Biology subjects

Oshima, J.

Publications and source records attributed to Oshima, J..

4 recordsLinked to original sources

bioRxiv2024

Werner syndrome RECQ helicase participates in and directs maintenance of the protein complexes of constitutive heterochromatin in proliferating human cells

The WRN RECQ helicase is responsible for the Werner syndrome of premature aging and cancer predisposition. Substantial progress has been made in delineating WRN functions in multiple aspects of DNA metabolism, including DNA replication, repair, transcription, and telomere maintenance. Nevertheless, a complete mechanistic understanding of how loss of WRN accelerates aging in humans has not been achieved yet. Here we show that WRN is involved in the maintenance of constitutive heterochromatin, CH, in proliferating, immortalized human fibroblasts. WRN is found within a complex with histone deacetylase 2, HDAC2, and WRN/HDAC2 association is mediated by heterochromatin protein alpha, HP1. WRN deficiency derepresses SATII pericentromeric satellite repeats and reduces a subset of protein-protein interactions that participate in the organization of CH in the nucleus. In particular, WRN deficiency reduces the complexes involving Lamin B1 and Lamin B receptor, LBR. Both mRNA level and subcellular distribution of LBR are affected by WRN deficiency, and the latter phenotype does not require WRN catalytic activities. At the mRNA level, WRN supports complete maturation of the LBR mRNA. All signs of heterochromatin disruption seen in WRN-deficient proliferating fibroblasts are also observed in WRN-proficient fibroblasts undergoing replicative or oncogene-induced senescence, and WRN complexes with HP1 and HDAC2 are also markedly downregulated in these senescing cells. The data suggest that WRN loss affects heterochromatin independently of the senescence program but can mimic aspects of it and thus sensitize cells to triggers of senescence.

molecular biology↗

bioRxiv2024

Maternal histone methyltransferases antagonistically regulate monoallelic expression in C. elegans

Undefined epigenetic programs act to probabilistically silence individual autosomal alleles, generating unique individuals, even from genetic clones. This sort of random monoallelic expression can explain variation in traits and diseases that differences in genes and environments cannot. Here, we developed the nematode Caenorhabditis elegans to study monoallelic expression in whole tissues, and defined a developmental genetic regulation pathway. We found maternal H3K9 histone methyltransferase (HMT) SET-25/SUV39/G9a works with HPL-2/HP1 and LIN-61/L3MBTL2 to randomly silence alleles in the intestinal progenitor E-cell of 8-cell embryos to cause monoallelic expression. SET-25 was antagonized by another maternal H3K9 HMT, MET-2/SETDB1, which works with LIN-65/ATF7ZIP and ARLE-14/ARL14EP to prevent monoallelic expression. The HMT-catalytic SET domains of both MET-2 and SET-25 were required for regulating monoallelic expression. Our data support a model wherein SET-25 and MET-2 regulate histones during development to generate patterns of somatic monoallelic expression that are persistent but not heritable.

systems biology↗

bioRxiv2022

Oxidative Stress Induced Senescence Gives Rise to Transcriptionally Distinct Physiological States

As people age, the risk of cardiovascular disease, diabetes, cancer, and Alzheimers disease increases, making age itself the greatest risk factor for many human diseases. Thus, understanding the aging process can have profound consequences for human health. One striking feature of the aging process is the accumulation of senescent cells with age. When cells become damaged, they can enter a state of senescence which is a permanent cell cycle exit associated with the secretion of inflammatory cytokines. In mouse models of aging, the destruction of senescent cells with senolytic drugs delays age-associated decline and extends healthy lifespan. Yet, despite the wealth of accumulated knowledge, we do not entirely understand the biology of senescent cells. Prior work has shown that senescence is associated with increased variation in gene expression, suggesting that there may exist distinct transcriptional signatures of senescence. Understanding the different transcriptional physiological states of senescent cells would allow us to better treat them with cell-type-specific senolytic drugs. Here, we performed large-scale single-cell RNA-sequencing time series experiments to understand the development of transcriptional heterogeneity among senescent cell types. Our approach allowed us to observe and classify different transcriptional signatures of senescent cells as they emerged through time. We found that upon entering oxidative stress-induced senescence, separate subpopulations of cells were reproducibly adopting two distinct transcriptional states, one of which was associated with stress response and the second one with tissue remodeling. Our data suggest that a combination of senolytic drugs may be needed to more effectively eliminate senescent cells by targeting physiologically distinct sub-populations.

cell biology↗

bioRxiv2021

Solving the Sample Size Problem for Resource Selection Analysis

O_LISample size sufficiency is a critical consideration for conducting Resource-Selection Analyses (RSAs) from GPS-based animal telemetry. Cited thresholds for sufficiency include a number of captured animals M [≥] 30 and as many relocations per animal N as possible. These thresholds render many RSA-based studies misleading if large sample sizes were truly insufficient, or unpublishable if small sample sizes were sufficient but failed to meet reviewer expectations. C_LIO_LIWe provide the first comprehensive solution for RSA sample size by deriving closed-form mathematical expressions for the number of animals M and the number of relocations per animal N required for model outputs to a given degree of precision. The sample sizes needed depend on just 2 biologically meaningful quantities: habitat selection strength and a novel measure of landscape complexity, which we define rigorously. The mathematical expressions are calculable for any environmental dataset at any spatial scale and are applicable to any study involving resource selection (including sessile organisms). We validate our analytical solutions using globally relevant empirical data including 5,678,623 GPS locations from 511 animals from 10 species (omnivores, carnivores, and herbivores living in boreal, temperate, and tropical forests, montane woodlands, swamps, and arctic tundra). C_LIO_LIOur analytic expressions show that the required M and N must decline with increasing selection strength and increasing landscape complexity, and this decline is insensitive to the definition of availability used in the analysis. Our results contradict conventional wisdom by demonstrating that the most biologically relevant effects on the utilization distribution (i.e. those landscape conditions with the greatest absolute magnitude of resource selection) can often be estimated with far fewer data than is commonly assumed. C_LIO_LIWe identify several critical steps in implementing these equations, including (i) a priori selection of expected model coefficients, and (ii) sampling intensity for background (absence/pseudo-absence) data within a given definition of availability. We show that random sampling of background data violates the underlying mathematics of RSA, leading to incorrect values for necessary M and N and potentially incorrect RSA model outputs. We argue that these equations should be a mandatory component for all future RSA studies. C_LI

ecology↗