Collectively, these data reveal dietary enrichment with ω-6 PUFAs as a new aetiology of peripheral neuropathy and risk factor for chronic pain and implicate multiple therapeutic considerations for clinical pain management.Global histone acetylation varies with changes in the nutrient and cell cycle phases; however, the mechanisms connecting these variations are not fully understood. Herein, we report that nutrient-related and cell-cycle-regulated nuclear acetate regulates global histone acetylation. Histone deacetylation-generated acetate accumulates in the nucleus and induces histone hyperacetylation. https://www.selleckchem.com/JAK.html The nuclear acetate levels were controlled by glycolytic enzyme triosephosphate isomerase 1 (TPI1). Cyclin-dependent kinase 2 (CDK2), which is phosphorylated and activated by nutrient-activated mTORC1, phosphorylates TPI1 Ser 117 and promotes nuclear translocation of TPI1, decreases nuclear dihydroxyacetone phosphate (DHAP) and induces nuclear acetate accumulation because DHAP scavenges acetate via the formation of 1-acetyl-DHAP. CDK2 accumulates in the cytosol during the late G1/S phases. Inactivation or blockade of nuclear translocation of TPI1 abrogates nutrient-dependent and cell-cycle-dependent global histone acetylation, chromatin condensation, gene transcription and DNA replication. These results identify the mechanism of maintaining global histone acetylation by nutrient and cell cycle signals.The interplay between light receptors and PHYTOCHROME-INTERACTING FACTORs (PIFs) serves as a regulatory hub that perceives and integrates environmental cues into transcriptional networks of plants1,2. Although occupancy of the histone variant H2A.Z and acetylation of histone H3 have emerged as regulators of environmentally responsive gene networks, how these epigenomic features interface with PIF activity is poorly understood3-7. By taking advantage of rapid and reversible light-mediated manipulation of PIF7 subnuclear localization and phosphorylation, we simultaneously assayed the DNA-binding properties of PIF7, as well as its impact on chromatin dynamics genome wide. We found that PIFs act rapidly to reshape the H2A.Z and H3K9ac epigenetic landscape in response to a change in light quality. Furthermore, we discovered that PIFs achieve H2A.Z removal through direct interaction with EIN6 ENHANCER (EEN), the Arabidopsis thaliana homolog of the chromatin remodeling complex subunit INO80 Subunit 6 (Ies6). Thus, we describe a PIF-INO80 regulatory module that is an intermediate step for allowing plants to change their growth trajectory in response to environmental changes.Plasma lipids are known heritable risk factors for cardiovascular disease, but increasing evidence also supports shared genetics with diseases of other organ systems. We devised a comprehensive three-phase framework to identify new lipid-associated genes and study the relationships among lipids, genotypes, gene expression and hundreds of complex human diseases from the Electronic Medical Records and Genomics (347 traits) and the UK Biobank (549 traits). Aside from 67 new lipid-associated genes with strong replication, we found evidence for pleiotropic SNPs/genes between lipids and diseases across the phenome. These include discordant pleiotropy in the HLA region between lipids and multiple sclerosis and putative causal paths between triglycerides and gout, among several others. Our findings give insights into the genetic basis of the relationship between plasma lipids and diseases on a phenome-wide scale and can provide context for future prevention and treatment strategies.Despite considerable advances in both in silico and in vitro approaches, in vivo studies that involve animal model systems remain necessary in many research disciplines. Neuroscience is one such area, with studies often requiring access to a complete nervous system capable of dynamically selecting between and then executing a full range of cognitive and behavioral outputs in response to a given stimulus or other manipulation. The involvement of animals in research studies is an issue of active public debate and concern and is therefore carefully regulated. Such regulations are based on the principles of the 3Rs of Replacement, Reduction and Refinement. In the sub-specialty of behavioral neuroscience, Full/Absolute Replacement remains a major challenge, as the complete ex vivo recapitulation of a system as complex and dynamic as the nervous system has yet to be achieved. However, a number of very positive developments have occurred in this area with respect to Relative Replacement and to both Refinement and Reduction. In this review, we discuss the Refinement- and Reduction-related benefits yielded by the introduction of touchscreen-based behavioral assessment apparatus. We also discuss how data generated by a specific panel of behavioral tasks developed for this platform might substantially enhance monitoring of laboratory animal welfare and provide robust, quantitative comparisons of husbandry techniques to define and ensure maintenance of best practice.The development of unnatural base pairs (UBPs) has greatly increased the information storage capacity of DNA, allowing for transcription of unnatural RNA by the heterologously expressed T7 RNA polymerase (RNAP) in Escherichia coli. However, little is known about how UBPs are transcribed by cellular RNA polymerases. Here, we investigated how synthetic unnatural nucleotides, NaM and TPT3, are recognized by eukaryotic RNA polymerase II (Pol II) and found that Pol II is able to selectively recognize UBPs with high fidelity when dTPT3 is in the template strand and rNaMTP acts as the nucleotide substrate. Our structural analysis and molecular dynamics simulation provide structural insights into transcriptional processing of UBPs in a stepwise manner. Intriguingly, we identified a novel 3'-RNA binding site after rNaM addition, termed the swing state. These results may pave the way for future studies in the design of transcription and translation strategies in higher organisms with expanded genetic codes.Drug discovery focused on target proteins has been a successful strategy, but many diseases and biological processes lack obvious targets to enable such approaches. Here, to overcome this challenge, we describe a deep learning-based efficacy prediction system (DLEPS) that identifies drug candidates using a change in the gene expression profile in the diseased state as input. DLEPS was trained using chemically induced changes in transcriptional profiles from the L1000 project. We found that the changes in transcriptional profiles for previously unexamined molecules were predicted with a Pearson correlation coefficient of 0.74. We examined three disorders and experimentally tested the top drug candidates in mouse disease models. Validation showed that perillen, chikusetsusaponin IV and trametinib confer disease-relevant impacts against obesity, hyperuricemia and nonalcoholic steatohepatitis, respectively. DLEPS can generate insights into pathogenic mechanisms, and we demonstrate that the MEK-ERK signaling pathway is a target for developing agents against nonalcoholic steatohepatitis.