Small-molecule-induced epigenetic rejuvenation promotes SREBP condensation and overcomes barriers to CNS myelin regeneration.

Remyelination failure in diseases like multiple sclerosis (MS) was thought to involve suppressed maturation of oligodendrocyte precursors; however, oligodendrocytes are present in MS lesions yet lack myelin production. We found that oligodendrocytes in the lesions are epigenetically silenced. Developing a transgenic reporter labeling differentiated oligodendrocytes for phenotypic screening, we identified a small-molecule epigenetic-silencing-inhibitor (ESI1) that enhances myelin production and ensheathment. ESI1 promotes remyelination in animal models of demyelination and enables de novo myelinogenesis on regenerated CNS axons. ESI1 treatment lengthened myelin sheaths in human iPSC-derived organoids and augmented (re)myelination in aged mice while reversing age-related cognitive decline. Multi-omics revealed that ESI1 induces an active chromatin landscape that activates myelinogenic pathways and reprograms metabolism. Notably, ESI1 triggered nuclear condensate formation of master lipid-metabolic regulators SREBP1/2, concentrating transcriptional co-activators to drive lipid/cholesterol biosynthesis. Our study highlights the potential of targeting epigenetic silencing to enable CNS myelin regeneration in demyelinating diseases and aging.

Nuclear morphology is shaped by loop-extrusion programs.

It is well established that neutrophils adopt malleable polymorphonuclear shapes to migrate through narrow interstitial tissue spaces1-3. However, how polymorphonuclear structures are assembled remains unknown4. Here we show that in neutrophil progenitors, halting loop extrusion-a motor-powered process that generates DNA loops by pulling in chromatin5-leads to the assembly of polymorphonuclear genomes. Specifically, we found that in mononuclear neutrophil progenitors, acute depletion of the loop-extrusion loading factor nipped-B-like protein (NIPBL) induced the assembly of horseshoe, banded, ringed and hypersegmented nuclear structures and led to a reduction in nuclear volume, mirroring what is observed during the differentiation of neutrophils. Depletion of NIPBL also induced cell-cycle arrest, activated a neutrophil-specific gene program and conditioned a loss of interactions across topologically associating domains to generate a chromatin architecture that resembled that of differentiated neutrophils. Removing NIPBL resulted in enrichment for mega-loops and interchromosomal hubs that contain genes associated with neutrophil-specific enhancer repertoires and an inflammatory gene program. On the basis of these observations, we propose that in neutrophil progenitors, loop-extrusion programs produce lineage-specific chromatin architectures that permit the packing of chromosomes into geometrically confined lobular structures. Our data also provide a blueprint for the assembly of polymorphonuclear structures, and point to the possibility of engineering de novo nuclear shapes to facilitate the migration of effector cells in densely populated tumorigenic environments.

Matching queried single-cell open-chromatin profiles to large pools of single-cell transcriptomes and epigenomes for reference supported analysis.

The true benefits of large single-cell transcriptome and epigenome data sets can be realized only with the development of new approaches and search tools for annotating individual cells. Matching a single-cell epigenome profile to a large pool of reference cells remains a major challenge. Here, we present scEpiSearch, which enables searching, comparison, and independent classification of single-cell open-chromatin profiles against a large reference of single-cell expression and open-chromatin data sets. Across performance benchmarks, scEpiSearch outperformed multiple methods in accuracy of search and low-dimensional coembedding of single-cell profiles, irrespective of platforms and species. Here we also demonstrate the unconventional utilities of scEpiSearch by applying it on single-cell epigenome profiles of K562 cells and samples from patients with acute leukaemia to reveal different aspects of their heterogeneity, multipotent behavior, and dedifferentiated states. Applying scEpiSearch on our single-cell open-chromatin profiles from embryonic stem cells (ESCs), we identified ESC subpopulations with more activity and poising for endoplasmic reticulum stress and unfolded protein response. Thus, scEpiSearch solves the nontrivial problem of amalgamating information from a large pool of single cells to identify and study the regulatory states of cells using their single-cell epigenomes.

SnapHiC-D: a computational pipeline to identify differential chromatin contacts from single-cell Hi-C data.

Single-cell high-throughput chromatin conformation capture technologies (scHi-C) has been used to map chromatin spatial organization in complex tissues. However, computational tools to detect differential chromatin contacts (DCCs) from scHi-C datasets in development and through disease pathogenesis are still lacking. Here, we present SnapHiC-D, a computational pipeline to identify DCCs between two scHi-C datasets. Compared to methods designed for bulk Hi-C data, SnapHiC-D detects DCCs with high sensitivity and accuracy. We used SnapHiC-D to identify cell-type-specific chromatin contacts at 10 Kb resolution in mouse hippocampal and human prefrontal cortical tissues, demonstrating that DCCs detected in the hippocampal and cortical cell types are generally associated with cell-type-specific gene expression patterns and epigenomic features. SnapHiC-D is freely available at https://github.com/HuMingLab/SnapHiC-D.

Associating pathways with diseases using single-cell expression profiles and making inferences about potential drugs.

Finding direct dependencies between genetic pathways and diseases has been the target of multiple studies as it has many applications. However, due to cellular heterogeneity and limitations of the number of samples for bulk expression profiles, such studies have faced hurdles in the past. Here, we propose a method to perform single-cell expression-based inference of association between pathway, disease and cell-type (sci-PDC), which can help to understand their cause and effect and guide precision therapy. Our approach highlighted reliable relationships between a few diseases and pathways. Using the example of diabetes, we have demonstrated how sci-PDC helps in tracking variation of association between pathways and diseases with changes in age and species. The variation in pathways-disease associations in mice and humans revealed critical facts about the suitability of the mouse model for a few pathways in the context of diabetes. The coherence between results from our method and previous reports, including information about the drug target pathways, highlights its reliability for multidimensional utility.

Improving gene network inference with graph wavelets and making insights about ageing-associated regulatory changes in lungs.

Using gene-regulatory-networks-based approach for single-cell expression profiles can reveal unprecedented details about the effects of external and internal factors. However, noise and batch effect in sparse single-cell expression profiles can hamper correct estimation of dependencies among genes and regulatory changes. Here, we devise a conceptually different method using graphwavelet filters for improving gene network (GWNet)-based analysis of the transcriptome. Our approach improved the performance of several gene network-inference methods. Most Importantly, GWNet improved consistency in the prediction of gene regulatory network using single-cell transcriptome even in the presence of batch effect. The consistency of predicted gene network enabled reliable estimates of changes in the influence of genes not highlighted by differential-expression analysis. Applying GWNet on the single-cell transcriptome profile of lung cells, revealed biologically relevant changes in the influence of pathways and master regulators due to ageing. Surprisingly, the regulatory influence of ageing on pneumocytes type II cells showed noticeable similarity with patterns due to the effect of novel coronavirus infection in human lung.

Effect of dimensions on function: A 2-dimensional sonographic assessment to correlate facial muscle and smile type.

OBJECTIVE: The aim of this study was to measure the dimensions of the select facial muscles and correlate them with different types of smiles. METHODS: The study group included 30 South Asian adults (17 men and 13 women) aged between 24 and 30 years divided into 3 groups of 10 subjects each according to Rubin's classification of smile. The zygomaticus major, levator labii superioris, depressor anguli oris, and mentalis muscles were ultrasonographically evaluated. The length and thickness of the muscles were measured bilaterally. The data obtained were analyzed statistically. RESULTS: The maximum mean value thickness of the zygomaticus major was found in the canine smile group. The maximum mean value thickness of the depressor anguli oris and mentalis was seen in the full denture smile group. However, the thickness of the levator labii superioris muscle was similar between the different smile groups. There was no significant difference in the measurements of the length of the muscles between the right and the left sides. CONCLUSIONS: This study did not find any statistically significant correlation between the type of smiles described in Rubin's classification and the dimensions of the associated facial muscle.

Electrophysiologic Toxicity of Chemoradiation.

PURPOSE OF REVIEW: There is growing awareness of the link between oncology treatments and cardiovascular (CV) complications. This has led to the development of cardio-oncology, a specialty aimed at managing CV risk and disease in cancer patients and survivors. Cardiac arrhythmias are potential adverse CV complications of cancer treatments; however, these cardiotoxicities are often underappreciated due to the uncertain arrhythmogenic mechanisms of various chemotherapeutic agents. RECENT FINDINGS: Chemotherapeutic agents can induce arrhythmias via direct electrophysiological effects on ion channels or intracellular signaling pathways, or indirectly from cardiac tissue damage. As more drugs are being linked to the development of arrhythmias, a deeper understanding of the pathophysiology of their electrophysiological (EP) effects will be necessary. Expanding research in this field has allowed for the identification of novel agents with potential arrhythmogenic properties and the development of preventative measures, early recognition, and closer surveillance of patients more susceptible to these EP side effects.

Identification of a distal enhancer regulating hedgehog interacting protein gene in human lung epithelial cells.

BACKGROUND: An intergenic region at chromosome 4q31 is one of the most significant regions associated with COPD susceptibility and lung function in GWAS. In this region, the implicated causal gene HHIP has a unique epithelial expression pattern in adult human lungs, in contrast to dominant expression in fibroblasts in murine lungs. However, the mechanism underlying the species-dependent cell type-specific regulation of HHIP remains largely unknown. METHODS: We employed snATAC-seq analysis to identify open chromatin regions within the COPD GWAS region in various human lung cell types. ChIP-quantitative PCR, reporter assays, chromatin conformation capture assays and Hi-C assays were conducted to characterize the regulatory element in this region. CRISPR/Cas9-editing was performed in BEAS-2B cells to generate single colonies with stable knockout of the regulatory element. RT-PCR and Western blot assays were used to evaluate expression of HHIP and epithelial-mesenchymal transition (EMT)-related marker genes. FINDINGS: We identified a distal enhancer within the COPD 4q31 GWAS locus that regulates HHIP transcription at baseline and after TGFß treatment in a SMAD3-dependent, but Hedgehog-independent manner in human bronchial epithelial cells. The distal enhancer also maintains chromatin topological domains near 4q31 locus and HHIP gene. Reduced HHIP expression led to increased EMT induced by TGFß in human bronchial epithelial cells. INTERPRETATION: A distal enhancer regulates HHIP expression both under homeostatic condition and upon TGFß treatment in human bronchial epithelial cells. The interaction between HHIP and TGFß signalling possibly contributes to COPD pathogenesis. FUNDING: Supported by NIH grants R01HL127200, R01HL148667 and R01HL162783 (to X. Z).

Functional glycomic analysis of human milk glycans reveals the presence of virus receptors and embryonic stem cell biomarkers.

Human milk contains a large diversity of free glycans beyond lactose, but their functions are not well understood. To explore their functional recognition, here we describe a shotgun glycan microarray prepared from isolated human milk glycans (HMGs), and our studies on their recognition by viruses, antibodies, and glycan-binding proteins (GBPs), including lectins. The total neutral and sialylated HMGs were derivatized with a bifunctional fluorescent tag, separated by multidimensional HPLC, and archived in a tagged glycan library, which was then used to print a shotgun glycan microarray (SGM). This SGM was first interrogated with well defined GBPs and antibodies. These data demonstrated both the utility of the array and provided preliminary structural information (metadata) about this complex glycome. Anti-TRA-1 antibodies that recognize human pluripotent stem cells specifically recognized several HMGs that were then further structurally defined as novel epitopes for these antibodies. Human influenza viruses and Parvovirus Minute Viruses of Mice also specifically recognized several HMGs. For glycan sequencing, we used a novel approach termed metadata-assisted glycan sequencing (MAGS), in which we combine information from analyses of glycans by mass spectrometry with glycan interactions with defined GBPs and antibodies before and after exoglycosidase treatments on the microarray. Together, these results provide novel insights into diverse recognition functions of HMGs and show the utility of the SGM approach and MAGS as resources for defining novel glycan recognition by GBPs, antibodies, and pathogens.

Patterns of transcription factor binding and epigenome at promoters allow interpretable predictability of multiple functions of non-coding and coding genes.

Understanding the biological roles of all genes only through experimental methods is challenging. A computational approach with reliable interpretability is needed to infer the function of genes, particularly for non-coding RNAs. We have analyzed genomic features that are present across both coding and non-coding genes like transcription factor (TF) and cofactor ChIP-seq (823), histone modifications ChIP-seq (n = 621), cap analysis gene expression (CAGE) tags (n = 255), and DNase hypersensitivity profiles (n = 255) to predict ontology-based functions of genes. Our approach for gene function prediction was reliable (>90% balanced accuracy) for 486 gene-sets. PubMed abstract mining and CRISPR screens supported the inferred association of genes with biological functions, for which our method had high accuracy. Further analysis revealed that TF-binding patterns at promoters have high predictive strength for multiple functions. TF-binding patterns at the promoter add an unexplored dimension of explainable regulatory aspects of genes and their functions. Therefore, we performed a comprehensive analysis for the functional-specificity of TF-binding patterns at promoters and used them for clustering functions to reveal many latent groups of gene-sets involved in common major cellular processes. We also showed how our approach could be used to infer the functions of non-coding genes using the CRISPR screens of coding genes, which were validated using a long non-coding RNA CRISPR screen. Thus our results demonstrated the generality of our approach by using gene-sets from CRISPR screens. Overall, our approach opens an avenue for predicting the involvement of non-coding genes in various functions.

SnapFISH: a computational pipeline to identify chromatin loops from multiplexed DNA FISH data.

Multiplexed DNA fluorescence in situ hybridization (FISH) imaging technologies have been developed to map the folding of chromatin fibers at tens of nanometers and up to several kilobases in resolution in single cells. However, computational methods to reliably identify chromatin loops from such imaging datasets are still lacking. Here we present a Single-Nucleus Analysis Pipeline for multiplexed DNA FISH (SnapFISH), to process the multiplexed DNA FISH data and identify chromatin loops. SnapFISH can identify known chromatin loops from mouse embryonic stem cells with high sensitivity and accuracy. In addition, SnapFISH obtains comparable results of chromatin loops across datasets generated from diverse imaging technologies. SnapFISH is freely available at https://github.com/HuMingLab/SnapFISH .

Improving Chromatin-Interaction Prediction Using Single-Cell Open-Chromatin Profiles and Making Insight Into the Cis-Regulatory Landscape of the Human Brain.

Single-cell open-chromatin profiles have the potential to reveal the pattern of chromatin-interaction in a cell type. However, currently available cis-regulatory network prediction methods using single-cell open-chromatin profiles focus more on local chromatin interactions despite the fact that long-range interactions among genomic sites play a significant role in gene regulation. Here, we propose a method that predicts both short and long-range interactions among genomic sites using single-cell open chromatin profiles. Our method, termed as single-cell epigenome based chromatin-interaction analysis (scEChIA) exploits signal imputation and refined L1 regularization. For a few single-cell open-chromatin profiles, scEChIA outperformed other tools even in terms of accuracy of prediction. Using scEChIA, we predicted almost 0.7 million interactions among genomic sites across seven cell types in the human brain. Further analysis revealed cell type for connection between genes and expression quantitative trait locus (eQTL) in the human brain and making insight about target genes of human-accelerated-elements and disease-associated mutations. Our analysis enabled by scEChIA also hints about the possible action of a few transcription factors (TFs), especially through long-range interaction in brain endothelial cells.

FITs: forest of imputation trees for recovering true signals in single-cell open chromatin profiles.

The advent of single-cell open-chromatin profiling technology has facilitated the analysis of heterogeneity of activity of regulatory regions at single-cell resolution. However, stochasticity and availability of low amount of relevant DNA, cause high drop-out rate and noise in single-cell open-chromatin profiles. We introduce here a robust method called as forest of imputation trees (FITs) to recover original signals from highly sparse and noisy single-cell open-chromatin profiles. FITs makes multiple imputation trees to avoid bias during the restoration of read-count matrices. It resolves the challenging issue of recovering open chromatin signals without blurring out information at genomic sites with cell-type-specific activity. Besides visualization and classification, FITs-based imputation also improved accuracy in the detection of enhancers, calculating pathway enrichment score and prediction of chromatin-interactions. FITs is generalized for wider applicability, especially for highly sparse read-count matrices. The superiority of FITs in recovering signals of minority cells also makes it highly useful for single-cell open-chromatin profile from in vivo samples. The software is freely available at https://reggenlab.github.io/FITs/.

Patterns of Anticoagulation Use in Patients With Cancer With Atrial Fibrillation and/or Atrial Flutter.

BACKGROUND: Atrial fibrillation (AF) is a common cardiovascular complication affecting patients with cancer, but management strategies are not well established. OBJECTIVES: The purpose of this retrospective cohort study was to evaluate cross-sectional patterns of anticoagulation (AC) use in patients with cancer with AF or atrial flutter (AFL) on the basis of their risk for stroke and bleeding. METHODS: Patients with cancer and electrocardiograms showing AF or AFL performed at Moffitt Cancer Center in either the inpatient or outpatient setting were included in this retrospective analysis. We described percentages of AC prescription by stroke and bleeding risk, as determined by individual CHA2DS2-VASc and HAS-BLED scores, respectively. Multivariable logistic regression evaluated clinical variables independently associated with anticoagulant prescription. RESULTS: The prevalence of electrocardiography-documented AF or AFL was 4.8% (n = 472). The mean CHA2DS2-VASc score was 2.8 ± 1.4. Among patients with CHA2DS2-VASc scores ≥2 and HAS-BLED scores <3, 44.3% did not receive AC, and of these, only 18.3% had platelet values <50,000/µl. In multivariable analysis, older age, hypertension, prior stroke, and history of venous thromboembolism were each directly associated with AC use, while current chemotherapy use, prior bleeding, renal disease, and thrombocytopenia were each inversely associated with AC use. CONCLUSIONS: Nearly one-half of patients with cancer, the majority with normal platelet counts, had an elevated risk for stroke but did not receive AC. In addition to known predictors, current chemotherapy use was independently associated with a lower odds of AC use. This study highlights the need to improve the application of AF treatment algorithms to cancer populations.

Comparative evaluation of smear layer removal by various chemomechanical caries removal agents: an in vitro SEM study.

OBJECTIVES: To comparatively evaluate the efficiency of various chemomechanical caries removal agents in smear layer removal. MATERIALS AND METHODS: Class V cavities were prepared on the buccal surface of 45 extracted, noncarious molars and were divided into three groups according to the chemical treatment received. The samples were then gold palladium coated and viewed under scanning electron microscope. The presence of smear layer was evaluated based on the microscopic observations. Result and Observation: The results indicated that smear layer removal was significantly higher in the sodium hypochlorite-based chemomechanical caries removal agents than in the papain-based chemomechanical caries removal agent and was least in the control group treated with saline. CONCLUSION: The smear layer removal was maximum with Carisolv followed by the cariecare and was minimum in the saline-treated group.

Comparative evaluation of microleakage in conventional glass ionomer cements and triclosan incorporated glass ionomer cements.

AIM AND OBJECTIVE: The aim of the following study is to comparatively evaluate the microleakage of triclosan incorporated GIC with conventional restorative GIC. MATERIALS AND METHODS: Triclosan in powder form was added to conventional GIC to formulate a concentration of 2.5%. Class five cavities were prepared in non-carious extracted molars and were respectively restored with conventional restorative GIC and triclosan incorporated GIC. Samples were kept in 10% methylene blue dye. Ground sections were obtained and were observed under a binocular microscope for dye penetration. RESULT: No significant difference was found in the microleakage of two groups. CONCLUSION: Triclosan incorporated GIC can be considered as an alternative to GIC with enhanced antibacterial property.