstructs the shallow thermal gradient with migration trajectory, indicating that AFD activity and the migration trajectory are sufficient as the encoded signals for thermal environment. Our study demonstrates bidirectional transformation between environmental thermal information and encoded neural activity. SIGNIFICANCE STATEMENT Deciphering how information is encoded in the nervous system is an important challenge for understanding the principles of information processing in neural circuits. During navigation behavior, animals transform spatial information to temporal patterns of neural activity. To elucidate how a sensory system achieves this transformation, we focused on a thermosensory neuron in Caenorhabditis elegans called AFD, which plays a major role in a sensory behavior. Using tracking and calcium imaging system for freely moving animals, we identified the response property of the AFD. The identified response property enabled us to reconstruct both neural activity from a temperature stimulus and a spatial thermal environment from neural activity. These results shed light on how a sensory system encodes the environment.

Novel and Conserved Protein Macoilin Is Required for Diverse Neuronal Functions in Caenorhabditis elegans

Neural signals are processed in nervous systems of animals responding to variable environmental stimuli. This study shows that a novel and highly conserved protein, macoilin (MACO-1), plays an essential role in diverse neural functions in Caenorhabditis elegans. maco-1 mutants showed abnormal behaviors, including defective locomotion, thermotaxis, and chemotaxis. Expression of human macoilin in the C. elegans nervous system weakly rescued the abnormal thermotactic phenotype of the maco-1 mutants, suggesting that macoilin is functionally conserved across species. Abnormal thermotaxis may have been caused by impaired locomotion of maco-1 mutants. However, calcium imaging of AFD thermosensory neurons and AIY postsynaptic interneurons of maco-1 mutants suggest that macoilin is required for appropriate responses of AFD and AIY neurons to thermal stimuli. Studies on localization of MACO-1 showed that C. elegans and human macoilins are localized mainly to the rough endoplasmic reticulum. Our results suggest that macoilin is required for various neural events, such as the regulation of neuronal activity.

Feedback regulation of microscopes by image processing

Computational microscope systems are becoming a major part of imaging biological phenomena, and the development of such systems requires the design of automated regulation of microscopes. An important aspect of automated regulation is feedback regulation, which is the focus of this review. As modern microscope systems become more complex, often with many independent components that must work together, computer control is inevitable since the exact orchestration of parameters and timings for these multiple components is critical to acquire proper images. A number of techniques have been developed for biological imaging to accomplish this. Here, we summarize the basics of computational microscopy for the purpose of building automatically regulated microscopes focus on feedback regulation by image processing. These techniques allow high throughput data acquisition while monitoring both short‐ and long‐term dynamic phenomena, which cannot be achieved without an automated system.

Uncoordinated centrosome cycle underlies the instability of non-diploid somatic cells in mammals

In animals, somatic cells are usually diploid and are unstable when haploid for unknown reasons. In this study, by comparing isogenic human cell lines with different ploidies, we found frequent centrosome loss specifically in the haploid state, which profoundly contributed to haploid instability through subsequent mitotic defects. We also found that the efficiency of centriole licensing and duplication changes proportionally to ploidy level, whereas that of DNA replication stays constant. This caused gradual loss or frequent overduplication of centrioles in haploid and tetraploid cells, respectively. Centriole licensing efficiency seemed to be modulated by astral microtubules, whose development scaled with ploidy level, and artificial enhancement of aster formation in haploid cells restored centriole licensing efficiency to diploid levels. The ploidy–centrosome link was observed in different mammalian cell types. We propose that incompatibility between the centrosome duplication and DNA replication cycles arising from different scaling properties of these bioprocesses upon ploidy changes underlies the instability of non-diploid somatic cells in mammals.

Japanese studies on neural circuits and behavior of Caenorhabditis elegans

The nematode Caenorhabditis elegans is an ideal organism for studying neural plasticity and animal behaviors. A total of 302 neurons of a C. elegans hermaphrodite have been classified into 118 neuronal groups. This simple neural circuit provides a solid basis for understanding the mechanisms of the brains of higher animals, including humans. Recent studies that employ modern imaging and manipulation techniques enable researchers to study the dynamic properties of nervous systems with great precision. Behavioral and molecular genetic analyses of this tiny animal have contributed greatly to the advancement of neural circuit research. Here, we will review the recent studies on the neural circuits of C. elegans that have been conducted in Japan. Several laboratories have established unique and clever methods to study the underlying neuronal substrates of behavioral regulation in C. elegans. The technological advances applied to studies of C. elegans have allowed new approaches for the studies of complex neural systems. Through reviewing the studies on the neuronal circuits of C. elegans in Japan, we will analyze and discuss the directions of neural circuit studies.

On the synchrony of morphological and molecular signaling events in cell migration

This paper investigates the dynamics of cell migration, which is the movement of a cell towards a certain target area. More specifically, the objective is to analyze the causal interdependence between cellular-morphological events and molecular-signaling events. To this end, a novel data analysis method is developed: first the local morphological changes and molecular signaling events are determined by means of edge evolution tracking (EET), next the interdependence of those events is quantified through the method of stochastic event synchrony (SES). The proposed method is applied to time-lapse fluorescence resonance energy transfer (FRET) images of Rac1 activity in motile HT1080 cells; the protein Rac1 is well known to induce filamentous structures that enable cells to migrate. Results show a significant delay between local Rac1 activity events and morphological events. This observation provides new insights into the dynamic relationship between cellular-morphological change and molecular-signaling of migrating cells, and may pave the way to novel biophysical models of cell migration.

Identification Of Animal Behavioral Strategy By Inverse Reinforcement Learning ~ Its Application To Thermotaxis In C. elegans ~

Animals are able to reach a desired state in an environment by controlling various behavioral patterns. Identification of the behavioral strategy used for this control is important for understanding animals’ decision-making and is fundamental to dissect information processing done by the nervous system. However, methods for quantifying such behavioral strategies have not been fully established. In this study, we developed an inverse reinforcement-learning (IRL) framework to identify an animal’s behavioral strategy from behavioral time-series data. As a particular target, we applied this framework to C. elegans thermotactic behavior; after cultivation at a constant temperature with or without food, the fed and starved worms prefer and avoid from the cultivation temperature on a thermal gradient, respectively. Our IRL approach revealed that the fed worms used both absolute and temporal derivative of temperature and that their strategy comprised mixture of two strategies: directed migration (DM) and isothermal migration (IM). The DM is a strategy that the worms efficiently reach to specific temperature, which explained thermotactic behaviors of the fed worms. The IM is a strategy that the worms track along a constant temperature, which reflects isothermal tracking well observed in previous studies. We also showed the neural basis underlying the strategies, by applying our method to thermosensory neuron-deficient worms. In contrast to fed animals, the strategy of starved animals indicated that they escaped the cultivation temperature using only absolute, but not temporal derivative of temperature. Thus, our IRL-based approach is capable of identifying animal strategies from behavioral time-series data and will be applicable to wide range of behavioral studies, including decision-making of other organisms. Author Summary Understanding animal decision-making has been a fundamental problem in neuroscience and behavioral ecology. Many studies analyze actions that represent decision-making in behavioral tasks, in which rewards are artificially designed with specific objectives. However, it is impossible to extend this artificially designed experiment to a natural environment, because in a natural environment, the rewards for freely-behaving animals cannot be clearly defined. To this end, we must reverse the current paradigm so that rewards are identified from behavioral data. Here, we propose a new reverse-engineering approach (inverse reinforcement learning) that can estimate a behavioral strategy from time-series data of freely-behaving animals. By applying this technique with thermotaxis in C. elegans, we successfully identified the reward-based behavioral strategy.