Age-related epigenome-wide DNA methylation and hydroxymethylation in longitudinal mouse blood

<p>DNA methylation at cytosine-phosphate-guanine (CpG) dinucleotides changes as a function of age in humans and animal models, a process that may contribute to chronic disease development. Recent studies have investigated the role of an oxidized form of DNA methylation – 5-hydroxymethylcytosine (5hmC) – in the epigenome, but its contribution to age-related DNA methylation remains unclear. We tested the hypothesis that 5hmC changes with age, but in a direction opposite to 5-methylcytosine (5mC), potentially playing a distinct role in aging. To characterize epigenetic aging, genome-wide 5mC and 5hmC were measured in longitudinal blood samples (2, 4, and 10 months of age) from isogenic mice using two sequencing methods – enhanced reduced representation bisulfite sequencing and hydroxymethylated DNA immunoprecipitation sequencing. Examining the epigenome by age, we identified 28,196 unique differentially methylated CpGs (DMCs) and 8,613 differentially hydroxymethylated regions (DHMRs). Mouse blood showed a general pattern of epigenome-wide hypermethylation and hypo-hydroxymethylation with age. Comparing age-related DMCs and DHMRs, 1,854 annotated genes showed both differential 5mC and 5hmC, including one gene – <i>Nfic</i> – at five CpGs in the same 250 bp chromosomal region. At this region, 5mC and 5hmC levels both decreased with age. Reflecting these age-related epigenetic changes, <i>Nfic</i> RNA expression in blood decreased with age, suggesting that age-related regulation of this gene may be driven by 5hmC, not canonical DNA methylation. Combined, our genome-wide results show age-related differential 5mC and 5hmC, as well as some evidence that changes in 5hmC may drive age-related DNA methylation and gene expression.</p

Statistiques des relations de travail

<p>Expression of Proteasome subunit encoding genes, that were significantly changed in the presence of hypoxic stress induced by Co⁺⁺. Cells were treated either with vehicle or Co⁺⁺ (n = 3 independent biological samples, n = 3 microarray chips per biological sample). Microarray analysis was performed to identify differentially expressed genes after addition of Co⁺⁺, using R statistical software and the <i>limma</i> Bioconductor package.</p

Hypoxia decreases expression of AQP5 protein and mRNA levels in MLE-12 cells.

<p>(A) Western blot analysis of total protein extract from MLE-12 cells exposed to normoxia and hypoxia (B) Quantitation of the Western blots using β-actin as the loading control (C) Northern blot analysis of total mRNA isolated from cells exposed to normoxia and hypoxia. (D) Quantitation of the Northern blots blot using L32 as the loading control. (E) Western blot analysis of nuclear extracts from cells exposed to normoxia and hypoxia. Lamin B was used as a loading control. Values for the blots are the mean ± SEM (n = 3). N, normoxia. H, hypoxia.</p

AQP5 expression is decreased in lung of mice exposed to hypoxia.

<p>(A) Western blot analysis of total protein extracts isolated from lungs of mice exposed to hypoxia and controls. (B) Quantitation of the Western blots using β-actin as the loading control. Values in the plot are the mean ± SEM (controls-n = 5; 3 day hypoxia-n = 6; 7 day hypoxia-n = 7, p<0.0001 using ANOVA).</p

<i>de novo</i> protein synthesis is necessary to down-regulate AQP5 expression.

<p>(A) Western blot analysis of MLE-12 cells pre-incubated with cycloheximide or vehicle (70% ethanol) followed by 100 μM cobalt. (B) Quantitation of the Western blots in panel B using β-actin as the loading control. (C) Northern blot analysis of MLE-12 cells pre-incubated with cycloheximide or vehicle (70% ethanol) followed by 100 μM cobalt. (D) Quantitation of the Northern blots in panel E using L32 as the loading control. Values in the all the blots are the mean ± SD (n = 3).</p

Hypoxia and Cobalt regulate expression of AQP5 via a proteasome dependent pathway.

<p>(A) Western blot analysis to determine AQP5 expression in total protein extracts isolated from cells exposed to normoxia, hypoxia or hypoxia with 10 μm proteasome inhibitor PI III for 24 h. β-actin is used as a loading control. (B)& (C) Western blot analysis of total protein extracts of cells were pre-treated with 10 μM proteasome inhibitor PI III or LC for 30 min, and then 100 μM Cobalt was added for 24 h. β-actin is used as loading control. (D) Quantitation of Western blots in panels A–C. (E)& (F) Northern blot analysis of total mRNA isolated from cells, which were pre-treated with 10 μM proteasome inhibitor PI III or LC for 30 min, and then 100 μM cobalt was added for 24 h. L32 is used as a loading control. (G) Quantitation of Northern blots in panels E and F. (H) Western blot analysis to determine HIF-1α expression in nuclear extracts from differently treated cells. Lane 1, normoxia; lane 2, hypoxia; lane 3, normoxia plus cobalt; lane 4, normoxia plus PI III; lane 5, hypoxia plus PI III; lane 6, normoxia plus PI III and cobalt. Values for the blots are the mean ± SD (n = 3).</p

HIF-1α is necessary to regulate AQP5 expression under hypoxic conditions.

<p>(A) Western blot analysis to determine AQP5 expression (bottom panel) in total protein extracts isolated from cells treated with vehicle, cobalt, PHD inhibitor-0041 at 25 µM, 100 µM, and 200 µM conc. Similarly, expression of HIF-1α in the top panel and expression of β-actin in the middle panel in the same groups. (B) Western blot analysis to determine AQP5 expression in total protein extracts isolated from cells treated with vehicle, cobalt, zinc chloride, cobalt plus zinc chloride (bottom panel) and β-actin (top panel). (C) Western blot analysis to determine AQP5 expression (bottom panel) and β-actin (top panel) in total protein extracts isolated from mock transfected MLE-12 cells, and MLE-12 cells transfected with HIF-1α dominant negative, treated with vehicle and cobalt. (D) Quantitation of the AQP5 expression using β-actin as the loading control in panel A. (E) Quantitation of AQP5 expression using β-actin as the loading control in panel B. (F) Quantitation of the AQP5 expression using β-actin as the loading control in panel C. (G) Western blot analysis to determine expression of HIF-1α (top panel) and Lamin B (bottom panel) in total protein extracts isolated from cells transfected with non-targeting siRNA and HIF-1α siRNA. Transfected cells were treated with vehicle and cobalt. (H) Quantitation of the HIF-1α expression using Lamin B as the loading control in panel G. (I) Western blot analysis to determine expression of AQP5 (bottom panel) and β-actin (top panel) in total protein extracts isolated from cells transfected with non-targeting siRNA and HIF-1α siRNA. Transfected cells were treated with vehicle and cobalt. (J) Quantitation of the AQP5 expression using β-actin as the loading control in panel I. Values for the blots are the mean ± SD (n = 3).</p

Cobalt regulates AQP5 expression via ERK signaling pathway.

<p>(A) Western blot analysis to determine AQP5 expression in total protein extracts isolated from cells treated with vehicle, cobalt, cobalt plus ERK pathway inhibitor PD98059 and PD98059 alone. (B) Quantitation of the Western blots in panel A using β-actin as the loading control. (C) Western blot analysis to determine phosphorylated ERK expression (upper panel) in total protein extracts isolated from cells shown in panel A. Total ERK expression in the same groups (lower panel). (D) Quantitation of the change in phosphorylation of ERK using total ERK for normalization. (E) Western blot analysis to determine HIF-1α expression in nuclear protein extracts isolated from cells treated with vehicle, cobalt, cobalt plus ERK pathway inhibitor PD98059 and PD98059 alone. (F) Quantitation of the Western blots in panel E using Lamin B as the loading control. Values for the blots are the mean ± SD (n = 3).</p

A putative model for the molecular pathway linking hypoxic stress to decreased AQP5 expression.

<p>Hypoxic stress activates HIF-1α via the ERK signaling pathway. HIF-1α activates a repressor of AQP5 transcription via a proteasome-mediated mechanism (which could act by degrading inhibitors of the repressor protein).</p

Detection of differential DNA methylation in repetitive DNA of mice and humans perinatally exposed to bisphenol A

<p>Developmental exposure to bisphenol A (BPA) has been shown to induce changes in DNA methylation in both mouse and human genic regions; however, the response in repetitive elements and transposons has not been explored. Here we present novel methodology to combine genomic DNA enrichment with RepeatMasker analysis on next-generation sequencing data to determine the effect of perinatal BPA exposure on repetitive DNA at the class, family, subfamily, and individual insertion level in both mouse and human samples. Mice were treated during gestation and lactation to BPA in chow at 0, 50, or 50,000 ng/g levels and total BPA was measured in stratified human fetal liver tissue samples as low (non-detect to 0.83 ng/g), medium (3.5 to 5.79 ng/g), or high (35.44 to 96.76 ng/g). Transposon methylation changes were evident in human classes, families, and subfamilies, with the medium group exhibiting hypomethylation compared to both high and low BPA groups. Mouse repeat classes, families, and subfamilies did not respond to BPA with significantly detectable differential DNA methylation. In human samples, 1251 individual transposon loci were detected as differentially methylated by BPA exposure, but only 19 were detected in mice. Of note, this approach recapitulated the discovery of a previously known mouse environmentally labile metastable epiallele, <i>Cabp</i>^<i>IAP</i>. Thus, by querying repetitive DNA in both mouse and humans, we report the first known transposons in humans that respond to perinatal BPA exposure.</p