Biology subjects

Iosub, I. A.

Publications and source records attributed to Iosub, I. A..

6 recordsLinked to original sources

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

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

Fine-tuning of RecBCD expression by post-transcriptional regulation is required for optimal DNA repair in Escherichia coli

All living organisms have developed strategies to respond to chromosomal damage and preserve genome integrity. One such response is the repair of DNA double-strand breaks (DSBs), one of the most toxic forms of DNA lesions. In Escherichia coli, DSBs are repaired via RecBCD-dependent homologous recombination. RecBCD is essential for accurate chromosome maintenance, but its over-expression can lead to reduced DNA repair ability. This apparent paradox suggests that RecBCD copy numbers may need to be tightly controlled within an optimal range. Using single-molecule fluorescence microscopy, we have established that RecB is present in very low abundance at mRNA and protein levels. RecB transcription shows high fluctuations, yet cell-to-cell protein variability remains remarkably low. Here, we show that the post-transcriptional regulator Hfq binds to recB mRNA and down-regulates RecB protein translation in vivo. Furthermore, specific disruption of the Hfq-binding site leads to more efficient translation of recB mRNAs. In addition, we observe a less effective reduction of RecB protein fluctuations in the absence of Hfq. This fine-tuning Hfq-mediated mechanism might have the underlying physiological function of maintaining RecB protein levels within an optimal range.

systems biology↗

bioRxiv2018

Hfq CLASH uncovers sRNA-target interaction networks enhancing adaptation to nutrient availability

By shaping gene expression profiles, small RNAs (sRNAs) enable bacteria to very efficiently adapt to constant changes in their environment. To better understand how Escherichia coli acclimatizes to changes in nutrient availability, we performed UV cross-linking, ligation and sequencing of hybrids (CLASH) to uncover sRNA-target interactions. Strikingly, we uncovered hundreds of novel Hfq-mediated sRNA-target interactions at specific growth stages, involving many novel 3UTR-derived sRNAs and a plethora of sRNA-sRNA interactions. We discovered sRNA-target interaction networks that play a role in adaptation to changes in nutrient availability. We characterized a novel 3UTR-derived sRNA (MdoR), which is part of a regulatory cascade that enhances maltose uptake by (a) inactivating repressive pathways that block the accumulation of maltose transporters and (b) by reducing the flux of general porins to the outer membrane. Our work provides striking examples of how bacteria utilize sRNAs to integrate multiple regulatory pathways to enhance nutrient stress adaptation.

systems biology↗