Histone acylation marks respond to metabolic perturbations and enable cellular adaptation

Acetylation is the most studied histone acyl modification and has been recognized as a fundamental player in metabolic gene regulation, whereas other short-chain acyl modifications have only been recently identified, and little is known about their dynamics or molecular functions at the intersection of metabolism and epigenetic gene regulation. In this study, we aimed to understand the link between nonacetyl histone acyl modification, metabolic transcriptional regulation, and cellular adaptation. Using antibodies specific for butyrylated, propionylated, and crotonylated H3K23, we analyzed dynamic changes of H3K23 acylation upon various metabolic challenges. Here, we show that H3K23 modifications were highly responsive and reversibly regulated by nutrient availability. These modifications were commonly downregulated by the depletion of glucose and recovered based on glucose or fatty acid availability. Depletion of metabolic enzymes, namely, ATP citrate lyase, carnitine acetyltransferase, and acetyl-CoA synthetase, which are involved in Ac-CoA synthesis, resulted in global loss of H3K23 butyrylation, crotonylation, propionylation, and acetylation, with a profound impact on gene expression and cellular metabolic states. Our data indicate that Ac-CoA/CoA and central metabolic inputs are important for the maintenance of histone acylation. Additionally, genome-wide analysis revealed that acyl modifications are associated with gene activation. Our study shows that histone acylation acts as an immediate and reversible metabolic sensor enabling cellular adaptation to metabolic stress by reprogramming gene expression. © 2020, The Author(s).1

Long non-coding RNA ChRO1 facilitates ATRX/DAXX-dependent H3.3 deposition for transcription-associated heterochromatin reorganization.

Constitutive heterochromatin undergoes a dynamic clustering and spatial reorganization during myogenic differentiation. However the detailed mechanisms and its role in cell differentiation remain largely elusive. Here, we report the identification of a muscle-specific long non-coding RNA, ChRO1, involved in constitutive heterochromatin reorganization. ChRO1 is induced during terminal differentiation of myoblasts, and is specifically localized to the chromocenters in myotubes. ChRO1 is required for efficient cell differentiation, with global impacts on gene expression. It influences DNA methylation and chromatin compaction at peri/centromeric regions. Inhibition of ChRO1 leads to defects in the spatial fusion of chromocenters, and mislocalization of H4K20 trimethylation, Suv420H2, HP1, MeCP2 and cohesin. In particular, ChRO1 specifically associates with ATRX/DAXX/H3.3 complex at chromocenters to promote H3.3 incorporation and transcriptional induction of satellite repeats, which is essential for chromocenter clustering. Thus, our results unveil a mechanism involving a lncRNA that plays a role in large-scale heterochromatin reorganization and cell differentiation.Individual Basic Researcher Program [2018R1D1A1B070 48056 to E.-J.C., 2017R1D1A1B03035883 to J.P.]; Advanced Research Center Program [NRF-2010-0029359 to E.-J.C.]; National Creative Research Laboratory Program [2012R1A3A2048767 to H.-D.Y.]; NRF-2012-Fostering Core Leaders of the Future Basic Science Program through the National Research Foundation of Korea [2012H1A8003093 to J.P.]

The tumor suppressor, parafibromin, mediates histone H3 K9 methylation for cyclin D1 repression

Parafibromin, a component of the RNA polymerase II-associated PAF1 complex, is a tumor suppressor linked to hyperparathyroidism-jaw tumor syndrome and sporadic parathyroid carcinoma. Parafibromin induces cell cycle arrest by repressing cyclin D1 via an unknown mechanism. Here, we show that parafibromin interacts with the histone methyltransferase, SUV39H1, and functions as a transcriptional repressor. The central region (128–227 amino acids) of parafibromin is important for both the interaction with SUV39H1 and transcriptional repression. Parafibromin associated with the promoter and coding regions of cyclin D1 and was required for the recruitment of SUV39H1 and the induction of H3 K9 methylation but not H3 K4 methylation. RNA interference analysis showed that SUV39H1 was critical for cyclin D1 repression. These data suggest that parafibromin plays an unexpected role as a repressor in addition to its widely known activity associated with transcriptional activation. Parafibromin as a part of the PAF1 complex might downregulate cyclin D1 expression by integrating repressive H3 K9 methylation during transcription

Genetic Traceability of Black Pig Meats Using Microsatellite Markers

Pork from Jeju black pig (population J) and Berkshire (population B) has a unique market share in Korea because of their high meat quality. Due to the high demand of this pork, traceability of the pork to its origin is becoming an important part of the consumer demand. To examine the feasibility of such a system, we aim to provide basic genetic information of the two black pig populations and assess the possibility of genetically distinguishing between the two breeds. Muscle samples were collected from slaughter houses in Jeju Island and Namwon, Chonbuk province, Korea, for populations J and B, respectively. In total 800 Jeju black pigs and 351 Berkshires were genotyped at thirteen microsatellite (MS) markers. Analyses on the genetic diversity of the two populations were carried out in the programs MS toolkit and FSTAT. The population structure of the two breeds was determined by a Bayesian clustering method implemented in structure and by a phylogenetic analysis in Phylip. Population J exhibited higher mean number of alleles, expected heterozygosity and observed heterozygosity value, and polymorphism information content, compared to population B. The FIS values of population J and population B were 0.03 and −0.005, respectively, indicating that little or no inbreeding has occurred. In addition, genetic structure analysis revealed the possibility of gene flow from population B to population J. The expected probability of identify value of the 13 MS markers was 9.87×10−14 in population J, 3.17×10−9 in population B, and 1.03×10−12 in the two populations. The results of this study are useful in distinguishing between the two black pig breeds and can be used as a foundation for further development of DNA markers

Clinical Characteristics of a Nationwide Hospital-based Registry of Mild-to-Moderate Alzheimer's Disease Patients in Korea: A CREDOS (Clinical Research Center for Dementia of South Korea) Study

With rapid population aging, the socioeconomic burden caused by dementia care is snowballing. Although a few community-based studies of Alzheimer's disease (AD) have been performed in Korea, there has never been a nationwide hospital-based study thereof. We aimed to identify the demographics and clinical characteristics of mild-to-moderate AD patients from the Clinical Research Center for Dementia of Korea (CREDOS) registry. A total of 1,786 patients were consecutively included from September 2005 to June 2010. Each patient underwent comprehensive neurological examination, interview for caregivers, laboratory investigations, neuropsychological tests, and brain MRI. The mean age was 74.0 yr and the female percentage 67.0%. The mean period of education was 7.1 yr and the frequency of early-onset AD (< 65 yr old) was 18.8%. Among the vascular risk factors, hypertension (48.9%) and diabetes mellitus (22.3%) were the most frequent. The mean score of the Korean version of Mini-Mental State Examination (K-MMSE) was 19.2 and the mean sum of box scores of Clinical Dementia Rating (CDR-SB) 5.1. Based on the well-structured, nationwide, and hospital-based registry, this study provides the unique clinical characteristics of AD and emphasizes the importance of vascular factors in AD in Korea

Prediction of cognitive impairment via deep learning trained with multi-center neuropsychological test data

Background Neuropsychological tests (NPTs) are important tools for informing diagnoses of cognitive impairment (CI). However, interpreting NPTs requires specialists and is thus time-consuming. To streamline the application of NPTs in clinical settings, we developed and evaluated the accuracy of a machine learning algorithm using multi-center NPT data. Methods Multi-center data were obtained from 14,926 formal neuropsychological assessments (Seoul Neuropsychological Screening Battery), which were classified into normal cognition (NC), mild cognitive impairment (MCI) and Alzheimers disease dementia (ADD). We trained a machine learning model with artificial neural network algorithm using TensorFlow (https://www.tensorflow.org) to distinguish cognitive state with the 46-variable data and measured prediction accuracies from 10 randomly selected datasets. The features of the NPT were listed in order of their contribution to the outcome using Recursive Feature Elimination. Results The ten times mean accuracies of identifying CI (MCI and ADD) achieved by 96.66 ± 0.52% of the balanced dataset and 97.23 ± 0.32% of the clinic-based dataset, and the accuracies for predicting cognitive states (NC, MCI or ADD) were 95.49 ± 0.53 and 96.34 ± 1.03%. The sensitivity to the detection CI and MCI in the balanced dataset were 96.0 and 96.0%, and the specificity were 96.8 and 97.4%, respectively. The time orientation and 3-word recall score of MMSE were highly ranked features in predicting CI and cognitive state. The twelve features reduced from 46 variable of NPTs with age and education had contributed to more than 90% accuracy in predicting cognitive impairment. Conclusions The machine learning algorithm for NPTs has suggested potential use as a reference in differentiating cognitive impairment in the clinical setting.The publication costs, design of the study, data management and writing the manuscript for this article were supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2017S1A6A3A01078538), Korea Ministry of Health & Welfare, and from the Original Technology Research Program for Brain Science through the National Research Foundation of Korea funded by the Korean Government (MSIP; No. 2014M3C7A1064752)