Biology subjects

Iwata, A.

Publications and source records attributed to Iwata, A..

5 recordsLinked to original sources

bioRxiv2025

Sox4 in Treg Cells Suppresses IL-10 Production via c-Maf Degradation and Exacerbates Type 2 Inflammation

The anti-inflammatory cytokine interleukin-10 (IL-10) produced by regulatory T (Treg) cells plays a crucial role in regulating allergic airway inflammation. However, the mechanisms governing IL-10 production in Treg cells remain unclear. In this study, we first identified Sox4 as a gene whose expression is down-regulated in IL-10-producing Treg cells. Comprehensive gene expression profiling of Sox4-deficient Treg cells and Sox4-overexpressing Treg cells revealed specific downregulation of Il10 and Ctla4 by Sox4. Sox4-deficient Treg cells exhibited increased IL-10 production and CTLA-4 expression both in vitro and in vivo and strongly suppressed Th2 cell proliferation compared with Sox4-expressing Treg cells. In a house dust mite (HDM)-induced asthma model, Treg-specific Sox4-deficient (Sox4-cKO) mice exhibited IL-10-dependent reductions in eosinophilic inflammation and Th2 cell infiltration in the airways. A comparison of Sox4-cKO and wild-type Treg cells in the same inflamed environment in mixed bone marrow chimeric mice with HDM-induced asthma revealed that Sox4-mediated suppression of c-Maf is cell-intrinsic. In addition, overexpression of Sox4 in Treg cells repressed the activation of c-Maf-regulated chromatin regions, including those around the Il10 and Ctla4 loci. Moreover, Sox4-induced suppression of IL-10 and CTLA-4 in Treg cells was rescued by forced expression of c-Maf. While Sox4 did not significantly affect Maf mRNA levels, Sox4 degraded c-Maf proteins in Treg cells through its 33 C-terminal residues. Via a domain distinct from its C-terminus, Sox4 physically interacted with c-Maf, subsequently facilitating its degradation through a ubiquitin-proteasome pathway. These findings elucidate a mechanism by which Sox4 influences the asthmatic responses by regulating the c-Maf/IL-10 axis in lung Treg cells.

immunology↗

bioRxiv2025

Aβ-HMGB1 complex is a pathogenic molecule at the advanced stage of Alzheimer's disease

Multiple molecules including A{beta}, tau and other inflammatory molecules mediate Alzheimers disease (AD) pathology. High mobility group box 1 (HMGB1), which is released from necrotic cells and binds to Toll-like receptors (TLRs) of surrounding neurons and microglia, also mediates AD pathology from the early stage. Paradoxically, HMGB1 concentration in cerebrospinal fluid (CSF) at the advanced stage of AD is not higher than that at the early stage. Here we show that A{beta}-HMGB1 complexes are generated in neurons undergoing secondary necrosis around A{beta} plaques in the AD brain at the advanced stage. A{beta}-HMGB1 complex triggers neurite degeneration and necrosis of human normal iPSC-derived neurons via binding to TLR4. Further, two anti-HMGB1 antibodies that inhibit its interaction with TLR4 successfully suppress the toxicity of A{beta}-HMGB1 complex to human iPSC-derived neurons, and recover cognitive impairment and A{beta}-HMGB1 complex-related brain pathology in AD model mice, while such therapeutic effects were not obvious with an anti-A{beta} antibody (lecanemab) approved for human AD patients. Enzyme-Linked Immuno Sorbent Assay (ELISA) revealed plasma level of A{beta}-HMGB1 complex was increased in a part of AD patients at the advanced stage. These findings for the molecular basis of toxicity to neurons suggest the significance of A{beta}-HMGB1 complex at the advanced stage of AD pathology, and might explain the discrepancy between A{beta} burdens and clinical symptoms of human AD patients treated with anti-A{beta} antibody.

neuroscience↗

bioRxiv2022

Proteomic profile of nuclei containing p62-positive inclusions in neuronal intranuclear inclusion disease

Neuronal intranuclear inclusion disease (NIID) is a neurodegenerative disease characterized by eosinophilic hyaline intranuclear inclusions in the neurons, glial cells, and other somatic cells. Although CGG repeat expansions in NOTCH2NLC have been identified in most East Asian patients with NIID, the pathophysiology of NIID remains unclear. Intranuclear inclusions are the pathological hallmark of NIID. Previously, immunohistochemistry has revealed that intranuclear inclusions are ubiquitin-, p62-, and SUMO-1-positive, suggesting the possible alteration of the ubiquitin-proteasomal protein degradation system in the nuclei with inclusions. However, the molecular mechanisms within these nuclei remain unclear. Herein, we analyzed the proteomic profile of nuclei with p62-positive inclusions in NIID with CGG repeat expansion in NOTCH2NLC to discover the proteins involved in the NIID pathophysiology. We used fluorescence-activated cell sorting and liquid chromatography-tandem mass spectrometry (LC-MS/MS) to quantify each protein identified in the nuclei with p62-positive inclusions. The distribution of increased proteins in the autopsy brain samples from three NIID patients was confirmed via immunofluorescence. Overall, 526 proteins were identified, of which 243 were consistently quantified using MS. A 1.4-fold increase was consistently observed for 20 proteins in nuclei with p62-positive inclusions compared to those without. Fifteen proteins identified with medium or high confidence in the LC-MS/MS analysis were further evaluated. Gene ontology enrichment analysis showed enrichment of several terms, including poly(A) RNA binding, nucleosomal DNA binding, and protein binding. Immunofluorescence studies confirmed that the fluorescent intensities of increased RNA-binding proteins identified by proteomic analysis, namely hnRNP A3, hnRNP A2/B1, and hnRNP C1/C2, were higher in the nuclei with p62-positive inclusions than those without; however, they were not confined to the intranuclear inclusions. We identified several increased proteins in nuclei with p62-positive inclusions. These data can form the basis for understanding the pathophysiology of NIID.

biochemistry↗

bioRxiv2020

Autocorrelation-based method to identify disordered rhythm in Parkinsons disease tasks: a novel approach applicable to multimodal devices

ObjectiveWe aim to propose a novel method of evaluating the degree of rhythmic irregularity during repetitive tasks in Parkinsons disease (PD) by using autocorrelation to extract serial perturbation in the periodicity of body part movements as recorded by objective devices. MethodsWe used publicly distributed sequential joint movement data recorded during a leg agility task or pronation-supination task. The sequences of body part trajectory were processed to extract their short-time autocorrelation (STACF) matrices; the sequences of single task conducted by participants were then divided into two clusters according to their similarity in terms of their STACF representation. The Unified Parkinsons Disease Rating Scale sub-score rated for each task was compared with cluster membership to obtain the area under the curve (AUC) to evaluate the discrimination performance of the clustering. We compared the AUC with those obtained from the clustering of the raw sequence or short-time Fourier transform (STFT). ResultsIn classifying the pose estimator-based trajectory data of the knee during the leg agility task, the AUC was the highest when the STACF sequence was used for clustering instead of other types of sequences with up to 0.815, being comparable to the results reported in the original analysis of the data using an approach different from ours. In addition, in classifying another dataset of accelerometer-based trajectory data of the wrist during a pronation-supination task, the AUC was again highest up to 0.785 when clustering was performed using the STACF rather than other types of sequence. ConclusionOur autocorrelation-based method achieved a fair performance in detecting sequences with irregular rhythm, suggesting that it might be used as another evaluation strategy that is potentially widely applicable to qualify the disordered rhythm of PD regardless of the kinds of task or the modality of devices, although further refinement is needed.

biophysics↗

bioRxiv2019

Quantifying normal and parkinsonian gait features from home movies: Practical application of a deep learning-based 2D pose estimator

ObjectiveGait movies recorded in daily clinical practice are usually not filmed with specific devices, which prevents neurologists benefitting from leveraging gait analysis technologies. Here we propose a novel unsupervised approach to quantifying gait features and to extract cadence from normal and parkinsonian gait movies recorded with a home video camera by applying OpenPose, a deep learning-based 2D-pose estimator that can obtain joint coordinates from pictures or videos recorded with a monocular camera.\n\nMethodsOur proposed method consisted of two distinct phases: obtaining sequential gait features from movies by extracting body joint coordinates with OpenPose; and estimating cadence of periodic gait steps from the sequential gait features using the short-time pitch detection approach.\n\nResultsThe cadence estimation of gait in its coronal plane (frontally viewed gait) as is frequently filmed in the daily clinical setting was successfully conducted in normal gait movies using the short-time autocorrelation function (ST-ACF). In cases of parkinsonian gait with prominent freezing of gait and involuntary oscillations, using ACF-based statistical distance metrics, we quantified the periodicity of each gait sequence; this metric clearly corresponded with the subjects baseline disease statuses.\n\nConclusionThe proposed method allows us to analyze gait movies that have been underutilized to date in a completely data-driven manner, and might broaden the range of movies for which gait analyses can be conducted.

neuroscience↗