Biology subjects

Ogawa, K.

Publications and source records attributed to Ogawa, K..

At least 19 recordsLinked to original sources

bioRxiv2026

HPV-Associated Tonsillar Intraepithelial Neoplasia and Oral High-Risk HPV mRNA as a Candidate Biomarker

Early detection of human papillomavirus (HPV)-associated oropharyngeal cancer is an unmet need, as its premalignant lesions remain unestablished. We hypothesized that such lesions exist in individuals with oral high-risk HPV (HR-HPV) mRNA. We preoperatively screened 1,180 individuals undergoing tonsillectomy due to benign conditions and detected five with oral HR-HPV mRNA. Serial sectioning of the entire excised tonsils identified HPV-associated intraepithelial lesions in three of these five individuals. A similar lesion was identified in an additional individual with oral HPV16 infection with unknown oral HR-HPV mRNA status. Intraepithelial lesions in two individuals were HPV16-associated and showed moderate-to-severe atypia, whereas those in the other two individuals were associated with other HR-HPV and showed minimal-to-mild atypia. Based on HPV life cycle, the former were classified as transforming lesions and the latter as productive-to-intermediate lesions. Spatial transcriptomic analysis revealed molecular profiles intermediate between those of normal epithelium and HPV-associated oropharyngeal cancer. These findings establish the first evidence for HPV-associated tonsillar premalignant lesions and suggest oral HR-HPV mRNA as a candidate biomarker.

cancer biology↗

bioRxiv2026

Scale-dependent spatial organisation of action observation network responses to hand actions and emotional faces

Human social perception relies on multiple visual signals, including object-directed actions and emotional facial expressions. It remains unclear whether responses to these signals converge within action-observation regions and whether apparent convergence depends on the spatial scale of analysis. We scanned 39 healthy human adults during two block-design fMRI tasks, hand action observations contrasted with paper-tube controls, and emotional expression observations contrasted with neutral faces. Using independently defined meta-analytic action observation network (AON) ROIs in the inferior frontal gyrus (IFG), inferior parietal lobule (IPL), and posterior superior temporal sulcus (pSTS), we analysed responses at whole-brain, ROI-average, and AON-constrained voxelwise scales. Whole-brain overlap between the two contrasts was localised primarily to the left lateral occipitotemporal extrastriate cortex, outside the AON. At the regional ROI-average scale, the IFG showed positive responses to both contrasts, whereas the IPL and pSTS showed opposing task preferences. Crucially, regional IFG co-engagement did not imply that the same voxels responded to both contrasts. Suprathreshold voxelwise overlap within the AON was virtually absent, and individual-level analysis revealed a small but reliable posterior displacement of hand action relative to emotional face within IFG. These findings show that spatial convergence between hand and emotion observation responses depends on the scale of analysis. The same IFG region can be engaged by both stimulus domains while retaining distinct local response topographies.

neuroscience↗

bioRxiv2026

Mitochondrial one-carbon enzyme MTHFD1L sustains stemness and metastatic progression in breast cancer

One-carbon (1C) metabolism is frequently upregulated in cancer to support anabolic growth and nucleotide biosynthesis. However, the contribution of mitochondrial 1C metabolism to cancer stemness and metastatic progression remains incompletely understood. Here, we identify methylenetetrahydrofolate dehydrogenase 1-like (MTHFD1L), a mitochondrial 1C metabolic enzyme, as a critical regulator of breast cancer stemness, tumor initiation, and lung metastasis. Genetic depletion of MTHFD1L in triple-negative breast cancer (TNBC) cell lines and patient-derived breast cancer models markedly impaired proliferation, sphere formation, tumorigenicity, and lung colonization. Metabolomic profiling revealed extensive metabolic rewiring following MTHFD1L loss, characterized by accumulation of the purine biosynthetic intermediates SAICAR and AICAR together with perturbations in glycolytic and pentose phosphate pathways. Importantly, suppression of lung metastasis was accompanied by reduced expression of the stemness-associated transcription factor SOX2 and decreased proliferative activity in metastatic lesions. Collectively, our findings establish MTHFD1L as a key metabolic dependency linking mitochondrial 1C metabolism to stem-like properties and metastatic progression in breast cancer, and highlight MTHFD1L as a promising therapeutic target in metastatic TNBC.

Cancer Biology↗

bioRxiv2026

Single-cell spatial multiomics identifies POSTN+ CAFs mediating chemoradiotherapy resistance in rectal cancer

Neoadjuvant chemoradiotherapy (CRT) is standard for locally advanced rectal cancer (LARC), yet many patients retain residual disease. To resolve CRT-associated remodeling of the tumor microenvironment, we generated a multimodal spatial atlas from serial sections of paired pretreatment and post-treatment specimens from 24 patients using Xenium single-cell spatial transcriptomics and PhenoCycler multiplex proteomics, profiling 2.8 million cells; matched Visium HD datasets were generated on adjacent serial sections. Resistance was most strongly associated with fibroblast and myeloid programs adjacent to residual tumor. We identify a periostin (POSTN)-expressing CAF subset selectively enriched around residual tumor cells in non-responders, displaying a myofibroblastic phenotype and activating extracellular matrix remodeling, noncanonical WNT signaling, and immunosuppressive pathways. Tumor cells neighboring POSTN+ CAFs show consistent epithelial-mesenchymal transition signatures. Together, this atlas enables interrogation of CRT-induced spatial remodeling and nominates POSTN+ CAFs as key mediators and targets of CRT resistance, with direct relevance to CRT-based combination strategies.

cancer biology↗

bioRxiv2026

Common neural representation between visual perception and imagery in eidetikers

Eidetic imagery is experienced as "seen" in external space, unlike typical visual mental imagery, which occurs in the minds eye. To investigate whether eidetic imagery and perception share common neural substrates, we measured brain activity in eidetikers and typical imagers using fMRI while they performed perception and imagery tasks. Multi-voxel pattern analysis (MVPA) revealed that imagined objects could be classified based on perceptual activation patterns in right BA19 for eidetikers, but not for typical imagers. This effect was specific to BA19 and was not observed in early visual areas (BA17/18). Subjective ratings confirmed that eidetikers experienced images as percept-like. These findings provide neural evidence for percept-like mental imagery and show that individual differences in subjective experience are reflected in the high-level visual cortex. Significance StatementHow does the brain support individual differences in subjective visual experience? Visual mental imagery partially shares neural substrates with perception, but how this shared activity relates to subjective conscious experience remains unclear. Some individuals, known as eidetikers, report images that are literally seen and percept-like, providing a unique opportunity to investigate the neural basis of individual variation. Using fMRI and multivariate pattern analysis, we show that in eidetikers, the neural representations of imagined objects are more strongly shared with perceptual representations in a higher-level visual area (BA19) than in typical imagers. These findings provide neural evidence for eidetic imagery and reveal how individual differences in subjective experience are reflected in the organization of visual representations in the human brain.

neuroscience↗

bioRxiv2025

Template-based RNA structure prediction advanced through a blind code competition

Automatically predicting RNA 3D structure from sequence remains an unsolved challenge in biology and biotechnology. Here, we describe a Kaggle code competition engaging over 1700 teams and 43 previously unreleased structures to tackle this challenge. The top three submitted algorithms achieved scores within statistical error of the winners of the recent CASP16 competition. Unexpectedly, the top Kaggle strategy involved a pipeline for discovering 3D templates, without the use of deep learning. We integrated this template-modeling pipeline and other Kaggle strategies to develop a single model RNAPro that retrospectively outperformed individual Kaggle models on the same test set. These results suggest a growing importance of template-based modeling in RNA structure prediction.

biophysics↗

bioRxiv2025

Focused acoustic-radiation-force microscopy for live-cell selective nucleus deformation and nucleus viscoelasticity measurement

Acoustic-radiation-force (ARF) microscopy was developed for non-invasive, selective mechanical stimulation to a single live-cell nucleus and long-term measurement of its mechanical properties. High-frequency focused ultrasound wave achieved a spatially confined ARF field around target nucleus, and its cyclic deformation was induced by amplitude modulation on the ultrasound wave, which was captured by a dark-field microscopy. This method was applied to human mesenchymal stem cells, revealing their extremely high mechanical homeostasis.

biophysics↗

bioRxiv2025

Novel humanized anti-Nav1.7 antibodies with long-lasting, side-effect-free analgesic effects

Neuropathic pain remains difficult to treat effectively because of the limitations of current pain medications. The Nav1.7 sodium channel plays a crucial role in pain sensation. The development of selective inhibitors has been challenging because of the high similarity among Nav channel subtypes. To address this issue, we developed monoclonal antibodies that selectively target Nav1.7 and humanized them for clinical use for the first time. When administered systemically to neuropathic pain model rats, a potent analgesic effect was observed that lasted for at least 96 hours. Electrophysiological studies revealed that the antibody reduced mechanically-evoked and spontaneous neuronal activity in the model. Importantly, the antibodies did not impact physiological pain or motor function. Collectively, our findings suggest that these novel Nav1.7-targeting antibodies are potentially effective analgesic drugs for chronic pain, including neuropathic pain. Our novel humanized anti-Nav1.7 antibodies have the potential to be used for the development of new analgesic, and one such antibody, S-151128 is currently in clinical trial.

pharmacology and toxicology↗

bioRxiv2025

Developing a Novel In Vitro Toxicity Assay for Predicting Inhalation Toxicity in Rats

The development of alternative in vitro methods for assessing acute inhalation toxicity is a critical step toward reducing animal testing and aligns with the principles of the 3Rs (replacement, reduction, and refinement). In this study, we developed and optimized a neutral red uptake (NRU) assay using human lung adenocarcinoma cells (A549) as a predictive model (A549-NRU) for acute inhalation toxicity. To improve assay efficiency and robustness, we introduced two key modifications: the incubation time was reduced to 15 minutes to enable rapid and high-throughput screening, and for chemicals reactive with polystyrene 6-well glass plates were used to prevent chemical-induced degradation and ensure assay consistency. LC50 values were determined for 49 chemicals and compared with reported LC50 values from 4-hour rat inhalation studies. A significant positive correlation was observed between A549-NRU-derived LC50 values and in vivo LC50 values for water-soluble compounds and chemicals containing aldehyde, ketone, alcohol, ether, and epoxide functional groups, suggesting that in vivo LC50 values may be predictable using the A549-NRU assay. Additionally, A549-NRU LC50 values showed significant negative correlations with molecular weight and octanol-water partition coefficients, indicating that chemicals with higher values tended to be less cytotoxic in vitro. Importantly, the A549-NRU assay demonstrated stronger correlation with in vivo LC50 values than the conventional NRU assay using mouse 3T3 fibroblast cells. These findings support the use of the A549-NRU assay to estimate starting doses for in vivo studies, and potentially as an in vitro alternative for predicting acute inhalation toxicity. Impact statementThe optimized A549-NRU assay demonstrates predictive potential for inhalation toxicity while reducing reliance on animal testing. This model serves as a human-relevant alternative for estimating starting doses for in vivo inhalation toxicity studies.

pharmacology and toxicology↗

bioRxiv2025

The common neural representation in the primary motor area between motor execution and kinesthetic motor imagery

Although motor imagery activates higher-order motor-related areas, the role of the primary motor area (M1) in motor imagery remains unclear. This study aimed to investigate whether motor imagery recruits a neural representation of fingers similar to that of motor execution in the hand M1. Ten healthy right-handed adults executed and kinesthetically imagined tapping using one of four fingers. Using functional magnetic resonance imaging with multi-voxel pattern analysis, we trained the decoder to classify which finger the participants were moving using brain activation during motor execution and tested whether it could predict which finger the participants were imaging to move during motor imagery (cross-classification). We also performed the classification in the reverse direction. The average accuracy of these cross-classifications was significantly higher than chance in the left hemisphere hand M1 (hand-M1). Analysis of the representational geometry showed that the distance of neural representations for the same fingers was statistically shorter than that for different fingers between motor execution and imagery. Furthermore, we conducted a replication study with 14 participants and found results similar to those of the original study. Our results suggest that the neural representation of kinesthetic motor imagery is partially similar to that of motor execution in the contralateral hand M1.

neuroscience↗

bioRxiv2024

Male and female gametophytes meet after winter: Testing the overwintering hypothesis for delayed fertilization in Japanese stone oak

PremiseFertilization delays of nearly a year have been observed in many acorn-producing Fagaceae trees. Despite this long-standing recognition, the underlying mechanisms and adaptive significance of delayed fertilization remain largely unexplored. It has been hypothesized that these prolonged delays may serve as an adaptive strategy, allowing ovules to be fertilized and seeds to develop during more favorable seasons, thereby avoiding the adverse conditions of winter. However, empirical evidence to support this hypothesis is still lacking. MethodsTo test the overwintering hypothesis, we observed the seasonal progression of pollen tube growth and ovule development in Lithocarpus edulis, a species exhibiting two flowering seasons, spring and autumn. We conducted monthly observations of pollen tube growth and ovule development in both spring and autumn flower samples. We employed microtome techniques and scanning confocal microscopy to closely examine the seasonal progression of pollen tube growth and ovule development. ResultsWe found that pollen tubes were arrested at the style-joining site, and ovules remained immature in both spring and autumn samples prior to winter. Following winter, pollen tube regrowth and ovule maturation were synchronized in the subsequent spring in both spring and autumn samples. ConclusionsOur results support the overwintering hypothesis, suggesting that delayed fertilization may serve as an adaptive strategy to ensure fertilization in spring, overcoming the reproductive challenges posed by cold winter conditions. Our study introduces a new avenue for studying the temporal organization of plant reproductive phenology, specifically the alignment of flowering, pollination, fertilization, and fruiting in seasonal environments.

plant biology↗

bioRxiv2024

Human sensorimotor cortex reactivates recent visuomotor experience during awake rest

Previous studies have suggested that awake rest after training is helpful in improving motor performance and memory consolidation in visuomotor learning. Re-emergence of task-related activation patterns during awake rest has been reported, which play a role in memory consolidation or perceptual learning. This study aimed to test whether such reactivation occurs after visuomotor learning in the primary sensorimotor cortex. During fMRI scanning, 42 normal participants learned visuomotor tracking, while a rotational perturbation was introduced between a cursor position and a joystick angle. This visuomotor learning block was interleaved with the control block, during which the participants passively viewed a replay of previously performed cursor movements of their own. Half of the participants used their right hand, and the other half used their left hand to control the joystick. The resting-state scans were measured before and after the visuomotor learning sessions. A multivariate pattern classifier was trained to classify task and control blocks and then tested with resting scans before and after learning. Results revealed a significant increase in the number of volumes classified as the task in the post-learning rest compared with the pre-learning, indicating a re-emergence of task-related activities. Representational similarity analysis also showed a more similar pattern of activity with the task during the post-learning rest period. Furthermore, this effect is specific to the primary sensorimotor cortex contralateral to the hand used and significantly correlated with motor improvement after rest. Our finding revealed the reactivation of task-related patterns in the primary sensorimotor cortex for offline visuomotor learning. Significance StatementPrevious research suggests that awake rest after learning promotes memory consolidation, which is subserved by the re-emergence of task-specific activity patterns. We aimed to determine whether such reactivation occurs in the primary sensorimotor cortex following visuomotor learning for offline memory consolidation. Our results showed a significant increase in task-classified brain volumes during the post-learning rest period compared to the pre-learning period, indicating a re-emergence of task-related activity. Furthermore, this effect was specific to the primary sensorimotor cortex contralateral to the hand used for the task and significantly correlated with the motor performance following the rest period. These findings provide evidence for the reactivation of task-related patterns during offline visuomotor learning, which may underlie memory consolidation processes.

neuroscience↗

bioRxiv2024

Transcriptome Analysis Identified SPP1+ Monocytes as a Key in Extracellular Matrix Formation in Thrombi

Thrombi follow various natural courses. They are known to become harder over time and may persist long-term; some of them can also undergo early spontaneous dissolution and disappearance. Hindering thrombus stability may contribute to the treatment of thrombosis and the prevention of embolisms. However, the detailed mechanisms underlying thrombus maturation remain unknown. Using RNA sequencing, we revealed the transcriptional landscape of thrombi retrieved from the cerebral vessels and identified SPP1 as a hub gene related to extracellular matrix formation. Immunohistochemistry confirmed the expression of osteopontin in monocytes/macrophages in the thrombi, particularly in older thrombi. Single-cell RNA sequencing of thrombi from the pulmonary artery revealed increased communication between SPP1-high monocytes/macrophages and fibroblasts. These data suggest that SPP1-high monocytes/macrophages play a crucial role in extracellular matrix formation in thrombi and provide a basis for new antithrombotic therapies targeting thrombus maturation. TeaserSPP1+ monocytes play a key role in thrombus maturation, which can be a potential target for novel antithrombotic therapies.

molecular biology↗

bioRxiv2024

Prediction of antidepressant treatment response with thalamo-somatomotor functional connectivity revealed by generalizable stratification of depressed patients

Major depressive disorder (MDD) is diagnosed based on symptoms and signs without relying on physical, biological, or cognitive tests. MDD patients exhibit a wide range of complex symptoms, and it is assumed that there are diverse underlying neurobiological backgrounds, possibly composed of several subtypes with relatively homogeneous biological features. Initiatives, including the Research Domain Criteria, emphasize the importance of biologically stratifying MDD patients into homogeneous subtypes using a data-driven approach while utilizing genetic, neuroscience, and cognitive information. If biomarkers can stratify MDD patients into biologically homogeneous subtypes at the first episode of depression, personalized precision medicine may be within our scope. Some pioneering studies have used resting-state functional brain connectivity (rs-FC) for stratification and predicted differential responses to various treatments for different subtypes. However, to our knowledge, little research has demonstrated reproducibility (i.e., generalizability) of stratification markers in independent validation cohorts. This issue may be due to inherent measurement and sampling biases in multi-site fMRI data, or overfitting of machine learning algorithms to discovery cohorts with small sample sizes, i.e., a lack of appropriate machine learning algorithms for generalizable stratification. To address this problem, we have constructed a multi-site, multi-disorder fMRI database with prospectively and retrospectively harmonized data from thousands of samples and proposed a hierarchical supervised/unsupervised learning strategy. In line with this strategy, our previous research first developed generalizable MDD diagnostic biomarkers using this fMRI database of MDD patients via supervised learning. The MDD diagnostic biomarker determines the importance of thousands to tens of thousands of rs-FCs across the whole brain for MDD diagnosis. In this study, we constructed stratification markers for MDD patients using unsupervised learning (Multiple co-clustering) with a subset of top-ranked rs-FCs in the MDD diagnostic biomarker. We developed a method to evaluate the clustering stability between two independent datasets as a generalization metric of stratification biomarkers. To discover stratification biomarkers with high stability across datasets, we utilized two multi-site datasets with substantial differences in data acquisition facilities and fMRI measurement protocols (Dataset-1: a dataset of 138 depressed patients obtained with a unified measurement protocol across three facilities; Dataset-2: a dataset of 181 depressed patients obtained with non-unified measurement protocols across four facilities, distinct from Dataset-1). Starting from several diagnostic biomarkers, we constructed some stratification markers and identified the stratification biomarker with the highest clustering stability between the two datasets. This stratification biomarker was based on several rs-FCs between the thalamus and the postcentral gyrus, and the MDD subgroups stratified by this biomarker showed significantly different treatment responsiveness to a selective serotonin reuptake inhibitor (SSRI). By narrowing down whole-brain rs-FCs using MDD diagnostic biomarkers and further dividing the rs-FCs using multiple co-clustering, the feature dimension was significantly reduced, thereby avoiding overfitting to the training data and successfully constructing stratification biomarkers that are highly stable between independent datasets, i.e., have generalizability. Furthermore, the correlation between MDD subgroups and antidepressant treatment response was demonstrated, suggesting the potential for achieving personalized precision medicine for MDD.

neuroscience↗

bioRxiv2024

Comprehensive evaluation of pipelines for diagnostic biomarkers of major depressive disorder using multi-site resting-state fMRI datasets

The objective diagnostic and stratification biomarkers developed with resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for mental disorders. Unfortunately, there are currently no widely accepted biomarkers, partially due to the large variety of analysis pipelines for developing them. In this study we comprehensively evaluated analysis pipelines using a large-scale, multi-site fMRI dataset for major depressive disorder (MDD) (1162 participants from eight imaging sites). We explored the combinations of options in four subprocesses of analysis pipelines: six types of brain parcellation, four types of estimations of functional connectivity (FC), three types of site difference harmonization, and five types of machine learning methods. 360 different MDD diagnostic biomarkers were constructed using the SRPBS dataset acquired with unified protocols (713 participants from four imaging sites) as a discovery dataset and evaluated with datasets from other projects acquired with heterogeneous protocols (449 participants from four imaging sites) for independent validation. To identify the optimal options regardless of the discovery dataset, we repeated the same procedure after swapping the roles of the two datasets. We found pipelines that included Glassers parcellation, tangent-covariance, no harmonization, and non-sparse machine learning methods tended to result in high classification performance. The diagnosis results of the top 10 biomarkers showed high similarity, and weight similarity was also observed between eight of the biomarkers, except two that used both data-driven parcellation and FC computation. We applied the top 10 pipelines to the datasets of other mental disorders (autism spectral disorder: ASD and schizophrenia: SCZ) and eight of the ten biomarkers showed sufficient classification performances for both disorders, except two pipelines that included Pearson correlation, ComBat harmonization and random forest classifier combination. HighlightsO_LIWe evaluated the analysis pipelines of rsFC biomarker development. C_LIO_LIFour subprocesses in them were investigated with two multi-site datasets. C_LIO_LIGlassers parcellation, tangent covariance, and non-sparse methods were preferred. C_LIO_LIThe weight patterns of eight of the top 10 biomarkers showed high commonality. C_LIO_LIEight of the top 10 pipelines were successful for developing SCZ/ASD biomarkers. C_LI

neuroscience↗

bioRxiv2023

Quantification of the escape from X chromosome inactivation with the million cell-scale human single-cell omics datasets reveals heterogeneity of escape across cell types and tissues

One of the two X chromosomes of females is silenced through X chromosome inactivation (XCI) to compensate for the difference in the dosage between sexes. Among the X-linked genes, several genes escape from XCI, which could contribute to the differential gene expression between the sexes. However, the differences in the escape across cell types and tissues are still poorly characterized because no methods could directly evaluate the escape under a physiological condition at the cell-cluster resolution with versatile technology. Here, we developed a method, single-cell Level inactivated X chromosome mapping (scLinaX), which directly quantifies relative gene expression from the inactivated X chromosome with droplet-based single-cell RNA-sequencing (scRNA-seq) data. The scLinaX and differentially expressed genes analyses with the scRNA-seq datasets of [~]1,000,000 blood cells consistently identified the relatively strong degree of escape in lymphocytes compared to myeloid cells. An extension of scLinaX for multi-modal datasets, scLinaX-multi, suggested a stronger degree of escape in lymphocytes than myeloid cells at the chromatin-accessibility level with a 10X multiome dataset. The scLinaX analysis with the human multiple-organ scRNA-seq datasets also identified the relatively strong degree of escape from XCI in lymphoid tissues and lymphocytes. Finally, effect size comparisons of genome-wide association studies between sexes identified the larger effect sizes of the PRKX gene locus-lymphocyte counts association in females than males. This could suggest evidence of the underlying impact of escape on the genotype-phenotype association in humans. Overall, scLinaX and the quantified catalog of escape identified the heterogeneity of escape across cell types and tissues and would contribute to expanding the current understanding of the XCI, escape, and sex differences in gene regulation.

genomics↗

bioRxiv2023

Neural substrates of top-down processing during perceptual duration-based timing and beat-based timing

Temporal context is a crucial factor in timing. Previous studies have revealed that the timing of regular stimuli, such as isochronous beats or rhythmic sequences (termed beat-based timing), activated the basal ganglia, whereas the timing of single intervals or irregular stimuli (termed duration-based timing) activated the cerebellum. We conducted a functional magnetic resonance imaging (fMRI) experiment to determine whether top-down processing of perceptual duration-based and beat-based timings affected brain activation patterns. Our participants listened to auditory sequences containing both single intervals and isochronous beats and judged either the duration of the intervals or the tempo of the beats. Whole-brain analysis revealed that both duration judgments and tempo judgments activated similar areas, including the basal ganglia and cerebellum, with no significant difference in the activated regions between the two conditions. In addition, an analysis of the regions of interest revealed no significant differences between the activation levels measured for the two tasks in the basal ganglia as well as the cerebellum. These results suggested that a set of common brain areas were involved in top-down processing of both duration judgments and tempo judgments. Our findings indicate that perceptual duration-based timing and beat-based timing are driven by stimulus regularity irrespective of top-down processing.

neuroscience↗

bioRxiv2023

UBL3 interaction with α-synuclein is downregulated by silencing MGST3

Ubiquitin-like 3 (UBL3) is a membrane-anchored protein that has been discovered to function as a protein post-translational modifier, helping to sort proteins into small extracellular vesicles (sEVs). Aggregations of alpha-synuclein (-syn) are associated with the pathology of neurodegenerative diseases such as Parkinsons disease (PD). The aggregation and toxicity of -syn can be influenced by its interactions with specific proteins. Recently, the interactions between UBL3 and -syn was uncovered. It is believed to play a role in eliminating excess -syn from neurons, or in the spread of -syn pathology in the brain associated with neurodegenerative diseases. However, the regulator that can mediate the interaction between UBL3 and -syn remains unclear. In this study, we employed the split gaussian luciferase complementation assay and RNA interference (RNAi) technology to discover that QSOX2, HTATIP2, UBE3C, MGST3, NSF, HECTD1, SAE1 and ATG3 are involved in downregulating the interaction between UBL3 and -syn. Among these proteins, silencing MGST3 had the most significant impact on the UBL3--syn interaction (with a fold change log2 of less than - 1). MGST3 is a part of the antioxidant system, and silencing MGST3 is believed to contribute to oxidative stress. We used hydrogen peroxide (H2O2) to induce oxidative stress and observed its effect on the UBL3--syn interaction. Our finding showed that an 800M concentration of H2O2 could also downregulate this interaction. However, the effect of oxidative stress caused by 800M H2O2 on the UBL3--syn interaction did not be enhanced by silencing MGST3. In conclusion, the interaction between UBL3 and -syn is downregulated by silencing MGST3.

molecular biology↗