Engineered fluorescent protein (FP) chimeras that modulate their fluorescence in response to changes in calcium ion (Ca²⁺) concentration are powerful tools for visualizing intracellular signaling ...activity. However, despite a decade of availability, the palette of single FP-based Ca²⁺ indicators has remained limited to a single green hue. We have expanded this palette by developing blue, improved green, and red intensiometric indicators, as well as an emission ratiometric indicator with an 11,000% ratio change. This series enables improved single-color Ca²⁺ imaging in neurons and transgenic Caenorhabditis elegans. In HeLa cells, Ca²⁺ was imaged in three subcellular compartments, and, in conjunction with a cyan FP—yellow FP—based indicator, Ca²⁺ and adenosine 5′-triphosphate were simultaneously imaged. This palette of indicators paints the way to a colorful new era of Ca²⁺ imaging.
Despite recent improvements in microscope technologies, segmenting and tracking cells in three-dimensional time-lapse images (3D + T images) to extract their dynamic positions and activities remains ...a considerable bottleneck in the field. We developed a deep learning-based software pipeline, 3DeeCellTracker, by integrating multiple existing and new techniques including deep learning for tracking. With only one volume of training data, one initial correction, and a few parameter changes, 3DeeCellTracker successfully segmented and tracked ~100 cells in both semi-immobilized and 'straightened' freely moving worm's brain, in a naturally beating zebrafish heart, and ~1000 cells in a 3D cultured tumor spheroid. While these datasets were imaged with highly divergent optical systems, our method tracked 90-100% of the cells in most cases, which is comparable or superior to previous results. These results suggest that 3DeeCellTracker could pave the way for revealing dynamic cell activities in image datasets that have been difficult to analyze.
In the field of neuroscience, neural modules and circuits that control biological functions have been found throughout entire neural networks. Correlations in neural activity can be used to identify ...such neural modules. Recent technological advances enable us to measure whole-brain neural activity with single-cell resolution in several species including Formula: see text. Because current neural activity data in C. elegans contain many missing data points, it is necessary to merge results from as many animals as possible to obtain more reliable functional modules.
In this work, we developed a new time-series clustering method, WormTensor, to identify functional modules using whole-brain activity data from C. elegans. WormTensor uses a distance measure, modified shape-based distance to account for the lags and the mutual inhibition of cell-cell interactions and applies the tensor decomposition algorithm multi-view clustering based on matrix integration using the higher orthogonal iteration of tensors (HOOI) algorithm (MC-MI-HOOI), which can estimate both the weight to account for the reliability of data from each animal and the clusters that are common across animals.
We applied the method to 24 individual C. elegans and successfully found some known functional modules. Compared with a widely used consensus clustering method to aggregate multiple clustering results, WormTensor showed higher silhouette coefficients. Our simulation also showed that WormTensor is robust to contamination from noisy data. WormTensor is freely available as an R/CRAN package https://cran.r-project.org/web/packages/WormTensor .
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Many animal species change their behavior according to their stage of development. However, the mechanisms involved in translating their developmental stage into the modifications of the neuronal ...circuits that underlie these behavioral changes remain unknown. Here we show that Caenorhabditis elegans changes its olfactory preferences during development. Larvae exhibit a weak chemotactic response to the food-associated odor diacetyl, whereas adults exhibit a strong response. We show that germline loss, caused either by laser ablation of germline precursor cells or mutations, results in a diacetyl-specific chemotactic defect in adult animals. These results suggest that germline cells, which proliferate dramatically during the larval stages, enhance chemotaxis to diacetyl. Removal experiments of specific neurons suggested that AWA olfactory neurons and their downstream interneurons, AIA and AIB, are required for germline-dependent chemotactic enhancement. Calcium imaging in animals lacking germline cells indicates that the neural responses of AWA and AIB to diacetyl stimuli are decreased compared with animals with an intact germline. These changes in neural activities may at least partly explain the behavioral change of animals lacking germline cells. Furthermore, this germline-dependent chemotactic change depends on the transcription factor DAF-16/FOXO. We find that organismal behavior changes throughout development by integrating information about physiological status from internal tissues to modify a simple sensory circuit.
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•Odor preference changes during development in C. elegans•Adults lacking a germline show chemotactic responses similar to those of larvae•Activities of AWA and AIB neurons in an olfactory circuit are affected by a germline•DAF-16/FOXO is required for germline-dependent chemotactic regulation
Fujiwara et al. demonstrate that germline cells of C. elegans, which proliferate in larvae, affect the chemotactic response of adult animals specifically to a food-associated odorant, diacetyl. This is accomplished through the function of DAF-16/FOXO. Activities of AWA and AIB neurons in an olfactory circuit are changed by germline cells.
The recent advancements in large-scale activity imaging of neuronal ensembles offer valuable opportunities to comprehend the process involved in generating brain activity patterns and understanding ...how information is transmitted between neurons or neuronal ensembles. However, existing methodologies for extracting the underlying properties that generate overall dynamics are still limited. In this study, we applied previously unexplored methodologies to analyze time-lapse 3D imaging (4D imaging) data of head neurons of the nematode Caenorhabditis elegans. By combining time-delay embedding with the independent component analysis, we successfully decomposed whole-brain activities into a small number of component dynamics. Through the integration of results from multiple samples, we extracted common dynamics from neuronal activities that exhibit apparent divergence across different animals. Notably, while several components show common cooperativity across samples, some component pairs exhibited distinct relationships between individual samples. We further developed time series prediction models of synaptic communications. By combining dimension reduction using the general framework, gradient kernel dimension reduction, and probabilistic modeling, the overall relationships of neural activities were incorporated. By this approach, the stochastic but coordinated dynamics were reproduced in the simulated whole-brain neural network. We found that noise in the nervous system is crucial for generating realistic whole-brain dynamics. Furthermore, by evaluating synaptic interaction properties in the models, strong interactions within the core neural circuit, variable sensory transmission and importance of gap junctions were inferred. Virtual optogenetics can be also performed using the model. These analyses provide a solid foundation for understanding information flow in real neural networks.
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Annotation of cell identity is an essential process in neuroscience that allows comparison of cells, including that of neural activities across different animals. In Caenorhabditis elegans, although ...unique identities have been assigned to all neurons, the number of annotatable neurons in an intact animal has been limited due to the lack of quantitative information on the location and identity of neurons.
Here, we present a dataset that facilitates the annotation of neuronal identities, and demonstrate its application in a comprehensive analysis of whole-brain imaging. We systematically identified neurons in the head region of 311 adult worms using 35 cell-specific promoters and created a dataset of the expression patterns and the positions of the neurons. We found large positional variations that illustrated the difficulty of the annotation task. We investigated multiple combinations of cell-specific promoters driving distinct fluorescence and generated optimal strains for the annotation of most head neurons in an animal. We also developed an automatic annotation method with human interaction functionality that facilitates annotations needed for whole-brain imaging.
Our neuron ID dataset and optimal fluorescent strains enable the annotation of most neurons in the head region of adult C. elegans, both in full-automated fashion and a semi-automated version that includes human interaction functionalities. Our method can potentially be applied to model species used in research other than C. elegans, where the number of available cell-type-specific promoters and their variety will be an important consideration.
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Sensory processing is regulated by the coordinated excitation and inhibition of neurons in neuronal circuits. The analysis of neuronal activities has greatly benefited from the recent development of ...genetically encoded Ca2+ indicators (GECIs). These molecules change their fluorescence intensities or colours in response to changing levels of Ca2+ and can, therefore, be used to sensitively monitor intracellular Ca2+ concentration, which enables the detection of neuronal excitation, including action potentials. These GECIs were developed to monitor increases in Ca2+ concentration; therefore, neuronal inhibition cannot be sensitively detected by these GECIs. To overcome this difficulty, we hypothesised that an inverse-type of GECI, whose fluorescence intensity increases as Ca2+ levels decrease, could sensitively monitor reducing intracellular Ca2+ concentrations. We, therefore, developed a Ca2+ indicator named inverse-pericam 2.0 (IP2.0) whose fluorescent intensity decreases 25-fold upon Ca2+ binding in vitro. Using IP2.0, we successfully detected putative neuronal inhibition by monitoring the decrease in intracellular Ca2+ concentration in AWCON and ASEL neurons in Caenorhabditis elegans. Therefore, IP2.0 is a useful tool for studying neuronal inhibition and for the detailed analysis of neuronal activities in vivo.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Glutamylation is a post-translational modification found on tubulin that can alter the interaction between microtubules (MTs) and associated proteins. The molecular mechanisms regulating tubulin ...glutamylation in response to the environment are not well understood. Here, we show that in the sensory cilia of Caenorhabditis elegans, tubulin glutamylation is upregulated in response to various signals such as temperature, osmolality, and dietary conditions. Similarly, tubulin glutamylation is modified in mammalian photoreceptor cells following light adaptation. A tubulin glutamate ligase gene ttll-4, which is essential for tubulin glutamylation of axonemal MTs in sensory cilia, is activated by p38 MAPK. Amino acid substitution of TTLL-4 has revealed that a Thr residue (a putative MAPK-phosphorylation site) is required for enhancement of tubulin glutamylation. Intraflagellar transport (IFT), a bidirectional trafficking system specifically observed along axonemal MTs, is required for the formation, maintenance, and function of sensory cilia. Measurement of the velocity of IFT particles revealed that starvation accelerates IFT, which was also dependent on the Thr residue of TTLL-4. Similarly, starvation-induced attenuation of avoidance behaviour from high osmolality conditions was also dependent on ttll-4. Our data suggest that a novel evolutionarily conserved regulatory system exists for tubulin glutamylation in sensory cilia in response to the environment.
To measure the activity of neurons using whole-brain activity imaging, precise detection of each neuron or its nucleus is required. In the head region of the nematode C. elegans, the neuronal cell ...bodies are distributed densely in three-dimensional (3D) space. However, no existing computational methods of image analysis can separate them with sufficient accuracy. Here we propose a highly accurate segmentation method based on the curvatures of the iso-intensity surfaces. To obtain accurate positions of nuclei, we also developed a new procedure for least squares fitting with a Gaussian mixture model. Combining these methods enables accurate detection of densely distributed cell nuclei in a 3D space. The proposed method was implemented as a graphical user interface program that allows visualization and correction of the results of automatic detection. Additionally, the proposed method was applied to time-lapse 3D calcium imaging data, and most of the nuclei in the images were successfully tracked and measured.
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DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Automated fluorescence microscopes produce massive amounts of images observing cells, often in four dimensions of space and time. This study addresses two tasks of time-lapse imaging analyses; ...detection and tracking of the many imaged cells, and it is especially intended for 4D live-cell imaging of neuronal nuclei of Caenorhabditis elegans. The cells of interest appear as slightly deformed ellipsoidal forms. They are densely distributed, and move rapidly in a series of 3D images. Thus, existing tracking methods often fail because more than one tracker will follow the same target or a tracker transits from one to other of different targets during rapid moves.
The present method begins by performing the kernel density estimation in order to convert each 3D image into a smooth, continuous function. The cell bodies in the image are assumed to lie in the regions near the multiple local maxima of the density function. The tasks of detecting and tracking the cells are then addressed with two hill-climbing algorithms. The positions of the trackers are initialized by applying the cell-detection method to an image in the first frame. The tracking method keeps attacking them to near the local maxima in each subsequent image. To prevent the tracker from following multiple cells, we use a Markov random field (MRF) to model the spatial and temporal covariation of the cells and to maximize the image forces and the MRF-induced constraint on the trackers. The tracking procedure is demonstrated with dynamic 3D images that each contain >100 neurons of C.elegans.
http://daweb.ism.ac.jp/yoshidalab/crest/ismb2014 SUPPLEMENTARY INFORMATION: Supplementary data are available at http://daweb.ism.ac.jp/yoshidalab/crest/ismb2014
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