Deconvolution of cellular subsets in human tissue based on targeted DNA methylation analysis at individual CpG sites

Immune cell distribution and DNA methylation signatures differ between tumor and stroma enriched compartment in pancreatic ductal adenocarcinoma

The presence of abundant tumor stroma is a prominent characteristic of pancreatic ductal adenocarcinomas (PDAC) that potentially influences disease progression and therapy response. This study aims to investigate immune cell infiltration and epigenetic profiles in tumor cell enriched ("Tumor") and stroma cell enriched ("Stroma") regions within human PDAC tissue samples. By comparing those regions, we identified 25,410 differentially methylated positions (DMPs) distributed across 6,963 unique genes. Pathway enrichment analysis using the top 2,000 DMPs that were either hyper- or hypomethylated indicated that immune response pathways and the estrogen receptor pathway are epigenetically dysregulated in Tumor and Stroma regions, respectively. In terms of immune cell infiltration, we observed overall low levels of T cells in both regions. In Tumor regions however, occurrence of tumor-associated macrophages (TAMs) was higher than in Stroma regions (p = 0.02) concomitant with a dualistic distribution that stratifies PDAC patients into those with high and low TAM infiltration. By categorizing TAM levels into quartiles, our analysis revealed that PDAC patients with more than 1,515 TAMs per mm² exhibited significantly shorter overall survival (p = 0.036). Our data suggest that variations in inflammatory characteristics between the Tumor and Stroma defined compartments of PDAC may primarily stem from the presence of macrophages rather than lymphocytes. The abundance of TAMs within regions enriched with tumor cells correlates with patient survival, underscoring the potential significance of exploring therapeutic interventions targeting TAMs. Furthermore, directing attention towards the estrogen receptor pathway may represent a promising strategy to address the stroma cell component within the PDAC tumor microenvironment.

Inflammatory breast cancer microenvironment repertoire based on DNA methylation data deconvolution reveals actionable targets to enhance the treatment efficacy

BACKGROUND

Although the clinical signs of inflammatory breast cancer (IBC) resemble acute inflammation, the role played by infiltrating immune and stromal cells in this aggressive disease is uncharted. The tumor microenvironment (TME) presents molecular alterations, such as epimutations, prior to morphological abnormalities. These changes affect the distribution and the intricate communication between the TME components related to cancer prognosis and therapy response. Herein, we explored the global DNA methylation profile of IBC and surrounding tissues to estimate the microenvironment cellular composition and identify epigenetically dysregulated markers.

METHODS

We used the HiTIMED algorithm to deconvolve the bulk DNA methylation data of 24 IBC and six surrounding non-tumoral tissues (SNT) (GSE238092) and determine their cellular composition. The prognostic relevance of cell types infiltrating IBC and their relationship with clinicopathological variables were investigated. CD34 (endothelial cell marker) and CD68 (macrophage marker) immunofluorescence staining was evaluated in an independent set of 17 IBC and 16 non-IBC samples.

RESULTS

We found lower infiltration of endothelial, stromal, memory B, dendritic, and natural killer cells in IBC than in SNT samples. Higher endothelial cell (EC) and stromal cell content were related to better overall survival. EC proportions positively correlated with memory B and memory CD8+ T infiltration in IBC. Immune and EC markers exhibited distinct DNA methylation profiles between IBC and SNT samples, revealing hypermethylated regions mapped to six genes (CD40, CD34, EMCN, HLA-G, PDPN, and TEK). We identified significantly higher CD34 and CD68 protein expression in IBC compared to non-IBC.

CONCLUSIONS

Our findings underscored cell subsets that distinguished patients with better survival and dysregulated markers potentially actionable through combinations of immunotherapy and epigenetic drugs.

Validating reference-based algorithms to determine cell-type heterogeneity in ovarian cancer DNA methylation studies

Information about cell composition in tissue samples is crucial for biomarker discovery and prognosis. Specifically, cancer tissue samples present challenges in deconvolution studies due to mutations and genetic rearrangements. Here, we optimized a robust, DNA methylation-based protocol, to be used for deconvolution of ovarian cancer samples. We compared several state-of-the-art methods (HEpiDISH, MethylCIBERSORT and ARIC) and validated the proposed protocol in an in-silico mixture and in an external dataset containing samples from ovarian cancer patients and controls. The deconvolution protocol we eventually implemented is based on MethylCIBERSORT. Comparing deconvolution methods, we paid close attention to the role of a reference panel. We postulate that a possibly high number of samples (in our case: 247) should be used when building a reference panel to ensure robustness and to compensate for biological and technical variation between samples. Subsequently, we tested the performance of the validated protocol in our own study cohort, consisting of 72 patients with malignant and benign ovarian disease as well as in five external cohorts. In conclusion, we refined and validated a reference-based algorithm to determine cell type composition of ovarian cancer tissue samples to be used in cancer biology studies in larger cohorts.

Benchmark of cellular deconvolution methods using a multi-assay reference dataset from postmortem human prefrontal cortex

Background

Cellular deconvolution of bulk RNA-sequencing (RNA-seq) data using single cell or nuclei RNA-seq (sc/snRNA-seq) reference data is an important strategy for estimating cell type composition in heterogeneous tissues, such as human brain. Computational methods for deconvolution have been developed and benchmarked against simulated data, pseudobulked sc/snRNA-seq data, or immunohistochemistry reference data. A major limitation in developing improved deconvolution algorithms has been the lack of integrated datasets with orthogonal measurements of gene expression and estimates of cell type proportions on the same tissue sample. Deconvolution algorithm performance has not yet been evaluated across different RNA extraction methods (cytosolic, nuclear, or whole cell RNA), different library preparation types (mRNA enrichment vs. ribosomal RNA depletion), or with matched single cell reference datasets.

Results

A rich multi-assay dataset was generated in postmortem human dorsolateral prefrontal cortex (DLPFC) from 22 tissue blocks. Assays included spatially-resolved transcriptomics, snRNA-seq, bulk RNA-seq (across six library/extraction RNA-seq combinations), and RNAScope/Immunofluorescence (RNAScope/IF) for six broad cell types. The Mean Ratio method, implemented in the DeconvoBuddies R package, was developed for selecting cell type marker genes. Six computational deconvolution algorithms were evaluated in DLPFC and predicted cell type proportions were compared to orthogonal RNAScope/IF measurements.

Conclusions

Bisque and hspe were the most accurate methods, were robust to differences in RNA library types and extractions. This multi-assay dataset showed that cell size differences, marker genes differentially quantified across RNA libraries, and cell composition variability in reference snRNA-seq impact the accuracy of current deconvolution methods.

Substrate elasticity does not impact DNA methylation changes during differentiation of pluripotent stem cells

BACKGROUND AIMS

Substrate elasticity may direct cell-fate decisions of stem cells. However, it is largely unclear how matrix stiffness affects the differentiation of induced pluripotent stem cells (iPSCs) and whether this is also reflected by epigenetic modifications.

METHODS

We cultured iPSCs on tissue culture plastic (TCP) and polydimethylsiloxane (PDMS) with different Young's modulus (0.2 kPa, 16 kPa or 64 kPa) to investigate the sequel on growth and differentiation toward endoderm, mesoderm and ectoderm.

RESULTS

Immunofluorescence and gene expression of canonical differentiation markers were hardly affected by the substrates. Notably, when we analyzed DNA methylation profiles of undifferentiated iPSCs or after three-lineage differentiation, we did not see any significant differences on the three different PDMS elasticities. Only when we compared DNA methylation profiles on PDMS-substrates versus TCP we did observe epigenetic differences, particularly on mesodermal differentiation.

CONCLUSIONS

Stiffness of PDMS substrates did not affect directed differentiation of iPSCs, whereas the moderate epigenetic differences on TCP might also be attributed to other chemical parameters.

Computational deconvolution of DNA methylation data from mixed DNA samples

In this review, we provide a comprehensive overview of the different computational tools that have been published for the deconvolution of bulk DNA methylation (DNAm) data. Here, deconvolution refers to the estimation of cell-type proportions that constitute a mixed sample. The paper reviews and compares 25 deconvolution methods (supervised, unsupervised or hybrid) developed between 2012 and 2023 and compares the strengths and limitations of each approach. Moreover, in this study, we describe the impact of the platform used for the generation of methylation data (including microarrays and sequencing), the applied data pre-processing steps and the used reference dataset on the deconvolution performance. Next to reference-based methods, we also examine methods that require only partial reference datasets or require no reference set at all. In this review, we provide guidelines for the use of specific methods dependent on the DNA methylation data type and data availability.

Temporal change of DNA methylation subclasses between matched newly diagnosed and recurrent glioblastoma

The longitudinal transition of phenotypes is pivotal in glioblastoma treatment resistance and DNA methylation emerged as an important tool for classifying glioblastoma phenotypes. We aimed to characterize DNA methylation subclass heterogeneity during progression and assess its clinical impact. Matched tissues from 47 glioblastoma patients were subjected to DNA methylation profiling, including CpG-site alterations, tissue and serum deconvolution, mass spectrometry, and immunoassay. Effects of clinical characteristics on temporal changes and outcomes were studied. Among 47 patients, 8 (17.0%) had non-matching classifications at recurrence. In the remaining 39 cases, 28.2% showed dominant DNA methylation subclass transitions, with 72.7% being a mesenchymal subclass. In general, glioblastomas with a subclass transition showed upregulated metabolic processes. Newly diagnosed glioblastomas with mesenchymal transition displayed increased stem cell-like states and decreased immune components at diagnosis and exhibited elevated immune signatures and cytokine levels in serum. In contrast, tissue of recurrent glioblastomas with mesenchymal transition showed increased immune components but decreased stem cell-like states. Survival analyses revealed comparable outcomes for patients with and without subclass transitions. This study demonstrates a temporal heterogeneity of DNA methylation subclasses in 28.2% of glioblastomas, not impacting patient survival. Changes in cell state composition associated with subclass transition may be crucial for recurrent glioblastoma targeted therapies.

Targeted DNA Methylation Analysis Facilitates Leukocyte Counts in Dried Blood Samples

BACKGROUND

Cell-type specific DNA methylation (DNAm) can be employed to determine the numbers of leukocyte subsets in blood. In contrast to conventional methods for leukocyte counts, which are based on cellular morphology or surface marker protein expression, the cellular deconvolution based on DNAm levels is applicable for frozen or dried blood. Here, we further enhanced targeted DNAm assays for leukocyte counts in clinical application.

METHODS

DNAm profiles of 40 different studies were compiled to identify CG dinucleotides (CpGs) with cell-type specific DNAm using a computational framework, CimpleG. DNAm levels at these CpGs were then measured with digital droplet PCR in venous blood from 160 healthy donors and 150 patients with various hematological disorders. Deconvolution was further validated with venous blood (n = 75) and capillary blood (n = 31) that was dried on Whatman paper or on Mitra microsampling devices.

RESULTS

In venous blood, automated cell counting or flow cytometry correlated well with epigenetic estimates of relative leukocyte counts for granulocytes (r = 0.95), lymphocytes (r = 0.97), monocytes (r = 0.82), CD4 T cells (r = 0.84), CD8 T cells (r = 0.94), B cells (r = 0.96), and NK cells (r = 0.72). Similar correlations and precisions were achieved for dried blood samples. Spike-in with a reference plasmid enabled accurate epigenetic estimation of absolute leukocyte counts from dried blood samples, correlating with conventional venous (r = 0.86) and capillary (r = 0.80) blood measurements.

CONCLUSIONS

The advanced selection of cell-type specific CpGs and utilization of digital droplet PCR analysis provided accurate epigenetic blood counts. Analysis of dried blood facilitates self-sampling with a finger prick, thereby enabling easier accessibility to testing.

Mouse methylation profiles for leukocyte cell types, and estimation of leukocyte fractions in inflamed gastrointestinal DNA samples

Precise analysis of tissue DNA and RNA samples is often hampered by contaminating non-target cells whose amounts are highly variable. DNA methylation profiles are specific to cell types, and can be utilized for assessment of the fraction of such contaminating non-target cells. Here, we aimed 1) to identify methylation profiles specific to multiple types of mouse leukocytes, and 2) to estimate the fraction of leukocytes infiltrating inflamed tissues using DNA samples. First, genome-wide DNA methylation analysis was conducted for three myeloid-lineage cells and four lymphoid-lineage cells isolated by fluorescence-activated cell sorting after magnetic-activated cell sorting from leukocytes in the spleen. Clustering analysis using CpG sites within enhancers separated the three myeloid-lineage cells and four lymphoid-lineage cells while that using promoter CpG islands (TSS200CGIs) did not. Among the 266,108 CpG sites analyzed, one CpG site was specifically hypermethylated (β value ≥ 0.7) in B cells, and four, seven, 183, and 34 CpG sites were specifically hypomethylated (β value < 0.2) in CD4+ T cells, CD8+ T cells, B cells, and NK cells, respectively. Importantly, cell type-specific hypomethylated CpG sites were located at genes involved in cell type-specific biological functions. Then, marker CpG sites to estimate the leukocyte fraction in a tissue with leukocyte infiltration were selected, and an estimation algorithm was established. The fractions of infiltrating leukocytes were estimated to be 1.6-12.4% in the stomach (n = 10) with Helicobacter pylori-induced inflammation and 1.5-4.3% in the colon with dextran sulfate sodium-induced colitis (n = 4), and the fractions were highly correlated with those estimated histologically using Cd45-stained tissue sections [R = 0.811 (p = 0.004)]. These results showed that mouse methylation profiles at CpG sites within enhancers reflected leukocyte cell lineages, and the use of marker CpG sites successfully estimated the leukocyte fraction in inflamed gastric and colon tissues.

Epigenetic profiling reveals a strong association between lack of 5-ALA fluorescence and EGFR amplification in IDH-wildtype glioblastoma

Background

5-aminolevulinic acid (5-ALA) fluorescence-guided resection increases the percentage of complete CNS tumor resections and improves the progression-free survival of IDH-wildtype glioblastoma patients. A small subset of IDH-wildtype glioblastoma shows no 5-ALA fluorescence. An explanation for these cases is missing. In this study, we used DNA methylation profiling to further characterize non-fluorescent glioblastomas.

Methods

Patients with newly diagnosed and recurrent IDH-wildtype glioblastoma that underwent surgery were analyzed. The intensity of intraoperative 5-ALA fluorescence was categorized as non-visible or visible. DNA was extracted from tumors and genome-wide DNA methylation patterns were analyzed using Illumina EPIC (850k) arrays. Furthermore, 5-ALA intensity was measured by flow cytometry on human gliomasphere lines (BT112 and BT145).

Results

Of 74 included patients, 12 (16.2%) patients had a non-fluorescent glioblastoma, which were compared to 62 glioblastomas with 5-ALA fluorescence. Clinical characteristics were equally distributed between both groups. We did not find significant differences between DNA methylation subclasses and 5-ALA fluorescence (P = .24). The distribution of cells of the tumor microenvironment was not significantly different between the non-fluorescent and fluorescent tumors. Copy number variations in EGFR and simultaneous EGFRvIII expression were strongly associated with 5-ALA fluorescence since all non-fluorescent glioblastomas were EGFR-amplified (P < .01). This finding was also demonstrated in recurrent tumors. Similarly, EGFR-amplified glioblastoma cell lines showed no 5-ALA fluorescence after 24 h of incubation.

Conclusions

Our study demonstrates an association between non-fluorescent IDH-wildtype glioblastomas and EGFR gene amplification which should be taken into consideration for recurrent surgery and future studies investigating EGFR-amplified gliomas.

Transformative Materials to Create 3D Functional Human Tissue Models In Vitro in a Reproducible Manner

Recreating human tissues and organs in the petri dish to establish models as tools in biomedical sciences has gained momentum. These models can provide insight into mechanisms of human physiology, disease onset, and progression, and improve drug target validation, as well as the development of new medical therapeutics. Transformative materials play an important role in this evolution, as they can be programmed to direct cell behavior and fate by controlling the activity of bioactive molecules and material properties. Using nature as an inspiration, scientists are creating materials that incorporate specific biological processes observed during human organogenesis and tissue regeneration. This article presents the reader with state-of-the-art developments in the field of in vitro tissue engineering and the challenges related to the design, production, and translation of these transformative materials. Advances regarding (stem) cell sources, expansion, and differentiation, and how novel responsive materials, automated and large-scale fabrication processes, culture conditions, in situ monitoring systems, and computer simulations are required to create functional human tissue models that are relevant and efficient for drug discovery, are described. This paper illustrates how these different technologies need to converge to generate in vitro life-like human tissue models that provide a platform to answer health-based scientific questions.

CimpleG: finding simple CpG methylation signatures

DNA methylation signatures are usually based on multivariate approaches that require hundreds of sites for predictions. Here, we propose a computational framework named CimpleG for the detection of small CpG methylation signatures used for cell-type classification and deconvolution. We show that CimpleG is both time efficient and performs as well as top performing methods for cell-type classification of blood cells and other somatic cells, while basing its prediction on a single DNA methylation site per cell type. Altogether, CimpleG provides a complete computational framework for the delineation of DNAm signatures and cellular deconvolution.

Quantification of hematopoietic stem and progenitor cells by targeted DNA methylation analysis

Hematopoietic stem and progenitor cells (HSPCs) are quantified in daily clinical practice by flow cytometry. In this study, we provide proof of concept that HSPCs can also be estimated by targeted DNA methylation (DNAm) analysis. The DNAm levels at three individual CG dinucleotides (CpG sites) in the genes MYO1D, STK17A, and SP140 correlated with CD34⁺ cell numbers in mobilized peripheral blood and with blast counts in leukemia. In the future, such epigenetic biomarkers can support the evaluation of stem cell mobilization, HSPC harvesting, or blast count in leukemia.

DNA Methylation Dynamics During Esophageal Epithelial Regeneration Following Repair with Acellular Silk Fibroin Grafts in Rat

Esophageal pathologies such as atresia and benign strictures often require surgical reconstruction with autologous tissues to restore organ continuity. Complications such as donor site morbidity and limited tissue availability have spurred the development of acellular grafts for esophageal tissue replacement. Acellular biomaterials for esophageal repair rely on the activation of intrinsic regenerative mechanisms to mediate de novo tissue formation at implantation sites. Previous research has identified signaling cascades involved in neoepithelial formation in a rat model of onlay esophagoplasty with acellular silk fibroin grafts, including phosphoinositide 3-kinase (PI3K), and protein kinase B (Akt) signaling. However, it is currently unknown how these mechanisms are governed by DNA methylation (DNAme) during esophageal wound healing processes. Reduced-representation bisulfite sequencing is performed to characterize temporal DNAme dynamics in host and regenerated tissues up to 1 week postimplantation. Overall, global hypermethylation is observed at postreconstruction timepoints and an inverse correlation between promoter DNAme and the expression levels of differentially expressed proteins during regeneration. Site-specific hypomethylation targets genes associated with immune activation, while hypermethylation occurs within gene bodies encoding PI3K-Akt signaling components during the tissue remodeling period. The data provide insight into the epigenetic mechanisms during esophageal regeneration following surgical repair with acellular grafts.

Investigating the effects of maltreatment and acute stress on the concordance of blood and DNA methylation methods of estimating immune cell proportions

BACKGROUND

Immune cell proportions can be used to detect pathophysiological states and are also critical covariates in genomic analyses. The complete blood count (CBC) is the most common method of immune cell proportion estimation, but immune cell proportions can also be estimated using whole-genome DNA methylation (DNAm). Although the concordance of CBC and DNAm estimations has been validated in various adult and clinical populations, less is known about the concordance of existing estimators among stress-exposed individuals. As early life adversity and acute psychosocial stress have both been associated with unique DNAm alterations, the concordance of CBC and DNAm immune cell proportion needs to be validated in various states of stress.

RESULTS

We report the correlation and concordance between CBC and DNAm estimates of immune cell proportions using the Illumina EPIC DNAm array within two unique studies: Study 1, a high-risk pediatric cohort of children oversampled for exposure to maltreatment (N = 365, age 8 to 14 years), and Study 2, a sample of young adults who have participated in an acute laboratory stressor with four pre- and post-stress measurements (N = 28, number of observations = 100). Comparing CBC and DNAm proportions across both studies, estimates of neutrophils (r = 0.948, p < 0.001), lymphocytes (r = 0.916, p < 0.001), and eosinophils (r = 0.933, p < 0.001) were highly correlated, while monocyte estimates were moderately correlated (r = 0.766, p < 0.001) and basophil estimates were weakly correlated (r = 0.189, p < 0.001). In Study 1, we observed significant deviations in raw values between the two approaches for some immune cell subtypes; however, the observed differences were not significantly predicted by exposure to child maltreatment. In Study 2, while significant changes in immune cell proportions were observed in response to acute psychosocial stress for both CBC and DNAm estimates, the observed changes were similar for both approaches.

CONCLUSIONS

Although significant differences in immune cell proportion estimates between CBC and DNAm exist, as well as stress-induced changes in immune cell proportions, neither child maltreatment nor acute psychosocial stress alters the concordance of CBC and DNAm estimation methods. These results suggest that the agreement between CBC and DNAm estimators of immune cell proportions is robust to exposure to child maltreatment and acute psychosocial stress.

Data-driven identification and classification of nonlinear aging patterns reveals the landscape of associations between DNA methylation and aging

BACKGROUND

Aging affects the incidence of diseases such as cancer and dementia, so the development of biomarkers for aging is an important research topic in medical science. While such biomarkers have been mainly identified based on the assumption of a linear relationship between phenotypic parameters, including molecular markers, and chronological age, numerous nonlinear changes between markers and aging have been identified. However, the overall landscape of the patterns in nonlinear changes that exist in aging is unknown.

RESULT

We propose a novel computational method, Data-driven Identification and Classification of Nonlinear Aging Patterns (DICNAP), that is based on functional data analysis to identify biomarkers for aging and potential patterns of change during aging in a data-driven manner. We applied the proposed method to large-scale, public DNA methylation data to explore the potential patterns of age-related changes in methylation intensity. The results showed that not only linear, but also nonlinear changes in DNA methylation patterns exist. A monotonous demethylation pattern during aging, with its rate decreasing at around age 60, was identified as the candidate stable nonlinear pattern. We also analyzed the age-related changes in methylation variability. The results showed that the variability of methylation intensity tends to increase with age at age-associated sites. The representative variability pattern is a monotonically increasing pattern that accelerates after middle age.

CONCLUSION

DICNAP was able to identify the potential patterns of the changes in the landscape of DNA methylation during aging. It contributes to an improvement in our theoretical understanding of the aging process.

Consistent DNA Hypomethylations in Prostate Cancer

With approximately 1.4 million men annually diagnosed with prostate cancer (PCa) worldwide, PCa remains a dreaded threat to life and source of devastating morbidity. In recent decades, a significant decrease in age-specific PCa mortality has been achieved by increasing prostate-specific antigen (PSA) screening and improving treatments. Nevertheless, upcoming, augmented recommendations against PSA screening underline an escalating disproportion between the benefit and harm of current diagnosis/prognosis and application of radical treatment standards. Undoubtedly, new potent diagnostic and prognostic tools are urgently needed to alleviate this tensed situation. They should allow a more reliable early assessment of the upcoming threat, in order to enable applying timely adjusted and personalized therapy and monitoring. Here, we present a basic study on an epigenetic screening approach by Methylated DNA Immunoprecipitation (MeDIP). We identified genes associated with hypomethylated CpG islands in three PCa sample cohorts. By adjusting our computational biology analyses to focus on single CpG-enriched 60-nucleotide-long DNA probes, we revealed numerous consistently differential methylated DNA segments in PCa. They were associated among other genes with NOTCH3, CDK2AP1, KLK4, and ADAM15. These can be used for early discrimination, and might contribute to a new epigenetic tumor classification system of PCa. Our analysis shows that we can dissect short, differential methylated CpG-rich DNA fragments and combinations of them that are consistently present in all tumors. We name them tumor cell-specific differential methylated CpG dinucleotide signatures (TUMS).

Epigenetic biomarkers to track differentiation of pluripotent stem cells

Quality control of induced pluripotent stem cells remains a challenge. For validation of the pluripotent state, it is crucial to determine trilineage differentiation potential toward endoderm, mesoderm, and ectoderm. Here, we report GermLayerTracker, a combination of site-specific DNA methylation (DNAm) assays that serve as biomarker for early germ layer specification. CG dinucleotides (CpGs) were identified with characteristic DNAm at pluripotent state and after differentiation into endoderm, mesoderm, and ectoderm. Based on this, a pluripotency score was derived that tracks reprogramming and may indicate differentiation capacity, as well as lineage-specific scores to monitor either directed differentiation or self-organized multilineage differentiation in embryoid bodies. Furthermore, we established pyrosequencing assays for fast and cost-effective analysis. In the future, the GermLayerTracker could be used for quality control of pluripotent cells and to estimate lineage-specific commitment during initial differentiation events.

A novel algicidal bacteria isolated from native snail lived in Taihu Lake against algal blooms: identification, degradation kinetic, and algicidal mechanism

Harmful algal blooms (HABs) impacted negatively the water ecosystem, and produced toxic microcystins that poses toxic effect on liver, nervous, and genital system. The introduction of useful and adaptive algae-degrading microbes or bio-augmentation can be regarded as an efficient way to inhibit the outbreak of HABs. The purpose of this study is to evaluate the application potential of algicidal bacteria named XMC, which is isolated from native snails. Response surface methodology (RSM) experiments showed that self-characteristic and various external conditions affected the actual algae inhibition ability of XMC. In particular, actual algicidal efficiency was strongly depend on the temperature and growth stage of XMC, and the maximum algicidal rate could reach 93.95% within 7 days. The degradation curve of Microcystis aeruginosa was compliant with the first-order kinetic model, which could be used to predict the degradation effect of Microcystis aeruginosa in engineering applications. The analysis results of algae dissolution products showed that algicidal bacteria XMC had both direct and indirect algicidal capacity. In addition, XMC had strong algicidal ability and greater environmental adaptability, and its algae dissolution products were environmentally friendly. All results indicated that XMC had the potential to be used in the bio-degradation of cyanobacteria bloom.

Disrupted methylation patterns at birth persist in early childhood: a prospective cohort analysis

BACKGROUND

Alterations in the epigenome are a risk factor in multiple disease states. We have demonstrated in the past that disruption of the epigenome during early pregnancy or periconception, as demonstrated by altered methylation, may be associated with both assisted reproductive technology and undesirable clinical outcomes at birth, such as low birth weight. We have previously defined this altered methylation, calculated based on statistical upper and lower limits of outlier CpGs compared to the population, as an 'outlier methylation phenotype' (OMP). Our aim in this study was to determine whether children thus identified as possessing an OMP at birth by DNA methylation in cord blood persist as outliers in early childhood based on salivary DNA methylation.

RESULTS

A total of 31 children were included in the analysis. Among 24 children for whom both cord blood DNA and salivary DNA were available, DNA methylation patterns, analyzed using the Illumina Infinium MethylationEPIC BeadChip (850 K), between cord blood at birth and saliva in childhood at age 6-12 years remain stable (R2 range 0.89-0.97). At birth, three out of 28 children demonstrated an OMP in multiple cord blood datasets and hierarchical clustering. Overall DNA methylation among all three OMP children identified as outliers at birth was remarkably stable (individual R2 0.908, 0.92, 0.915), even when only outlier CpG sites were considered (R2 0.694, 0.738, 0.828).

CONCLUSIONS

DNA methylation signatures in cord blood remain stable over time as demonstrated by a strong correlation with epigenetic salivary signatures in childhood. Future work is planned to identify whether a clinical phenotype is associated with OMP and, if so, could undesirable clinical outcomes in childhood and adulthood be predicted at birth.

Hematopoietic differentiation persists in human iPSCs defective in de novo DNA methylation

BACKGROUND

DNA methylation is involved in the epigenetic regulation of gene expression during developmental processes and is primarily established by the DNA methyltransferase 3A (DNMT3A) and 3B (DNMT3B). DNMT3A is one of the most frequently mutated genes in clonal hematopoiesis and leukemia, indicating that it plays a crucial role for hematopoietic differentiation. However, the functional relevance of Dnmt3a for hematopoietic differentiation and hematological malignancies has mostly been analyzed in mice, with the specific role for human hematopoiesis remaining elusive. In this study, we therefore investigated if DNMT3A is essential for hematopoietic differentiation of human induced pluripotent stem cells (iPSCs).

RESULTS

We generated iPSC lines with knockout of either exon 2, 19, or 23 and analyzed the impact of different DNMT3A exon knockouts on directed differentiation toward mesenchymal and hematopoietic lineages. Exon 19^-/- and 23^-/- lines displayed an almost entire absence of de novo DNA methylation during mesenchymal and hematopoietic differentiation. Yet, differentiation efficiency was only slightly reduced in exon 19^-/- and rather increased in exon 23^-/- lines, while there was no significant impact on gene expression in hematopoietic progenitors (iHPCs). Notably, DNMT3A^-/- iHPCs recapitulate some DNA methylation patterns of acute myeloid leukemia (AML) with DNMT3A mutations. Furthermore, multicolor genetic barcoding revealed growth advantage of exon 23^-/- iHPCs in a syngeneic competitive differentiation assay.

CONCLUSIONS

Our results demonstrate that iPSCs with homozygous knockout of different exons of DNMT3A remain capable of mesenchymal and hematopoietic differentiation-and exon 23^-/- iHPCs even gained growth advantage-despite loss of almost the entire de novo DNA methylation. Partial recapitulation of DNA methylation patterns of AML with DNMT3A mutations by our DNMT3A knockout iHPCs indicates that our model system can help to elucidate mechanisms of clonal hematopoiesis.

How to Translate DNA Methylation Biomarkers Into Clinical Practice

Recent advances in sequencing technologies provide unprecedented opportunities for epigenetic biomarker development. Particularly the DNA methylation pattern—which is modified at specific sites in the genome during cellular differentiation, aging, and disease—holds high hopes for a wide variety of diagnostic applications. While many epigenetic biomarkers have been described, only very few of them have so far been successfully translated into clinical practice and almost exclusively in the field of oncology. This discrepancy might be attributed to the different demands of either publishing a new finding or establishing a standardized and approved diagnostic procedure. This is exemplified for epigenetic leukocyte counts and epigenetic age-predictions. To ease later clinical translation, the following hallmarks should already be taken into consideration when designing epigenetic biomarkers: 1) Identification of best genomic regions, 2) pre-analytical processing, 3) accuracy of DNA methylation measurements, 4) identification of confounding parameters, 5) accreditation as diagnostic procedure, 6) standardized data analysis, 7) turnaround time, and 8) costs and customer requirements. While the initial selection of relevant genomic regions is usually performed on genome wide DNA methylation profiles, it might be advantageous to subsequently establish targeted assays that focus on specific genomic regions. Development of an epigenetic biomarker for clinical application is a long and cumbersome process that is only initiated with the identification of an epigenetic signature.

Physical activity specifically evokes release of cell-free DNA from granulocytes thereby affecting liquid biopsy

Physical activity impacts immune homeostasis and leads to rapid and marked increase in cell-free DNA (cfDNA). However, the origin of cfDNA during exercise remains elusive and it is unknown if physical activity could improve or interfere with methylation based liquid biopsy. We analyzed the methylation levels of four validated CpGs representing cfDNA from granulocytes, lymphocytes, monocytes, and non-hematopoietic cells, in healthy individuals in response to exercise, and in patients with hematological malignancies under resting conditions. The analysis revealed that physical activity almost exclusively triggered DNA release from granulocytes, highlighting the relevance as a pre-analytical variable which could compromise diagnostic accuracy.

DNA methylation profiling in mummified human remains from the eighteenth-century

Reconstruction of ancient epigenomes by DNA methylation (DNAm) can shed light into the composition of cell types, disease states, and age at death. However, such analysis is hampered by impaired DNA quality and little is known how decomposition affects DNAm. In this study, we determined if EPIC Illumina BeadChip technology is applicable for specimens from mummies of the eighteenth century CE. Overall, the signal intensity on the microarray was extremely low, but for one of two samples we were able to detect characteristic DNAm signals in a subset of CG dinucleotides (CpGs), which were selected with a stringent processing pipeline. Using only these CpGs we could train epigenetic signatures with reference DNAm profiles of multiple tissues and our predictions matched the fact that the specimen was lung tissue from a 28-year-old woman. Thus, we provide proof of principle that Illumina BeadChips are applicable for DNAm profiling in ancient samples.

Targeted methods for epigenetic age predictions in mice

Age-associated DNA methylation reflects aspect of biological aging—therefore epigenetic clocks for mice can elucidate how the aging process in this model organism is affected by specific treatments or genetic background. Initially, age-predictors for mice were trained for genome-wide DNA methylation profiles and we have recently described a targeted assay based on pyrosequencing of DNA methylation at only three age-associated genomic regions. Here, we established alternative approaches using droplet digital PCR (ddPCR) and barcoded bisulfite amplicon sequencing (BBA-seq). At individual CG dinucleotides (CpGs) the correlation of DNA methylation with chronological age was slightly higher for pyrosequencing and ddPCR as compared to BBA-seq. On the other hand, BBA-seq revealed that neighboring CpGs tend to be stochastically modified at murine age-associated regions. Furthermore, the binary sequel of methylated and non-methylated CpGs in individual reads can be used for single-read predictions, which may reflect heterogeneity in epigenetic aging. In comparison to C57BL/6 mice the single-read age-predictions using BBA-seq were also accelerated in the shorter-lived DBA/2 mice, and in C57BL/6 mice with a lifespan quantitative trait locus of DBA/2 mice. Taken together, we describe alternative targeted methods for epigenetic age predictions that provide new perspectives for aging-intervention studies in mice.