Biology subjects

Takaku, T.

Publications and source records attributed to Takaku, T..

2 recordsLinked to original sources

bioRxiv2026

Human club cells derived from pluripotent stem cells reveal new insights into epithelial lineage plasticity through structural and functional validation

Airway epithelial homeostasis relies on multiple specialized cell types, with club cells playing central roles in maintaining epithelial integrity and regulating inflammation. Environmental insults such as allergens, viral infections, or pollutants preferentially damage club cells, impairing epithelial repair and contributing to pulmonary diseases. However, the functional properties of club cells remain incompletely defined, and tractable human models are lacking. Herein, we establish a robust platform to differentiate human pluripotent stem cells (hPSCs) into club cells exhibiting their hallmark secretory features, appropriate epithelial organization, and functional properties. Single-cell transcriptomic analyses and lineage trajectory inference revealed unexpected epithelial plasticity: hPSC-derived club cells give rise to multiciliated epithelial cells through a deuterosomal intermediate--a previously uncharacterized trajectory. Additionally, a distinct club cell subset exhibited transcriptional features indicative of neuroendocrine and goblet cell differentiation potential. This study uncovers club cell plasticity and establishes a hPSC-based platform for studying airway development, regeneration and disease modeling.

cell biology↗

bioRxiv2023

Artificial Intelligence Enables the Label-Free Identification of Chronic Myeloid Leukemia Cells with Mitochondrial Morphological Alterations

Long-term tyrosine kinase inhibitor (TKI) treatment for patients with chronic myeloid leukemia (CML) causes various adverse events. Achieving a deep molecular response (DMR) is necessary for discontinuing TKIs and attaining treatment-free remission. Thus, early diagnosis is crucial as a lower DMR achievement rate has been reported in high-risk patients. Therefore, we attempted to identify CML cells using a novel technology that combines artificial intelligence (AI) with flow cytometry and investigated the basis for AI- mediated identification. Our findings indicate that BCR-ABL1-transduced cells and leukocytes from patients with CML showed significantly fragmented mitochondria and decreased mitochondrial membrane potential. Additionally, BCR-ABL1 enhanced the phosphorylation of Drp1 via the mitogen-activated protein kinase pathway, inducing mitochondrial fragmentation. Finally, the AI identified cell line models and patient leukocytes that showed mitochondrial morphological changes. Our study suggested that this AI- based technology enables the highly sensitive detection of BCR-ABL1-positive cells and early diagnosis of CML.

cancer biology↗