Biology subjects

Akamatsu, K.

Publications and source records attributed to Akamatsu, K..

8 recordsLinked to original sources

bioRxiv2026

Direct Injection NanoHILIC/MS/MS Proteomics from Reversed-Phase StageTip Eluate

NanoHILIC/MS/MS provides high sensitivity for low-input peptide analysis, yet its use in bottom-up proteomics has been constrained by a persistent solvent mismatch: tryptic peptides exhibit poor solubility in the [≥]95% acetonitrile (ACN) required for nanoHILIC injection. Our previously reported two-step solubilization method [Anal Chem 2025, 97 (19), 10227-10235] alleviated this issue but required large dilution volumes, limiting the amount of sample that could be injected. Here, we introduce DiReCT (Dissolution from Reverse-Phase Chromatography Tips), a StageTip-based workflow that integrates peptide solubilization, desalting, and nanoHILIC-compatible elution into a single operation. During elution from RP-StageTips, residual water on the stationary phase is rapidly displaced by a small volume of high-ACN solvent, generating a transient mid-ACN environment that maximizes peptide solubility without drying. This mechanism enables high-recovery peptide concentration and allows direct injection of the entire eluate onto nanoHILIC/MS/MS. Using [~]0.25 ng of HeLa digest, DiReCT/nanoHILIC/MS/MS identified 1177 peptides and 410 proteins, representing 8.9- and 6.7-fold increases over nanoRPLC/MS/MS, respectively.

biochemistry↗

bioRxiv2025

Feedforward representation of face information in the fusiform face area revealed by VASO 7T layer fMRI

Recognizing faces is a critical cognitive process in social interaction. Face recognition has been extensively studied with functional magnetic resonance imaging (fMRI), ranging from large coverage studies comprehensively examining the entire face pathway to high-resolution laminar-specific (layer) fMRI studies probing feedforward and feedback signals in early visual and face-selective areas during particular face processing. However, it is still unclear which brain region structures face information in the face pathway. To further elucidate this mechanism, we investigated fusiform face area (FFA) during passive face image presentation using a whole-brain vascular space occupancy (VASO) 7T layer fMRI open dataset combined with multi-voxel pattern analysis (MVPA). We analysed lateral occipital cortex (LOC) as a control region and BOLD data in the dataset as a control contrast. We trained multiple binary classification decoders with various image categories (e.g., face vs. others, house vs. others) and three cortical layer groups independently to assess information representation across cortical depths. Our results revealed that decoding accuracies in VASO data peaked in the middle layer of FFA, suggesting a feedforward signature specifically during face processing. This effect was not observed in LOC or in decoders for other image categories. These findings indicate that face information is structured prior to processing in the FFA, consistent with previous reports suggesting that face-related features are partially extracted before reaching higher-level face areas. Overall, this study highlights the potential of combining high-specificity VASO layer-fMRI with high-sensitivity MVPA to dissect cortical information flow.

neuroscience↗

bioRxiv2025

Functionally-structured Bayesian model for localizing neural activity and information in magnetoencephalography signals

Magnetoencephalography (MEG) is a noninvasive method that can measure human brain activity with high temporal resolution. However, the spatial resolution of MEG is not sufficient to reveal neural mechanisms. Although MEG source estimation overcomes this problem to some extent, the combination of MEG source estimation and multivariate analysis results in "information spreading", where significant predictions are observed in brain areas outside the true signal source location. This paper describes a model that achieves high source estimation accuracy and suppresses information spreading simultaneously. The proposed approach is based on a Bayesian estimation model that utilizes functional structure of the human brain. We compare the performance of the proposed model with simulated data generated under various signal-to-noise ratio conditions. The results show that the functionally-structured Bayesian model achieves source estimation accuracy that is better than that of conventional source estimation models. Additionally, the comparison of information spreading among the models reveals that our model outperforms the conventional ones. These results suggest that information spreading in the MEG source estimation can be suppressed while maintaining high source estimation accuracy.

neuroscience↗

bioRxiv2024

Fc-independent SARS-CoV-2 infection-enhancing antibodies decouple N-terminal and receptor-binding domains by cross-linking neighboring spikes

Antibody dependent enhancement (ADE) is a serious concern in vaccine development. The canonical ADE pathways are dependent on the fragment crystallizable (Fc) region of the antibody. In SARS-CoV-2 several antibodies have been discovered that inflict ADE in vitro. These antibodies target the N-terminal domain (NTD) of the SARS-CoV-2 spike protein. We previously proposed that these NTD-targeting infection-enhancing antibodies (NIEAs) cross-link neighboring spike proteins via their NTDs, and that this results in a decoupling between the NTD and receptor binding domain (RBD), facilitating the "RBD down" to "up" transition. In this study we present a combination of molecular dynamics simulations and cryogenic electron microscopy data that, together, demonstrate that NIEAs are indeed able to cross-link neighboring SARS-CoV-2 spike proteins, and that this cross-linking results in a decoupling of the NTD and RBD domains. These findings provide support for an Fc region independent ADE pathway that is not only relevant for SARS-CoV-2 but also for other viruses of which the spike proteins undergo a conformational change upon host cell entry.

molecular biology↗

bioRxiv2023

An engineered ACE2 decoy broadly neutralizes Omicron subvariants and shows therapeutic effect in SARS-CoV-2-infected cynomolgus macaques

The Omicron variant continuously evolves under the humoral immune pressure obtained by vaccination and SARS-CoV-2 infection and the resultant Omicron subvariants exhibit further immune evasion and antibody escape. Engineered ACE2 decoy composed of high-affinity ACE2 and IgG1 Fc domain is an alternative modality to neutralize SARS-CoV-2 and we previously reported its broad spectrum and therapeutic potential in rodent models. Here, we show that engineered ACE2 decoy retains the neutralization activity against Omicron subvariants including the currently emerging XBB and BQ.1 which completely evade antibodies in clinical use. The culture of SARS-CoV-2 under suboptimal concentration of neutralizing drugs generated SARS-CoV-2 mutants escaping wild-type ACE2 decoy and monoclonal antibodies, whereas no escape mutant emerged against engineered ACE2 decoy. As the efficient drug delivery to respiratory tract infection of SARS-CoV-2, inhalation of aerosolized decoy treated mice infected with SARS-CoV-2 at a 20-fold lower dose than the intravenous administration. Finally, engineered ACE2 decoy exhibited the therapeutic efficacy for COVID-19 in cynomolgus macaques. Collectively, these results indicate that engineered ACE2 decoy is the promising therapeutic strategy to overcome immune-evading SARS-CoV-2 variants and that liquid aerosol inhalation can be considered as a non-invasive approach to enhance efficacy in the treatment of COVID-19.

microbiology↗

bioRxiv2022

Acquisition and processing methods of whole-brain layer-fMRI VASO and BOLD: The Kenshu dataset.

Cortical depth-dependent functional magnetic resonance image (fMRI), also known as layer-fMRI, has the potential to capture directional neural information flow of brain computations within and across large-scale cortical brain networks. E.g., layer-fMRI can differentiate feedforward and feedback cortical input in hierarchically organized brain networks. Recent advancements in 3D-EPI sampling approaches and MR contrast generation strategies have allowed proof-of-principle studies showing that layer-fMRI can provide sufficient data quality for capturing laminar changes in functional connectivity. These studies have however not shown how reliable the signal is and how repeatable the respective results are. It is especially unclear whether whole-brain layer-fMRI functional connectivity protocols are widely applicable across common neuroscience-driven analysis approaches. Moreover, there are no established preprocessing fMRI methods that are optimized to work for whole-brain layer-fMRI datasets. In this work, we aimed to serve the field of layer-fMRI and build tools for future routine whole-brain layer-fMRI in application-based neuroscience research. We have developed publicly available sequences, acquisition protocols, and processing pipelines for whole-brain layer-fMRI. These protocols are validated across 60 hours of scanning in nine participants. Specifically, we identified and exploited methodological advancements for maximizing tSNR efficiency and test-retest reliability. We are sharing an extensive multi-modal whole-brain layer-fMRI dataset (20 scan hours of movie-watching in a single participant) for the purpose of benchmarking future method developments: The Kenshu dataset. With this dataset, we are also exemplifying the usefulness of whole brain layer-fMRI for commonly applied analysis approaches in modern cognitive neuroscience fMRI studies. This includes connectivity analyses, representational similarity matrix estimations, general linear model analyses, principal component analysis clustering, etc. We believe that this work paves the road for future routine measurements of directional functional connectivity across the entire brain. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=132 SRC="FIGDIR/small/504502v1_ufig1.gif" ALT="Figure 1"> View larger version (89K): org.highwire.dtl.DTLVardef@1c6579forg.highwire.dtl.DTLVardef@a2bbecorg.highwire.dtl.DTLVardef@1dfa41aorg.highwire.dtl.DTLVardef@18ee67f_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗

bioRxiv2022

Spatiotemporal bias of the human gaze toward hierarchical visual features during natural scene viewing

The human gaze is directed at various locations from moment to moment in acquiring information necessary to recognize the external environment at the fine resolution of foveal vision. Previous studies showed that the human gaze is biased to particular locations in the visual field at a particular timing, but it remains unclear what visual features produce such spatiotemporal bias. In this study, we used a deep convolutional neural network model to extract hierarchical visual features from natural scene images and evaluated how much the human gaze is attracted to the visual features in space and time. Eye movement measurement and visual feature analysis using the deep convolutional neural network model showed that the gaze was strongly attracted to spatial locations containing higher-order visual features than lower-order visual features and conventional saliency. Analysis of the gaze time course revealed that the bias to higher-order visual features was prominent within a short period after the beginning of observation of the natural scene images. These results demonstrate that higher-order visual features are a strong gaze attractor in both space and time, suggesting that the human visual system uses foveal vision resources to extract information from higher-order visual features with higher spatiotemporal priority.

neuroscience↗

bioRxiv2021

The SARS-CoV-2 Delta variant is poised to acquire complete resistance to wild-type spike vaccines

mRNA-based vaccines provide effective protection against most common SARS-CoV-2 variants. However, identifying likely breakthrough variants is critical for future vaccine development. Here, we found that the Delta variant completely escaped from anti-N-terminal domain (NTD) neutralizing antibodies, while increasing responsiveness to anti-NTD infectivity-enhancing antibodies. Although Pfizer-BioNTech BNT162b2-immune sera neutralized the Delta variant, when four common mutations were introduced into the receptor binding domain (RBD) of the Delta variant (Delta 4+), some BNT162b2-immune sera lost neutralizing activity and enhanced the infectivity. Unique mutations in the Delta NTD were involved in the enhanced infectivity by the BNT162b2-immune sera. Sera of mice immunized by Delta spike, but not wild-type spike, consistently neutralized the Delta 4+ variant without enhancing infectivity. Given the fact that a Delta variant with three similar RBD mutations has already emerged according to the GISAID database, it is necessary to develop vaccines that protect against such complete breakthrough variants.

microbiology↗