18 Age-associated hypomethylated open sea blocks enriched for CGIs undergoing age-associated hypermethylation, and containing at least 10 such CGIs.

<p>Columns label chromosome, length of block (Mb), number of contiguous open sea regions defining hypomethylated block, the family wise error rate (FWER) for the hypomethylated block, observed number of age-hyperM CGIs within block, expected number of age-hyperM CGIs within block and Binomial P-value of enrichment of age-hyperM CGIs within block. In bold-face we indicate those significant under adjustment for multiple testing (Benjamini-Hochberg FDR < 0.05).</p><p>18 Age-associated hypomethylated open sea blocks enriched for CGIs undergoing age-associated hypermethylation, and containing at least 10 such CGIs.</p

Age-associated hypomethylated blocks enriched for hypermethylated CGIs.

<p><b>A)</b> Example of a large genomic region on chromosome-19 containing a significant age-associated hypomethylated block (indicated in green). y-axis gives the fit from the Bumphunter algorithm indicating the methylation change for an increase in 10 age-years, x-axis the genomic position. <b>B)</b> Selected age-hypomethylated blocks enriched for CGIs undergoing hypermethylation. Each plot shows the fit from the Bumphunter algorithm indicating the methylation change per 10 age-years (y-axis) as a function of opensea probe position (x-axis). In blue we indicate the positions of CGIs, and in red those that are significantly hypermethylated with age. Some of the genes associated with the age-hypermethylated CGIs are indicated in red.</p

Enrichment of TFBSs among age-DMRs.

<p><b>A)</b> Left top panel depicts the age of the individuals from which the blood samples were taken, sorted by increasing age. Heatmap depicts relative DNA methylation levels for the top 500 age-hypomethylated and top 500 age-hypermethylated DMRs (blue = relative high DNA methylation, yellow = relative low DNA methylation), with samples sorted by increasing age. Right panel depicts (with black lines) which DMRs overlap with transcription factor binding sites (TFBS) for a number of TFs which exhibited highly significant enrichment either for age-hypermethylated or age-hypomethylated DMRs (or both). Below the panels we give the odds ratios (OR) and Fisher-test P-values (P) of enrichment of the corresponding TFBSs among age-hypermethylated and age-hypomethylated regions of the top 5% of age-DMRs. <b>B)</b> Combinatorial enrichment analysis of TFBSs. TFs have been sorted according to the strength of association (P-value) of their binding profile with the association of a region’s DNA methylation with age, as assessed from a multivariate linear regression model. Color code for P-values: white (<i>P</i> > 0.01), pink (<i>P</i> < 0.01), red (<i>P</i> < 1<i>e</i> − 5), brown (<i>P</i> < 1<i>e</i> − 10). Below P-value bar we show the corresponding estimated t-statistic in the multivariate analysis (magenta = strongly significant (<i>P</i> < 0.001) positive values, cyan = strongly significant (<i>P</i> < 0.001) negative values).</p

Age-associated hypermethylation (hypomethylation) targets lowly (highly) expressed genes.

<p><b>A)</b> Boxplots of mRNA expression levels in cord blood and placenta samples, for three sets of genes: (i) genes undergoing age-associated hypomethylation in their CGI promoters (AgeHypoM), (ii) genes not undergoing any age-associated DNAm changes (NonAgeDMR), and (iii) genes undergoing age-associated hypermethylation in their CGI promoters (AgeHyperM). P-values shown between groupds are from a Wilcoxon-rank sum test comparing the respective neighboring gene classes. The number of genes in each class is indicated below plot. The P-value from a linear regression of expression against gene-class is also indicated in red. <b>B)</b> Left panel: As A) but for the whole blood samples of de Jong et al 2014, for individuals under the age of 30. Right panel: As left panel, but now for 49 whole blood samples from people over the age of 50. <b>C)</b> As B) but now for the expression data set of Beineke et al 2012.</p

Age-associated hypomethylated blocks exhibit preferential hypomethylation in cancer.

<p>Left boxplots show the average beta methylation levels over open-sea regions within an age-associated hypomethylated block on Chr-10 in normal tissue and age-matched cancers from the TCGA. (<b>A)</b> Endometrial Cancer (UCEC), <b>B)</b> Lung Adenoma Carcinoma (LUAD), <b>C)</b> Breast Cancer, <b>D)</b> Lung Squamous Cell Carcinoma (LSCC). P-values in boxplots are from a Wilcoxon rank sum test. Number of samples in each group is indicated. Right panel depicts the density distribution of the t-statistics of all age-hypomethylated blocks (magenta), as assessed between normal and age-matched cancer tissue. The cyan curve represents the corresponding statistics for a random set of non-age associated blocks, matched for number and length distribution of the observed age-hypomethylated blocks. P-value is from a Kolmogorov-Smirnov test.</p

Identification of pluripotent and lineage-specific TFs by integration of Illumina 450k DNAm with ENCODE data.

<p><b>A)</b> Probabilities that a randomly picked open-sea, shore/shelf and CpG-island region is a DMR between pluripotent and differentiated cells (defined as the top 5% of DMRs). <b>B)</b> Relative numbers of DMRs hypomethylated within hESCs and differentiated cell types and within each regional class. <b>C)</b> Enrichment heatmap of transcription factor binding sites (as assessed in H1-hESC) for 58 TFs, among the DMRs hypomethylated in hESCs (HypoESC) and DMRs hypomethylated in differentiated cells (HypoDIFF). <b>D)</b> Enrichment heatmap of transcription factor binding sites (HepG2 line) for the top ranked 58 TFs, among DMRs hypomethylated in hESCs (HypoESC) and DMRs hypomethylated in liver cells (HypoLIV). In C-D), TFs have been ranked according to the significance of enrichment among HypoESC DMRs. Color codes: white (<i>P</i> > 0.01), pink (<i>P</i> < 0.01), red (<i>P</i> < 1<i>e</i> − 5), brown (<i>P</i> < 1<i>e</i> − 10). ChIP-Seq binding profiles of the same TF but generated by different labs are distinguished by an abbreviation of the corresponding lab: SF (Stanford), HA (Hudson-Alpha).</p

Mechanistic Studies and Modeling Reveal the Origin of Differential Inhibition of Gag Polymorphic Viruses by HIV-1 Maturation Inhibitors

<div><p>HIV-1 maturation inhibitors (MIs) disrupt the final step in the HIV-1 protease-mediated cleavage of the Gag polyprotein between capsid p24 capsid (CA) and spacer peptide 1 (SP1), leading to the production of infectious virus. BMS-955176 is a second generation MI with improved antiviral activity toward polymorphic Gag variants compared to a first generation MI bevirimat (BVM). The underlying mechanistic reasons for the differences in polymorphic coverage were studied using antiviral assays, an LC/MS assay that quantitatively characterizes CA/SP1 cleavage kinetics of virus like particles (VLPs) and a radiolabel binding assay to determine VLP/MI affinities and dissociation kinetics. Antiviral assay data indicates that BVM does not achieve 100% inhibition of certain polymorphs, even at saturating concentrations. This results in the breakthrough of infectious virus (partial antagonism) regardless of BVM concentration. Reduced maximal percent inhibition (MPI) values for BVM correlated with elevated EC₅₀ values, while rates of HIV-1 protease cleavage at CA/SP1 correlated inversely with the ability of BVM to inhibit HIV-1 Gag polymorphic viruses: genotypes with more rapid CA/SP1 cleavage kinetics were less sensitive to BVM. <i>In vitro</i> inhibition of wild type VLP CA/SP1 cleavage by BVM was not maintained at longer cleavage times. BMS-955176 exhibited greatly improved MPI against polymorphic Gag viruses, binds to Gag polymorphs with higher affinity/longer dissociation half-lives and exhibits greater time-independent inhibition of CA/SP1 cleavage compared to BVM. Virological (MPI) and biochemical (CA/SP1 cleavage rates, MI-specific Gag affinities) data were used to create an integrated semi-quantitative model that quantifies CA/SP1 cleavage rates as a function of both MI and Gag polymorph. The model outputs are in accord with <i>in vitro</i> antiviral observations and correlate with observed <i>in vivo</i> MI efficacies. Overall, these findings may be useful to further understand antiviral profiles and clinical responses of MIs at a basic level, potentially facilitating further improvements to MI potency and coverage.</p></div

Schematic for Cleavage of CA/SP1.

<p>A) Schematic for the processing HIV Gag at CA/SP1 and SP1/NC sites by HIV-protease. B) Detail of the cleavage region around CA/SP1 showing sites for HIV-1 protease cleavage (H1 and H2) and sites for subsequent cleavage by trypsin (T).</p

Modeling of the rate of CA/SP1 cleavage of HIV-1 WT, V370A, V362I and ΔV370 VLP in the presence of 300 nM MI.

<p>Modeled fractional rate of production of SP1 peptide from Gag VLP cleavage using model 2a at 300 nM MI, as noted in text; no MI: diamonds; BVM: squares; BMS-955176: triangles; y-axis: fraction of CA/SP1 cleavage is a surrogate for production of mature virus, as indicated in <a href="http://www.plospathogens.org/article/info:doi/10.1371/journal.ppat.1005990#ppat.1005990.g005" target="_blank">Fig 5</a>; A) WT; B) V370A; C)V362I; D) ΔV370</p

Inhibition of HIV-1 protease mediated CA/SP1 cleavage by MIs.

<p>A) BVM, B) BMS-955176: Inhibition of CA/SP1 cleavage of WT, ΔV370 and A364V VLPs <i>in vitro</i> as monitored by LC/MS analysis (Materials and Methods); values are an average of 9 replicates; bars are SEM; MI concentrations: 3 μM.</p