Single molecule-level detection and long read-based phasing of epigenetic variations in bacterial methylomes

Comprehensive genome-wide analyses of bacterial DNA methylation have not been possible until the recent advent of single molecule, real-time (SMRT) sequencing. This technology enables the direct detection of N6-methyladenine (6mA) and 4-methylcytosine (4mC) at single nucleotide resolution on a genome-wide scale. The distributions of these two major types of DNA methylation, along with 5-methylcytosine (5mC), comprise the bacterial methylome, some rare exceptions notwithstanding. SMRT sequencing has already revealed marked diversity in bacterial methylomes as well as the existence of heterogeneity of methylation in cells in single bacterial colonies, where such ‘epigenetic’ variation can enable bacterial populations to rapidly adapt to changing conditions. However, current methods for studying bacterial methylomes using SMRT sequencing mainly rely on population-level summaries that do not provide the single-cell resolution necessary for dissecting the epigenetic heterogeneity in bacterial populations. Here, we present a novel SMRT sequencing-based framework, consisting of two complementary methods, for single molecule-level detection of DNA methylation and assessment of methyltransferase activity through single molecule-level long read-based epigenetic phasing. Using seven bacterial strains and integrating data from SMRT and Illumina sequencing, we show that our method yields significantly improved resolution compared to existing population-level methods, and reveals several distinct types of epigenetic heterogeneity. Our approach enables new investigations of the complex architecture and dynamics of bacterial methylomes and provides a powerful new tool for the study of bacterial epigenetic control.

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DNA methylation patterns in bacteria of the genus Ensifer during free-living growth and during nitrogen-fixing symbiosis with Medicago spp

10.1101/2021.03.08.434416 ◽

2021 ◽

Author(s):

George C. diCenzo ◽

Lisa Cangioli ◽

Quentin Nicoud ◽

Janis H.T. Cheng ◽

Matthew J. Blow ◽

...

Keyword(s):

Cell Cycle ◽

Dna Methylation ◽

Nitrogen Fixation ◽

Single Molecule ◽

Dna Sequences ◽

Regulatory Mechanism ◽

Terminal Differentiation ◽

Nitrogen Fixing ◽

Genome Wide ◽

A Genome

ABSTRACTMethylation of specific genomic DNA sequences is ubiquitous in bacteria and has known roles in immunity and regulation of cellular processes, such as the cell cycle. Here, we explored DNA methylation in bacteria of the genus Ensifer, including its potential role in regulating the process of terminal differentiation occurring during nitrogen-fixing symbiosis with legumes. Using single-molecule real-time sequencing, six unique genome-wide methylated motifs were identified across four Ensifer strains, five of which were strain-specific. These five motifs were nearly fully methylated across the genomes in all tested conditions, and they were not enriched in the promoter regions of symbiosis, carbon source, or cell cycle-regulated genes, suggesting that most DNA methylation is not a major regulatory mechanism in the genus Ensifer. Only the GANTC motif, recognized by the cell cycle-regulated CcrM methyltransferase, was methylated in all strains. In actively dividing cells, methylation of GANTC motifs increased progressively from the ori to ter region in each replicon, in agreement with a cell cycle-dependent regulation of CcrM. The GANTC methylation profile transited into a genome-wide pattern of near full methylation in the early stage of symbiotic differentiation, followed by a progressive decrease in methylation from the ori to ter regions of fully differentiated symbiotic bacteria. This is evidence of a dysregulated and constitutive CcrM activity during terminal differentiation, which we suggest is a driving factor for endoreduplication of terminally differentiated bacteroids.IMPORTANCENitrogen fixation by bacteria (rhizobia) in symbiosis with legumes is economically and ecologically important. In some cases, the symbiosis involves a complex bacterial transformation, known as terminal differentiation, that includes major shifts in the transcriptome and cell cycle. Epigenetic regulation via DNA methylation is an important regulatory mechanism contributing to the biology of diverse bacteria; however, the roles of DNA methylation in rhizobia and symbiotic nitrogen fixation have been poorly investigated. We show that aside from cell cycle regulation, DNA methylation is unlikely to be a major mechanism of transcriptional regulation in rhizobia and non-rhizobia of the genus Ensifer. However, we found strong evidence that the cell cycle methyltransferase CcrM is dysregulated during symbiosis, which may be a key factor driving the cell cycle switch in terminal differentiation and the establishment of effective rhizobium – legume symbioses. These novel results advance our understanding of this highly important, yet incompletely understood process.

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The DNA methylation landscape in cancer

Essays in Biochemistry ◽

10.1042/ebc20190037 ◽

2019 ◽

Vol 63 (6) ◽

pp. 797-811 ◽

Cited By ~ 12

Author(s):

Ksenia Skvortsova ◽

Clare Stirzaker ◽

Phillippa Taberlay

Keyword(s):

Dna Methylation ◽

Dna Hydroxymethylation ◽

Disease States ◽

Genome Wide ◽

A Genome ◽

Long Read ◽

Profiling Techniques ◽

Wide Scale ◽

Improved Methods ◽

Methylation Profiling

Abstract As one of the most abundant and well-studied epigenetic modifications, DNA methylation plays an essential role in normal development and cellular biology. Global alterations to the DNA methylation landscape contribute to alterations in the transcriptome and deregulation of cellular pathways. Indeed, improved methods to study DNA methylation patterning and dynamics at base pair resolution and across individual DNA molecules on a genome-wide scale has highlighted the scope of change to the DNA methylation landscape in disease states, particularly during tumorigenesis. More recently has been the development of DNA hydroxymethylation profiling techniques, which allows differentiation between 5mC and 5hmC profiles and provides further insights into DNA methylation dynamics and remodeling in tumorigenesis. In this review, we describe the distribution of DNA methylation and DNA hydroxymethylation in different genomic contexts, first in normal cells, and how this is altered in cancer. Finally, we discuss DNA methylation profiling technologies and the most recent advances in single-cell methods, bisulfite-free approaches and ultra-long read sequencing techniques.

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The NCTC 3000 project: development and optimization of DNA extraction methods for 3000 different bacterial strains suitable for long-read PacBio SMRT sequencing

10.26226/morressier.56d5ba27d462b80296c95fcb ◽

2016 ◽

Author(s):

Mohammed Fazal

Keyword(s):

Dna Extraction ◽

Extraction Methods ◽

Project Development ◽

Bacterial Strains ◽

Smrt Sequencing ◽

Long Read ◽

Dna Extraction Methods ◽

Pacbio Smrt Sequencing

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MBRS-47. RAPID MOLECULAR SUBGROUPING OF MEDULLOBLASTOMA BASED ON DNA METHYLATION BY NANOPORE SEQUENCING

Neuro-Oncology ◽

10.1093/neuonc/noaa222.556 ◽

2020 ◽

Vol 22 (Supplement_3) ◽

pp. iii406-iii406

Author(s):

Julien Masliah-Planchon ◽

Elodie Girard ◽

Philipp Euskirchen ◽

Christine Bourneix ◽

Delphine Lequin ◽

...

Keyword(s):

Dna Methylation ◽

Single Molecule ◽

Nanopore Sequencing ◽

Molecular Subgroup ◽

Group Assignment ◽

Group 4 ◽

Methylation Assay ◽

Tumor Group ◽

Long Read ◽

Group 3

Abstract Medulloblastoma (MB) can be classified into four molecular subgroups (WNT group, SHH group, group 3, and group 4). The gold standard of assignment of molecular subgroup through DNA methylation profiling uses Illumina EPIC array. However, this tool has some limitation in terms of cost and timing, in order to get the results soon enough for clinical use. We present an alternative DNA methylation assay based on nanopore sequencing efficient for rapid, cheaper, and reliable subgrouping of clinical MB samples. Low-depth whole genome with long-read single-molecule nanopore sequencing was used to simultaneously assess copy number profile and MB subgrouping based on DNA methylation. The DNA methylation data generated by Nanopore sequencing were compared to a publicly available reference cohort comprising over 2,800 brain tumors including the four subgroups of MB (Capper et al. Nature; 2018) to generate a score that estimates a confidence with a tumor group assignment. Among the 24 MB analyzed with nanopore sequencing (six WNT, nine SHH, five group 3, and four group 4), all of them were classified in the appropriate subgroup established by expression-based Nanostring subgrouping. In addition to the subgrouping, we also examine the genomic profile. Furthermore, all previously identified clinically relevant genomic rearrangements (mostly MYC and MYCN amplifications) were also detected with our assay. In conclusion, we are confirming the full reliability of nanopore sequencing as a novel rapid and cheap assay for methylation-based MB subgrouping. We now plan to implement this technology to other embryonal tumors of the central nervous system.

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DNA Methylation at ATP11A cg11702988 Is a Biomarker of Lung Disease Severity in Cystic Fibrosis: A Longitudinal Study

Genes ◽

10.3390/genes12030441 ◽

2021 ◽

Vol 12 (3) ◽

pp. 441

Author(s):

Fanny Pineau ◽

Davide Caimmi ◽

Sylvie Taviaux ◽

Maurane Reveil ◽

Laura Brosseau ◽

...

Keyword(s):

Cystic Fibrosis ◽

Dna Methylation ◽

Clinical Trials ◽

Lung Disease ◽

Disease Severity ◽

Genome Wide ◽

A Genome ◽

Lung Disease Severity ◽

Epigenetic Biomarker

Cystic fibrosis (CF) is a chronic genetic disease that mainly affects the respiratory and gastrointestinal systems. No curative treatments are available, but the follow-up in specialized centers has greatly improved the patient life expectancy. Robust biomarkers are required to monitor the disease, guide treatments, stratify patients, and provide outcome measures in clinical trials. In the present study, we outline a strategy to select putative DNA methylation biomarkers of lung disease severity in cystic fibrosis patients. In the discovery step, we selected seven potential biomarkers using a genome-wide DNA methylation dataset that we generated in nasal epithelial samples from the MethylCF cohort. In the replication step, we assessed the same biomarkers using sputum cell samples from the MethylBiomark cohort. Of interest, DNA methylation at the cg11702988 site (ATP11A gene) positively correlated with lung function and BMI, and negatively correlated with lung disease severity, P. aeruginosa chronic infection, and the number of exacerbations. These results were replicated in prospective sputum samples collected at four time points within an 18-month period and longitudinally. To conclude, (i) we identified a DNA methylation biomarker that correlates with CF severity, (ii) we provided a method to easily assess this biomarker, and (iii) we carried out the first longitudinal analysis of DNA methylation in CF patients. This new epigenetic biomarker could be used to stratify CF patients in clinical trials.

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A Genome-Wide Integrative Association Study of DNA Methylation and Gene Expression Data and Later Life Cognitive Functioning in Monozygotic Twins

Frontiers in Neuroscience ◽

10.3389/fnins.2020.00233 ◽

2020 ◽

Vol 14 ◽

Cited By ~ 1

Author(s):

Mette Soerensen ◽

Dominika Marzena Hozakowska-Roszkowska ◽

Marianne Nygaard ◽

Martin J. Larsen ◽

Veit Schwämmle ◽

...

Keyword(s):

Gene Expression ◽

Dna Methylation ◽

Cognitive Functioning ◽

Association Study ◽

Gene Expression Data ◽

Monozygotic Twins ◽

Later Life ◽

Expression Data ◽

Genome Wide ◽

A Genome

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A genome-wide screen for differentially methylated long noncoding RNAs identified that lncAC007255.8 is regulated by promoter DNA methylation in Beas-2B cells malignantly transformed by NNK

Toxicology Letters ◽

10.1016/j.toxlet.2021.04.013 ◽

2021 ◽

Author(s):

Enzhao Chen ◽

Jiaxin Zhou ◽

Enwu Xu ◽

Cheng Zhang ◽

Jiayu Liu ◽

...

Keyword(s):

Dna Methylation ◽

Noncoding Rnas ◽

Long Noncoding Rnas ◽

Genome Wide ◽

A Genome ◽

Promoter Dna Methylation ◽

Promoter Dna

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Fast and efficient Rmap assembly using the Bi-labelled de Bruijn graph

Algorithms for Molecular Biology ◽

10.1186/s13015-021-00182-9 ◽

2021 ◽

Vol 16 (1) ◽

Author(s):

Kingshuk Mukherjee ◽

Massimiliano Rossi ◽

Leena Salmela ◽

Christina Boucher

Keyword(s):

Single Molecule ◽

De Bruijn Graph ◽

Anabas Testudineus ◽

E Coli ◽

Genome Wide ◽

A Genome ◽

De Bruijn ◽

Optical Maps ◽

Definition Of ◽

Numeric Representation

AbstractGenome wide optical maps are high resolution restriction maps that give a unique numeric representation to a genome. They are produced by assembling hundreds of thousands of single molecule optical maps, which are called Rmaps. Unfortunately, there are very few choices for assembling Rmap data. There exists only one publicly-available non-proprietary method for assembly and one proprietary software that is available via an executable. Furthermore, the publicly-available method, by Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006), follows the overlap-layout-consensus (OLC) paradigm, and therefore, is unable to scale for relatively large genomes. The algorithm behind the proprietary method, Bionano Genomics’ Solve, is largely unknown. In this paper, we extend the definition of bi-labels in the paired de Bruijn graph to the context of optical mapping data, and present the first de Bruijn graph based method for Rmap assembly. We implement our approach, which we refer to as rmapper, and compare its performance against the assembler of Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006) and Solve by Bionano Genomics on data from three genomes: E. coli, human, and climbing perch fish (Anabas Testudineus). Our method was able to successfully run on all three genomes. The method of Valouev et al. (Proc Natl Acad Sci USA 103(43):15770–15775, 2006) only successfully ran on E. coli. Moreover, on the human genome rmapper was at least 130 times faster than Bionano Solve, used five times less memory and produced the highest genome fraction with zero mis-assemblies. Our software, rmapper is written in C++ and is publicly available under GNU General Public License at https://github.com/kingufl/Rmapper.

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Stable DNMT3L overexpression in SH-SY5Y neurons recreates a facet of the genome-wide Down syndrome DNA methylation signature

Epigenetics & Chromatin ◽

10.1186/s13072-021-00387-7 ◽

2021 ◽

Vol 14 (1) ◽

Author(s):

Benjamin I. Laufer ◽

J. Antonio Gomez ◽

Julia M. Jianu ◽

Janine M. LaSalle

Keyword(s):

Dna Methylation ◽

Down Syndrome ◽

Neuronal Differentiation ◽

Molecular Mechanisms ◽

Cpg Island ◽

Differential Methylation ◽

Chromosome 21 ◽

Pairwise Comparisons ◽

Genome Wide ◽

A Genome

Abstract Background Down syndrome (DS) is characterized by a genome-wide profile of differential DNA methylation that is skewed towards hypermethylation in most tissues, including brain, and includes pan-tissue differential methylation. The molecular mechanisms involve the overexpression of genes related to DNA methylation on chromosome 21. Here, we stably overexpressed the chromosome 21 gene DNA methyltransferase 3L (DNMT3L) in the human SH-SY5Y neuroblastoma cell line and assayed DNA methylation at over 26 million CpGs by whole genome bisulfite sequencing (WGBS) at three different developmental phases (undifferentiated, differentiating, and differentiated). Results DNMT3L overexpression resulted in global CpG and CpG island hypermethylation as well as thousands of differentially methylated regions (DMRs). The DNMT3L DMRs were skewed towards hypermethylation and mapped to genes involved in neurodevelopment, cellular signaling, and gene regulation. Consensus DNMT3L DMRs showed that cell lines clustered by genotype and then differentiation phase, demonstrating sets of common genes affected across neuronal differentiation. The hypermethylated DNMT3L DMRs from all pairwise comparisons were enriched for regions of bivalent chromatin marked by H3K4me3 as well as differentially methylated sites from previous DS studies of diverse tissues. In contrast, the hypomethylated DNMT3L DMRs from all pairwise comparisons displayed a tissue-specific profile enriched for regions of heterochromatin marked by H3K9me3 during embryonic development. Conclusions Taken together, these results support a mechanism whereby regions of bivalent chromatin that lose H3K4me3 during neuronal differentiation are targeted by excess DNMT3L and become hypermethylated. Overall, these findings demonstrate that DNMT3L overexpression during neurodevelopment recreates a facet of the genome-wide DS DNA methylation signature by targeting known genes and gene clusters that display pan-tissue differential methylation in DS.

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