Biology subjects

Nagai, J.

Publications and source records attributed to Nagai, J..

8 recordsLinked to original sources

bioRxiv2026

Calcium-independent biosensors for multiplexed in vivo imaging of extracellular lactate dynamics

Extracellular L-lactate reports cellular metabolism, but resolving its dynamics alongside intracellular metabolism and neuronal activity remains challenging. Here we develop eLACCO3 and R-eLACCO3, green and red cell-surface lactate biosensors with Ca2+-independent responses and faster response and recovery kinetics in cultured cells. Selected variants provide larger fluorescence responses than their predecessors in brain cells, slices, and living mice and improve detection of glucose-evoked extracellular lactate oscillations. Combining R-eLACCO3 with GCaMP6f enabled imaging of extracellular L-lactate simultaneously with odor-evoked activity in anesthetized mice and cortical activity in awake mice. These biosensors enable multiplexed measurements of extracellular lactate dynamics in relation to intracellular metabolism and neuronal activity.

molecular biology↗

bioRxiv2026

AtlasOT - The Fused Unbalanced Gromov-Wasserstein for Multimodal Integration of Disease Atlases

Single-cell and spatial multiomics technologies are transforming disease atlas construction, but computational integration of unpaired modalities remains challenging, as existing methods overlook two biological constraints of data with matching samples. First, cells should only be mapped across modalities within the same donor or biospecimen, and second, cell recovery frequently differs substantially between modalities. To address these gaps, we present AtlasOT, an optimal-transport framework based on the fused unbalanced Gromov-Wasserstein (FUGW) formulation for multi-modal integration. AtlasOT jointly models a shared cross-modality feature space and modality-specific geometric structures while restricting transport to within-sample cell pairs. Moreover, AtlasOT relaxes strict mass conservation of the balanced optimal transport optimization to accommodate unbalanced cell numbers. We benchmark AtlasOT against state-of-the-art methods on scRNA-scATAC and scRNA-spatial transcriptomics mapping scenarios. Our results indicate that AtlasOT outperforms baselines and state-of-the-art methods in all considered scenarios. Moreover, we demonstrate that AtlasOT's transport plan can be used to improve several relevant tasks such as the detection of rare cell populations, spot-level cell-type deconvolution, spatial gene imputation, and reconstruction of transcription-factor-driven spatial regulatory dynamics. These results establish AtlasOT as a unified, biologically constrained framework for multimodal integration in disease atlas studies, with broad applicability to label transfer, imputation, and regulatory network analysis.

bioinformatics↗

bioRxiv2025

Progenitor T cells drive chronic pulmonary type 2 inflammation

Type 2 inflammation unfolds over time and is coordinated by remarkably durable CD4+ Th2 cell responses, standing in contrast to the collapse of adaptive immunity seen in chronic infection and malignancy. In experimental models, short-lived Th2 effector cells and type 2 innate lymphocytes (ILC2) contribute to acute type 2 inflammation, yet the cellular architecture that drives chronic type 2 inflammation and prevents exhaustion remains poorly understood. To define the Th2 landscape in chronic type 2 inflammation, we established a mouse model of long-term pulmonary allergen exposure and found that type 2 inflammation was broadly sustained over at least 4 months despite chronic stimulation. Th2 cells in the lung parenchyma during chronic inflammation were distinct from acute inflammation and resting memory phases, and included an expanded T cell factor-1 (TCF1)-expressing progenitor-like Th2 population. Tissue Th2 progenitors were absent in the nose and in helminth infections, suggesting that type 2 immunopathology is context-specific. Transcriptomic deconstruction of acute and chronic pulmonary Th2 responses defined divergent effector programs as well as the transcriptional signature of a tissue Th2 memory population that resembled human Th2 progenitors. Integrated transcriptomic analysis comparing type 2 inflammation to chronic viral infection revealed a distinct stemness module underlying chronic Th2 inflammation that was separable from a common core memory module. In vivo, lung Th2 progenitors coupled self-renewal with effector cell differentiation and could be sustained for weeks without antigen persistence or contribution from the lymph node. Maintenance of Th2 progenitors was partially dependent on lung parenchymal B cells and associated with bronchus-associated lymphoid tissue formation. Moreover, Th2 progenitors, in contrast to Th2 effectors and ILC2s, were sufficient to both initiate and sustain type 2 inflammation. Thus, we define tissue Th2 progenitors as a distinct cellular state that arises during chronic type 2 inflammation and establish the central role of these cells in maintaining the architecture of Th2 responses over time.

immunology↗

bioRxiv2025

PILOT-GM-VAE: Patient-Level Analysis of single cell Disease Atlas with Optimal Transport of Gaussian Mixture Variational Autoencoders

MotivationThe analysis of single cell disease atlases represents a challenge due to the presence of batch effects, low quality of disease samples, and the multi-scale nature of the data, i.e., samples are described by different cell distributions. Because of these, few computational approaches are performing sample-level disease progression analysis so far. ResultsHere, we introduce Patient-Level Analysis with Optimal Transport based on Gaussian Mixture Variational Autoencoders (PILOT-GM-VAE). PILOT-GM-VAE explores the power of GM-VAE to estimate models describing complex single cell distributions through efficient optimal transport algorithms for estimating the distance between Gaussian Mixtures. Extensive benchmarking on several single cell disease atlases and competing approaches demonstrates the performance of PILOT-GM-VAE in sample-level clustering, sample-level trajectory inference, and batch correction tasks. Moreover, we performed a case study on a breast cancer disease atlas, where PILOT-GM-VAE highlighted cellular and molecular changes associated with breast cancer disease progression. AvailabilityThe software, code, and data for benchmarking are available at https://github.com/CostaLab/PILOT-GM-VAE/tree/main

bioinformatics↗

bioRxiv2025

Wnt-dependent spatiotemporal reprogramming ofbone marrow niches drives fibrosis

Bone marrow fibrosis is the most extensive matrix remodeling of the microenvironment and can include de novo formation of bone (osteosclerosis). Spatiotemporal information on the contribution of distinct bone marrow niche populations to this process is incomplete. We demonstrate that fibrosis-inducing hematopoietic cells cause profibrotic reprogramming of perivascular CXCL12 abundant reticular (CAR) progenitor cells resulting in loss of their hematopoiesis-support and upregulation of osteogenic and pro-apoptotic programs. In turn, peritrabecular osteolineage cells (OLCs) are activated in an injury-specific, Wnt-dependent manner, comparable to skeletal repair. OLCs fuel bone marrow fibrosis through their expansion and skewed differentiation, resulting in osteosclerosis and expansion of Ly6a+ fibroblasts. NCAM1 expression marks peritrabecular OLCs and their expansion into the central marrow is specific for fibrosis in mice and patients. Peritrabecular stromal b-catenin expression is linked to fibrosis in patients and inhibition of Wnt signaling reduces bone marrow fibrosis and osteosclerosis, possibly being a clinically relevant therapeutic target.

molecular biology↗

bioRxiv2022

scMEGA: Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference

The increasing availability of single-cell multi-omics data allows to quantitatively characterize gene regulation. We here describe scMEGA (Single-cell Multiomic Enhancer-based Gene Regulatory Network Inference) to infer gene regulatory networks by combining single-cell gene expression and chromatin accessibility profiles. This enables to study of complex gene regulation mechanisms for dynamic biological processes, such as cellular differentiation and disease-driven cellular remodeling. We provide a case study on gene regulatory networks controlling myofibroblast activation in human myocardial infarction

bioinformatics↗

bioRxiv2019

A Stomata Classification and Detection System in Microscope Images of Maize Cultivars

Research on stomata, i.e., morphological structures of plants, has increased in popularity in the last years. These structures (pores) are in charge of the interaction between the internal plant system and the environment, working on different processes such as photosynthesis and transpiration stream. Besides, a better understanding of the pore mechanism plays a significant role when exploring the evolution process, as well as the behavior of plants. Although the study of stomata in dicots species of plants has advanced considerably in the past years, there is little information about stomata of cereal grasses. Also, automated detection of these structures have been considered in the literature, but some gaps are still uncovered. This fact is motivated by high morphological variation of stomata and the presence of noise from the image acquisition step. In this work, we propose a new methodology for automatic stomata classification and a new detection system in microscope images for maize cultivars. We have achieved an approximated accuracy of 97.1% in the identification of stomata regions using classifiers based on deep learning features, which figures out as a nearly perfect classification system.

plant biology↗

bioRxiv2018

A genetically encoded single-wavelength sensor for imaging cytosolic and cell surface ATP

Adenosine 5 triphosphate (ATP) is a universal intracellular energy source1 and an evolutionarily ancient2 extracellular signal3-5. Here, we report the generation and characterization of single-wavelength genetically encoded fluorescent sensors (iATPSnFRs) for imaging extracellular and cytosolic ATP from insertion of circularly permuted superfolder GFP into the epsilon subunit of F0F1-ATPase from Bacillus PS3. On the cell surface and within the cytosol, iATPSnFR1.0 responded to relevant ATP concentrations (30 M to 3 mM) with fast increases in fluorescence. iATPSnFRs can be genetically targeted to specific cell types and sub-cellular compartments, imaged with standard light microscopes, do not respond to other nucleotides and nucleosides, and when fused with a red fluorescent protein function as ratiometric indicators. iATPSnFRs represent promising new reagents for imaging ATP dynamics.

physiology↗