Biology subjects

Yamane, J.

Publications and source records attributed to Yamane, J..

4 recordsLinked to original sources

bioRxiv2022

AMPK-p38 axis converts human pluripotent stem cells to naïve state

Pluripotent stem cells (PSCs) have been reported to exhibit two stages of pluripotency, primed and naive states. Typical human PSCs (hPSCs) are in the primed state. Though several methods for conversion from primed to naive state have been reported, the mechanism of the process is not fully understood. Here, we report that 5 adenosine monophosphate-activated protein kinase (AMPK) and its downstream p38 is a signaling axis that can induce the naive conversion of hPSCs with single pathway activation. The simple addition of an AMPK activator, 5-aminoimidazole-4-carboxamide-1-{beta}-D-ribofuranoside (AICAR), or overexpression of a constitutive active form of p38 (CA-p38) alone in primed hPSCs induced naive hPSCs that satisfied naive state criteria: differentiation ability to three germ layers and naive state-specific transcriptional expression, epigenomic resetting, and mitochondrial activity. RNA-seq analysis demonstrated that our AICAR- or CA-p38-induced naive hPSCs show closely similar gene expression patterns to naive state human embryonic stem cells (HNES1) derived from human inner cell mass (ICM). This novel and simple naive conversion method provides new avenues for understanding and elucidating the fundamental mechanism of naive conversion.

cell biology↗

bioRxiv2021

Prediction of broad chemical toxicities using induced pluripotent stem cells and gene networks by transfer learning from embryonic stem cell data

The assessment of toxic chemicals using animals has limited applicability to humans. Moreover, from the perspective of animal protection, effective alternatives are also desired. Previously, we developed a method that combines developmental toxicity testing based on undifferentiated human embryonic stem (ES) cells (KhES-3) and gene networks. We showed that [≥] 95% accurate predictions could be achieved for neurotoxins, genotoxic carcinogens, and non-genotoxic carcinogens. Here, we expanded this method to predict broad toxicities and predicted the toxicity of 24 chemicals in six categories (neurotoxins, cardiotoxins, hepatotoxins, nephrotoxins [glomerular nephrotoxins/tubular nephrotoxins], and non-genotoxic carcinogens) and achieved high prediction accuracy (AUC = 0.90-1.00) in all categories. Moreover, to develop a testing system with fewer ethical issues, we screened for an induced pluripotent stem (iPS) cell line on the basis of cytotoxic sensitivity and used this line to predict toxicity in the six categories based on the gene networks of iPS cells using transfer learning from the ES cell gene networks. We successfully predicted toxicities in four toxin categories (neurotoxins, hepatotoxins, glomerular nephrotoxins, and non-genotoxic carcinogens) at high accuracy (AUC = 0.82-0.99). These results demonstrate that the prediction of chemical toxicity is possible even with iPS cells by transfer learning once a gene expression database has been developed from an ES cell line. This method holds promise for tailor-made safety evaluations using individual iPS cells.

pharmacology and toxicology↗

bioRxiv2021

eSPRESSO: a spatial self-organizing-map clustering method for single-cell transcriptomes of various tissue structures using graph-based networks

Animal cells are spatially organized as tissues and cellular gene expression data contain such information that governs body structure and morphogenesis during developmental process. Although several computational tissue reconstruction methods using transcriptomic data have been proposed, those methods are insufficient with regard to arranging cells in their correct positions in tissues or organs unless spatial information is explicitly provided. Here, we propose eSPRESSO, a powerful in silico three-dimensional (3D) tissue reconstruction method using stochastic self-organizing map (stochastic-SOM) clustering, together with optimization of gene set by Markov chain Monte Carlo (MCMC) framework, to estimate the spatial domain structure of cells in any topology of tissues or organs from only their transcriptome profiles. We confirmed the performance of eSPRESSO by mouse embryo, embryonic heart, adult cortical layers, and human pancreas organoid with high reproducibility (success rate = 72.5-100%), while discovering morphologically important spatial discriminator genes (SDGs). Furthermore, we applied eSPRESSO to analysis of human adult heart diseases by virtual gene knockouts, and revealed candidate mechanisms of deformation of heart structure. The eSPRESSO may provide novel methods to analyze the mechanisms of 3D structure formation and morphology-based disease mechanisms.

bioinformatics↗

bioRxiv2020

Cell Pluripotency and Its Effect on Sensitivity to Chemical Exposure

Pluripotent stem cells (PSCs) possess unique characteristics that distinguish them from other cell types. Human embryonic stem (ES) cells are recently gaining attention as a powerful tool for human toxicity assessment without the use of experimental animals, and an embryonic stem cell test (EST) was introduced for this purpose. However, human PSCs have not been thoroughly investigated in terms of drug resistance or compared with other cell types or cell states, such as naive state, to date. Aiming to close this gap in research knowledge, we assessed and compared several human PSC lines for their resistance to drug exposure. Firstly, we report that RIKEN-2A human induced pluripotent stem (iPS) cells possessed approximately the same sensitivity to selected drugs as KhES-3 human ES cells. Secondly, both ES and iPS cells were several times less resistant to drug exposure than other non-pluripotent cell types. Finally, we showed that iPS cells subjected to naive-state induction procedures exhibited a sharp increase in drug sensitivity. Upon passage of these naive-like cells in non-naive PSC culture medium, their sensitivity to drug exposure decreased. We thus revealed differences in sensitivity to drug exposure among different types or states of PSCs and, importantly, indicated that naive-state induction could increase this sensitivity.

pharmacology and toxicology↗