Biology subjects

Fujita, H.

Publications and source records attributed to Fujita, H..

At least 19 recordsLinked to original sources

bioRxiv2026

ELAplus: Fast and accurate analysis platform for energy landscape analysis facilitated by fine-tuning optimization algorithm.

1. Large-scale community-composition datasets, especially from microbiome studies, increasingly provide opportunities to identify major community compositional types (e.g., enterotypes in human microbiomes) and potential transitions depending on environmental factors. Energy landscape analysis based on maximum entropy models has emerged as a promising framework for characterizing such multi-stability in ecological communities. However, its application to diverse, high-dimensional compositional datasets remains limited by computational inefficiency, insufficient evaluation of predictability, and lack of systematic assessment of uncertainty. 2. Here, we present a computationally tractable inference framework for energy landscape analysis of multispecies communities, implemented in the R package ELAplus. We introduce a framework combining cross-validation-based selection of optimization settings, enabling accurate and computationally efficient model fitting across a wide range of simulated community datasets. In addition, we incorporate a bootstrap-based approach to quantify the reliability of inferred stable states, providing a systematic measure of uncertainty in landscape structures. 3. Simulation analyses demonstrate improved predictive performance and robustness compared to existing implementations. Applications to empirical datasets further illustrate how the framework can reveal stable states, basins of attraction, and potential tipping points under varying environmental conditions. The package also provides visualization tools, including disconnectivity graphs and energy surface plots, to facilitate intuitive interpretation of complex ecological landscapes. 4. Our framework enables robust and computationally efficient inference of ecological stability from compositional and environmental data, expanding the applicability of energy landscape approaches in diverse natural communities.

ecology↗

bioRxiv2026

Response diversity can stabilize or destabilize community dynamics depending on the number of insensitive species

Investigating the factors that stabilize biological communities is a central topic in ecology. Response diversity, defined as variation in species responses to environmental change, has been proposed as a key mechanism underlying the biodiversity-ecosystem functional stability (BEFS) relationship, whereby greater species diversity enhances ecological stability. Previous studies have shown that response diversity promotes ecological stability by generating asynchronous population fluctuations and the resulting compensatory dynamics. Although several metrics have been proposed to quantify response diversity, they do not explicitly consider the presence of insensitive species whose performance is unaffected by current environmental conditions. To examine how insensitive species influence response diversity, species persistence, and ecological stability, we conducted numerical simulations of a generalized Lotka-Volterra model under environmental forcing. We first confirmed that increasing variation among sensitive species increased the response diversity index and stabilized community dynamics. We then examined a scenario in which response diversity depended solely on the proportion of sensitive and insensitive species, assuming that all sensitive species responded identically to environmental change. Under this assumption, the response diversity index was maximized when sensitive and insensitive species occurred in equal proportions, whereas increasing the number of sensitive species monotonically destabilized community dynamics. Consequently, the relationship between response diversity and community stability depended on how response diversity was generated, such that higher response diversity could even be associated with lower community stability. These findings demonstrate that overlooking environmentally insensitive species can obscure the mechanisms linking response diversity and ecological stability. More broadly, our results reveal that response diversity comprises at least two distinct biological components--species sensitivity and response variation among sensitive species--that can have contrasting consequences for community stability. We therefore highlight the need to quantify sensitive species empirically and to develop response diversity metrics that distinguish these components. Author SummaryUnderstanding why some communities remain stable despite environmental change is a longstanding goal in ecology. Response diversity, which refers to differences in how species respond to environmental change, has been proposed as a key mechanism explaining why greater biodiversity (species richness) can promote ecological stability. Because species respond differently to changing environments, declines in some species can be compensated by increases in others, helping to stabilize community dynamics. However, previous studies have rarely considered species that are insensitive to current environmental changes. Using a mathematical model, we show that response diversity can arise from two distinct biological components--the number of sensitive species and variation in their responses--and that these components can have contrasting effects on ecological stability. When response diversity reflects variation among sensitive species, greater response diversity stabilizes community dynamics, as expected. In contrast, when response diversity changes only because of the proportions of sensitive and insensitive species, higher response diversity can be associated with lower community stability. Our findings highlight the importance of quantifying the number of sensitive species and developing response diversity metrics that distinguish species sensitivity from variation in responses among sensitive species.

ecology↗

bioRxiv2026

Aptamer charge-amplified field-effect transistor biosensors achieve picomolar detection limits for small-molecule biomarkers in complex biological matrices

Aptamers are attractive receptors for small-molecule biomarker detection in complex samples because of their high stability, affinity, and specificity, but aptamer-based sensors generally lack the sensitivity to detect low-abundance analytes. As a solution, we developed the charge-amplified FET (CAFET) aptamer biosensor, which is designed to amplify the net charge variation within the Debye length that occurs as a consequence of aptamer-target binding. Our sensor utilizes a strand-displacement aptamer switch, which releases an initially-hybridized displacement strand (DS) upon target binding and thus induces a measurable net charge variation within the Debye length that is amplified to a large FET current response as signal readout. This signal can be further enhanced by adding a charge label to the DS. As a consequence, our sensor can achieve far greater sensitivity than previously described aptamer-FET sensors, where the binding-induced local charge variation is modest. We demonstrate 3-hydroxykynurenine and progesterone detection with a picomolar limit of detection in undiluted human plasma--four orders of magnitude lower than the dissociation constant (KD) of the aptamer component. The CAFET sensor design is modular and should be adaptable for the detection of a wide range of clinically-informative low-abundance analytes in complex samples.

bioengineering↗

bioRxiv2026

Impaired Motor Awareness of Balance Control is Associated with Postural Instability in Parkinson's Disease

BackgroundBalance instability is a major contributor to disability and falls in people with Parkinsons disease (PwP) and is often insufficiently explained by motor impairment alone. Altered awareness of motor control has been suggested to contribute to sensorimotor dysfunction in PwP, but its relationship with balance performance is poorly understood. ObjectiveTo determine whether awareness of balance control, assessed using a control detection task (CDT), differs between healthy controls (HC) and PwP, and whether CDT performance is associated with balance-related measures. MethodsHealthy older adults (n=20) and PwP (n=22) performed a standing version of the CDT based on center-of-pressure (COP) control, using a force plate. CDT accuracy was used as the primary outcome measure. Static balance during quiet standing was assessed using the COP trajectory length and rectangular area. Dynamic standing balance was assessed using the Index of Postural Stability (IPS). Group differences were examined by independent-samples t-tests. Correlations between CDT accuracy and balance measures were analyzed. ResultsThe PwP group showed significantly lower CDT accuracy. Higher CDT accuracy was associated with better static balance in the HC group and the combined sample, and with higher IPS primarily in the PwP group. ConclusionsMotor awareness during postural tasks is altered in PwP and is associated with balance control. These findings suggest that balance instability in Parkinsons disease may involve altered balance-related action-outcome monitoring in addition to motor dysfunction.

neuroscience↗

bioRxiv2025

Discovery of high-specificity DNA aptamers for progesterone using a high-throughput array platform

Aptamer-based biosensors offer several advantages for detecting small molecules, including chemical stability and compatibility with diverse sensing formats. However, developing highly specific DNA aptamers that can distinguish between structurally similar small-molecule analytes remains a major challenge. Steroid hormones share a common four-ring scaffold, and even small modifications in functional groups can lead to distinct biological activities. Although DNA aptamers targeting the female reproductive hormone progesterone have been previously reported, many exhibit substantial cross-reactivity with other steroid hormones. In this work, we report the discovery of DNA aptamers with high affinity and specificity for progesterone using our aptamer array platform, which can characterize millions of aptamer candidates in a single, automated experiment. This platform allows us to profile aptamer libraries from earlier rounds of systematic evolution of ligands by exponential enrichment (SELEX), while preserving sequence diversity. Using this strategy, we identified multiple aptamers with nanomolar affinity for progesterone and minimal cross-reactivity to structurally related steroids. These high-specificity aptamers provide a strong foundation for the development of biosensors applicable to both clinical diagnostics and biological research.

bioengineering↗

bioRxiv2025

Accelerated Discovery of Aptamer Beacons via Massively Parallel Screening

Aptamer beacons are unimolecular probes that undergo a reversible conformational change upon target binding, making them a promising tool for the real-time detection and monitoring of molecular analytes. However, the development of such sensors has been impeded by the lack of generalizable tools for the efficient discovery and optimization of aptamer beacons for diverse molhhtmlecular targets. Here, we present a scalable approach for converting existing strand-displacement aptamer switches into aptamer beacons by introducing targeted mismatches within their non-target-binding stem domain, destabilizing the aptamer structure to an extent that it can only refold upon binding its target. In order to perform this screening in a high-throughput fashion, we have developed the Massively-parallel Aptamer Performance Analyzer (MAPA), an automated, fluorescence-based screening platform based on a reconfigured sequencing instrument that can functionally evaluate millions of aptamer variants in parallel. Using MAPA, we identified multiple aptamer beacons for glucose, serotonin, and dopamine, and demonstrated that these beacons retain their sensing performance when translated from the on-chip surface-based MAPA format to a solution-based assay. We performed all three aptamer beacon experiments on a single MAPA chip, and even greater multiplexing should be possible, greatly accelerating the discovery of aptamer-based sensors for real-time molecular detection.

bioengineering↗

bioRxiv2025

Axonal pathology differentially affects human Purkinje cell subtypes in the essential tremor cerebellum

The cerebellar cortex is organized into discrete regions populated by molecularly distinct Purkinje cells (PCs), the sole cortical output neurons. While studies in animal models have shown that PC subtypes differ in their vulnerability to disease, our understanding of human PC subtype and vulnerability remains limited. Here, we demonstrate that human cerebellar regions specialized for motor vs cognitive functions (lobule HV vs Crus I) contain distinct PC populations characterized by specific molecular and anatomical features, which show selective vulnerability in essential tremor (ET), a cerebellar degenerative disorder. Using a known PC subtype marker, neurofilament heavy chain (NEFH), we found that motor lobule HV contains PCs with high NEFH expression, while cognitive lobule Crus I contains PCs with low NEFH expression in post-mortem samples from healthy controls. In the same cerebella, PC axons in lobule HV were 2.2-fold thicker than those in Crus I. Across lobules, axon caliber positively correlated with NEFH expression. In ET cerebella, we identified motor lobule-specific PC axon pathology with a 1.5-fold reduction in caliber and increased axon variability in lobule HV, while Crus I axons were unaffected. Tremor severity and duration in ET correlated with axon diameter variability selectively in lobule HV PCs. Given that axonal caliber is a major determinant of neural signaling capacity, our results (1) suggest that disrupted cerebellar corticonuclear signaling is occurring in ET, (2) provide evidence of region-specific PC subtypes in the human cerebellum and offer insight into how selective PC vulnerability may contribute to the pathophysiology of cerebellar degeneration. Significance StatementThe cerebellar cortex has a uniform laminar architecture but contains heterogeneous cell types. Purkinje cells (PCs), the sole output cells of the cerebellar cortex, include subtypes whose lobular distribution is thought to underlie functional segmentation and patterned degeneration of the cerebellum in animal models. However, human PC subtypes and their disease vulnerability remain unknown. Here, we establish the existence of human PC subtypes that appear conserved across mammalian species using both marker expression and axonal thickness. Consistent with its phenotype, we demonstrate differential PC vulnerability to degeneration in essential tremor cerebella, where motor function- mediating PC subtypes display significant axonal thinning, while axons of cognitive function-mediating PC subtypes are spared. These findings advance Purkinje cell type- oriented research in cerebellar disorders.

neuroscience↗

bioRxiv2024

Dynamic remodeling of mechano-sensing complexes in suspended fibroblast cell-sheets under external mechanical stimulus

Freestanding cell-sheets are valuable bio-materials for use in regenerative medicine and tissue engineering. Because cell-sheets experience various mechanical stimulations during handling, it is important to understand the responses of cells to these stimulations. Here, we demonstrate changes in the localization of various proteins during the stretching of fibroblast cell-sheets. These proteins are known to be involved in mechano-sensing. Upon stretching, actin filaments appear parallel to the stretching direction. At cell-cell junctions, {beta}-catenin forms clusters that co-localize with accumulated vinculin and zyxin as well as the actin filaments. The p130 Crk-associated substrate, known to be present in focal adhesions, is also recruited to these clusters and phosphorylated. Our results suggest that mechano-sensing machinery is formed at cell-cell junctions when the cell-sheets are stretched.

bioengineering↗

bioRxiv2024

The lysosomal membrane protein LAMP2B mediates microlipophagy to target obesity-related disorders

Lifestyle diseases, such as obesity, diabetes, and metabolic syndrome, are leading health problems, most of which are related to abnormal lipid metabolism. Lysosomes can degrade lipid droplets (LDs) via microautophagy. Here, we report the molecular mechanism and pathophysiological roles of microlipophagy, regulated by the lysosomal membrane protein LAMP2B. Our study revealed that LAMP2B interacts with phosphatidic acid, facilitating lysosomal-LD interactions and enhancing lipid hydrolysis via microlipophagy depending on endosomal sorting complexes required for transport. Correlative light and electron microscopy demonstrated direct LDs uptake into lysosomes at contact sites. Moreover, LAMP2B overexpression in mice prevents high-fat diet-induced obesity, insulin resistance, and adipose tissue inflammation; liver lipidomics analysis suggested enhanced triacylglycerol hydrolysis. Overall, the findings of this study elucidated the mechanism of microlipophagy, which could be promising for the treatment of obesity and related disorders.

cell biology↗

bioRxiv2024

High-throughput screening for Cushing's disease: therapeutic potential of thiostrepton via cell cycle regulation

Cushings disease is a life-threatening disorder caused by autonomous secretion of adrenocorticotropic hormone (ACTH) from pituitary neuroendocrine tumors (PitNETs). Few drugs are indicated for inoperative Cushings disease, in particular that due to aggressive PitNETs. To explore agents that regulate ACTH-secreting PitNETs, we conducted high-throughput screening (HTS) using AtT-20, a murine pituitary tumor cell line characterized by ACTH secretion. For the HTS, we constructed a live cell- based ACTH reporter assay for high-throughput evaluation of ACTH changes. This assay was based on HEK293T cells overexpressing components of the ACTH receptor and a fluorescent cAMP biosensor, with high-throughput acquisition of fluorescence images at the single-cell level. Of 2480 screened bioactive compounds, over 50% inhibition of ACTH secreted from AtT-20 cells was seen with 84 compounds at 10 M, and 20 compounds at 1 M. Among these hit compounds, we focused on thiostrepton (TS) and determined its antitumor effects in both in vitro and in vivo xenograft models of Cushings disease. Transcriptome and flow cytometry analyses revealed that TS administration induced AtT-20 cell cycle arrest at the G2/M phase, which was mediated by FOXM1-independent mechanisms including downregulation of cyclins. Simultaneous TS administration with a CDK 4/6 inhibitor that affected the cell cycle at the G0/1 phase showed cooperative antitumor effects. Thus, TS is a promising therapeutic agent for Cushings disease. Our list of hit compounds and new mechanistic insights into TS effects serve as a valuable foundation for future research.

cell biology↗

bioRxiv2023

Transcriptomic Landscape of Hyperthyroidism in Mice Overexpressing Thyroid Stimulating Hormone

Hyperthyroidism is a condition with excessive thyroid hormone secretion. Activation of thyroid stimulating hormone receptor (TSHR) fundamentally leads to hyperthyroidism. The details of TSHR signaling remain to be elucidated. We conducted transcriptome analyses for hyperthyroid mice that we generated by overexpressing TSH. TSH overexpression via hydrodynamic gene delivery with pLIVE-TSHB and pLIVE-CGA vectors consistently caused hyperthyroidism and goiters for at least 4 weeks in C57BL/6J mice. RNA sequencing analysis of their thyroid glands revealed that thiamazole slightly changed the thyroid transcriptome, which reinforces a conventional theory that thiamazole decreases thyroid hormone secretion via inhibition of thyroid peroxidase activity. Meanwhile, TSH overexpression drastically changed the thyroid transcriptome. In particular, enrichment analyses identified the cell cycle, phosphatidylinositol-3 kinase/Akt pathway, and Ras-related protein 1 pathway as possibly associated with goiter development. Regarding the role of TSHR signaling in hyperthyroidism, it is noteworthy that Slc26a4 was exclusively upregulated among genes crucial to thyroid hormone secretion at both 1 and 4 weeks after hydrodynamic gene delivery. To verify the relationship between this upregulation and hyperthyroidism, we overexpressed TSH in Slc26a4 knockout mice. TSH overexpression caused hyperthyroidism in Slc26a4 knockout mice, equivalent to that in control mice. To summarize, we analyzed hyperthyroid mice generated by TSH overexpression. We did not observe significant changes in known genes and pathways involved in thyroid hormone secretion. Thus, our datasets might include candidate genes that have not yet been identified as regulators of thyroid function. Our transcriptome datasets regarding hyperthyroidism can contribute to future research on TSHR signaling.

physiology↗

bioRxiv2023

HOIL-1L deficiency induces cell cycle alteration which causes immaturity of myocyte and fibrogenesis

HOIL-1L deficiency was recently reported to be one of the causes of myopathy and dilated cardiomyopathy (DCM). However, the mechanisms by which myopathy and DCM develop have not been clearly elucidated. Here, we sought to elucidate these mechanisms using the murine myoblast cell line C2C12 and disease-specific human induced pluripotent stem cells (hiPSCs). Myotubes were differentiated from control and HOIL-1L-KO C2C12 cells. Cardiomyocytes (CMs) were differentiated from control and patient-derived hiPSCs. We investigated the impact of HOIL-1L on differentiation of myotubes and CMs. Myotubes differentiated from HOIL-1L-KO C2C12 cells exhibited deteriorated differentiation and mitotic cell accumulation. CMs differentiaed from patient-derived hiPSCs had an abnormal morphology with a larger size and were excessively multinucleated compared with CMs differentiaed from control hiPSCs. Further analysis of hiPSC- derived CMs showed that HOIL-1L deficiency caused cell cycle alteration and mitotic cell accumulation. These results were supported by RNA sequencing of C2C12 cell-derived myotubes. In addition, SerpinE2, a cardiac fibrogenesis gene, was significantly upregulated in CMs differentiaed from patient-derived hiPSCs. These results demonstrate that abnormal cell maturation and fibrosis possibly contribute to the development of DCM and myopathy. In conclusion, HOIL-1L is an important intrinsic regulator of cell cycle-related myotube and CM maturation and cell proliferation.

cell biology↗

bioRxiv2023

Soil Prokaryotic and Fungal Biome Structures Associated with Crop Disease Status across the Japan Archipelago

Archaea, bacteria, and fungi in the soil are increasingly recognized as determinants of agricultural productivity and sustainability. A crucial step for exploring soil microbiomes with high ecosystem functions is to perform statistical analyses on potential relationship between microbiome structure and functions based on comparisons of hundreds or thousands of environmental samples collected across broad geographic ranges. In this study, we integrated agricultural field metadata with microbial community analyses by targeting > 2,000 soil samples collected along a latitudinal gradient from cool-temperate to subtropical regions in Japan (26.1- 42.8 {degrees}N). The data involving 632 archaeal, 26,868 bacterial, and 4,889 fungal operational taxonomic units detected across the fields of 19 crop plant species allowed us to conduct statistical analyses (permutational analyses of variance, generalized linear mixed models, and randomization analyses) on relationship among edaphic factors, microbiome compositions, and crop disease prevalence. We then examined whether the diverse microbes form species sets varying in potential ecological impacts on crop plants. A network analysis suggested that the observed prokaryotes and fungi were actually classified into several species sets (network modules), which differed substantially in associations with crop disease prevalence. Within the network of microbe-to-microbe coexistence, ecologically diverse microbes, such as an ammonium-oxidizing archaeum, an antibiotics-producing bacterium, and a potentially mycoparasitic fungus, were inferred to play key roles in shifts between crop-disease-promotive and crop-disease-suppressive states of soil microbiomes. The birds-eye view of soil microbiome structure will provide a basis for designing and managing agroecosystems with high disease-suppressive functions. IMPORTANCEUnderstanding how microbiome structure and functions are organized in soil ecosystems is one of the major challenges in both basic ecology and applied microbiology. Given the ongoing worldwide degradation of agroecosystems, building frameworks for exploring structural diversity and functional profiles of soil microbiomes is an essential task. Our study provides an overview of cropland microbiome states in light of potential crop-disease-suppressive functions. The large dataset allowed us to explore highly functional species sets that may be stably managed in agroecosystems. Furthermore, an analysis of network architecture highlighted species that are potentially used to cause shifts from disease-prevalent states of agroecosystems to disease-suppressive states. By extending the approach of comparative analyses towards broader geographic ranges and diverse agricultural practices, agroecosystem with maximized biological functions will be further explored.

microbiology↗

bioRxiv2023

Deterministic and stochastic processes generating alternative states of microbiomes

The structure of microbial communities is often classified into discrete or semi-discrete compositions of taxa as represented by "enterotypes" of human gut microbiomes. Elucidating mechanisms that generate such "alternative states" of microbiome compositions has been one of the major challenges in ecology and microbiology. In a time-series analysis of experimental microbiomes, we here show that both deterministic and stochastic ecological processes drive divergence of alternative microbiome states. We introduced species-rich soil-derived microbiomes into eight types of culture media with 48 replicates, monitoring shifts in community compositions at six time points (8 media x 48 replicates x 6 time points = 2,304 community samples). We then confirmed that microbial community structure diverged into a few discrete states in each of the eight medium conditions as predicted in the presence of both deterministic and stochastic community processes. In other words, microbiome structure was differentiated into a small number of reproducible compositions under the same environment. This fact indicates not only the presence of selective forces leading to specific equilibria of community-scale resource use but also the influence of demographic drift (fluctuations) across basins of such equilibria. A reference-genome analysis further suggested that the observed alternative states differed in ecosystem-level functions. These findings will help us examine how microbiome structure and functions can be controlled by changing the "stability landscapes" of ecological community compositions.

ecology↗

bioRxiv2023

Facilitative interaction networks in experimental microbial community dynamics

Understanding potential roles of facilitative interactions between species is one of the major challenges in ecology and microbiology. However, we still have limited knowledge of entangled webs of facilitative interactions in ecosystems. By compiling whole-genome shotgun metagenomic data of an experimental microbial community, we tested the hypothesis that architecture of facilitative interaction networks could change through time. A metabolic modeling approach for estimating dependence between microbial genomes (species) allowed us to infer the network structure of potential facilitative interactions at 13 time points through the 110-day monitoring of experimental microbiomes. We then found that positive feedback loops, which were theoretically predicted to promote cascade breakdown of ecological communities, existed within the inferred networks of metabolic interactions prior to the drastic community-compositional shift observed in the microbiome time-series. We further applied "directed-graph" analyses to pinpoint potential keystone species located at the "upper stream" positions of such feedback loops. These analyses on facilitative interactions will help us understand key mechanisms causing catastrophic shifts in microbial community structure.

ecology↗

bioRxiv2023

Metagenomic analysis of ecological niche overlap and community collapse in microbiome dynamics

Species utilizing the same resources often fail to coexist for extended periods of time. Such competitive exclusion mechanisms potentially underly microbiome dynamics, causing breakdowns of communities composed of species with similar genetic backgrounds of resource utilization. Although genes responsible for competitive exclusion among a small number of species have been investigated in pioneering studies, it remains a major challenge to integrate genomics and ecology for understanding stable coexistence in species-rich communities. Here, we show that community-scale analyses of functional gene redundancy can provide a useful platform for interpreting and predicting collapse of bacterial communities. Through 110-day time-series of experimental microbiome dynamics, we analyzed the metagenome-assembled genomes of co-occurring bacterial species. We then inferred ecological niche space based on the multivariate analysis of the genome compositions. The analysis allowed us to evaluate potential shifts in the level of niche overlap between species through time. We hypothesized that community-scale pressure of competitive exclusion could be evaluated by quantifying overlap of genetically determined resource-use profiles (metabolic pathway profiles) among coexisting species. We found that the degree of community compositional changes observed in the experimental microbiome was explained by the magnitude of gene-repertoire overlaps among bacterial species. The metagenome-based analysis of genetic potential for competitive exclusion will help us forecast major events in microbiome dynamics such as sudden community collapse (i.e., dysbiosis).

microbiology↗

bioRxiv2022

Spontaneous and multifaceted ATP release from astrocytes at the scale of hundreds of synapses

Astrocytes participate in information processing by releasing neuroactive substances termed gliotransmitters, including ATP. Individual astrocytes come into contact with thousands of synapses with their ramified structure, but the spatiotemporal dynamics of ATP gliotransmission remain unclear, especially in physiological brain tissue. Using a genetically encoded fluorescent sensor, GRABATP1.0, we discovered that extracellular ATP increased locally and transiently in absence of stimuli in neuron-glia co-cultures, cortical slices, and the anesthetized mouse brain. Spontaneous ATP release events were tetrodotoxin-insensitive but suppressed by gliotoxin, fluorocitrate, and typically spread over 50-250 m2 area at concentrations capable of activating purinergic receptors. Besides, most ATP events did not coincide with Ca2+ transients. Clustering analysis revealed that these events followed multiple distinct kinetics, and blockade of exocytosis only decreased a minor group of slow events. Overall, astrocytes spontaneously release ATP through multiple mechanisms, mainly in non-vesicular and Ca2+-independent manners, thus potentially regulating hundreds of synapses all together.

neuroscience↗

bioRxiv2022

PNPO-PLP Axis Senses Prolonged Hypoxia by Regulating Lysosomal Activity

Oxygen is critical for all metazoan organisms on the earth and impacts various biological processes in physiological and pathological conditions. While oxygen sensing systems inducing acute hypoxic response, including HIF pathway, have been identified, those operating in prolonged hypoxia remain to be elucidated. Here, we show that pyridoxine 5-phosphate oxidase (PNPO) that catalyzes bioactivation of vitamin B6 serves as an oxygen sensor and regulates lysosomal activity in macrophages. Decline of PNPO activity under prolonged hypoxia reduced an active form of vitamin B6, pyridoxal 5-phosphate (PLP), and inhibited lysosomal activity, leading to the augmentation of inflammatory response of macrophages. The PNPO-PLP axis creates a distinct layer of oxygen sensing, which gradually turns down and up the PLP-dependent metabolism according to prolonged changes in oxygen availability.

biochemistry↗