Biology subjects

Maslan, A.

Publications and source records attributed to Maslan, A..

6 recordsLinked to original sources

bioRxiv2025

Integrated analysis of multimodal long-read epigenetic assays

Long-read sequencing assays that detect base modifications are becoming increasingly important research tools for the study of epigenetic regulation, especially with the development of DiMeLo-seq and similar methods that deposit non-native base modifications to mark a range of epigenetic features such as protein-DNA interactions and chromatin accessibility. A main benefit of these methods is their inherent capacity for multimodality, enabling the encoding of multiple genomic signals onto single nucleic acid molecules. However, there are limited tools available for visualization and statistical analysis of this type of multimodal data. Here we introduce dimelo-toolkit, a python package built to enable flexible visualizations and easy integration into custom data processing workflows. We demonstrate the utility of dimelo-toolkits preset visualizations of multiple base modifications in long-read single-molecule sequencing data with a novel extension of the DiMeLo-seq protocol that can capture three separate aspects of chromatin state on the same single reads: target protein binding, CpG methylation, and chromatin accessibility. We apply this multimodal method to simultaneously map chromatin accessibility, CpG methylation, and LMNB1 and CTCF binding patterns, respectively, in GM12878 cells. Our flexible design allows us to investigate previously unexplored technical biases that arise when working with this type of multimodal data. Additionally, we show that dimelo-toolkit enables analysis for a wide range of other long-read sequencing methods, such as mapping endogenous patterns in RNA base modifications with direct RNA sequencing. This software tool will pave the way for developing well-optimized protocols and help unlock previously inaccessible biological insights.

genomics↗

bioRxiv2025

DiMeLo-cito: a one-tube protocol for mapping protein-DNA interactions reveals CTCF bookmarking in mitosis

Genome regulation relies on complex and dynamic interactions between DNA and proteins. Recently, powerful methods have emerged that leverage third-generation sequencing to map protein-DNA interactions genome-wide. For example, Directed Methylation with Long-read sequencing (DiMeLo-seq) enables mapping of protein-DNA interactions along long, single chromatin fibers, including in highly repetitive genomic regions. However, DiMeLo-seq involves lossy centrifugation-based wash steps that limit its applicability to many sample types. To address this, we developed DiMeLo-cito, a single-tube, wash-free protocol that maximizes the yield and quality of genomic DNA obtained for long-read sequencing. This protocol enables the interrogation of genome-wide protein binding with as few as 100,000 cells and without the requirement of a nuclear envelope, enabling confident measurement of protein-DNA interactions during mitosis. Using this protocol, we detected strong binding of CTCF to mitotic chromosomes in diploid human cells, in contrast with earlier studies in karyotypically unstable cancer cell lines, suggesting that CTCF "bookmarks" specific sites critical for maintaining genome architecture across cell divisions. By expanding the capabilities of DiMeLo-seq to a broader range of sample types, DiMeLo-cito can provide new insights into genome regulation and organization.

genomics↗

bioRxiv2022

Mapping protein-DNA interactions with DiMeLo-seq

We recently developed Directed Methylation with Long-read sequencing (DiMeLo-seq) to map protein-DNA interactions genome wide. DiMeLo-seq is capable of mapping multiple interaction sites on single DNA molecules, profiling protein binding in the context of endogenous DNA methylation, identifying haplotype specific protein-DNA interactions, and mapping protein-DNA interactions in repetitive regions of the genome that are difficult to study with short-read methods. With DiMeLo-seq, adenines in the vicinity of a protein of interest are methylated in situ by tethering the Hia5 methyltransferase to an antibody using protein A. Protein-DNA interactions are then detected by direct readout of adenine methylation with long-read, single-molecule, DNA sequencing platforms such as Nanopore sequencing. Here, we present a detailed protocol and practical guidance for performing DiMeLo-seq. This protocol can be run on nuclei from fresh, lightly fixed, or frozen cells. The protocol requires 1-2 days for performing in situ targeted methylation, 1-5 days for library preparation depending on desired fragment length, and 1-3 days for Nanopore sequencing depending on desired sequencing depth. The protocol requires basic molecular biology skills and equipment, as well as access to a Nanopore sequencer. We also provide a Python package, dimelo, for analysis of DiMeLo-seq data. Key papersAltemose, N., Maslan, A., Smith, O.K., Sundararajan, K., Brown, R.R., Mishra, R., Detweiler, A.M., Neff, N., Miga, K.H., Straight, A.F. and Streets, A., 2022. DiMeLo-seq: a long-read, single-molecule method for mapping protein-DNA interactions genome wide. Nature Methods, pp.1-13. (https://doi.org/10.1038/s41592-022-01475-6)

genomics↗

bioRxiv2021

DiMeLo-seq: a long-read, single-molecule method for mappingprotein-DNA interactions genome-wide

Molecular studies of genome regulation often rely on the ability to map where specific proteins interact with genomic DNA. Existing techniques for mapping protein-DNA interactions genome-wide rely on DNA amplification methods followed by sequencing with short reads, which dissociates joint binding information at neighboring sites, removes endogenous DNA methylation information, and precludes the ability to reliably map interactions in repetitive regions of the genome. To address these limitations, we created a new protein-DNA mapping method, called Directed Methylation with Long-read sequencing (DiMeLo-seq), which methylates DNA near each target proteins DNA binding site in situ, then leverages the ability to distinguish methylated and unmethylated bases on long, native DNA molecules using long-read, single-molecule sequencing technologies. We demonstrate the optimization and utility of this method by mapping the interaction sites of a variety of different proteins and histone modifications across the human genome, achieving a single-molecule binding site resolution of less than 200 bp. Furthermore, we mapped the positions of the centromeric histone H3 variant CENP-A in repetitive regions that are unmappable with short reads, while simultaneously analyzing endogenous CpG methylation and joint binding events on single molecules. DiMeLo-seq is a versatile method that can provide multimodal and truly genome-wide information for investigating protein-DNA interactions.

genomics↗

bioRxiv2021

Mechanical phenotyping of acute promyelocytic leukemia reveals unique biomechanical responses in retinoic acid-resistant populations

While all-trans retinoic acid (ATRA) is an essential therapy in the treatment of acute promyelocytic leukemia (APL), an aggressive subtype of acute myeloid leukemia, nearly 20% of APL patients are resistant to ATRA. As no biomarkers for ATRA resistance yet exist, we investigated whether cell mechanics could be associated with this pathological phenotype. Using mechano-node-pore sensing, a single-cell mechanical phenotyping platform, and patient-derived APL cell lines, NB4 (ATRA-sensitive) and AP-1060 (ATRA-resistant), we discovered that ATRA-resistant APL cells are less mechanically pliable. By investigating how different subcellular components of APL cells contribute to whole-cell mechanical phenotype, we determined that nuclear mechanics strongly influence an APL cells mechanical response. By arresting APL cells in S-phase or M-phase in the cell cycle, we found cell pliability to be inversely related to DNA content. In addition to DNA content affecting cell pliability, we observed that chromatin condensation also affects nuclear mechanics: decondensing chromatin with trichostatin A is especially effective in softening ATRA-resistant APL cells. RNA-Seq allowed us to compare the transcriptomic differences between ATRA-resistant and ATRA-responsive APL cells and highlighted gene expression changes that could be associated with mechanical changes. Overall, we demonstrate the potential of "physical" biomarkers in identifying APL resistance.

bioengineering↗

bioRxiv2019

μDamID: a microfluidic approach for imaging and sequencing protein-DNA interactions in single cells

Genome regulation depends on carefully programmed protein-DNA interactions that maintain or alter gene expression states, often by influencing chromatin organization. Most studies of these interactions to date have relied on bulk methods, which in many systems cannot capture the dynamic single-cell nature of these interactions as they modulate cell states. One method allowing for sensitive single-cell mapping of protein-DNA interactions is DNA adenine methyltransferase identification (DamID), which records a proteins DNA-binding history by methylating adenine bases in its vicinity, then selectively amplifies and sequences these methylated regions. These interaction sites can also be visualized using fluorescent proteins that bind to methyladenines. Here we combine these imaging and sequencing technologies in an integrated microfluidic platform (DamID) that enables single-cell isolation, imaging, and sorting, followed by DamID. We apply this system to generate paired single-cell imaging and sequencing data from a human cell line, in which we map and validate interactions between DNA and nuclear lamina proteins, providing a measure of 3D chromatin organization and broad gene regulation patterns. DamID provides the unique ability to compare paired imaging and sequencing data for each cell and between cells, enabling the joint analysis of the nuclear localization, sequence identity, and variability of protein-DNA interactions.

bioengineering↗