Biology subjects

Mognetti, B. M.

Publications and source records attributed to Mognetti, B. M..

5 recordsLinked to original sources

bioRxiv2025

Organization and triggered release of liposomes with DNA-based synthetic condensates

Cells use a combination of membrane-bound and membrane-less compartments to dynamically orchestrate internal biochemical processes and sustain intracellular communication. Recapitulating the hierarchical integration and interplay between these physically and chemically diverse structures is required to enhance the functionalities of synthetic cells and other advanced biomimetic systems. Here, we describe the use of synthetic DNA condensates to selectively uptake and spatially organize lipid vesicles, interacting with the condensates thanks to cholesterol-DNA anchors. By modulating anchor density, the liposomes can be programmably localized on the surface or interior of the condensates, while base-pairing selectivity can be leveraged to target individual internal domains in multi-phasic condensates. The embedded liposomes can be released by adding a nucleic acid trigger and captured by a second condensate population, thus imitating extracellular vesicles in their ability to support long-range cellular communication. This modular platform demonstrates the potential of DNA-based condensates to program the spatial distribution of membranous subcompartments and to support dynamic cargo-handling capabilities. These features are valuable for engineering cell mimics, microreactors, and delivery systems.

synthetic biology↗

bioRxiv2025

Understanding Influenza A Virus particles detaching from reconstructed cell surfaces

Influenza infection is a multistage process that involves the trafficking of viral particles across the cell membrane. Before endocytosis, virions target the membrane by binding hemagglutinin ligands to sialic acid residues on cell receptors. After budding, neuraminidase cleaves these residues, enabling virions to detach from the infected cell surface. ln this paper, we examine detachment dynamics through simulations and the-oretical analysis. We explain experimental findings showing that the time required for virions to detach can decrease as the single-trajectory average number of bridges increases-a counterintuitive result specific to neuraminidase activity. Furthermore, we demonstrate that the detachment time is not governed by a Poisson distribution but depends on multiple factors, including ligand-receptor reaction rates, virion size, and receptor diffusion constant. These results clarify how biochemical parameters regulate the residence time of virions at the cell surface. TOC Graphic O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=111 SRC="FIGDIR/small/668852v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@2ae5d4org.highwire.dtl.DTLVardef@56e756org.highwire.dtl.DTLVardef@16de32dorg.highwire.dtl.DTLVardef@15dda8f_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2025

Evolutionary chemical learning in dimerization networks

We present a novel framework for chemical learning based on Com- petitive Dimerization Networks (CDNs)-- systems in which multiple molecular species, e.g. proteins or DNA/RNA oligomers, reversibly bind to form dimers. We show that these networks can be trained in vitro through directed evolution, enabling the implementation of complex learning tasks such as multiclass classification without digital hardware or explicit parameter tuning. Each molecular species functions analogously to a neuron, with binding affinities acting as tunable synaptic weights. A training protocol involving mutation, selection, and amplification of DNA-based components allows CDNs to robustly discriminate among noisy input patterns. The resulting classifiers exhibit strong output contrast and high mutual information between input and output, especially when guided by a contrastenhancing loss function. Comparative analysis with in silico gradient descent training reveals closely correlated performance. These results establish CDNs as a promising platform for analog physical computation, bridging synthetic biology and machine learning, and advancing the development of adaptive, energy-efficient molecular computing systems. Significance StatementThis study introduces a new paradigm for learning based on chemical reaction networks rather than digital circuits. Using Competitive Dimerization Networks (CDNs)--biomolecular systems in which species reversibly bind to form dimers--complex classification tasks are learned through in vitro directed evolution. This approach eliminates the need for digital hardware or gradient-based optimization, relying instead on intrinsic molecular dynamics for computation. The resulting chemical classifiers achieve high fidelity and robustness to noise, with performance comparable to that of gradient descent training. These findings establish CDNs as a scalable, energy-efficient platform for molecular computing, suggesting broad potential applications in diagnostics, biosensing, synthetic biology, and nanotechnology, where programmable, adaptive chemical systems could serve as alternatives to conventional electronic processors.

bioengineering↗

bioRxiv2023

The sliding motility of the bacilliform virions of Influenza A Viruses

Influenza A virus (IAV) infection relies on the action of the hemagglutinin (HA) and neuraminidase (NA) membrane proteins. The HA ligands anchor the IAV virion to the cells surface by binding the sialic acid (SA) present on the hosts receptors while NA is an enzyme capable of cleaving the SA from the extracellular environment. It is believed that the activity of NA ligands increases the motility of the virions favoring the propagation of the infection. In this work, we develop a numerical framework to study the dynamics of a virion moving across the cell surface for timescales much bigger than the typical ligand-receptor reaction times. We find that the rates controlling the ligand-receptor reactions and the maximal distance at which a pair of ligand-receptor molecules can interact greatly affect the motility of the virions. We also report on how different ways of organizing the two types of ligands on the virions surface result in different types of motion that we rationalize using general principles. In particular, we show how the emerging motility of the virion is less sensitive to the rate controlling the enzymatic activity when NA ligands are clustered. These results help to assess how variations in the biochemical properties of the ligand-receptor interactions (as observed across different IAV subtypes) affect the dynamics of the virions at the cell surface.

biophysics↗

bioRxiv2023

DNA-origami line-actants control domain organisation and fission in synthetic membranes

Cells can precisely program the shape and lateral organisation of their membranes using protein machinery. Aiming to replicate a comparable degree of control, here we introduce DNA-Origami Line-Actants (DOLAs) as synthetic analogues of membrane-sculpting proteins. DOLAs are designed to selectively accumulate at the line-interface between co-existing domains in phase-separated lipid membranes, modulating the tendency of the domains to coalesce. With experiments and coarse-grained simulations, we demonstrate that DOLAs can reversibly stabilise two-dimensional analogues of Pickering emulsions on synthetic giant liposomes, enabling dynamic programming of membrane lateral organisation. The control afforded over membrane structure by DOLAs extends to three-dimensional morphology, as exemplified by a proof-of-concept synthetic pathway leading to vesicle fission. With DOLAs we lay the foundations for mimicking, in synthetic systems, some of the critical membrane-hosted functionalities of biological cells, including signalling, trafficking, sensing, and division.

biophysics↗