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Yamauchi, K.

Publications and source records attributed to Yamauchi, K..

13 recordsLinked to original sources

Ultrastructurally planar growth cones during neocortical axon navigation

Neurons extend axons toward spatially defined but often distant targets to establish brain circuits. Callosal projection neurons exemplify this organization, linking corresponding cortical territories between the two hemispheres. Growing axons rely on growth cones to regulate direction and speed through densely packed tissues. Although growth cone morphology and dynamics have been extensively characterized in cultured neurons and invertebrate models, how growth cones navigate the three-dimensional environment of the developing mammalian brain remains poorly explored. Here, we combined a genetically encoded electron microscopy (EM)-labeling strategy and zero-shot deep-learning-based tracing with high-resolution volume EM to reconstruct growth cones of identified callosal projection neurons in the developing mouse brain. Mediolaterally extending growth cones exhibited a planar, fan-shaped morphology, preferentially expanded along the dorsoventral axis. Filopodia extended from the edges of this plane and aligned predominantly with the same axis but showed no directional bias toward the growing direction. Longitudinal in vivo imaging revealed that increased growth cone complexity associated with filopodial extension coincided with lower instantaneous velocity but preceded accelerated extension. Together, these findings reveal a dorsoventrally oriented planar growth cone architecture in which filopodial extension precedes accelerated axon growth, suggesting a structural constraint that may restrict axon navigation to the callosal plane.

neuroscience↗

Learning by forgetting: A computational model of insect brain

In this study, resource-constrained learning methods were developed as a model for the learning behavior of the fly brain, specifically the mushroom body. Recent research on the mushroom bodies of flies shows that unfamiliar odors activate certain output neurons (MBONs); however, these effects are rapidly suppressed upon repeated exposure to the same odor. Such MBON behaviors appear to reflect odor learning. We investigated how flies continue learning about odors throughout their lives despite their small brains. Researchers have suggested that learning about new odors can help flies forget existing memories. Therefore, we hypothesized that the main reason for continual learning is that it serves as a strategy for forgetting. To test the validity of this hypothesis, we designed three models using a kernel perceptron. This approach is suitable for estimating ongoing learning capacity within a budget. According to the results of computer simulations and theoretical analysis, the model demonstrated the importance of forgetting mechanisms for two reasons: first, to prepare for subsequent learning sessions, and second, to reduce the negative effects of deleting memories. Author summaryDrosophila mushroom body output neurons (MBONs) in the 3 compartment of the fruit fly brain are highly activated by novel odors, and their activation triggers alerting behavior. Interestingly, these specific neurons react only to unfamiliar odor information, suggesting they constantly undergo incremental learning of new odors. This study was aimed at constructing three incremental learning models of the MBON 3 neurons. Although there have been numerous studies on complex circuit designs to reproduce activation waveforms, herein we constructed a fundamental learning model based on a kernelized learning method. Since kernelized learning models interpret Hebbian learning as the addition or subtraction of kernel functions, the model is easy to analyze theoretically. Consequently, we conclude that the forgetting property observed in the MBON 3 neurons is essential for reducing error when learning occurs within a brain of limited capacity.

neuroscience↗

The difference in immunohistochemical reactivity of monoclonal antibodies against amino-terminal residues of amyloid-β peptide

Immunohistochemistry for amyloid-{beta} (A{beta}) peptide is an indispensable method for Alzheimers disease (AD) research. Despite a wide variety of available antibodies against the peptides, the difference of immunohistochemical reactivity is not fully described among anti-A{beta} antibodies. Immunohistochemical reactivity of Abs against A{beta} peptides is critical for accurate and reliable evaluation of A{beta} burden in patients as well as models of AD. Here, we examined immunohistochemical reactivity of two mouse and one rabbit monoclonal antibodies against A{beta} N-terminal regions using two AD mouse models, AppNL-F and AppNL-G-F. 6E10, 82E1 and D54D2 A{beta} antibodies were used in this study. We found significant differences in the immunohistochemical reactivity in both AppNL-F and AppNL-G-F models. While 6E10 immunoreactivity was mainly localized to A{beta} plaques, D54D2 and 82E1 antibodies stained much more broadly beyond plaques. Interestingly, the latter two Abs showed blurred filamentous immunoreactivity beyond amyloid plaque cores. Double immunostaining using a tyramide signal amplification method, Fluorochromized Tyramide-Glucose Oxidase (FT-GO), suggested that the differential immunohistochemical outcomes were only partially attributable to their sensitivity. Moreover, heat induced epitope retrieval (HIER) did not affect the differential immunohistochemical outcomes. Our analysis indicates that outcomes of A{beta} immunohistochemistry highly depends on the antibody used in the study.

neuroscience↗

Development and characterization of bioinks for 3D bioprinting of in vitro skeletal muscle constructs

The use of 3D bioprinting to construct in vitro skeletal muscle models presents a promising approach; however, selecting an optimal bioink remains a common challenge. This study focuses on the development and characterization of bioinks for extrusion-based 3D bioprinting, specifically targeting the creation of accurate skeletal muscle models. By exploring various compositions of alginate, gelatin, fibrinogen, and nanofiber cellulose, we evaluate these formulations based on printability and their support for the growth and differentiation of C2C12 myoblast cells. While alginate provided a strong, stable matrix for printing scaffolds embedded with C2C12 cells, it did not effectively promote cell growth and differentiation. The addition of fibrinogen to alginate enhanced cell growth and differentiation but was limited mainly to the scaffold surfaces, even with the inclusion of gelatin as a sacrificial ink. Notably, replacing alginate with nanofiber cellulose (NFC) alongside fibrinogen significantly improved cell growth and differentiation, leading to the formation of mature myotubes. Cell distribution was observed both inside and on the surfaces of the scaffolds, indicating effective spatial cell distribution. Furthermore, the scaffolds were tailored to form skeletal muscle bundles anchored between PDMS pillars for contractility testing. Upon exposure to electrical stimulation, the cells displayed measurable displacement, demonstrating contractile function. These findings offer valuable insights into optimizing bioink formulations that promote myoblast growth and differentiation into skeletal muscle in vitro, with potential applications in future neuromuscular disease modeling.

bioengineering↗

A Three Dimensional Immunolabeling Method with Peroxidase-fused Nanobodies and Fluorochromized Tyramide-Glucose Oxidase Signal Amplification

Three dimensional immunohistochemistry (3D-IHC), immunolabeling of 3D tissues, reveals the spatial organization of molecular and cellular assemblies in the context of the tissue architecture. Deep and rapid penetration of antibodies into 3D tissues and highly sensitive detection are critical for high-throughput imaging analysis of immunolabeled 3D tissues. Here, we report a nanobody (nAb)-based 3D-IHC, POD-nAb/FT-GO 3D-IHC, for high-speed and high-sensitive detection of targets within 3D tissues. Peroxidase-fused nAbs (POD-nAbs) enhanced immunolabeling depth and allowed for highly sensitive detection by combined with a fluorescent tyramide signal amplification system, Fluorochromized Tyramide-Glucose Oxidase (FT-GO). Multiplex labeling was implemented to the 3D-IHC by quenching POD with sodium azide. Using the 3D-IHC technique, we successfully visualized somata and processes of neuronal and glial cells in millimeter-thick mouse brain tissues within three days. Given its high-speed and high-sensitive detection, our 3D-IHC protocol, POD-nAb/FT-GO 3D-IHC, would provide a useful platform for histochemical analysis in 3D tissues.

neuroscience↗

Florigen-producing cells express FPF1-LIKE PROTEIN 1 that accelerates flowering and stem growth in long days with sunlight red/far-red ratio in Arabidopsis

Seasonal changes in spring induce flowering by expressing the florigen, FLOWERING LOCUS T (FT), in Arabidopsis. FT is expressed in unique phloem companion cells with unknown characteristics. The question of which genes are co-expressed with FT and whether they have roles in flowering remains elusive. Through tissue-specific translatome analysis, we discovered that under long-day conditions with the natural sunlight red/far-red ratio, the FT-producing cells express a gene encoding FPF1-LIKE PROTEIN 1 (FLP1). The master FT regulator, CONSTANS (CO), controls FLP1 expression, suggesting FLP1s involvement in the photoperiod pathway. FLP1 promotes early flowering independently of FT, is active in the shoot apical meristem, and induces the expression of SEPALLATA 3 (SEP3), a key E-class homeotic gene. Unlike FT, FLP1 facilitates inflorescence stem elongation. Our cumulative evidence indicates that FLP1 may act as a mobile signal. Thus, FLP1 orchestrates floral initiation together with FT and promotes inflorescence stem elongation during reproductive transitions.

plant biology↗

Plaque-associated endogenous IgG and its impact on immunohistochemical detection of mouse monoclonal IgG antibodies in mouse models of Alzheimer's disease

Experimental studies for Alzheimers disease (AD) have largely depended on transgenic mice with {beta}-amyloidosis. Here, we report plaque-associated endogenous immunoglobulin G (PA-IgG) and its impact on indirect immunohistochemical detection of mouse monoclonal IgG antibodies (Ms monoclonal IgG Abs) in the brain of AD mouse models. Immunostaining for Ms IgG in AD mouse models demonstrated endogenous IgG in the brain parenchyma accumulated on microglia associated with amyloid {beta} (A{beta}) plaques and/or A{beta} plaques themselves. This PA-IgG caused robust off-target binding of secondary Abs against Ms IgG (H+L) in indirect immunohistochemistry using Ms monoclonal IgG Abs. Blocking with Fab fragments of anti-Ms IgG (H+L) Ab was not effective against off-target binding. Unexpectedly, we found that secondary Abs that specifically recognize Ms IgG1, 2a, 2b, and 3 did not cause off-target binding on frozen brain sections of AppNL-G-F/NL-G-Fmice, and enabled specific labeling of Ms monoclonal IgG Abs in the AD mouse model brains. We further demonstrated that indirect detection with a conventional secondary Ab against Ms IgG (H+L) Ab could lead to erroneous conclusions regarding A{beta} plaque burden and phosphorylated tau accumulation in AppNL-G-F/NL-G-Fmice, and the use of Ms IgG subclass specific secondary Abs allowed to avoid the inevitable impediment caused by the endogenous IgG accumulation. Specific indirect detection of Ms monoclonal IgG Abs in AD mouse models by the use of secondary Abs against Ms IgG subclass would accelerate AD research by expanding the choice of Abs available for histochemical analysis in AD studies.

neuroscience↗

Coatomer complex I is required for the transport of SARS-CoV-2 progeny virions from the endoplasmic reticulum-Golgi intermediate compartment

SARS-CoV-2 undergoes budding within the lumen of the endoplasmic reticulum-Golgi intermediate compartment (ERGIC) and delivers progeny virions to the cell surface by employing vesicular transport. However, the molecular mechanisms remain poorly understood. Using three-dimensional electron microscopic analysis, such as array tomography and electron tomography, we found that virion-transporting vesicles possessed a coated protein on their membrane and demonstrated that the coated protein was coatomer complex I (COPI). During the later stages of SARS-CoV-2 infection, we observed a notable alteration in the distribution of COPI and ERGIC throughout the cytoplasm. Depletion of COPB2, a key component of COPI, led to the confinement of SARS-CoV-2 structural proteins in the perinuclear region, where progeny virions were accumulated within the ERGIC. While the expression levels of viral proteins within cells were comparable, this depletion significantly reduced the efficiency of virion release, leading to the significant inhibition of viral replication. Hence, our findings suggest COPI as a critical player in facilitating the transport of SARS-CoV-2 progeny virions from the ERGIC. Thus, COPI could be a promising target for the development of antivirals against SARS-CoV-2.

microbiology↗

FT-GO: a multiplex fluorescent tyramide signal amplification system for histochemical analysis

Tyramide signal amplification (TSA) is a highly sensitive method for histochemical analysis. Previously, we reported a TSA system, BT-GO, for bright-filed imaging. Here, we develop FT-GO (Fluorochromized Tyramide-Glucose Oxidase) as a multiplex fluorescent TSA system. FT-GO involves peroxidase-catalyzed deposition of FT with hydrogen peroxide produced in enzymatic reaction between glucose and glucose oxidase. We showed that FT-GO enhanced immunofluorescence signals while maintaining low background signals. Compared with indirect immunofluorescence detections, FT-GO demonstrated a more widespread distribution of monoaminergic projection systems in mouse and marmoset brains. For multiplex labeling with FT-GO, we quenched Ab-conjugated peroxidase using sodium azide. We applied FT-GO to multiplex fluorescent in situ hybridization, and succeeded in labeling neocortical interneuron subtypes by coupling with immunofluorescence. FT-GO immunofluorescence further increased the detectability of an adeno-associated virus tracer. Given its simplicity and a staining with a high signal-to-noise ratio, FT-GO would provide a versatile platform for histochemical analysis.

neuroscience↗

Myoscaffolds reveal laminin scarring is detrimental for stem cell function while sarcospan induces compensatory fibrosis

We developed an on-slide decellularization approach to generate acellular extracellular matrix (ECM) scaffolds that can be repopulated with various cell types to interrogate cell-ECM interactions. Using this platform, we investigated whether fibrotic ECM scarring affected human skeletal muscle progenitor cell (SMPC) functions that are essential for myoregeneration. SMPCs exhibited robust adhesion, motility, and differentiation on healthy muscle-derived myoscaffolds. All SPMC interactions with fibrotic myoscaffolds from dystrophic muscle were severely blunted including reduced motility rate and migration. Furthermore, SMPCs were unable to remodel laminin dense fibrotic scars within diseased myoscaffolds. Proteomics and structural analysis revealed that excessive collagen deposition alone is not pathological, and can be compensatory, as revealed by overexpression of sarcospan and its associated ECM receptors in dystrophic muscle. Our in vivo data also supported that ECM remodeling is important for SMPC engraftment and that fibrotic scars may represent one barrier to efficient cell therapy.

cell biology↗

Inhibition of N-myristoyltransferase Promotes Naive Pluripotency in Mouse and Human Pluripotent Stem Cells

Naive and primed states are distinct states of pluripotency during early embryonic development that can be captured and converted to each other in vitro. To elucidate the regulatory mechanism of pluripotency, we performed a recessive genetic screen of homozygous mutant mouse embryonic stem cells (mESCs) and found that suppression of N-myristoyltransferase (Nmt) promotes naive pluripotency. Disruption of Nmt1 in mESCs conferred resistance to differentiation. Suppression of Nmt in mouse epiblast stem cells (mEpiSCs) promoted the conversion from the primed to the naive state. This effect was independent of Src, which is a major substrate of Nmt and is known to promote differentiation of mESCs. Suppression of Nmt in naive-state human induced pluripotent stem cells (hiPSCs) increased the expression of the naive-state marker. These results indicate that Nmt is a novel target for the regulation of naive pluripotency conserved between mice and humans.

developmental biology↗

Multi-Scale LM/EM Neuronal Imaging from Brain to Synapse with a Tissue Clearing Method, ScaleSF

The mammalian brain is organized over sizes that span several orders of magnitude, from synapses to the entire brain. Thus, a technique to visualize neural circuits across multiple spatial scales (multi-scale neuronal imaging) is vital for deciphering brain-wide connectivity. Here, we developed this technique by coupling successive light microscope/electron microscope (LM/EM) imaging with an ultrastructurally-preserved tissue clearing method, ScaleSF. Our multi-scale neuronal imaging incorporates 1) brain-wide macroscopic observation, 2) mesoscopic circuit mapping, 3) microscopic subcellular imaging, and 4) EM imaging of nanoscopic structures, allowing seamless integration of structural information from the brain to synapses. We applied the technique to three neural circuits of two different species, mouse striatofugal, mouse callosal, and marmoset corticostriatal projection systems, and succeeded in the simultaneous interrogation of their circuit structure and synaptic connectivity in a targeted way. Our multi-scale neuronal imaging will significantly advance the understanding of brain-wide connectivity by expanding the scales of objects.

neuroscience↗

Validation and tuning of in situ transcriptomics image processing workflows with crowdsourced annotations

Recent advancements in in situ methods, such as multiplexed in situ RNA hybridization and in situ RNA sequencing, have deepened our understanding of the way biological processes are spatially organized in tissues. Automated image processing and spot-calling algorithms for analyzing in situ transcriptomics images have many parameters which need to be tuned for optimal detection. Having ground truth datasets (images where there is very high confidence on the accuracy of the detected spots) is essential for evaluating these algorithms and tuning their parameters. We present a first-in-kind open-source toolkit and framework for in situ transcriptomics image analysis that incorporates crowdsourced annotations, alongside expert annotations, as a source of ground truth for the analysis of in situ transcriptomics images. The kit includes tools for preparing images for crowdsourcing annotation to optimize crowdsourced workers ability to annotate these images reliably, performing quality control (QC) on worker annotations, extracting candidate parameters for spot-calling algorithms from sample images, tuning parameters for spot-calling algorithms, and evaluating spot-calling algorithms and worker performance. These tools are wrapped in a modular pipeline with a flexible structure that allows users to take advantage of crowdsourced annotations from any source of their choice. We tested the pipeline using real and synthetic in situ transcriptomics images and annotations from the Amazon Mechanical Turk system obtained via Quanti.us. Using real images from in situ experiments and simulated images produced by one of the tools in the kit, we studied worker sensitivity to spot characteristics and established rules for annotation QC. We explored and demonstrated the use of ground truth generated in this way for validating spot-calling algorithms and tuning their parameters, and confirmed that consensus crowdsourced annotations are a viable substitute for expert-generated ground truth for these purposes. Data AvailabilityThe iPython notebooks, input images, and In Situ Transcriptomics Annotation (INSTA) pipeline software are available from https://github.com/czbiohub/instapipeline. The SpotImage software is available from https://github.com/czbiohub/spotimage. The files and iPython notebooks used to generate the figures for this paper are available from https://github.com/czbiohub/instapaper.

bioengineering↗