Biology subjects

Ebenstein, Y.

Publications and source records attributed to Ebenstein, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Beyond Bisulfite Sequencing: Resolving 5-hmC with Nanopore Sequencing Unmasks the True-5mC Methylation Entropy Landscape

DNA methylation dynamically regulates cellular function and phenotype. At the tissue level, stochasticity in methylation patterns, as measured by methylation entropy, drives plasticity, development, cancer, and aging. Modulation of methylation patterns is facilitated by erasure of 5-methylcytosine (5mC) via the oxidized intermediate 5-hydroxymethylcytosine (5hmC). Bisulfite sequencing cannot distinguish the two modifications, labeling them both as 5-mC. We quantitatively analyze the effect of this historical conflation on the genome-wide distribution of methylation levels and methylation entropy. Using nanopore sequencing with direct 5mC and 5hmC calling, we compare True-mC to bisulfite-like analysis in two model systems, kidney cancer and the mouse medial prefrontal cortex. We show that bisulfite sequencing introduces systematic, tissue-specific shifts in methylation distribution that affect the mechanistic interpretation of the underlying biology. The distortion scaled with endogenous 5hmC content: substantial in brain, where over half of the entropy-associated gene ontology terms recovered under bisulfite-like analysis were absent under True-mC, and minimal in the low-5hmC kidney cancer sample, which delimits the regime in which bisulfite-derived entropy remains interpretable. Together, these findings establish that True-5mC-based methylation entropy redefines the physical mapping of certain epigenomes, demonstrating that in some contexts, what has previously been interpreted as stochastic maintenance failure is frequently the structured signature of distinct and mechanistically interpretable cytosine biochemistry.

bioinformatics↗

bioRxiv2026

Epigenetic Liquid Biopsy Enables Universal Mutation-Agnostic Molecular Surveillance for High-Risk Neuroblastoma

Pediatric solid tumors present a challenge for precision oncology as most tumors harbor low mutational burden, limiting the applicability of standard mutation-based liquid biopsy approaches for molecular monitoring. To overcome this, we developed a mutation-independent liquid biopsy framework based on Oxford Nanopore Technology sequencing, utilizing robust DNA methylation-based biomarkers for detection and surveillance of high-risk neuroblastoma (HR-NBL), a common pediatric solid tumor. Comparative analysis of tumor-derived DNA methylation profiles against a comprehensive atlas of normal human cell types identified 72 NBL-specific differentially methylated regions (termed meNBLs). Integration of 25 selected meNBLs into the methylation atlas enabled quantitative deconvolution of NBL-derived cfDNA, outperforming copy number and mutation-based estimates. NBL-specific blood plasma-derived cfDNA was detected at diagnosis but not in healthy controls, absent during remission, and markedly elevated at relapse, even before clinical detection of disease recurrence. These findings establish methylation-based deconvolution as a robust, mutation-independent approach for cfDNA monitoring in HR-NBL.

cancer biology↗

bioRxiv2025

Single cell transcriptomics reveals enrichment of aggregation-prone alpha-synuclein isoforms across synucleinopathies

Alpha-synuclein (-Syn) is the primary component of Lewy bodies, the pathological hallmark of neurodegenerative synucleinopathies, including Parkinsons disease (PD) and dementia with Lewy bodies (DLB). Dysregulated expression of its encoding gene, SNCA, has been identified in association with both PD and DLB in short-read sequencing studies. However, such studies do not capture variation in transcript isoforms expressed. Here we combine for the first time SNCA-targeted long-read multiplexed arrays isoform sequencing (MAS-Iso-seq) with unbiased short-read single nucleus (sn) RNA-seq for simultaneous characterization of the SNCA transcript isoform landscape and mapping of isoform expression to specific cell types and subtypes in PD, DLB, and control sample cortical tissues. This approach enabled discovery of numerous SNCA transcript isoforms displaying novel splicing patterns and incorporating novel exons. We further identified an abundant class of transcript isoforms encoding a previously unreported -Syn protein variant (-Syn-115) and displaying increased proportional detection in excitatory neurons of PD and DLB tissues in comparison to controls. The proportion of these isoforms was found to be especially high within several specific glutamatergic neuron subtypes. In-depth characterization of the predicted structural and biochemical properties of -Syn-115 using an in silico modeling approach revealed a greater aggregative affinity compared with canonical -Syn-140, suggesting the potential for increased cytosolic -Syn-115 abundance to induce aggregation between heterogeneous -Syn isoforms, potentially driving fibril formation and disease progression. Together, our findings provide new insights into the molecular mechanisms underlying -Syn involvement in multiple synucleinopathies and have translational implications for the development of new precision medicine strategies to combat these diseases, indicating the potential for treatments targeting both specific transcript and protein isoforms, as well as disease-driving cell subtypes.

neuroscience↗

bioRxiv2025

A Spectral Image Scanning Microscope for Multi-Color High-Resolution Imaging

Fluorescence confocal microscopy is a fundamental and widely used tool for biological, medical, and chemical research. It enables color-coded visualization of sample components, enhancing our understanding of lifes building blocks and their interactions. The recent realization of image scanning microscopy (ISM) using confocal spinning disks (CSD) enhanced the spatial resolution of fluorescence microscopy to twice the diffraction limit with minimal sample perturbation and fast acquisition rates. However, capturing multi-color images using ISM is still time-consuming and introduces temporal artifacts as different colors are not acquired simultaneously. Here, we present a spectral CSD-ISM system designed for concurrent high-resolution and simultaneous multi-color acquisition. By integrating a custom linear Amici prism into the CSD-ISM optical detection path, we achieve multi-color, super-resolution images at a fraction of the acquisition time and with a flexible color palette selection. A digital signal processor (DSP) is employed together with accompanying software as a cost-effective alternative to Field-Programmable Gate Arrays (FPGAs) used in previous studies. We provide an accompanying GPU-compatible, python-based image processing pipeline to decompose spectral signatures into multi-color channel-based images, preserving the optical resolution. System characterization using three color fluorescent beads demonstrated 1.74-fold resolution improvement over the diffraction limit and accurate color classification with three times faster acquisition compared to standard CSD-ISM. Application to neuron cells expressing a Parkinsons disease-associated mutation, showcased improved resolution and contrast of four distinctly labeled cellular components. This spectral CSD-ISM system provides a valuable tool for biological imaging, enabling the simultaneous acquisition of high-resolution spatial information and multi-color spectral data.

biophysics↗

bioRxiv2025

Write and read: Harnessing Synthetic DNA Modifications for Nanopore Sequencing.

An exciting feature of nanopore sequencing is its ability to record multi-omic information on the same sequenced DNA molecule. Well-trained models allow the detection of nucleotide-specific molecular signatures through changes in ionic current as DNA molecules translocate through the nanopore. Thus, naturally occurring DNA modifications, such as DNA methylation and hydroxymethylation, may be recorded simultaneously with the genetic sequence. Additional genomic information, such as chromatin state or the locations of bound transcription factors, may also be recorded if their locations are chemically encoded into the DNA. Here, we present a versatile "write-and-read" framework, where chemo-enzymatic DNA labeling with unnatural synthetic tags results in predictable electrical fingerprints in nanopore sequencing. As a proof-of-concept, we explore a DNA glucosylation approach that selectively modifies 5-hydroxymethylcytosine (5hmC) with glucose or glucose-azide adducts. We demonstrate that these modifications generate distinct and reproducible electrical shifts, enabling the direct detection of chemically altered nucleotides. We further demonstrate that enzymatic alkylation, such as the enzymatic transfer of azide residues to the N6 position of adenines, also produces characteristic nanopore signal shifts relative to the native adenine and 6-methyladenine. Beyond direct nucleotide detection, this approach introduces new possibilities for bio-orthogonal DNA labeling, enabling an extended alphabet of sequence-specific detectable moieties. The future use of programmable chemical modifications for simultaneous analysis of multiple omics features on individual molecules opens new avenues for genetic research and discovery.

bioengineering↗

bioRxiv2024

Long-Read Structural and Epigenetic Profiling of a Kidney Tumor-matched Sample with Nanopore Sequencing and Optical Genome Mapping

Carcinogenesis often involves significant alterations in the cancer genome architecture, marked by large structural and copy number variations (SVs and CNVs) that are difficult to capture with short-read sequencing. Traditionally, cytogenetic techniques are applied to detect such aberrations, but they are limited in resolution and do not cover features smaller than several hundred kilobases. Optical genome mapping and nanopore sequencing are attractive technologies that bridge this resolution gap and offer enhanced performance for cytogenetic applications. These methods profile native, individual DNA molecules, thus capturing epigenetic information. We applied both techniques to characterize a clear cell renal cell carcinoma (ccRCC) tumors structural and copy number landscape, highlighting the relative strengths of each method in the context of variant size and average read length. Additionally, we assessed their utility for methylome and hydroxymethylome profiling, emphasizing differences in epigenetic analysis applicability.

genomics↗

bioRxiv2023

OM2Seq: Learning retrieval embeddings for optical genome mapping

MotivationGenomics-based diagnostic methods that are quick, precise, and economical are essential for the advancement of precision medicine, with applications spanning the diagnosis of infectious diseases, cancer, and rare diseases. One technology that holds potential in this field is optical genome mapping (OGM), which is capable of detecting structural variations, epigenomic profiling, and microbial species identification. It is based on imaging of linearized DNA molecules that are stained with fluorescent labels, that are then aligned to a reference genome. However, the computational methods currently available for OGM fall short in terms of accuracy and computational speed. ResultsThis work introduces OM2Seq, a new approach for the rapid and accurate mapping of DNA fragment images to a reference genome. Based on a Transformer-encoder architecture, OM2Seq is trained on acquired OGM data to efficiently encode DNA fragment images and reference genome segments to a common embedding space, which can be indexed and efficiently queried using a vector database. We show that OM2Seq significantly outperforms the baseline methods in both computational speed (by two orders of magnitude) and accuracy. Availability and implementationhttps://github.com/yevgenin/om2seq Contactyoavsh@bm.technion.ac.il

bioinformatics↗

bioRxiv2023

Design of optimal labeling patterns for optical genome mapping via information theory

Optical genome mapping (OGM) is a technique that extracts partial genomic information from optically imaged and linearized DNA fragments containing fluorescently labeled short sequence patterns. This information can be used for various genomic analyses and applications, such as the detection of structural variations and copy-number variations, epigenomic profiling, and microbial species identification. Currently, the choice of labeled patterns is based on the available bio-chemical methods, and is not necessarily optimized for the application. In this work, we develop a model of OGM based on information theory, which enables the design of optimal labeling patterns for specific applications and target organism genomes. We validated the model through experimental OGM on human DNA and simulations on bacterial DNA. Our model predicts up to 10-fold improved accuracy by optimal choice of labeling patterns, which may guide future development of OGM bio-chemical labeling methods and significantly improve its accuracy and yield for applications such as epigenomic profiling and cultivation-free pathogen identification in clinical samples.

bioinformatics↗

bioRxiv2022

DeepOM: Single-molecule optical genome mapping via deep learning

Efficient tapping into genomic information from a single microscopic image of an intact DNA molecule fragment is an outstanding challenge and its solution will open new frontiers in molecular diagnostics. Here, a new computational method for optical genome mapping utilizing Deep Learning is presented, termed DeepOM. Utilization of a Convolutional Neural Network (CNN), trained on simulated images of labeled DNA molecules, improves the success rate in alignment of DNA images to genomic references. The method is evaluated on acquired images of human DNA molecules stretched in nano-channels. The accuracy of the method is benchmarked against state-of-the-art commercial software Bionano Solve. The results show a significant advantage in alignment success rate for molecules shorter than 50 kb. DeepOM improves yield, sensitivity and throughput of optical genome mapping experiments in applications of human genomics and microbiology.

bioinformatics↗

bioRxiv2022

Simultaneous global labeling (SiGL) of 5-methylcytosine and 5-hydroxymethylcytosine by DNA alkylation with a synthetic cofactor and engineered methyltransferase

5-methylcytosine and 5-hydroxymethylcytosine are epigenetic modifications involved in gene regulation and cancer. Here, we describe a new, simple, and high-throughput platform for multi-colour epigenetic analysis. The novelty of our approach is the ability to multiplex methylation and de-methylation signals in the same assay. We utilize an engineered methyltransferase enzyme that recognizes and labels all unmodified CpG sites with a fluorescent cofactor. In combination with the already established labelling of the de-methylation mark 5-hydroxymethylcytosine via enzymatic glycosylation, we obtained a robust platform for simultaneous epigenetic analysis of these marks. We assessed the global epigenetic levels in multiple samples of colorectal cancer and observed a reduction in 5-hydroxymethylcytosine levels, but no change in DNA methylation levels between sick and healthy individuals. We also measured epigenetic modifications in chronic lymphocytic leukaemia and observed a decrease in both modification levels. Our results indicate that this assay may be used for the epigenetic characterization of clinical samples for research and patient management.

genetics↗

bioRxiv2022

Optical Genome and Epigenome Mapping of Clear Cell Renal Cell Carcinoma

Cancer cells display complex genomic aberrations that include large-scale genetic rearrangements and epigenetic modulation that are not easily characterized by short-read sequencing. We present a method for simultaneous profiling of long-range genetic/epigenetic changes in matched cancer samples. Clear cell renal cell carcinoma (ccRCC) is the most common subtype of kidney cancer. Most ccRCC cases demonstrate somatic genomic alterations involving the short arm of chromosome 3 (3p), most often targeting the von Hippel-Lindau (VHL) gene. Aiming to identify somatic alterations that characterize early stage ccRCC, we performed comprehensive genetic, cytogenetic and epigenetic analyses comparing ccRCC tumor to adjacent non-tumorous tissue. Optical genome mapping identified genomic aberrations such as structural and copy number variations, complementing exome-sequencing results. Single-molecule methylome and hydroxymethylome mapping revealed multiple differential regions, some of them known to be associated with ccRCC pathogenesis. Among them, metabolic pathways were significantly enriched. Moreover, significant global epigenetic differences were detected between the tumor and the adjacent non-tumorous tissue, and a correlation between epigenetic signals and gene expression was found. This is the first reported comparison of a human tumor and a matched tissue by optical genome/epigenome mapping, revealing well-established and novel somatic aberrations.

genomics↗

bioRxiv2022

Epigenetic aging waves:Artificial intelligence detects clustering of switch points in DNA methylation rate in defined sex-dependent age periods

BackgroundAging is linked to hypermethylation of CpG sites on promoters and enhancers, along with loss of methylation in intergenic zones. That such changes are not necessarily a continuous process is exemplified by the extensive changes in DNA methylation during development with another significant time of change during adolescence. However, the relation between age and DNA methylation during adult life has not been systematically evaluated. In particular, potential changes in methylation trends in the same CpGs over the years that may occur with aging remain largely unexplored. MethodsHere we set out to determine the average trends by age of the CpG sites represented in the Illumina 450 platform, based on data from 2143 subjects of the age range of 20 to 80 years, compiled from 24 different cohorts. Using several mathematical procedures, we initially separated stationary probes from probes whose methylation changes with age. Among the latter, representing [~]20% of the probes, we then focused on the identification of CpG sites with switch points, i.e., a point where a stable trend of change in the age-averaged methylation is replaced by another linear trend. ResultsUsing several mathematical modeling steps, we generated a machine learning model that identified 5175 CpG sites with switch points in age-related changes in the trend of methylation over the years. Switch points reflect acceleration, deceleration or change of direction of the alteration of methylation with age. The 5175 switch points were limited to 2813 genes in three waves, 80% of which were identical in men and women. A medium-size wave was seen in the early forties, succeeded by a dominant wave as of the late fifties, lasting up to 8 years each. Waves appeared[~]4-5 years earlier in men. No switch points were detected on CpGs mapped to the X chromosome. ConclusionIn non-stationary CpG sites, concomitant switch points in age related changes in methylations can be seen in a defined group of sites and genes, which cluster in 3 age- and sex-specific waves.

genomics↗

bioRxiv2021

Deconvolution of the epigenetic age discloses distinct inter-personal variability in epigenetic aging patterns

BackgroundThe epigenetic age can now be extrapolated from one of several epigenetic clocks, which are based on age-related changes in DNA methylation levels at specific multiple CpG sites. Accelerated aging, calculated from the discrepancy between the chronological age and the epigenetic age, has shown to predict morbidity and mortality rate. We assumed that deconvolution of epigenetic age to its components could shed light on the diversity of epigenetic, and by inference, on inter-individual variability in the causes of biological aging. ResultsUsing the Horvath original epigenetic clock, we identified several CpG sites linked to distinct genes that quantitatively explain much of the interpersonal variability in epigenetic aging, with CpG sites related to secretagogin and malin being the most variable. We show that equal epigenetic age in different subjects can result from variable contribution size of the same CpG sites to the total epigenetic age. In a healthy cohort, the most variable CpG sites are responsible for accelerated and decelerated epigenetic aging, relative to chronological age. ConclusionsOf the 353 CpG sites that form the basis for the Horvath epigenetic age, we have found the CpG sites that are responsible for accelerated and decelerated epigenetic aging in healthy subjects. However, the relative contribution of each site to aging varies between individuals, leading to variable personal aging patterns. Our findings pave the way to form personalized aging cards allowing the identification of specific genes related to CpG sites, as aging markers, and perhaps treatment of these targets in order to hinder undesirable age drifting.

developmental biology↗

bioRxiv2021

Nanopore callers for epigenetics from limited supervised data

Nanopore sequencing platforms combined with supervised machine learning (ML) have been effective at detecting base modifications in DNA such as 5mC and 6mA. These ML-based nanopore callers have typically been trained on data that span all modifications on all possible DNA k-mer backgrounds--a complete training dataset. However, as nanopore technology is pushed to more and more epigenetic modifications, such complete training data will not be feasible to obtain. Nanopore calling has historically been performed with Hidden Markov Models (HMMs) that cannot make successful calls for k-mer contexts not seen during training because of their independent emission distributions. However, deep neural networks (DNNs), which share parameters across contexts, are increasingly being used as callers, often outperforming their HMM cousins. It stands to reason that a DNN approach should be able to better generalize to unseen k-mer contexts. Indeed, herein we demonstrate that a common DNN approach (DeepSignal) outperforms a common HMM approach (Nanopolish) in the incomplete data setting. Furthermore, we propose a novel hybrid HMM-DNN approach, Amortized-HMM, that outperforms both the pure HMM and DNN approaches on 5mC calling when the training data are incomplete. Such an approach is expected to be useful for calling 5hmC and combinations of cytosine modifications, where complete training data are not likely to be available.

bioinformatics↗

bioRxiv2021

Chemoenzymatic labeling of DNA methylation patterns for single-molecule epigenetic mapping

DNA methylation, specifically, methylation of cytosine (C) nucleotides at the 5-carbon position (5-mC), is the most studied and among the most significant epigenetic modifications. Here we developed a chemoenzymatic procedure to fluorescently label non-methylated cytosines in the CpG context allowing epigenetic profiling of single DNA molecules spanning hundreds of thousands of base pairs. For this method, a CpG methyltransferase was used to transfer an azide to cytosines from a synthetic S-adenosyl-l-methionine cofactor analog. A fluorophore was then clicked onto the DNA, reporting on the amount and position of non-methylated CpGs. We found that labeling efficiency was increased two-fold by the addition of a nucleosidase that degrades the inactive by-product of the azide-cofactor after labeling, and prevents its inhibitory effect. We first used the method to determine the decline in global DNA methylation in chronic lymphocytic leukemia patients and then performed whole genome methylation mapping of the model plant Arabidopsis thaliana. Our genome maps show high concordance with published methylation maps produced by bisulfite sequencing. Although mapping resolution is limited by optical detection to 500-1000 base pairs, the labeled DNA molecules produced by this approach are hundreds of thousands of base pairs long, allowing access to long repetitive and structurally variable genomic regions.

genomics↗

bioRxiv2021

Genome wide mapping of DNA lesions by Repair Assisted Damage Detection sequencing - RADD-Seq

Mapping DNA damage and its repair has immense potential in understanding environmental exposures, their genotoxicity, and their impact on human health. Monitoring changes in genomic stability also aids in the diagnosis of numerous DNA-related diseases, like cancer, and assists in monitoring their progression and prognosis. However, genome-wide maps of DNA damage distribution are challenging to produce. Here we describe the localization of DNA damage and repair loci by Repair Assisted Damage Detection sequencing - RADD-Seq. Based on the enrichment of damage lesions coupled with a pull-down assay and followed by next generation sequencing, this method is easy to perform and can produce compelling results with minimal coverage. RADD-seq enables the localization of both DNA damage and repair sites for a wide range of single-strand damage types. Using this technique, we created a genome-wide map of oxidative DNA damage loci before and after repair. Oxidative lesions were heterogeneously distributed along the human genome, with less damage occurring in tight chromatin regions. Furthermore, we showed repair is prioritized for highly expressed, essential genes and in open chromatin regions. RADD-seq sheds light on cellular repair mechanisms and capable of identifying genomic hotspots prone to mutation.

genomics↗

bioRxiv2021

Long Reads Capture Simultaneous Enhancer-Promoter Methylation Status for Cell-type Deconvolution

MotivationWhile promoter methylation is associated with reinforcing fundamental tissue identities, the methylation status of distant enhancers was shown by genome-wide association studies to be a powerful determinant of cell-state and cancer. With recent availability of long-reads that report on the methylation status of enhancer-promoter pairs on the same molecule, we hypothesized that probing these pairs on the single-molecule level may serve the basis for detection of rare cancerous transformations in a given cell population. We explore various analysis approaches for deconvolving cell-type mixtures based on their genome-wide enhancer-promoter methylation profiles. ResultsTo evaluate our hypothesis we examine long-read optical methylome data for the GM12787 cell line and myoblast cell lines from two donors. We identified over 100,000 enhancer-promoter pairs that co-exist on at least 30 individual DNA molecules per pair. We developed a detailed methodology for mixture deconvolution and applied it to estimate the proportional cell compositions in synthetic mixtures based on analyzing their enhancer-promoter pairwise methylation. We found our methodology to lead to very accurate estimates, outperforming our promoter-based deconvolutions. Moreover, we show that it can be generalized from deconvolving different cell types to subtle scenarios where one wishes to deconvolve different cell populations of the same cell-type. AvailabilityThe code used in this work to analyze single-molecule Bionano Genomics optical maps is available via the GitHub repository https://github.com/ebensteinLab/Single_molecule_methylation_in_EP. Contactuv@post.tau.ac.il (Y.E), roded@tauex.tau.ac.il (R.S)

bioinformatics↗

bioRxiv2020

Multi-Modal Single-Molecule Imaging with Continuously Controlled Spectral-resolution (CoCoS) Microscopy

Color is a fundamental contrast mechanism in fluorescence microscopy, providing the basis for numerous imaging and spectroscopy techniques. The ever-growing need to acquire high-throughput, dynamic data from multicolor species is driving the development of optical schemes that optimize the achievable spectral, temporal, and spatial resolution needed in order to follow biological, chemical and physical processes. Here we introduce Continuously Controlled Spectral-resolution (CoCoS) microscopy, an imaging scheme that encodes color into spatial read-out in the image plane, with continuous control over the spectral resolution. The concept enables single-frame acquisition of multiple color channels, allowing simultaneous, single-molecule colocalization for barcoding and Forster resonance energy transfer (FRET) experiments. The simple control over the spectral dispersion allows switching between imaging modalities at a click of a button. We demonstrate the utility of CoCoS for multicolor localization microscopy of microRNA barcodes in clinical samples, single-molecule FRET measurements, and single-molecule spectroscopy. CoCoS may be integrated as a simple add-on to existing microscopes and will find use in applications that aim to record dynamic, multicolor localization events such as in multiplex FRET and tracking of multi-component, interacting complexes.

biophysics↗