Biology subjects

Delli Ponti, R.

Publications and source records attributed to Delli Ponti, R..

8 recordsLinked to original sources

bioRxiv2026

A circRNA-derived IRES-like element enables programmable translational activation of the endogenous chaperone HSP90

Circular RNAs (circRNAs) are covalently closed transcripts that lack a 5' cap, consequently their translation depends on cap-independent initiation, in most cases through Internal Ribosome Entry Sites (IRESs). Whereas IRES-mediated translation has been studied almost exclusively in cis, the use of IRES-containing circRNAs to activate translation of an independent mRNA in trans has only recently begun to be explored. Here, we characterize SynFarsa, a synthetic circRNA-derived IRES-like element that promotes cap-lindependent translation in mouse and human cells. We engineered SynFarsa into a trans-acting regulator by fusing it to a short antisense sequence complementary to a selected region of a target mRNA. This reproduces the architecture of a circular SINEUP, in which IRES activity promotes translation in trans of a transcript recognized through antisense complementarity. Directing this construct to the hsp90 3'UTR increased HSP90 protein levels approximately 1.6-lfold without altering hsp90 mRNA abundance, whereas the hsp70 3'UTR and the 5'UTRs of both transcripts were not permissive, indicating that activity depends strongly on target site selection. In a FUSP525L neuroblastoma model of Amyotrophic Lateral Sclerosis, this increase in HSP90 was accompanied by a reduction in the number and size of cytoplasmic FUS aggregates. SynFarsa thus provides a circRNA-derived effector domain for targeted translational upregulation of an endogenous protein.

biochemistry↗

bioRxiv2025

Integrating RNA Structure and Protein Interactions to Uncover the Mechanisms of Viral and Cellular IRES Function

BackgroundRNAs fold into complex structures that critically influence gene expression. A prominent class of regulatory elements resides in the 5' untranslated region (5' UTR), where internal ribosome entry sites (IRESs) promote cap-independent translation by directly engaging the ribosome. First discovered in viral genomes, IRESs have been classified into four types according to their structural compactness and factor requirements. While viral IRESs are well studied, cellular IRESs remain poorly understood: they display limited sequence conservation, reduced structural compactness, and variable dependence on auxiliary RNA-binding proteins known as IRES trans-acting factors (ITAFs). Whether their activity relies mainly on RNA structure or protein assistance remains unresolved. Here, we present a computational framework that combines in silico mutagenesis and RNA-protein interaction profiling to investigate IRES mechanisms and guide the design of synthetic elements. ResultsUsing the Hepatitis C Virus (HCV) IRES as a benchmark, we performed systematic single-nucleotide mutagenesis coupled with structural predictions. Mutations were classified as synonymous or non-synonymous based on their effect on the secondary structure. The HCV IRES showed overall robustness, but the domain interacting with eIF3 was particularly sensitive, consistent with its essential role in translation initiation. Extending this approach to other viral IRES families revealed distinct profiles of resilience: Aphthoviruses retained structural integrity despite extensive sequence variation, whereas Cripaviruses displayed higher variability. We then applied the same analysis to cellular IRESs, which proved more structurally sensitive, suggesting stronger reliance on cofactor support. To probe this connection, we used the catRAPID approach to predict interactions with translation-related proteins. The method distinguished IRESs with known ITAF binding, such as PTBP1, and highlighted stability-promoting mutations that increased the predicted affinity for translation factors. ConclusionsOur in silico analysis indicates that mutational tolerance mirrors IRES cofactor dependence: compact viral IRESs are structurally robust, whereas non-viral IRESs are more reliant on protein interactions. By linking structure prediction with interaction profiling, we identify variants that both stabilize IRESs and improve binding to ITAFs or translation factors. This framework provides mechanistic insight into sequence-structure-function relationships and supports the rational design of synthetic IRES elements for therapeutic and biotechnological applications.

biochemistry↗

bioRxiv2024

Rationalizing the Effects of RNA Modifications on Protein Interactions

RNA modifications play a crucial role in regulating gene expression by altering RNA structure and modulating interactions with RNA-binding proteins (RBPs). In this study, we explore the impact of specific RNA chemical modifications--N6-methyladenosine (mA), A-to-I editing, and pseudouridine ({Psi})--on RNA secondary structure and protein-RNA interactions. Utilizing genome-wide data, including RNA secondary structure predictions and protein-RNA interaction datasets, we classify proteins into distinct categories based on their binding behaviors: modification-specific and structure-independent, or modification-promiscuous and structure-dependent. For instance, mA readers like YTHDF2 exhibit modification-specific and structure-independent binding, consistently attaching to mA regardless of structural changes. Conversely, proteins such as U2AF2 display modification-promiscuous and structure-dependent behavior, altering their binding preferences in response to structural changes induced by different modifications. A-to-I editing, which causes significant structural changes, typically reduces protein interactions, while {Psi} enhances RNA structural stability, albeit with variable effects on protein binding. To better predict these interactions, we developed the catRAPID 2.0 RNA modifications algorithm, which forecasts the effects of RNA modifications on protein-RNA binding propensities. This algorithm serves as a valuable tool for researchers, enabling the prediction and analysis of RNA modifications impact on protein interactions, thus offering new insights into RNA biology and engineering. The catRAPID 2.0 RNA modifications tool is available at http://service.tartaglialab.com/new_submission/catrapid_omicsv2_rna_mod. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/610603v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@136148corg.highwire.dtl.DTLVardef@17f2d65org.highwire.dtl.DTLVardef@7d4ce9org.highwire.dtl.DTLVardef@447e47_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2020

Structural analysis of SARS-CoV-2 andprediction of the human interactome

Specific elements of viral genomes regulate interactions within host cells. Here, we calculated the secondary structure content of >2000 coronaviruses and computed >100000 human protein interactions with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The genomic regions display different degrees of conservation. SARS-CoV-2 domain encompassing nucleotides 22500 - 23000 is conserved both at the sequence and structural level. The regions upstream and downstream, however, vary significantly. This part codes for the Spike S protein that interacts with the human receptor angiotensin-converting enzyme 2 (ACE2). Thus, variability of Spike S may be connected to different levels of viral entry in human cells within the population. Our predictions indicate that the 5 end of SARS-CoV-2 is highly structured and interacts with several human proteins. The binding proteins are involved in viral RNA processing such as double-stranded RNA specific editases and ATP-dependent RNA-helicases and have strong propensity to form stress granules and phase-separated complexes. We propose that these proteins, also implicated in viral infections such as HIV, are selectively recruited by SARS-CoV-2 genome to alter transcriptional and post-transcriptional regulation of host cells and to promote viral replication.

bioinformatics↗

bioRxiv2019

N1-methyladenine safeguards against aberrant RNA-protein association during proteostasis stress

Post-transcriptional modifications of nucleotide bases can effect several aspects of mRNA function. For example, the recent work has established the role of m6A in the coordinated regulation of transcriptome turnover and translation during cellular differentiation and tumorigenesis. The levels of m1A in mRNAs reach up to 10% of those of m6A, yet the functional consequences of this modification are much less clear. Here we show that N1-methyladenine protects mRNAs against aberrant interactions during heat shock and amyloidogenesis in mammalian cells. The m1A methylation motif correlated with the enhanced sequestration of transcripts in stress granules (SG). The cognate methyltransferase TRMT6/61A accumulated and m1A was enriched in SG. Downregulation of the catalytic subunit TRMT61A enhanced amyloidogenesis in the cytosol and increased bystander protein and RNA co-aggregation with A{beta} aggregates. Faulty granulation of mutant RNAs has been implicated in pathogenesis of protein aggregation disorders. Our results demonstrate that also normal mRNAs succumb to co-aggregation with proteins if RNA dynamics during stress is disturbed due to the insufficient N1-adenine methylation.

cell biology↗

bioRxiv2019

CROSSalive: a web server for predicting the in vivo structure of RNA molecules

Here we introduce CROSSalive, an algorithm to predict the RNA secondary structure profile (double and single stranded regions) in vivo and without sequence length limitations. Using predictions of protein interactions CROSSalive predicts the effect of N6 adenosine methylation (m6a) on RNA structure. Trained on icSHAPE data in presence (m6a+) and absence (m6a-) of methylation CROSSalive achieves an accuracy of 0.88 on the test set. The algorithm was also applied to the murine long non-coding RNA Xist (17900 nt, not present in the training) and shows a Pearsons correlation of 0.45 with SHAPE-map data. CROSSalive webserver is freely accessible at the following page: http://service.tartaglialab.com/new_submission/crossalive

bioinformatics↗

bioRxiv2018

A method for RNA structure prediction shows evidence for structure in lncRNAs

To compare the secondary structures of RNA molecules we developed the CROSSalign method. CROSSalign is based on the combination of the Computational Recognition Of Secondary Structure (CROSS) algorithm to predict the RNA secondary structure at single-nucleotide resolution using sequence information, and the Dynamic Time Warping (DTW) method to align profiles of different lengths. We applied CROSSalign to investigate the structural conservation of long non-coding RNAs such as XIST and HOTAIR as well as ssRNA viruses including HIV. In a pool of sequences with the same secondary structure CROSSalign accurately recognizes repeat A of XIST and domain D2 of HOTAIR and outperforms other methods based on covariance modelling. CROSSalign can be applied to perform pair-wise comparisons and is able to find homologues between thousands of matches identifying the exact regions of similarity between profiles of different lengths. The algorithm is freely available at the webpage http://service.tartaglialab.com//new_submission/CROSSalign.

bioinformatics↗

bioRxiv2018

Phase Separations Driven by RNA Scaffolds and Protein Sequestration in FXTAS

Recent evidence indicates that specific RNAs promote formation of ribonucleoprotein condensates by acting as scaffolds for RNA-binding proteins (RBPs).\n\nWe systematically investigated RNA-RBP interaction networks to understand ribonucleoprotein assembly. We found that highly-contacted RNAs are highly structured, have long untranslated regions (UTRs) and contain nucleotide repeat expansions. Among the RNAs with such properties, we identified the FMR1 3 UTR that harbors CGG expansions implicated in Fragile X-associated Tremor/Ataxia Syndrome (FXTAS).\n\nWe studied FMR1 binding partners in silico and in vitro and prioritized the splicing regulator TRA2A for further characterization. In a FXTAS cellular model we validated TRA2A-FRM1 interaction and investigated implications of its sequestration at both transcriptomic and post-transcriptomic levels. We found that TRA2A co-aggregates with FMR1 in a FXTAS mouse model and in post mortem human samples.\n\nOur integrative study identifies key components of ribonucleoprotein aggregates, providing links to neurodegenerative disease and allowing the discovery of new therapeutic targets.

molecular biology↗