Exploratory analysis of the human breast DNA methylation profile upon soymilk exposure

Upon soy consumption, isoflavone metabolites attain bioactive concentrations in breast tissue possibly affecting health. Though in vitro epigenetic activity of soy metabolites has been described, the in vivo impact on the epigenome is largely unknown. Therefore, in this case-control study, the breast glandular tissue DNA methylome was explored in women undergoing an aesthetic breast reduction. After a run-in phase, 10 generally healthy Belgian or Dutch women received soymilk for 5 days. MethylCap-seq methylation profiles were compared with those of 10 matched controls. Isoflavones and their microbial metabolites were quantified in urine, serum, and glandular breast tissue (liquid chromatography-mass spectrometry) and 17 beta-estradiol in glandular breast tissue (immunoassay). Global DNA methylation levels were obtained for 6 cases and 5 controls using liquid chromatography-mass spectrometry. Although lower MethylCap-seq coverages were observed, mass spectrometry results and computational LINE-1 methylation analysis did not provide evidence supporting global methylation alterations upon treatment. At a false discovery rate of 0.05, no differentially methylated loci were identified. Moreover, a set of previously identified loci was specifically tested, but earlier reported results could not be validated. In conclusion, after a 5-day soymilk treatment, no major general epigenetic reprogramming in breast tissue could be found in this exploratory study

A non-parametric method to assess the presence of significant DNA-methylation in enrichment-based NGS data

Background: Over the last decade, DNA-methylation research has shifted from a gene-based approach to genome-wide analyses. DNA-methylation, featured by the enzymatic methylation of cytosines in a predominantly CpG-dinucleotide context, is an epigenetic process that is tightly associated with gene expression regulation. A novel generation of methodologies has enabled researchers to profile DNAmethylation in a genome-wide manner, e.g. by Methyl-Binding Domain (MBD)-based affinity purification followed by NGS (MBD-seq). While MBD-seq provides an excellent combination of sensitivity and cost-efficiency, it is featured by a set of bioinformatics and statistical challenges that complicates the subsequent data-analysis. The data-analysis pipeline for quantitative NGS applications typically consists of quality control, sequence mapping, data summary, data normalization and statistical analysis. Several of these steps require specific solutions for MBD-seq data: - Quality control is difficult yet necessary as sensitivity and specificity of enrichment procedures may vary. - Data summary is complicated by the lack of a functional unit for DNA-methylation, cf. the exon as unit for RNA-seq data summary. - Most data normalization procedures assume that the overall profiles are similar between samples, an assumption that is invalid for DNA-methylation. - The identification of significant enrichment is usually based on a Poisson background model. This model has several restrictions, resulting in suboptimal power. Therefore, we aimed at developing tailor-made solutions for each of these challenges. Methods: Captured fragments were paired-end sequenced (Illumina GAIIx). Sequenced reads were mapped on the human genome with BOWTIE. R, Perl, Java and MySQL were used to implement the different solutions. Results: We could demonstrate that the CpG-density profile of the sequenced fragments provides a solid basis for quality control, including the evaluation of sensitivity and specificity. A Map of the Human Methylome was constructed based on a large collection of MBD-seq profiles. This map consists of putatively independently methylated genomic regions, i.e. Methylation Cores (MCs), that can be used for data summary. For data normalization, a procedure called “Massively Enriched Loci Normalization" (MELON) was developed, based on the assumption that there exists a set of massively enriched loci of which the degree of DNA-methylation is similar between samples. A novel statistical framework, that provides higher power and sensitivity than the standard Poisson model has (partially) been developed, and can also be used for other enrichment based NGS applications. Conclusions: An optimized pipeline for high-quality MBD-seq data-analysis has largely been developed and implemented

Next-generation technologies and data analytical approaches for epigenomics

Epigenetics refers to the collection of heritable features that modulate the genome-environment interaction without being encoded in the actual DNA sequence. While being mitotically and sometimes even meiotically transmitted, epigenetic traits often demonstrate extensive flexibility. This allows cells to acquire diverse gene expression patterns during differentiation, but also to adapt to a changing environment. However, epigenetic alterations are not always beneficial to the organism, as they are, for example, frequently identified in human diseases such as cancer. Accurate and cost-efficient genome-scale profiling of epigenetic features is thus of major importance to pinpoint these epimutations, for example, to monitor the epigenetic impact of environmental exposure. Over the last decade, the field of epigenetics has been revolutionized by several innovative epigenomics technologies exactly addressing this need. In this review, we discuss and compare widely used next-generation methods to assess DNA methylation and hydroxymethylation, noncoding RNA expression, histone modifications, and nucleosome positioning. Although recent methods are typically based on second-generation sequencing, we also pay attention to still commonly used array- and PCR-based methods, and look forward to the additional advantages of single-molecule sequencing. As the current bottleneck in epigenomics research is the analysis rather than generation of data, the basic difficulties and problem-solving strategies regarding data preprocessing and statistical analysis are introduced for the different technologies. Finally, we also consider the complications associated with epigenomic studies of species with yet unsequenced genomes and possible solutions. 2013 Wiley Periodicals, Inc

SNP-guided identification of monoallelic DNA-methylation events from enrichment-based sequencing data

Monoallelic gene expression is typically initiated early in the development of an organism. Dysregulation of monoallelic gene expression has already been linked to several non-Mendelian inherited genetic disorders. In humans, DNA-methylation is deemed to be an important regulator of monoallelic gene expression, but only few examples are known. One important reason is that current, cost-affordable truly genome-wide methods to assess DNA-methylation are based on sequencing post-enrichment. Here, we present a new methodology based on classical population genetic theory, i.e. the Hardy-Weinberg theorem, that combines methylomic data from MethylCap-seq with associated SNP profiles to identify monoallelically methylated loci. Applied on 334 MethylCap-seq samples of very diverse origin, this resulted in the identification of 80 genomic regions featured by monoallelic DNA-methylation. Of these 80 loci, 49 are located in genic regions of which 25 have already been linked to imprinting. Further analysis revealed statistically significant enrichment of these loci in promoter regions, further establishing the relevance and usefulness of the method. Additional validation was done using both 14 whole-genome bisulfite sequencing data sets and 16 mRNA-seq data sets. Importantly, the developed approach can be easily applied to other enrichment-based sequencing technologies, like the ChIP-seq-based identification of monoallelic histone modifications

Exploratory analysis of the human breast DNA methylation profile upon soymilk exposure

Upon soy consumption, isoflavone metabolites attain bioactive concentrations in breast tissue possibly affecting health. Though in vitro epigenetic activity of soy metabolites has been described, the in vivo impact on the epigenome is largely unknown. Therefore, in this case-control study, the breast glandular tissue DNA methylome was explored in women undergoing an aesthetic breast reduction. After a run-in phase, 10 generally healthy Belgian or Dutch women received soymilk for 5 days. MethylCap-seq methylation profiles were compared with those of 10 matched controls. Isoflavones and their microbial metabolites were quantified in urine, serum, and glandular breast tissue (liquid chromatography-mass spectrometry) and 17β-estradiol in glandular breast tissue (immunoassay). Global DNA methylation levels were obtained for 6 cases and 5 controls using liquid chromatography-mass spectrometry. Although lower MethylCap-seq coverages were observed, mass spectrometry results and computational LINE-1 methylation analysis did not provide evidence supporting global methylation alterations upon treatment. At a false discovery rate of 0.05, no differentially methylated loci were identified. Moreover, a set of previously identified loci was specifically tested, but earlier reported results could not be validated. In conclusion, after a 5-day soymilk treatment, no major general epigenetic reprogramming in breast tissue could be found in this exploratory study.status: publishe

Genetic characterization of ESBL-producing and ciprofloxacin-resistant Escherichia coli from Belgian broilers and pigs

Background: The increasing number of infections caused by Escherichia coli resistant to clinically important antibiotics is a global concern for human and animal health. High overall levels of extended-spectrum beta-lactamase (ESBL)-producing and ciprofloxacin-resistant (ciproR) Escherichia coli in livestock are reported in Belgium. This cross-sectional study aimed to genotypically characterize and trace ESBL-and ciproR-E. coli of Belgian food-producing animals. Methods: A total of 798 fecal samples were collected in a stratified-random sampling design from Belgian broilers and sows. Consequently, 77 ESBL-E. coli and 84 ciproR-E. coli were sequenced using Illumina MiSeq. Minimum inhibitory concentration (MIC) for fluoroquinolones and cephalosporins were determined. Molecular in silico typing, resistance and virulence gene determination, and plasmid identification was performed. Scaffolds harboring ESBL or plasmid-mediated quinolone resistance (PMQR) genes were analyzed to detect mobile genetic elements (MGEs) and plasmid origins. Core genome allelic distances were used to determine genetic relationships among isolates. Results: A variety of E. coli sequence types (ST) (n = 63), resistance genes and virulence profiles was detected. ST10 was the most frequently encountered ST (8.1%, n = 13). The pandemic multidrug-resistant clone ST131 was not detected. Most farms harbored more than one ESBL type, with bla(CTX-M-1) (41.6% of ESBL-E. coli) being the most prevalent and bla(CTX M-15) (n = 3) being the least prevalent. PMQR genes (15.5%, n = 13) played a limited role in the occurrence of ciproR-E. coli. More importantly, sequential acquisition of mutations in quinolone resistance-determining regions (QRDR) of gyrA and parC led to increasing MICs for fluoroquinolones. GyrA S83L, D87N and ParC S80I mutations were strongly associated with high-level fluoroquinolone resistance. Genetically related isolates identified within the farms or among different farms highlight transmission of resistant E. coli or the presence of a common reservoir. IncI1-I(alpha) replicon type plasmids carried different ESBL genes (bla(CTX-M-1), bla(CTX-M-32) and bla(TEM-52C)). In addition, the detection of plasmid replicons with associated insertion sequence (IS) elements and ESBL/PMQR genes in different farms and among several STs (e.g., IncI1-I(alpha)/IncX3) underline that plasmid transmission could be another important contributor to transmission of resistance in these farms. Conclusion: Our findings reveal a multifaceted narrative of transmission pathways. These findings could be relevant in understanding and battling the problem of antibiotic resistance in farms