Biology subjects

Iida, K.

Publications and source records attributed to Iida, K..

13 recordsLinked to original sources

bioRxiv2025

Transient ATM inhibition enhances knock-in efficiency in hematopoietic stem cells by attenuating the DNA damage response

Precise genome editing in hematopoietic stem cells (HSCs) offers great potential for treating inherited blood disorders, but low knock-in (KI) efficiency, due to HSC quiescence and a preference for non-homologous end joining (NHEJ) and DNA damage-induced apoptosis, remains a major barrier. Here, we demonstrate that transient inhibition of Ataxia-Telangiectasia Mutated (ATM) kinase markedly enhances KI efficiency in mouse HSCs genome-edited with Cas9/RNP and AAV donor DNA. Phosphoproteomic analysis and capillary western blotting revealed that ATM inhibition suppressed the Cas9-AAV-induced ATM activation and subsequent DNA damage response, reduced p53-dependent apoptosis and preserved knock-in competent cells. In transplantation experiments, ATM inhibition preserved long-term engrafting genome-edited HSCs, increasing their frequency from [~]0.3% to [~]40% in secondary recipients - a >100-fold enhancement compared to untreated cells. Furthermore, in an X-SCID mouse model, ATM inhibition enhanced KI efficiency and restored expression of IL-2 receptor {gamma} chain (CD132). These strikingly novel findings highlight transient ATM inhibition as a powerful and clinically relevant approach to enhance KI-mediated genome editing in HSCs, while preserving their long-term repopulating capacity. Key pointsO_LIATM inhibition enhances knock-in efficiency in mouse hematopoietic stem cells C_LIO_LIATM inhibition suppresses Cas9-AAV-induced overactivation of ATM and subsequent p53-dependent apoptosis. C_LI

cell biology↗

bioRxiv2024

An attention-based deep neural network model to detect cis-regulatory elements at the single-cell level from multi-omics data

Cis-regulatory elements (cREs) play a crucial role in regulating gene expression and determining cell differentiation and state transitions. To capture the heterogeneous transitions of cell states associated with these processes, detecting cRE activity at the single-cell level is essential. However, current analytical methods can only capture the average behavior of cREs in cell populations, thereby obscuring cell-specific variations. To address this limitation, we proposed an attention-based deep neural network framework that integrates DNA sequences, genomic distances, and single-cell multi-omics data to detect cREs and their activities in individual cells. Our model shows higher accuracy in identifying cREs within single-cell multi- omics data from healthy human peripheral blood mononuclear cells than other existing methods. Furthermore, it clusters cells more precisely based on predicted cRE activities, enabling a finer differentiation of cell states. When applied to publicly available single-cell data from patients with glioma, the model successfully identified tumor-specific SOX2 activity. Additionally, it revealed the heterogeneous activation of the ZEB1 transcription factor, a regulator of epithelial-to-mesenchymal transition-related genes, which conventional methods struggle to detect. Overall, our model is a powerful tool for detecting cRE regulation at the single-cell level, which may contribute to revealing drug resistance mechanims in cell sub- populations.

bioinformatics↗

bioRxiv2024

MECOM promotes leukemia progression and inhibits mast cell differentiation through functional competition with GATA2

MECOM is a nuclear transcription factor essential for the proliferation of hematopoietic stem cells (HSCs) and myeloid leukemia cells. MECOM contains N- and C-terminal zinc finger domains (ZFDs) and binding motifs for the corepressor CtBP to regulate gene expression. Recent studies have shown that germline MECOM variants are associated with thrombocytopenia, radioulnar synostosis, and bone marrow failure, collectively termed MECOM-associated syndromes. Although the mutations are clustered in the C-terminal ZFD, how these mutations affect MECOM function has remained unclear. In addition, the individual genes and pathways regulated by MECOM are less well understood. In this study, we showed that the C-terminal ZFD is a major DNA-binding domain of MECOM and that the disease-associated mutations abolish the DNA-binding ability. We also found that MECOM functionally antagonizes GATA2 through the C-terminal ZFD-mediated DNA binding and CtBP interaction, thereby promoting myeloid leukemogenesis while inhibiting mast cell differentiation. Furthermore, we generated mutant MECOM knockin mice harboring a C-terminal ZFD mutation that recapitulate several features of MECOM-associated syndromes, including HSC and B-cell reduction. Our study demonstrates that C-terminal ZFD mutations are loss-of-function mutations with reduced DNA-binding ability, reveals the critical role of MECOM in inhibiting GATA2, and provides a novel mouse model for MECOM-associated syndromes.

molecular biology↗

bioRxiv2024

Identifying key regulatory genes in drug resistance acquisition: Modeling pseudotime trajectories of single-cell transcriptome

Single-cell RNA-sequencing (scRNA-seq) technology has provided significant insights into cancer drug resistance at the single-cell level. However, understanding dynamic cell transitions at the molecular systems level remains limited, requiring a systems biology approach. We present an approach that combines mathematical modeling with pseudotime analysis using time-series scRNA-seq data obtained from the breast cancer cell line MCF-7 treated with tamoxifen. Our single-cell analysis identified five distinct subpopulations, including tamoxifen-sensitive and -resistant groups. Using a single-gene mathematical model, we discovered approximately 560-680 genes out of 6,000 exhibiting multistable expression states in each subpopulation, including key estrogen receptor-positive breast cancer cell survival genes, such as RPS6KB1. Bifurcation analysis elucidated their regulatory mechanisms, and we mapped these genes into a molecular network associated with cell survival and metastasis-related pathways. Our modeling approach comprehensively identifies key regulatory genes for drug resistance acquisition, enhancing our understanding of potential drug targets in breast cancer. SummaryDespite recent advancements in experimental technology for genome-wide molecular profiling, our understanding of the dynamic mechanism underlying cancer drug resistance remains limited. In this study, we present an approach that combines mathematical modeling with the pseudotime analysis of single-cell time-series transcriptome data of drug-treated breast cancer cells. Our method identifies approximately 600 genes out of 6,000 exhibiting multistable expression states, including RPS6KB1, a predictor of poor prognosis, cell survival, and growth in estrogen receptor-positive breast cancers. The bifurcation analysis elucidates the regulatory mechanisms of the key regulatory genes, which can also be mapped into a molecular network based on cell survival and metastasis-related pathways, providing a comprehensive understanding of the interplay between signaling pathways and regulatory genes. Our method serves as a powerful tool for deciphering the complexities of drug resistance mechanisms in human diseases.

bioinformatics↗

bioRxiv2023

Positive and negative feedback regulation of the TGF-β1-SMAD4 axis explains two equilibrium states in human skin aging

Skin homeostasis during aging is critical not only for the appearance but also biological defense of the human body. In this study, we identified thrombospondin-1 (THBS1) and fibromodulin (FMOD) as positive and negative regulators, respectively, of the TGF-{beta}1-SMAD4 axis in human skin aging based on in vitro and in vivo omics analyses and mathematical modeling. Transcriptomic and epigenetic analyses of senescent dermal fibroblasts identified TGF-{beta}1 as the key upstream regulator. Bifurcation analysis identified a binary senescent/non-senescent switch, with THBS1 as the main controller. Sensitivity analysis of the TGF-{beta}1 signaling pathway indicated that THBS1 expression was sensitively regulated while FMOD was robustly regulated, suggesting that THBS1 is a controllable factor. Inhibition of SMAD4 complex formation was experimentally validated as a promising manner to control THBS1 production and senescence. This study demonstrates the potential of a data-driven mathematical approach in determining the mechanisms of skin aging. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/546970v1_ufig1.gif" ALT="Figure 1"> View larger version (69K): org.highwire.dtl.DTLVardef@12b4f29org.highwire.dtl.DTLVardef@5a3e95org.highwire.dtl.DTLVardef@c2daa5org.highwire.dtl.DTLVardef@a09042_HPS_FORMAT_FIGEXP M_FIG C_FIG eTOC BlurbHaga, Iida and Okada revealed that the balance between FMOD and THBS1 determines the two equilibrium states of skin homeostasis and THBS1 is a controllable factor in skin aging HighlightsO_LIMulti-omics analysis identified TGF-{beta}1-SMAD4 as key regulators in human skin aging C_LIO_LITHBS1 and FMOD promoted and suppressed factors in skin aging, respectively C_LIO_LITHBS1 controlled the senescent and non-senescent states of the aging switch C_LIO_LISMAD4 is a potential target for inhibiting THBS1 expression and cell senescence C_LI

systems biology↗

bioRxiv2022

The role of rice SOG1 and SOG1-like in DNA damage response

Higher plants are constantly exposed to environmental stresses, and therefore complicated defense systems, including DNA damage response (DDR) and DNA repair systems, have developed to protect plant cells. In Arabidopsis, the transcription factor SUPPRESSOR OF GAMMA RESPONSE 1 (SOG1) has been reported to play a key role in DDR. Here, we focus on DDR in rice--thought to be a simpler system compared with Arabidopsis due to lack of induction of endocycle even under DNA damage stress. Rice SOG1 (OsSOG1) and SOG1-like (OsSGL) were identified as putative AtSOG1 orthologs with complete or partial conservation of the serine-glutamine (SQ) motifs involved in activation via phosphorylation. In addition to OsSOG1- or OsSGL-knockout mutants, OsSOG1 non-phosphorylatable mutants (OsSOG1-7A) were generated by homologous recombination-mediated gene targeting. Based on DNA damage susceptibility and transcriptome analysis using these mutants, we demonstrated that OsSOG1, but not OsSGL, plays a central role in the DDR and DNA repair. OsSOG1 regulated target genes via CTT (N)7 AAG motifs reported previously as AtSOG1 recognition sites. The loss of transcription activities and DNA damage tolerance of OsSOG1-7A was not complete compared with OsSOG1-knockout mutants, raising the possibility that another phosphorylation site might be involved in the activation of OsSOG1. Furthermore, our findings have highlighted differences in SOG1-mediated DDR between rice and Arabidopsis, especially regarding induction of cell-cycle arrest and endocycle arrest, revealing rice-specific DDR mechanisms. One sentence summaryRice transcription factor SUPPRESSOR OF GAMMA RESPONSE 1 controls DNA damage response and DNA repair through activation via phosphorylation and the direct regulation of expression of numerous genes.

plant biology↗

bioRxiv2021

Distinct and interchangeable growing patterns in colorectal cancer stem-like cells are regulated by Musashi-1

The dynamic and heterogeneous features of cancer stem-like cells (CSCs) have been widely recognized, but their nongenetic cellular plasticity mechanisms remain elusive. By using colorectal cancer organoids, we phenotypically tracked their spheroid formation and growth capacity to a single-cell resolution, and we discovered that the spheroid-forming cells exhibit a heterogeneous growth pattern, consisting of slow- and fast-growing spheroids. The isolated fast-growing spheroids seem to preserve a dual-growing pattern through multiple passages, whereas the isolated slow-growing spheroids are restricted to a slow-growing pattern. Notably, the spheroids of both patterns were tumorigenic. Moreover, the expression of CSC markers varied among the subpopulations with different growth patterns. The isolated slow-growing spheroids adopted the dual-growing pattern by various extrinsic triggers, in which Musashi-1 plays a key role. The slow-growing fraction was resistant to chemotherapy, and its successful isolation can provide an in vitro platform allowing us to elucidate their role in drug resistance.

cancer biology↗

bioRxiv2021

Switching of OAS1 splicing isoforms mitigates SARS-CoV-2 infection

BackgroundThe rapidly accumulating disease susceptibility information collected from coronavirus disease (COVID-19) patient genomes must be urgently utilized to develop therapeutic interventions for SARS-CoV-2 infection. Chromosome 12q24.13, which encodes the 2-5-oligoadenylate synthetase (OAS) family of proteins that sense viral genomic RNAs and trigger an antiviral response, is identified as one of the genomic regions that contains SNPs associated with COVID-19 severity. A high-risk SNP identified at the splice acceptor site of OAS1 exon 6 is known to change the proportions of the various splicing isoforms and the activity of the enzyme. MethodsWe employed in-silico motif search and RNA pull-down assay to define a factor responsible for the OAS1 splicing. Next, we rationally selected a candidate for slicing modulator to modulate this splicing. ResultsWe found that inhibition of CDC-like kinase with a small chemical compound induces switching of OAS1 splice isoforms in human lung cells. In this condition, increased resistance to SARS-CoV-2 infection, enhanced RNA degradation, and transcriptional activation of interferon {beta}1, were also observed. ConclusionsThe results indicate the possibility of using chemical splicing modifiers aided by genome-based precision medicine to boost the innate immune response against SARS-CoV-2 infection.

genomics↗

bioRxiv2021

Functional annotation-driven unsupervised clustering of single-cell transcriptomes

MotivationSingle-cell RNA sequencing (scRNA-seq) analysis reveals heterogeneity and dynamic cell transitions. However, conventional gene-based analyses require intensive manual curation to interpret the biological implications of computational results. Hence, a theory for efficiently annotating individual cells is necessary. ResultsWe present ASURAT, a computational pipeline for simultaneously performing unsupervised clustering and functional annotation of disease, cell type, biological process, and signaling pathway activity for single-cell transcriptomic data, using correlation graph-based decomposition of genes based on database-derived functional terms. We validated the usability and clustering performance of ASURAT using scRNA-seq datasets for human peripheral blood mononuclear cells, which required fewer manual curations than existing methods. Moreover, we applied ASURAT to scRNA-seq and spatial transcriptome datasets for small cell lung cancer and pancreatic ductal adenocarcinoma, identifying previously overlooked subpopulations and differentially expressed genes. ASURAT is a powerful tool for dissecting cell subpopulations and improving biological interpretability of complex and noisy transcriptomic data. AvailabilityA GPLv3-licensed implementation of ASURAT is on GitHub (https://github.com/keita-iida/ASURAT).

bioinformatics↗

bioRxiv2020

Novel candidates of pathogenic variants of the BRCA1 and BRCA2 genes in a 3,552 Japanese whole-genome sequence dataset (3.5KJPNv2)

Identification of pathogenic germline variants yet no clinical evidence in BRCA genes has become important in patient care of hereditary breast and ovarian cancer syndrome (HBOC). Computational scoring and prospective cohort studies may help to identify such pathogenic variants. We annotated the variants in the BRCA1 and BRCA2 genes from a dataset of 3,552 whole-genome sequences obtained from members of the genome cohorts by Tohoku Medical Megabank Project (TMM) with the InterVar software. Computational impact scores (CADD_phred and Eigen_raw) and minor allele frequencies (MAF) of pathogenic (P) and likely pathogenic (LP) variants in ClinVar are used for filtration criteria. Familial predispositions in cancers among the 35,000 TMM genome cohort participants are analyzed to verify the pathogenicity. Seven potentially pathogenic variants were newly identified. Carriers of these potential pathogenic variants and definite P and LP variants among participants of the TMM prospective cohort show a statistically significant preponderance in cancer onset in sisters in the self-reported cancer history. Filtering by computational scoring and MAF is useful to identify potential pathogenic variants in BRCA genes for Japanese population. These results will be helpful to follow up the carriers of variants of uncertain significance in the HBOC genes.

genetics↗

bioRxiv2020

Integrated gut-liver-on-a-chip platform as an in vitro human model of non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) afflicts a large percentage of the population, but no effective treatments have been established so far because of the unsuitability of in vitro assays and experimental models using animals. By co-culturing human gut and liver cell lines interconnected via microfluidics for a closed circulation loop, we created a gut-liver-on-a-chip (iGLC) platform as an in vitro human model of the gut-liver axis (GLA) for the initiation and progression of NAFLD. Microscopic high-content analysis followed by mRNA sequencing showed that co-culturing the gut and liver cells significantly affected each cell type compared to culturing them separately. NAFLD-inducing free fatty acids (FFAs) accumulated in the gut cells and elevated gene expressions associated with retinol metabolism and glucuronidation. The FFA-treated liver cells accumulated intracellular lipid droplets and showed an increase in gene expressions associated with a cellular response to copper ions and endoplasmic reticulum stress. As an in vitro human GLA model, the iGLC platform may serve as an alternative to animal experiments for investigating NAFLD mechanisms.

bioengineering↗

bioRxiv2018

Quantifying heterogeneity of stochastic gene expression

The heterogeneity of stochastic gene expression, which refers to the temporal fluctuation of the gene product and its cell-to-cell variation, has attracted considerable interest from biologists, physicists, and mathematicians. The dynamics of protein production and degradation have been modeled as random processes with transition probabilities. However, there is a gap between theory and phenomena, particularly in terms of analytical formulation and parameter estimation. In this study, we propose a theoretical framework in which we present a basic model of a gene regulatory system, derive a steady-state solution, and provide a Bayesian approach for estimating the model parameters from single-cell experimental data. The proposed framework is demonstrated to be applicable for various scales of single-cell experiments at both the mRNA and protein levels, and it is useful for comparing kinetic parameters across species, genomes, and cell strains.

biophysics↗

bioRxiv2017

Correlation of gene expressions between nucleus and cytoplasm reflects single-cell physiology

BackgroundEukaryotes transcribe RNAs in nuclei and transport them to the cytoplasm through multiple steps of post-transcriptional regulation. Existing single-cell sequencing technologies, however, are unable to analyse nuclear (nuc) and cytoplasmic (cyt) RNAs separately and simultaneously. Hence, there remain challenges to discern correlation, localisation, and translocation between them.\n\nResultsHere we report a microfluidic system that physically separates nucRNA and cytRNA from a single cell and enables single-cell integrated nucRNA and cytRNA-sequencing (SINC-seq). SINC-seq constructs two individual RNA-seq libraries, nucRNA and cytRNA per cell, quantifies gene expression in the subcellular compartments and combines them to create a novel single-cell RNA-seq data enabled by our system, which we here term in-silico single cell.\n\nConclusionsLeveraging SINC-seq, we discovered three distinct natures of correlation among cytRNA and nucRNA that reflected the physiological state of single cells: The cell-cycle-related genes displayed highly correlated expression pattern with minor differences; RNA splicing genes showed lower nucRNA-to-cytRNA correlation, suggesting a retained intron may be implicated in inhibited mRNA transport; A chemical perturbation, sodium butyrate treatment, transiently distorted the correlation along differentiating human leukemic cells to erythroid cells. These data uniquely provide insights into the regulatory network of mRNA from nucleus toward cytoplasm at the single cell level.

genomics↗