Biology subjects

Chiodo, L.

Publications and source records attributed to Chiodo, L..

4 recordsLinked to original sources

bioRxiv2026

Modularity-dependent storage of dynamic spiking patterns: bridging micro- and mesoscopic representations

Biological systems rely on asynchronous and temporally overlapping dynamics, allowing for the concurrent activation of multiple processes. This principle is particularly evident in brain function, where cognitive tasks engage distributed, interacting regions rather than sequentially isolated ones. To investigate the mechanisms enabling such coordination, we study a modular spiking neural network composed of leaky integrate-and-fire neurons and governed by spike-timing-dependent plasticity (STDP). Our model stores modular spatiotemporal patterns both at the mesoscopic level (sequences of modules) and at the microscopic level (precise spike timings) and includes a parameter, , which regulates the degree of temporal overlap between modules activations. By tuning , the network transitions from sequential to overlapping regimes, ranging from synfire chain-like dynamics to fully co-activated modules. We investigate how the temporal structure influences the networks capacity to encode and selectively retrieve multiple dynamical patterns, while considering biological constraints such as the cost of long-range connectivity. Our results offer insight into how spatiotemporal coding and network organisation support robust, large-scale memory storage and replay.

neuroscience↗

bioRxiv2025

Decoding RNA Triple Helices: Identification from Sequence and Secondary Structure

The discovery of long non-coding RNAs has revealed additional layers of gene-expression control. Specific interactions of lncRNAs with DNA, RNAs, and RNA-binding proteins enable regulation in both cytoplasmic and nuclear compartments; for example, a conserved triple-helix motif is essential for MALAT1 stability and oncogenic activity. Here we present a secondary-structure-based framework to annotate and detect RNA triple helices. First, we extend the dot-bracket formalism with a third annotation line that encodes Hoogsteen contacts. Second, we introduce TripleMatcher, which searches for a triple-helix pattern, filters candidates by C1'-C1' distance thresholds, and merges overlaps into region-level zones. Using telomerase RNAs and RNA-stability elements with experimentally established triple helices (8 RNAs), TripleMatcher localized all annotated regions (structure-wise detection 8/8); geometric filtering removed most spurious candidates and improved precision (PPV from 0.42 to 0.81) and overall accuracy (F1 from 0.42 to 0.62) while maintaining sensitivity. Benchmarking eight predictors showed that pseudoknot-aware methods most reliably reproduce the local architecture required for detection, aligning secondary-structure quality with downstream triple-helix recovery. Applied prospectively, the framework identified candidate regions directly from predicted secondary structures and scaled to a screen of 4,147 RNAs, where distance filtering reduced 150,948 raw candidates to 90 geometrically feasible regions across seven molecules, including human telomerase complexes. Together, the notation and TripleMatcher provide a concise route from secondary structure to a small, interpretable set of triple-helix candidates suitable for targeted experimental validation.

bioinformatics↗

bioRxiv2024

Criticality explains structure-function relationships in the human brain

Healthy brain exhibits a rich dynamical repertoire, with flexible spatiotemporal patterns replays on both microscopic and macroscopic scales. How do fixed structural connections yield a diverse range of dynamic patterns in spontaneous brain activity? We hypothesize that the observed relationship between empirical structure and functional patterns is best explained when the microscopic neuronal dynamics is close to a critical regime. Using a modular Spiking Neuronal Network model based on empirical connectomes, we posit that multiple stored functional patterns can transiently reoccur when the system operates near a critical regime, generating realistic brain dynamics and structural-functional relationships. The connections in the model are chosen as to force the network to learn and propagate suited modular spatiotemporal patterns. To test our hypothesis, we employ magnetoencephalography and tractography data from five healthy individuals. We show that the critical regime of the model is able to generate realistic features, and demonstrate the relevance of near-critical regimes for physiological brain activity.

neuroscience↗

bioRxiv2022

In silico conformational features of botulinum toxins A1 and E1 according to the intraluminal acidification

Although the botulinum neurotoxins (BoNTs) are among the most toxic compounds found in nature, their molecular mechanism of action is far from being elucidated. A key event is the conformational transition due to the acidification of the interior of synaptic vesicles, and leading to the translocation of the BoNT catalytic domain into the neuronal cytosol. To investigate these conformational variations, homology modelling and atomistic simulations are combined to explore the internal dynamics of the subtypes BoNT/A1, the most-used in medical applications, and BoNT/E1, the most kinetically efficient. This first simulation study of di-chain BoNTs in closed and open states includes the effects of neutral and acidic pH. The conformational mobility is driven by domains displacements; the ganglioside binding site in the receptor binding domain, the translocation domain (HCNT) switch and the belt helix visit multiple conformations depending on the primary sequence and on the pH. Fluctuations of the belt helix are observed for closed conformations of the toxins and at acidic pH, and patches of more accessible residues appear in the same conditions in the core translocation domain HCNT. These findings suggest that during translocation, the larger mobility of belt could be transmitted to HCNT, leading to a favorable interaction of HCNT residues with the non-polar membrane environment. Key ContributionThe molecular dynamics simulations presented here provide a structural and functional annotation of full-length BoNTs composed by two distinct protein chains. Two different conformations (open and closed) as well as two different protonation states, corresponding to acidic and neutral pH, have been considered. Results from the present work supports a model of mobility in which the individual domains fluctuate around stable conformations and the overall structure mobility arise from relative displacements of the domains.

neuroscience↗