Scalable in vitro production of defined mouse erythroblasts

Mouse embryonic stem cells (mESCs) can be manipulated in vitro to recapitulate the process of erythropoiesis, during which multipotent cells undergo lineage specification, differentiation and maturation to produce erythroid cells. Although useful for identifying specific progenitors and precursors, this system has not been fully exploited as a source of cells to analyse erythropoiesis. Here, we establish a protocol in which characterised erythroblasts can be isolated in a scalable manner from differentiated embryoid bodies (EBs). Using transcriptional and epigenetic analysis, we demonstrate that this system faithfully recapitulates normal primitive erythropoiesis and fully reproduces the effects of natural and engineered mutations seen in primary cells obtained from mouse models. We anticipate this system to be of great value in reducing the time and costs of generating and maintaining mouse lines in a number of research scenarios.

Community-wide epigenetics provides novel perspectives on the ecology and evolution of marine microbiome

DNA methylation in prokaryotes is involved in many different cellular processes including cell cycle regulation and defense against viruses. To date, most prokaryotic methylation systems have been studied in culturable microorganisms, resulting in a limited understanding of DNA methylation from a microbial ecology perspective. Here, we analyze the distribution patterns of several microbial epigenetics marks in the ocean microbiome through genome-centric metagenomics across all domains of life. We show that overall, DNA methylation can readily be detected across dominant oceanic bacterial, archaeal, and viral populations, and microbial epigenetic changes correlate with population differentiation. Furthermore, our genome-wide epigenetic analysis of Pelagibacter suggests that GANTC, a DNA methyltransferase target motif, is related to the cell cycle and is affected by environmental conditions. Yet, the presence of this motif also partitions the phylogeny of the Pelagibacter phages, possibly hinting at a competitive co-evolutionary history and multiple effects of a single methylation mark.

In silico approach to understand epigenetics of POTEE in ovarian cancer

Ovarian cancer is the third leading cause of cancer-related deaths in India. Epigenetics mechanisms seemingly plays an important role in ovarian cancer. This paper highlights the crucial epigenetic changes that occur in POTEE that get hypomethylated in ovarian cancer. We utilized the POTEE paralog mRNA sequence to identify major motifs and also performed its enrichment analysis. We identified 6 motifs of varying lengths, out of which only three motifs, including CTTCCAGCAGATGTGGATCA, GGAACTGCC, and CGCCACATGCAGGC were most likely to be present in the nucleotide sequence of POTEE. By enrichment and occurrences identification analyses, we rectified the best match motif as CTTCCAGCAGATGT. Since there is no experimentally verified structure of POTEE paralog, thus, we predicted the POTEE structure using an automated workflow for template-based modeling using the power of a deep neural network. Additionally, to validate our predicted model we used AlphaFold predicted POTEE structure and observed that the residual stretch starting from 237-958 had a very high confidence per residue. Furthermore, POTEE predicted model stability was evaluated using replica exchange molecular dynamic simulation for 50 ns. Our network-based epigenetic analysis discerns only 10 highly significant, direct, and physical associators of POTEE. Our finding aims to provide new insights about the POTEE paralog.

Multiplexed Single-Molecule Epigenetic Analysis of Plasma-Isolated Nucleosomes for Cancer Diagnostics

The analysis of cell-free DNA (cfDNA) in plasma represents a rapidly advancing field in medicine, providing information on pathological processes in the body. Blood cfDNA is in the form of nucleosomes, which maintain their tissue- and cancer-specific epigenetic state. We developed EPINUC, a single-molecule multi-parametric assay to comprehensively profile the Epigenetics of Plasma Isolated Nucleosomes, DNA methylation and cancer-specific protein biomarkers. Our system allows high-resolution detection of six active and repressive histone modifications, their ratios and combinatorial patterns, on millions of individual nucleosomes by single-molecule imaging. In addition, it provides sensitive and quantitative data on plasma proteins, including detection of non-secreted tumor-specific proteins such as mutant p53. Applying this analysis to a cohort of plasma samples detected colorectal cancer at high accuracy and sensitivity, even at early stages. Finally, combining EPINUC with direct single-molecule DNA sequencing revealed the tissue-of-origin of the tumor. EPINUC provides multi-layered clinical-relevant information from limited liquid biopsy material, establishing a novel approach for cancer diagnostics.

Comparative epigenetic analysis of tumour initiating cells and syngeneic EPSC-derived neural stem cells in glioblastoma

Epigenetic mechanisms which play an essential role in normal developmental processes, such as self-renewal and fate specification of neural stem cells (NSC) are also responsible for some of the changes in the glioblastoma (GBM) genome. Here we develop a strategy to compare the epigenetic and transcriptional make-up of primary GBM cells (GIC) with patient-matched expanded potential stem cell (EPSC)-derived NSC (iNSC). Using a comparative analysis of the transcriptome of syngeneic GIC/iNSC pairs, we identify a glycosaminoglycan (GAG)-mediated mechanism of recruitment of regulatory T cells (Tregs) in GBM. Integrated analysis of the transcriptome and DNA methylome of GBM cells identifies druggable target genes and patient-specific prediction of drug response in primary GIC cultures, which is validated in 3D and in vivo models. Taken together, we provide a proof of principle that this experimental pipeline has the potential to identify patient-specific disease mechanisms and druggable targets in GBM.

Precise Epigenetic Analysis Using Targeted Bisulfite Genomic Sequencing Distinguishes FSHD1, FSHD2, and Healthy Subjects

The true prevalence of facioscapulohumeral muscular dystrophy (FSHD) is unknown due to difficulties with accurate clinical evaluation and the complexities of current genetic diagnostics. Interestingly, all forms of FSHD are linked to epigenetic changes in the chromosome 4q35 D4Z4 macrosatellite, suggesting that epigenetic analysis could provide an avenue for sequence-based FSHD diagnostics. However, studies assessing DNA methylation at the FSHD locus have produced conflicting results; thus, the utility of this technique as an FSHD diagnostic remains controversial. Here, we critically compared two protocols for epigenetic analysis of the FSHD region using bisulfite genomic sequencing: Jones et al., that contends to be individually diagnostic for FSHD1 and FSHD2, and Gaillard et al., that can identify some changes in DNA methylation levels between groups of clinically affected FSHD and healthy subjects, but is not individually diagnostic for any form of FSHD. We performed both sets of assays on the same genetically confirmed samples and showed that this discrepancy was due strictly to differences in amplicon specificity. We propose that the epigenetic status of the FSHD-associated D4Z4 arrays, when accurately assessed, is a diagnostic for genetic FSHD and can readily distinguish between healthy, FSHD1 and FSHD2. Thus, epigenetic diagnosis of FSHD, which can be performed on saliva DNA, will greatly increase accessibility to FSHD diagnostics for populations around the world.