Biology subjects

Miotto, M.

Publications and source records attributed to Miotto, M..

9 recordsLinked to original sources

bioRxiv2025

Missense mutations on SynGAP C2 domain impair membrane diffusion

SYNGAP1 mutations have been linked to a range of neuropathological disorders and, more recently, to the insurgence of cancer. Despite its emerging relevance, the molecular basis of SynGAPs action remains poorly understood. Here, using extensive molecular dynamics simulations integrated with structural analysis, we define how the SynGAP C2 domain associates with lipid bilayers. In particular, we observed spontaneous membrane binding of the domain in two distinct orientations, top and side, defined by the relative positioning of the C2 domain to its fold. These modes display markedly different dynamical properties: the top mode enables faster lateral diffusion on the membrane surface, whereas the side mode establishes more stable but less mobile contacts. Interestingly, pathogenic missense mutations mapping to the membrane-facing loops of SynGAP C2 disrupt these dynamics, leading to reduced diffusivity and altered membrane avidity. Our findings reveal a dual binding mechanism that underlies SynGAPs membrane versatility and offer a general framework for how diverse mutations may perturb SynGAP activity across its polyedric biological functions.

biophysics↗

bioRxiv2025

Preventing pathogenic dimerization in a misfolded antibody light chain through the design of an inhibitory peptide

Immunoglobulin light chain (AL) amyloidosis is the most common form of systemic amyloidosis. The disease correlates with the formation of insoluble aggregates mostly composed by patient-specific antibody light chains, whose hypervariable regions make each case unique and highlight the need for personalized therapeutics. In this study, we focused on a pathogenic homodimer we previously obtained from a patient-derived light chain. By analyzing the dynamics and the interface of this dimer, we identified a 15-residue peptide with potential inhibitory activity. The peptide was then refined using a computational mutagenesis protocol that iteratively improved its sequence to maximize complementarity with the protein interface, taking into account shape, electrostatics, and hydropathy. The resulting optimized peptide is found to bind the monomer with a binding affinity comparable to that of the full pathogenic interface. These results suggest that the designed peptide could act as an effective antagonist of the pathogenic dimer, and demonstrate that our computational strategy could provide a general framework for designing patient-specific inhibitory peptides against aggregation-prone proteins.

biochemistry↗

bioRxiv2025

Targeted Antisense Oligonucleotide Treatment Rescues Developmental Alterations in Spinal Muscular Atrophy Organoids

Spinal muscular atrophy (SMA) is a severe neurological disease caused by mutations in the SMN1 gene, characterized by early onset and degeneration of lower motor neurons. Understanding early neurodevelopmental defects in SMA is crucial for optimizing therapeutic interventions. Using spinal cord and cerebral organoids generated from multiple SMA type I donors, we revealed widespread disease mechanisms beyond motor neuron degeneration. Single-cell transcriptomics uncovered pervasive alterations across neural populations, from progenitors to neurons, demonstrating SMN-dependent dysregulation of neuronal differentiation programs. Multi-electrode array analysis identified consistent hyperexcitability in both spinal and brain organoids, establishing altered electrical properties as a central nervous system-wide feature of pathogenesis. Early administration of an optimized antisense oligonucleotide (ASO) that restored SMN levels rescued morphological and functional deficits in spinal cord organoids across different genetic backgrounds. Importantly, this early intervention precisely corrected aberrant splicing in newly identified SMN1 targets enriched at critical nodes of neuronal differentiation. Our findings demonstrate that early developmental defects are core features of SMA pathogenesis that can be prevented by timely therapeutic intervention, providing new insights for optimizing treatment strategies.

neuroscience↗

bioRxiv2022

Molecular dynamics analysis of Superoxide Dismutase 1 mutations suggests decoupling between mechanisms underlying ALS onset and progression

Mutations in the superoxide dismutase 1 (SOD1) gene are the second most common known cause of ALS. SOD1 variants express high phenotypic variability and over 200 have been reported in people with ALS. Investigating how different SOD1 variants affect the protein dynamics might help in understanding their pathogenic mechanism and explaining their heterogeneous clinical presentation. It was previously proposed that variants can be broadly classified in two groups, wild-type like (WTL) and metal binding region (MBR) variants, based on their structural location and biophysical properties. MBR variants are associated with a loss of SOD1 enzymatic activity. In this study we used molecular dynamics and large clinical datasets to characterise the differences in the structural and dynamic behaviour of WTL and MBR variants with respect to the wild-type SOD1, and how such differences influence the ALS clinical phenotype. Our study identified marked structural differences, some of which are observed in both variant groups, while others are group specific. Moreover, applying graph theory to a network representation of the proteins, we identified differences in the intramolecular contacts of the two classes of variants. Finally, collecting clinical data of approximately 500 SOD1 ALS patients carrying variants from both classes, we showed that the survival time of patients carrying an MBR variant is generally longer (~6 years median difference, p < 0.001) with respect to patients with a WTL variant. In conclusion, our study highlights key differences in the dynamic behaviour of the WTL and MBR SOD1 variants, and wild-type SOD1 at an atomic and molecular level. We identified interesting structural features that could be further investigated to explain the associated phenotypic variability. Our results support the hypothesis of a decoupling between mechanisms of onset and progression of SOD1 ALS, and an involvement of loss-of-function of SOD1 with the disease progression.

neuroscience↗

bioRxiv2022

Novel Computational Models of Evoked Dopamine Release In Vivo Measured by Fast Scan Cyclic Voltammetry Quantify the Regulation of Presynaptic Kinetics by Synucleins

Dopamine neurotransmission in the striatum is central to many normal and disease functions. Ventral midbrain dopamine neurons exhibit ongoing tonic firing that produce low extrasynaptic levels of dopamine below the detection of extrasynaptic electrochemical recordings ([~]10 - 20 nanomolar), with superimposed bursts that can saturate the dopamine uptake transporter and produce transient micromolar concentrations. The bursts have previously been shown to lead to presynaptic plasticity via multiple mechanisms, but analysis methods for these kinetic parameters are limited. To provide a deeper understanding of the mechanics of dopamine neurotransmission, we present three computational models of dopamine release with different levels of spatiotemporal complexity to analyze in vivo fast-scan cyclic voltammetry recordings from the dorsal striatum of mice. The models accurately fit to the cyclic voltammetry data and provide estimates of presynaptic dopamine facilitation/depression kinetics and dopamine transporter reuptake kinetics. We use the models to analyze the role of synuclein proteins in neurotransmission and quantify recent findings linking presynaptic protein -synuclein to the short-term facilitation and long-term depression of dopamine release.

neuroscience↗

bioRxiv2021

Inferring the stabilization effects of SARS-CoV-2 variants on the binding with ACE2 receptor

With the progression of the SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) pandemic, several variants of the virus are emerging with mutations distributed all over the viral sequence. While most of them are expected to have little to no effects at the phenotype level, some of these variants presenting specific mutations on the Spike protein are rapidly spreading, making urgent the need of characterizing their effects on phenotype features like contagiousness and antigenicity. With this aim, we performed extensive molecular dynamics simulations on a selected set of possible Spike variants in order to assess the stabilizing effect of particular amino acid substitutions, with a special focus on the mutations that are both characteristic of the top three most worrying variants at the moment, i.e the English, South African and Amazonian ones, and that occur at the molecular interface between SARS-CoV-2 Spike protein and its human ACE2 receptor. We characterize these variants effect in terms of (i) residues mobility, (ii) compactness, studying the network of interactions at the interface, and (iii) variation of shape complementarity via expanding the molecular surfaces in the Zernike basis. Overall, our analyses highlighted greater stability of the three variant complexes with respect to both the wild type and two negative control systems, especially for the English and Amazonian variants. In addition, in the three variants, we investigate the effects a not-yet observed mutation in position 501 could provoke on complex stability. We found that a phenylalanine mutation behaves similarly to the English variant and may cooperate in further increasing the stability of the South African one, hinting at the need for careful surveillance for the emergence of such kind of mutations in the population. Ultimately, we show that the observables we propose describe key features for the stability of the ACE2-spike complex and can help to monitor further possible spike variants.

biophysics↗

bioRxiv2021

Asymmetric Binomial Statistics Explains Organelle Partitioning Variance in Cancer Cell Proliferation

Asymmetric inheritance of organelle and cellular compounds between daughter cells impacts on the phenotypic variability and was found to be a hallmark for differentiation and rejuvenation in stem-like cells as much as a mechanism for enhancing resistance in bacteria populations. Whether the same processes take place in the context of cancer cell lines is still poorly investigated. Here, we present a method that allows the measurement of asymmetric organelle partitioning, and we use it to simultaneously measure the partitioning of three kinds of cellular elements, i.e. cytoplasm, membrane, and mitochondria in a proliferating population of human Jurkat T-cells. For this porpoise, we use multiple live cell markers which permit us both to follow the partitioning process for multiple generations and to investigate the correlations between the partitioning of different cellular constituents. Assuming a minimal model of asymmetric partitioning where cell sub-components are divided according to a biased binomial statistics, we derived exact analytical relationships for the average fluorescence intensity and its fluctuations as a function of the generation, obtaining an excellent agreement with the experimental measurements. We found that although cell cytoplasm is divided symmetrically, mitochondria and membrane lipids are asymmetrically distributed between the two daughter cells and present a stable positive correlation with cytoplasm apportioning, which is incompatible with an independent division mechanism. Therefore, our findings show that asymmetric segregation mechanisms can also arise in cancer cell populations, and that, in this case, membrane lipids and mitochondria do not respectively segregate independently from the cytoplasm. This helps us understand the high phenotypic variability reported in these cancer cell lines. In perspective, this could be particularly relevant in the case of tumor micro-environment diversity, where comprehension of the non-genetic cell heterogeneity could pave the way to novel and more targeted therapies. Moreover, the developed experimental and theoretical apparatus can be easily generalized to different cell kinds and different cell sub-components providing a powerful tool for understanding partitioning-driven heterogeneity.

systems biology↗

bioRxiv2020

In-Silico evidence for two receptors based strategy of SARS-CoV-2

We propose a novel numerical method able to determine efficiently and effectively the relationship of complementarity between portions of protein surfaces. This innovative and general procedure, based on the representation of the molecular iso-electron density surface in terms of 2D Zernike polynomials, allows the rapid and quantitative assessment of the geometrical shape complementarity between interacting proteins, that was unfeasible with previous methods. We first tested the method with a large dataset of known protein complexes obtaining an overall area under the ROC curve of 0.76 in the blind recognition of binding sites and then applied it to investigate the features of the interaction between the Spike protein of SARS-CoV-2 and human cellular receptors. Our results indicate that SARS-CoV-2 uses a dual strategy: its spike protein could also interact with sialic acid receptors of the cells in the upper airways, in addition to the known interaction with Angiotensin-converting enzyme 2.

biophysics↗

bioRxiv2018

Insights on protein thermal stability: a graph representation of molecular interactions

Understanding the molecular mechanisms of thermal stability is a challenge in protein biology. Indeed, knowing the temperature at which proteins are stable has important theoretical implications, which are intimately linked with properties of the native fold, and a wide range of potential applications from drug design to the optimization of enzyme activity.\n\nHere, we present a novel graph-theoretical framework to assess thermal stability based on the structure without any a priori information. In our approach we describe proteins as energy-weighted graphs and compare them using ensembles of interaction networks. Investigating the position of specific interactions within the 3D native structure, we developed a parameter-free network descriptor that permits to distinguish thermostable and mesostable proteins with an accuracy of 76% and Area Under the Roc Curve of 78%.

bioinformatics↗