Blood cell counts often fail to report on immune processes occurring in remote tissues. Here we use immune cell type-specific methylation patterns in circulating cell-free DNA (cfDNA) for studying human immune cell dynamics. We characterized cfDNA released from specific immune cell types in healthy individuals (N=242), cross sectionally and longitudinally. Immune cfDNA levels had no individual steady state as opposed to blood cell counts, suggesting that cfDNA concentration reflects adjustment of cell survival to maintain homeostatic cell numbers. We also observed selective elevation of immune-derived cfDNA upon perturbations of immune homeostasis. Following influenza vaccination (N=92), B-cell-derived cfDNA levels increased prior to elevated B-cell counts and predicted efficacy of antibody production. Patients with Eosinophilic Esophagitis (N=21) and B-cell lymphoma (N=27) showed selective elevation of eosinophil and B-cell cfDNA respectively, which were undetectable by cell counts in blood. Immune-derived cfDNA provides a novel biomarker for monitoring immune responses to physiological and pathological processes that are not accessible using conventional methods.
All data generated or analyzed during this study are included in the manuscript and supporting files.The whole-genome bisulfite sequencing data reported in the paper, from 46 samples, is uploaded to GEO as described. The paper also reports data from PCR reactions that were analyzed by massively parallel sequencing. This is a very large set of data that is extremely low in information content and is of little interest to readers or even to people interested in replicating our results or interrogating them further. The key information (methylation status) in each sample is provided in the supplementary information, and we also uploaded the analysis algorithm and some sequence data. The entire set of raw sequencing data is available in the Dor lab to anyone interested.Please contact Prof. Yuval Dor firstname.lastname@example.org . All information will be shared. There is no need for any paperwork.Code is uploaded to GitHub as described in the paper.The methylation status of each marker in each sample is provided in Supplementary file 1. This data was used to generate the graphs shown in the paper. Sheets in this file indicate which figure they relate to.
No external funding was received for this work.
Human subjects: This study was conducted according to protocols approved by the Institutional Review Board at each study site (Hadassah Medical Center: HMO-14-0198. A Method to Diagnose Cell Death Based on Methylation Signature of Circulating Cell-Free DNA, Cininnati Children's Hospital: CCHMC IRB protocol 2008-0090: Eosinophils and Inflammation, an Expanded Study), with procedures performed in accordance with the Declaration of Helsinki. Blood and tissue samples were obtained from donors who have provided written informed consent. When using material from deceased organ donor those with legal authority were consented. Subject characteristics are presented in Supplementary File 1.
- Iwijn De Vlaminck
© 2021, Fox-Fisher et al.
This article is distributed under the terms of the Creative Commons Attribution License permitting unrestricted use and redistribution provided that the original author and source are credited.
Two epigenetic pathways of transcriptional repression, DNA methylation and Polycomb repressive complex 2 (PRC2) are known to regulate neuronal development and function. However, their respective contributions to brain maturation are unknown. We found that conditional loss of the de novo DNA methyltransferase Dnmt3a in mouse excitatory neurons altered expression of synapse-related genes, stunted synapse maturation, and impaired working memory and social interest. At the genomic level, loss of Dnmt3a abolished postnatal accumulation of CG and non-CG DNA methylation, leaving adult neurons with an unmethylated, fetal-like epigenomic pattern at ~222,000 genomic regions. The PRC2-associated histone modification, H3K27me3, increased at many of these sites. Our data support a dynamic interaction between two fundamental modes of epigenetic repression during postnatal maturation of excitatory neurons, which together confer robustness on neuronal regulation.
A single Dcp1-Dcp2 decapping enzyme targets diverse classes of yeast mRNAs for decapping-dependent 5' to 3' decay, but the molecular mechanisms controlling mRNA selectivity by the enzyme remain elusive. Through extensive genetic analyses we reveal that Dcp2 C-terminal domain cis-regulatory elements control decapping enzyme target specificity by orchestrating formation of distinct decapping complexes. Two Upf1-binding motifs direct the decapping enzyme to NMD substrates, a single Edc3-binding motif targets both Edc3 and Dhh1 substrates, and Pat1-binding leucine-rich motifs target Edc3 and Dhh1 substrates under selective conditions. Although it functions as a unique targeting component of specific complexes, Edc3 is a common component of multiple complexes. Scd6 and Xrn1 also have specific binding sites on Dcp2, allowing them to be directly recruited to decapping complexes. Collectively, our results demonstrate that Upf1, Edc3, Scd6, and Pat1 function as regulatory subunits of the holo-decapping enzyme, controlling both its substrate specificity and enzymatic activation.