Biology subjects

Matsuda, N.

Publications and source records attributed to Matsuda, N..

12 recordsLinked to original sources

bioRxiv2026

UFD1 Recognition of Initiator and Proximal Ubiquitin Drives p97-Mediated Substrate Unfolding enhanced by FAF1, FAF2, and UBXD7

The AAA-ATPase p97 and its primary adaptor UFD1-NPL4 (UN) unfold ubiquitinated substrates for their proteasomal degradation. Although cryo-EM has shown that substrate processing begins with unfolding of the initiator ubiquitin and its capture by NPL4, the specific contribution of UFD1 to K48-linked ubiquitin chain engagement has not been fully defined. Here we report a 1.31 [A] crystal structure of the human UFD1-UT3 bound to a K48-linked di-ubiquitin mimic, revealing that UFD1-UT3 engages the unfolded initiator ubiquitin via its Nc subdomain and the proximal ubiquitin via its Nn subdomain. AlphaFold3-guided analyses further demonstrate that accessory adaptors FAF1, FAF2, and UBXD7 enhance p97-UN activity through divergent strategies. FAF1 and FAF2 scaffold UFD1-UT3 near the NPL4-tower, whereas UBXD7 stabilizes transient interactions between UFD1 and the ubiquitin chain. Our results provide a comprehensive molecular model for the initiation of p97-mediated substrate unfolding.

biochemistry↗

bioRxiv2025

Advanced neural activity mapping in brain organoids via field potential imaging with ultra-high-density CMOS microelectrodes.

Human iPSC-derived brain organoids and assembloids have emerged as promising in vitro models for recapitulating human brain development, neurological disorders, and drug responses. However, detailed analysis of their electrophysiological properties requires advanced measurement techniques. Here, we present a novel analytical approach utilizing ultra-high-density (UHD) CMOS microelectrode arrays (MEAs) containing 236,880 electrodes (10.52 m x 10.52 m each) distributed over a broad sensing area of 32.45 mm2 for field potential imaging (FPI) of brain organoids. Neuronal activity was recorded simultaneously from over 46,000 electrodes interfaced with brain organoids, allowing for the identification of single-cell firing events and the assessment of neuronal network connectivity based on individual spikes. In midbrain organoids, administration of L-DOPA revealed both excitatory and inhibitory cellular responses, with a dose-dependent increase in the proportion of excitatory responses, suggesting enhanced network connectivity. Capitalizing on the spatial and temporal resolution of UHD-CMOS-MEAs, we introduced new endpoints for network activity: propagation velocity and propagation area. In cortical organoids, application of the GABAA receptor antagonist picrotoxin led to increased propagation velocity, whereas the NMDA receptor antagonist MK-801 resulted in a broad reduction of propagation area, along with localized increases. As FPI enables direct recording of electrical potential waveforms, frequency-domain analyses were also conducted. Spontaneous activity in cortical organoids exhibited region-specific frequency distributions, with gamma-band activity displaying distinct patterns compared to other frequency bands. Additionally, in midbrain-striatal assembloids, electrophysiological activity was observed in both regions. Connectivity analysis showed that treatment with 4-aminopyridine enhanced inter-organoid connection strength. This large-scale, single-cell-resolved recording approach using UHD-CMOS-MEAs facilitates comprehensive analysis of network connectivity, propagation velocity and propagation area, and frequency characteristics. It represents a powerful platform for advancing our understanding of the electrophysiological functions of brain organoids and assembloids, and holds significant potential for drug screening and disease modeling in human neuroscience research.

neuroscience↗

bioRxiv2025

Development of a Microelectrode Array System for Simultaneous Measurement of Field Potential and Glutamate Release in Brain Slices

Disorders of the central nervous system and complex side effects caused by abnormal neurotransmitter release have been widely reported. If neurotransmitter release and field potential (FP) could be simultaneously measured in real time, it would be possible to capture the relationship between changes in neurotransmitter release and alterations in electrical activity. In this study, we developed a novel microelectrode array (MEA) system capable of simultaneously measuring FP and electrochemical (EC) signals. Additionally, we developed an enzyme-modified carbon nanotube (CNT)-MEA capable of detecting glutamate, a major neurotransmitter, with high sensitivity in the range of several nM to several hundred nM. Using the developed enzyme-modified CNT-MEA and the simultaneous FP/EC measurement system, we successfully recorded extracellular potentials and glutamate release from hippocampal brain slices, detecting both an increase in oscillatory activity and temporal changes in glutamate release following caffeine administration. Furthermore, we also achieved the recording of dopamine release from brain slices using this system. We believe that the enzyme-modified CNT-MEA and the simultaneous FP/EC measurement system, which enable the real-time, simultaneous measurement of FP, glutamate release, and dopamine release, will contribute to a deeper understanding of brain circuit mechanisms, pathological brain conditions, and the evaluation of pharmacological compounds. HighlightsO_LIThe MEA system was customized to facilitate real-time simultaneous measurement of field potential (FP) and electrochemical (EC) signals. C_LIO_LIThe enzyme-modified CNT-MEA demonstrated the capability to detect glutamate at concentrations ranging from a few nM to several hundred nM. C_LIO_LIUsing the enzyme-modified CNT-MEA and the simultaneous FP/EC measurement system, we concurrently recorded FP and glutamate release from hippocampal brain slices, as well as their dynamic changes induced by caffeine administration. C_LIO_LIThe developed enzyme-modified CNT-MEA successfully detected dopamine release from brain slices. C_LIO_LIThe simultaneous recording of neural activity, glutamate release, and dopamine release achieved in this study is expected to contribute to elucidating the principles of brain circuit function, investigating brain pathologies, and evaluating compounds for drug discovery. C_LI

neuroscience↗

bioRxiv2025

Analysis of β rhythm induction in acute brain slices using field potential imaging with ultra-high-density CMOS-based microelectrode array.

Carbachol-induced beta rhythms in acute brain slices provide a promising ex vivo platform for evaluating compound effects under arousal-like hippocampal activity. Although microelectrode array (MEA) systems offer a non-invasive means of recording network dynamics, conventional MEAs have been limited by low electrode counts and small sensing areas, allowing only fragmented evaluation of neural activity. In this study, we applied field potential imaging (FPI) using an ultra-high-density (UHD) CMOS-MEA comprising 236,880 electrodes to simultaneously and spatially resolve carbachol-induced activity changes in the hippocampus and neocortex. Treatment with 10 {micro}M carbachol reliably induced oscillatory activity in the hippocampus at 1.33 {+/-} 0.33 Hz. Repetitive and temporally precise firing patterns originated in the CA3 region and propagated toward CA1. The average duration of individual oscillatory events was 52.82 {+/-} 6.44 ms, corresponding to a frequency of 18.93 {+/-} 3.03 Hz--within the beta frequency band. Cluster analysis based on waveform morphology revealed spatial groupings that reflected underlying anatomical structures. Beta-band power was significantly enhanced in both hippocampal and cortical regions following carbachol treatment. These findings demonstrate that the FPI platform enables high-resolution mapping of relationships between anatomical structures and brain function in acute slices, and holds promise as a pharmacological evaluation tool for assessing compound effects on hippocampal and cortical networks under wakefulness-like conditions.

neuroscience↗

bioRxiv2025

Field potential Imaging in human iPSC- derived Cardiomyocytes using UHD-CMOS-MEA

Evaluation using beat propagation analysis of human iPS cardiomyocytes is an effective approach for assessing human cardiac safety in drug development. However, current applications are primarily focused on detecting QT prolongation and arrhythmia risk, while its ability to comprehensively detect cardiotoxicity remains insufficient. Additionally, predicting the mechanism of action, which is crucial in drug development, remains challenging. In this study, we employed field potential imaging (FPI) using an ultra-high-density (UHD) CMOS microelectrode array (MEA) comprising 236,880 electrodes with high spatiotemporal resolution, capable of recording the activity of a monolayer of cardiomyocytes with tens of electrodes per cell. This method enabled the establishment of novel electrophysiological endpoints, including the number of excitation origins, fluctuations in origin positions, conduction velocity, and propagation area. Pharmacological characterization revealed drug-specific effects: isoproterenol increased excitation origins, mexiletine reduced conduction velocity, and E-4031 decreased propagation area while inducing early afterdepolarizations. Multivariate analysis of 13 compounds across 17 electrophysiological endpoints distinguished conduction velocity and propagation patterns based on their mechanisms of action. Additionally, 0.1 M doxorubicin exposure for 24 hours significantly reduced conduction velocity and propagation area, allowing early detection of chronic cardiotoxicity. These findings suggest that UHD-CMOS-MEA-based FPI enhances cardiotoxicity detection at low concentrations and precisely characterizes ion channel activity across different drug concentrations. The integration of novel electrophysiological endpoints derived from UHD-CMOS-MEA-based FPI, including excitation origin analysis, conduction velocity, and propagation area, along with multivariate analysis, is anticipated to establish a next-generation in vitro platform for comprehensive cardiotoxicity risk assessment and mechanism-based prediction of drug candidates.

pharmacology and toxicology↗

bioRxiv2024

Development of a novel microphysiological system for neurotoxicity prediction using human iPSC-derived neurons with morphological deep learning

Microphysiological system (MPS) is an in vitro culture technology that reproduces the physiological microenvironment and functionality of humans, and is expected to be applied for drug screening. In this study, we developed a MPS for structured culture of human iPSC-derived neurons, then predict drug-induced neurotoxicity by morphological deep learning. For human iPSC-derived cortical neurons, after administration of three different amyloid {beta} (A{beta}) peptides, neurotoxicity effects were evaluated by a deep learning image analysis, training two artificial intelligence (AI) models on neurites and PSD-95 images. The combined results indicated that A{beta} 1-42 and 1-40, but not 1-28, induced synaptic degeneration, which is close to clinical reports. For human iPSC-derived sensory neurons, after administration of representative CIPN-related anti-cancer drugs, the toxic effects on soma and axons were evaluated by AI model using neurites images. Significant toxicity was detected in positive drugs and could be classified by different effects on soma or axon, suggesting that the current method provides an effective evaluation of chemotherapy-induced peripheral neuropathy. Taken together, it suggests that the present MPS combined with morphological deep learning is a useful platform for in vitro neurotoxicity assessment.

pharmacology and toxicology↗

bioRxiv2023

Involvement of the splicing factor SART1 in the BRCA1-dependent homologous recombination repair of DNA double-strand breaks

Although previous studies have reported that pre-mRNA splicing factors (SFs) are involved in the repair of DNA double-strand breaks (DSBs) via homologous recombination (HR), their exact role in promoting HR remains poorly understood. Here, we showed that SART1, an SF upregulated in several types of cancer, promotes DSB end resection, which is an essential step in HR, without affecting the expression of HR factors. In the promotion of resection, SART1 is epistatic with BRCA1, an HR factor known to promote resection. Mechanistically, SART1 cooperates with BRCA1 to counteract the resection blockade posed by 53BP1 and RIF1. Moreover, SART1 is required for recruitment of the HR-promoting portion of BRCA1 to DSBs. Laser microirradiation experiments revealed that SART1 is recruited to DSBs in a BRCA1-dependent manner, and that the arginine/serine (RS)-rich domain is required for SART1 recruitment to DSBs. We also obtained evidence that SART1 is involved in transcription-associated HR together with BRCA1. Furthermore, chromosome analysis demonstrated that SART1 and BRCA1 epistatically suppressed genomic alterations caused by DSB misrepair in the G2 phase. Collectively, these results indicate that SART1 and BRCA1 cooperatively facilitate resection of DSBs arising in transcriptionally active genomic regions, thereby promoting faithful HR repair of such DSBs and suppressing genome instability.

cell biology↗

bioRxiv2023

Decoding auditory working memory content from intracranial high frequency activity in humans

Working memory (WM), the human brains system for maintaining and manipulating information over short timescales, is critical for goal-directed behavior. Classic neurophysiological models, which emphasize persistent delay activity, are being challenged by an idea that WM is maintained through dynamic and activity-silent mechanisms, where the memory trace is preserved by transient changes in the connections between neurons. To date, human evidence for this alternative model has been limited to non-invasive studies. Here, leveraging high-resolution intracranial stereo-EEG with advanced machine learning decoding techniques, we investigate neuronal mechanisms of human auditory WM. Neuronal activity is quantified as broadband high frequency activity (70-190 Hz), a correlate of neuronal firing activity. Our multivariate pattern analyses, validated via robust non-parametric permutation testing, show that WM content is represented in multiple brain regions, exhibiting dynamic rather than persistent delay activity. Crucially, by using task-irrelevant sounds to probe latent mnemonic states, we provide the first human intracranial evidence of activity silent WM maintenance in a local sensory network.

neuroscience↗

bioRxiv2023

Optineurin provides a mitophagy contact site for TBK1 activation

Tank-binding kinase 1 (TBK1) is a Ser/Thr kinase involved in many intracellular processes including innate immunity, cell cycle, and apoptosis. TBK1 is also important for phosphorylating autophagy adaptors critical in selective autophagic removal of damaged mitochondria (mitophagy). However, the mechanism by which TBK1 is activated by PINK1/Parkin-mediated mitophagy remains largely unknown. Here, we show that the autophagy adaptor OPTN provides a unique platform for TBK1 activation. The OPTN-ubiquitin and OPTN-autophagy machinery interaction axes facilitate assembly of the OPTN-TBK1 complex at a contact site between damaged mitochondria and the autophagosome formation site. This assembly point serves as a positive feedback loop for TBK1 activation by accelerating hetero-autophosphorylation of the protein. Furthermore, expression of monobodies engineered in this study against OPTN impaired assembly of OPTN at the contact sites as well as the subsequent activation of TBK1 and mitochondrial degradation. Taken together the findings reveal that a positive reciprocal relationship between OPTN and TBK1 initiates autophagosome biogenesis on damaged mitochondria.

cell biology↗

bioRxiv2022

An in vitro microfluidic culture device for peripheral neurotoxicity prediction at low concentration based on deep learning

In this study, a microfluidic culture device was developed including related evaluation methods using deep learning for the purpose of constructing a rapid assessment platform for peripheral neuropathy caused by compounds. Primary rodent dorsal root ganglion was cultured in the microfluidic culture device that could separate the cell body and neurites, and the neurites morphological changes were analyzed by immunofluorescence images. Separated neurites successful culture in the microfluidic device for more than 1 month indicated that a series of test processes from culture to drug stimulation and fluorescence observation is possible. Additionally, cultured samples were treated with several anticancer drugs known to cause peripheral neurotoxicity (i.e., vincristine, oxaliplatin, and paclitaxel) and analyzed the neurites morphological changes by deep learning for image analysis. After training, artificial intelligence (AI) could identify neurite morphological changes caused by each compound and precisely predicted the toxicity positivity, even at low concentrations. For testing compounds, AI could also precisely detect toxicity negative and positive based on neurite images, even at low concentrations. Therefore, this microfluidic culture system is supposed to be useful for in vitro toxicity assessment.

pharmacology and toxicology↗

bioRxiv2022

Large-area electrical imaging having single neuron resolution using 236,880 electrodes CMOS-MEA technology

The electrophysiological technology having a high spatio-temporal resolution at the single-cell level, and noninvasive measurements of large areas provides insights on underlying neuronal function. Here, we used a complementary metal-oxide semiconductor (CMOS)-microelectrode array (MEA) that uses 236,880 electrodes each with an electrode size of 11.22 x 11.22 {micro}m and 236,880 covering a wide area of 5.5 x 5.7 mm in presenting a detailed and single-cell-level neural activity analysis platform for brain slices, human iPS cell-derived cortical networks, peripheral neurons, and human brain organoids. Propagation pattern characteristics between brain regions changes the synaptic strength into compounds based on single-cell time-series patterns, classification based on single DRG neuron firing patterns and compound responses, axonal conduction characteristics and changes to anticancer drugs, and network activities and transition to compounds in brain organoids were extracted. This detailed analysis of neural activity at the single-cell level using our CMOS-MEA provides a new understanding the basic mechanisms of brain circuits in vitro and ex vivo, on human neurological diseases for drug discovery, and compound toxicity assessment.

neuroscience↗

bioRxiv2017

System Identification Using Compressed Sensing Reveals Signaling-Decoding System By Gene Expression

Cells decode information of signaling activation at a scale of tens of minutes by downstream gene expression with a scale of hours to days, leading to cell fate decisions such as cell differentiation. However, no system identification method with such different time scales exists. Here we used compressed sensing technology and developed a system identification method using data of different time scales by recovering signals of missing time points. We measured phosphorylation of ERK and CREB, immediate early gene expression products, and mRNAs of decoder genes for neurite elongation in PC12 cell differentiation and performed system identification, revealing the input-output relationships between signaling and gene expression with sensitivity such as graded or switch-like response and with time delay and gain, representing signal transfer efficiency. We predicted and validated the identified system using pharmacological perturbation. Thus, we provide a versatile method for system identification using data with different time scales.\n\nHighlightsO_LIWe developed a system identification method using compressed sensing.\nC_LIO_LIThis method allowed us to find a pathway using data of different time scales.\nC_LIO_LIWe identified a selective signaling-decoding system by gene expression.\nC_LIO_LIWe validated the identified system by pharmacological perturbation.\nC_LI\n\neTOC BlurbWe describe a system identification method of molecular networks with different time-scale data using a signal recovery technique in compressed sensing.

systems biology↗