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Iuchi, H.

Publications and source records attributed to Iuchi, H..

4 recordsLinked to original sources

Age-associated erosion of organ-specific endothelial programs compromises tissue function and resilience

Endothelial cells (ECs) express organ-specific gene programs supporting tissue homeostasis and resilience. However, the mechanisms by which aging reshapes these organ-specific endothelial programs and how the resulting changes affect tissue homeostasis, resilience, and disease susceptibility remain largely unknown. Herein, we performed single-cell RNA sequencing of ECs harvested from five organs across the lifespan and found that aging progressively erodes organ-specific endothelial programs while inducing shared interferon-responsive and antigen-presentation programs across organs. Although vascular subtype identity and conserved capillary subset identity were mostly preserved, these organ-specific transcriptional programs were broadly attenuated with aging, indicating erosion of organ-specific endothelial identity to be a fundamental feature of endothelial aging. Importantly, these alterations were associated with declines in specialized EC functions, including alveolar barrier maintenance in the lung, scavenging activity in the liver, angiogenic capacity in the heart, and homeostatic programs in the kidneys and the brain, suggesting that age-related EC alterations compromise tissue homeostasis and resilience in multiple organs. Furthermore, we established a single-cell aging index for alveolar capillary ECs in mice and humans, revealing stress-associated endothelial activation to potentially be an intermediate state linking functional deterioration to cellular senescence, and also demonstrating marked heterogeneity in aging states even among ECs from animals of the same chronological age. Notably, alveolar capillary ECs exhibited progressive functional decline before reaching a senescent-like state, suggesting endothelial dysfunction to precede overt cellular senescence as the organism ages. Collectively, our findings establish progressive erosion of organ-specific endothelial programs as a central feature of vascular aging and provide a conceptual framework for elucidating how endothelial aging contributes to tissue dysfunction and reduced resilience across organs.

physiology↗

Integrating spatial and single-cell multi-omics analysis of induced pluripotent stem cell-derived cervical adenocarcinoma model

Human papillomavirus 18 (HPV18) preferentially infects cervical stem cell-like cells and is strongly associated with adenocarcinoma. However, the mechanisms underlying differentiation into cervical adenocarcinoma remain unclear due to the lack of appropriate experimental models. We aimed to establish a model of HPV18-associated cervical adenocarcinoma and elucidate its molecular and cellular differentiation mechanisms. HPV18 E6/E7 were introduced into induced pluripotent stem cell-derived reserve cell-like cells (iRCs) to generate tumor models. Spatial transcriptomics and single-cell multi-omics analyses were performed to integrate histological and molecular data. A distinct component (Gland_A) exhibited morphological and immunohistochemical features of cervical adenocarcinoma and was efficiently induced in iRC-18 tumors. Gland_A showed increased chromatin accessibility and elevated expression of FOXA1, FOXA2, and ALDH1A1. Analysis of clinical samples confirmed enrichment of ALDH1A1 in HPV-associated adenocarcinomas. This model recapitulates key features of HPV18-associated cervical adenocarcinoma and provides insights into its differentiation mechanisms.

cancer biology↗

The Lomb-Scargle periodogram-based differentially expressed gene detection along pseudotime

MotivationIn recent years, single-cell RNA sequencing (scRNA-seq) has provided high-resolution snapshots of biological processes and has contributed to the understanding of cell dynamics. Trajectory inference has the potential to provide a quantitative representation of cell dynamics, and several trajectory inference algorithms have been developed. However, the downstream analysis of trajectory inference, such as the analysis of differentially expressed genes (DEG), remains challenging. ResultsIn this study, we introduce a Lomb-Scargle (LS) periodogram-based algorithm for identifying DEGs associated with pseudotime in a trajectory analysis. The algorithm is capable of analyzing any inferred trajectory, including tree structures with multiple branching points, leading to diverse cell types. We validated this approach using simulated data and real datasets, and our results showed that our approach was superior when performing DEG analysis on complex structured trajectories. Our approach will contribute to gene characterization in trajectory analysis and help gain deeper biological insights. AvailabilityAll code used in our proposed method can be found at https://github.com/hiuchi/LS. Contacthitoshi.iuchi@hamadalab.com Supplementary informationSupplementary data are available at Journal Name online.

bioinformatics↗

Representation learning applications in biological sequence analysis

Remarkable advances in high-throughput sequencing have resulted in rapid data accumulation, and analyzing biological (DNA/RNA/protein) sequences to discover new insights in biology has become more critical and challenging. To tackle this issue, the application of natural language processing (NLP) to biological sequence analysis has received increased attention, because biological sequences are regarded as sentences and k-mers in these sequences as words. Embedding is an essential step in NLP, which converts words into vectors. This transformation is called representation learning and can be applied to biological sequences. Vectorized biological sequences can be used for function and structure estimation, or as inputs for other probabilistic models. Given the importance and growing trend in the application of representation learning in biology, here, we review the existing knowledge in representation learning for biological sequence analysis.

bioinformatics↗