Biology subjects

Chakrabarti, A. M.

Publications and source records attributed to Chakrabarti, A. M..

13 recordsLinked to original sources

bioRxiv2025

Recovery of human upper airway epithelium after smoking cessation is driven by a slow-cycling stem cell population and immune surveillance

The upper airway epithelium in humans is maintained in homeostasis by a resident population of basal stem cells. In the presence of tobacco smoke these gain mutations that significantly increase their risk of transformation to lung squamous cell carcinoma. Previous studies show that a small proportion of stem cells avoid the mutational damage caused by carcinogens in tobacco and are more abundant in the lungs of former smokers than ongoing smokers, indicating unexplained tissue-level genomic recovery. This mirrors epidemiological risk, which falls rapidly after quitting smoking. Somatic evolutionary mechanistic hypotheses have been proposed to explain these observations. Here, we present a computational framework to model each of these hypotheses within the upper airway epithelial stem cell population over the entire patient lifetimes of a cohort with diverse smoking histories. Applying a mechanistic learning approach based on a set of biologically informed metrics to single cell-derived whole-genome sequencing data, we identified subtle differences between epithelia modelled under different combinations of hypotheses. A slow-cycling subpopulation of stem cells, combined with suppression of immune predation of highly mutated stem cells while smoking, best matched observed data, a result converged upon by multiple distinct machine learning methodologies. Our findings, drawing on an evolutionary model of mutagen exposure at a whole-lifetime scale that is not feasible to model in vivo, reveal the mechanisms behind reduction in lung squamous cell carcinoma risk on cessation of smoking and inform future therapeutic interventions to prevent lung cancer initiation.

evolutionary biology↗

bioRxiv2025

Defining the ordered pathway for ZAP-mediated RNA decay

Zinc-finger Antiviral Protein (ZAP)-mediated RNA decay (ZMD) restricts replication of viruses containing CpG dinucleotide clusters. However, why ZAP isoforms differ in antiviral activity and how they recruit cofactors to mediate RNA decay is unclear. Therefore, we determined the ordered events of the ZMD pathway. The long ZAP isoform preferentially binds viral RNA and has distinct binding motifs compared to the short isoform. The endoribonuclease KHNYN then cleaves viral RNA at positions of ZAP binding. The 5 cleavage fragment undergoes TUT4/TUT7-mediated 3 uridylation and degradation by DIS3L2. The 3 cleavage fragment is degraded by XRN1. ZAP and TRIM25 interact with KHNYN, TUT7, DIS3L2 and XRN1 in a RNase-resistant manner. Viral infection promotes the interaction between TRIM25 with these enzymes, leading to viral RNA decay while also decreasing the abundance of cellular transcripts. Overall, the long isoform of ZAP recruits key enzymes to assemble an RNA decay complex on viral RNA.

immunology↗

bioRxiv2025

PRMT activity promotes global 3' UTR shortening in proliferating cells

Protein methyltransferase (PRMT)-catalysed arginine methylation is a widespread post-translational modification that regulates numerous RNA-binding proteins and frequently becomes dysregulated in cancer. While PRMT inhibitors have shown promise as an anti-cancer strategy, greater understanding of the downstream pathways linking arginine methylation to tumour-promoting phenotypes is needed to improve patient stratification and develop more effective therapeutic approaches. Here, we reveal arginine methylation as a critical regulator of alternative polyadenylation (APA) patterns that are fundamental to tumour progression. 3' RNA-sequencing assays uncover a rapid and global shift toward longer 3' UTR isoforms upon dual (symmetric and asymmetric) methylation (DMAi), impacting a broad range of cellular proliferation and signalling genes. Arginine methylation is required for sustaining proximal poly(A) site usage under high proliferative demand, as DMAi treatment blocks use of such sites in activated T cells, various cancer cell lines and patient-derived lung organoids. DMAi also counteracts the 3' UTR shortening caused by reduced CFIM25 expression, which normally promotes oncogenic isoforms. DMAi treatment affects APA in many of the same mRNAs as impaired cleavage and polyadenylation activity, and these mRNAs contain characteristic signatures such as high GC-content and long 3 UTRs. This systematic impact of PRMT activity on APA regulation broadens the potential utility of PRMT inhibitors as therapeutic agents for both cancer and immune-related diseases.

molecular biology↗

bioRxiv2024

Integrative analysis of higher-order transcriptome organisation and RNA condensation principles

Complex RNA-protein networks play a pivotal role in the formation of many types of biomolecular condensates. How intrinsic RNA features contribute to condensate formation however remains unclear. Here, we integrate tailored transcriptomics assays to identify a distinct class of developmental condensation-prone RNAs termed smOOPs (semi-extractable, orthogonal organic phase separation-enriched RNAs). These transcripts are localised to larger intracellular foci, form denser RNA-RNA interaction subnetworks than expected and are heavily bound by RNA binding proteins (RBPs). Using an explainable deep learning framework, we reveal that smOOPs harbor characteristic sequence composition with lower sequence complexity, increased intramolecular folding and specific RBP binding patterns. Intriguingly, these RNAs encode proteins bearing extensive intrinsically disordered regions and are markedly predicted to be involved in biomolecular condensates, indicating an interplay between RNA- and protein-based features in phase separation. This work advances our understanding of condensation-prone RNAs and provides a versatile resource to further investigate RNA-driven condensation principles.

molecular biology↗

bioRxiv2023

m6a methylation orchestrates IMP1 regulation of microtubules during human neuronal differentiation

Neuronal differentiation requires building a complex intracellular architecture, and therefore the coordinated regulation of defined sets of genes. RNA-binding proteins (RBPs) play a key role in this regulation. However, while their action on individual mRNAs has been explored in depth, the mechanisms used to coordinate expression of the gene programs shaping neuronal morphology are poorly understood. To address this, we analysed how the paradigmatic RBP IMP1 (IGF2BP1), an essential developmental factor, selects and regulates its RNA targets during the differentiation of human neurons. We performed a combination of system-wide and molecular analyses, revealing that IMP1 developmentally transitions to and directly regulates the expression of mRNAs encoding essential regulators of the microtubule network, a key component of neuronal morphology. Furthermore, we showed that m6A methylation drives the selection of specific IMP1 mRNA targets and their protein expression during the developmental transition from neural precursors to neurons, providing a molecular principle for the onset of target selectivity.

molecular biology↗

bioRxiv2023

Flow: a web platform and open database to analyse, store, curate and share bioinformatics data at scale

Ever-increasing volumes of sequencing data offer potential for large-scale meta-analyses to address significant biological questions. However, challenges such as insufficient data processing information, data quality concerns, and issues related to accessibility and curation often present obstacles. Additionally, most experimental biologists lack the time and expertise needed to independently analyse, manage and share their own data. To overcome these hurdles, we present Flow, a web-based platform that links bioinformatic analysis and database solutions with a user-friendly interface and web API. Flow currently accommodates a range of genomics methods and further DSL2-compliant Nextflow pipelines can be added via a simple JSON schema file. Deployable on local systems or cloud services, an instance is freely accessible to academic researchers at https://flow.bio.

bioinformatics↗

bioRxiv2023

Mutual homeostasis of charged proteins

Protein dosage is regulated to maintain cellular homeostasis and health. The dosage of proteins containing disordered low complexity domains (LCDs) must be particularly well-controlled to prevent aberrant disease, yet no mechanism to maintain homeostasis has been identified1, 2. Here we report a mutual homeostatic mechanism that controls the concentration of such proteins, termed interstasis, in which proteins with similar LCDs co-regulate their combined dosage through collective negative feedback. We focused on the mechanism that exploits the fundamental multivalency of GA-rich RNA regions that encode charged LCDs, including those with arginine-enriched mixed charge domains (R-MCDs). Modest variations in the abundance of an R-MCD protein change the properties of nuclear speckles, a protein-RNA condensate, selectively trapping multivalent GA-rich mRNAs to promote their nuclear retention. This interstasis depends on conserved codon biases, shared by amniotes, which enhance the multivalency of GA-rich regions encoding charged LCDs. The threshold of interstasis is modulated by CLK kinases, which affect the nuclear speckle localisation of proteins such as TRA2B, key binder of GA-rich RNAs. Notably, many classes of LCDs are encoded by RNA regions containing multivalency-enhancing codon biases, each preferentially bound by specific proteins, suggesting that interstasis might co-regulate many classes of functionally related LCD-containing proteins through dose-sensitivity of various types of protein-RNA condensates.

molecular biology↗

bioRxiv2022

A computationally-enhanced hiCLIP atlas reveals Staufen1 RNA binding features and links 3' UTR structure to RNA metabolism

The structure of mRNA molecules plays an important role in its interactions with trans-acting factors, notably RNA binding proteins (RBPs), thus contributing to the functional consequences of this interplay. However, current transcriptome-wide experimental methods to chart these interactions are limited by their poor sensitivity. Here we extend the hiCLIP atlas of duplexes bound by Staufen1 (STAU1) [~]10-fold, through careful consideration of experimental assumptions, and the development of bespoke computational methods which we apply to existing data. We present Tosca, a Nextflow computational pipeline for the processing, analysis and visualisation of proximity ligation sequencing data generally. We use our extended duplex atlas to discover insights into the RNA selectivity of STAU1, revealing the importance of structural symmetry and duplex-span-dependent nucleotide composition. Furthermore, we identify heterogeneity in the relationship between STAU1-bound 3 UTRs and metabolism of the associated RNAs that we relate to RNA structure: transcripts with short-range proximal 3 UTR duplexes have high degradation rates, but those with long-range duplexes have low rates. Overall, our work enables the integrative analysis of proximity ligation data delivering insights into specific features and effects of RBP-RNA structure interactions.

genomics↗

bioRxiv2021

clipplotr - a comparative visualisation and analysis tool for CLIP data

CLIP technologies are now widely used to study RNA-protein interactions and many datasets are now publicly available. An important first step in CLIP data exploration is the visual inspection and assessment of processed genomic data on selected genes or regions and performing comparisons: either across conditions within a particular project, or incorporating publicly available data. However, the output files produced by data processing pipelines or preprocessed files available to download from data repositories are often not suitable for direct comparison and usually need further processing. Furthermore, to derive biological insight it is usually necessary to visualise CLIP signal alongside other data such as annotations, or orthogonal functional genomic data (e.g. RNA-seq). We have developed a simple, but powerful, command-line tool: clipplotr, which facilitates these visual comparative and integrative analyses with normalisation and smoothing options for CLIP data and the ability to show these alongside reference annotation tracks and functional genomic data. These data can be supplied as input to clipplotr in a range of file formats, which will output a publication quality figure. It is written in R and can both run on a laptop computer independently, or be integrated into computational workflows on a high-performance cluster. Releases, source code and documentation are freely available at: https://github.com/ulelab/clipplotr.

bioinformatics↗

bioRxiv2021

An improved iCLIP protocol

Crosslinking and Immunoprecipitation (CLIP) is a powerful technique to obtain transcriptome-wide maps of in vivo protein-RNA interactions, which are important to understand the post-transcriptional mechanisms mediated by RNA binding proteins (RBPs). Many variant CLIP protocols have been developed to improve the efficiency and convenience of cDNA library preparation. Here we describe an improved individual nucleotide resolution CLIP protocol (iiCLIP), which can be completed within 4 days from UV crosslinking to libraries for sequencing. For benchmarking, we directly compared PTBP1 iiCLIP libraries with the iCLIP2 protocol produced under standardised conditions, and with public eCLIP and iCLIP PTBP1 data. We visualised enriched motifs surrounding the identified crosslink positions and RNA maps of these crosslinks around the alternative exons regulated by PTBP1. Notably, motif enrichment was higher in iiCLIP and iCLIP2 in comparison to public eCLIP and iCLIP, and we show how this impacts the specificity of RNA maps. In conclusion, iiCLIP is technically convenient and efficient, and enables production of highly specific datasets for identifying RBP binding sites.

molecular biology↗

bioRxiv2018

Target-specific precision of CRISPR-mediated genome editing

The CRISPR-Cas9 system has successfully been adapted to edit the genome of various organisms. However, our ability to predict editing accuracy, efficacy and outcome at specific sites is limited by an incomplete understanding of how the bacterial system interacts with eukaryotic genomes and DNA repair machineries. Here, we performed the largest comparison of indel profiles to date, examining over one thousand sites in the genome of human cells, and uncovered general principles guiding CRISPR-mediated DNA editing. We find that precision of DNA editing varies considerably among sites, with some targets showing one highly-preferred indel and others displaying a wide range of infrequent indels. Editing precision correlates with editing efficiency, homology-associated end-joining for both insertions and deletions, and a preference for single-nucleotide insertions. Precise targets and the identity of their preferred indel can be predicted based on simple rules that mainly depend on the fourth nucleotide upstream of the PAM sequence. Regardless of precision, site-specific indel profiles are highly robust and depend on both DNA sequence and chromatin features. Our findings have important implications for clinical applications of CRISPR technology and reveal general patterns of broken end-joining that can inform us on DNA repair mechanisms in human cells.

molecular biology↗

bioRxiv2018

Heteromeric RNP assembly at LINEs controls lineage-specific RNA processing

It is challenging for RNA processing machineries to select exons within long intronic regions. We find that intronic LINE repeat sequences (LINEs) contribute to this selection by recruiting dozens of RNA-binding proteins (RBPs). This includes MATR3, which promotes binding of PTBP1 to multivalent binding sites in LINEs. Both RBPs repress splicing and 3 end processing within and around LINEs, as demonstrated in cultured human cells and mouse brain. Notably, repressive RBPs preferentially bind to evolutionarily young LINEs, which are confined to deep intronic regions. These RBPs insulate both LINEs and surrounding regions from RNA processing. Upon evolutionary divergence, gradual loss of insulation diversifies the roles of LINEs. Older LINEs are located closer to exons, are a common source of tissue-specific exons, and increasingly bind to RBPs that enhance RNA processing. Thus, LINEs are hubs for assembly of repressive RBPs, and contribute to evolution of new, lineage-specific transcripts in mammals.

genomics↗

bioRxiv2017

Data Science Issues in Understanding Protein-RNA Interactions

An interplay of experimental and computational methods is required to achieve a comprehensive understanding of protein-RNA interactions. Crosslinking and immunoprecipitation (CLIP) identifies endogenous interactions by sequencing RNA fragments that co-purify with a selected RBP under stringent conditions. Here we focus on approaches for the analysis of resulting data and appraise the methods for peak calling, visualisation, analysis and computational modelling of protein-RNA binding sites. We advocate a combined assessment of cDNA complexity and specificity for data quality control. Moreover, we demonstrate the value of analysing sequence motif enrichment in peaks assigned from CLIP data, and of visualising RNA maps, which examine the positional distribution of peaks around regulated landmarks in transcripts. We use these to assess how variations in CLIP data quality, and in different peak calling methods, affect the insights into regulatory mechanisms. We conclude by discussing future opportunities for the computational analysis of protein-RNA interaction experiments.

bioinformatics↗