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Nucleic acids and lipids function in close proximity in biological processes, as well as in nanoengineered constructs for therapeutic applications. As both molecules carry a rich charge profile, and frequently coexist in complex ionic solutions, the electrostatics surely play a pivotal role in interactions between them. Here we discuss how each component of a DNA/ion/lipid system determines its electrostatic attachment. We examine membrane binding of a library of DNA molecules varying from nanoengineered DNA origami through plasmids to short DNA domains, demonstrating the interplay between the molecular structure of the nucleic acid and the phase of lipid bilayers. Furthermore, the magnitude of DNA/lipid interactions is tuned by varying the concentration of magnesium ions in the physiologically relevant range. Notably, we observe that the structural and mechanical properties of DNA are critical in determining its attachment to lipid bilayers and demonstrate that binding is correlated positively with the size, and negatively with the flexibility of the nucleic acid. The findings are utilized in a proof-of-concept comparison of membrane interactions of two DNA origami designs - potential nanotherapeutic platforms - showing how the results can have a direct impact on the choice of DNA geometry for biotechnological applications.

The interplay between nucleic acids and lipids underpins several key processes in molecular biology, synthetic biotechnology, vaccine technology, and nanomedicine. These interactions are often electrostatic in nature, and much of their rich phenomenology remains unexplored in view of the chemical diversity of lipids, the heterogeneity of their phases, and the broad range of relevant solvent conditions. Here we unravel the electrostatic interactions between zwitterionic lipid membranes and DNA nanostructures in the presence of physiologically relevant cations, with the purpose of identifying new routes to program DNA-lipid complexation and membrane-active nanodevices. We demonstrate that this interplay is influenced by both the phase of the lipid membranes and the valency of the ions and observe divalent cation bridging between nucleic acids and gel-phase bilayers. Furthermore, even in the presence of hydrophobic modifications on the DNA, we find that cations are still required to enable DNA adhesion to liquid-phase membranes. We show that the latter mechanism can be exploited to control the degree of attachment of cholesterol-modified DNA nanostructures by modifying their overall hydrophobicity and charge. Besides their biological relevance, the interaction mechanisms we explored hold great practical potential in the design of biomimetic nanodevices, as we show by constructing an ion-regulated DNA-based synthetic enzyme.

Evaluating the toxicity of self-assembled protein states is a key step towards developing effective strategies against amyloidogenic pathologies such as Alzheimer's and Parkinson's diseases. Such analysis is directly connected to quantitatively probing the stability of the cellular membrane upon interaction with different protein states. Using a combination of spectroscopic techniques, morphological observations, and spectral analysis of membrane fluctuations, we identify different destabilisation routes for giant unilamellar vesicles interacting with native-like states, prefibrillar species and amyloid-like fibrils of α-lactalbumin. These effects range from substantially lowering the bending rigidity of the membranes to irreversible structural changes and complete disruption of the lipid bilayers. Our findings clearly indicate how the wide heterogeneity in structures occurring during protein aggregation can result in different destabilisation pathways, acting on different length scales and not limited to enhanced membrane permeability.

Ligand/receptor multivalent interactions have been exploited to drive self-assembly of nanoparticles, hard colloids, and, more recently, compliant units including emulsion droplets and lipid vesicles. In deformable liposomes, formation of links between two membranes produces morphological changes depending on the amount of ligands in the environment. Here, we study a proof-of-concept biosensing system in which single lipid vesicles adhere to a flat supported lipid bilayer, both decorated with membrane-anchored biotinylated receptors. Adhesion is driven by multivalent streptavidin (SA) ligands forming bridges between the vesicles and the supported bilayer. Upon changing the concentration of ligands, we characterize the morphological and mechanical changes of the vesicles, including the formation of a stable adhesion patch, membrane tension, and the kinetics of bridge rupture/formation. We observe vesicle binding only within a specific range of ligand concentrations: adhesion does not occur if the amount of SA is either too low or too high. A theoretical model is presented, elucidating the mechanism underlying this observation, particularly, the role of SA multivalency in determining the onset of adhesion. We elaborate on how the behavior of membranes studied here could be exploited in next-generation (bio)molecular analytical devices.

We study phase behaviour of lipid-bilayer vesicles functionalised by ligand-receptor complexes made of synthetic DNA by introducing a modelling framework and a dedicated experimental platform. In particular, we perform Monte Carlo simulations that combine a coarse grained description of the lipid bilayer with state of art analytical models for multivalent ligand-receptor interactions. Using density of state calculations, we derive the partition function in pairs of vesicles and compute the number of ligand-receptor bonds as a function of temperature. Numerical results are compared to microscopy and fluorimetry experiments on large unilamellar vesicles decorated by DNA linkers carrying complementary overhangs. We find that vesicle aggregation is suppressed when the total number of linkers falls below a threshold value. Within the model proposed here, this is due to the higher configurational costs required to form inter-vesicle bridges as compared to intra-vesicle loops, which are in turn related to membrane deformability. Our findings and our numerical/experimental methodologies are applicable to the rational design of liposomes used as functional materials and drug delivery applications, as well as to study inter-membrane interactions in living systems, such as cell adhesion.

Multivalent interactions between deformable mesoscopic units are ubiquitous in biology, where membrane macromolecules mediate the interactions between neighbouring living cells and between cells and solid substrates. Lately, analogous artificial materials have been synthesised by functionalising the outer surface of compliant Brownian units, for example emulsion droplets and lipid vesicles, with selective linkers, in particular short DNA sequences. This development extended the range of applicability of DNA as a selective glue, originally applied to solid nano and colloidal particles. On very deformable lipid vesicles, the coupling between statistical effects of multivalent interactions and mechanical deformation of the membranes gives rise to complex emergent behaviours, as we recently contributed to demonstrate [Parolini et al., Nat. Commun., 2015, 6, 5948]. Several aspects of the complex phenomenology observed in these systems still lack a quantitative experimental characterisation and a fundamental understanding. Here we focus on the DNA-mediated multivalent interactions of a single liposome adhering to a flat supported bilayer. This simplified geometry enables the estimate of the membrane tension induced by the DNA-mediated adhesive forces acting on the liposome. Our experimental investigation is completed by morphological measurements and the characterisation of the DNA-melting transition, probed by in situ Förster Resonant Energy Transfer spectroscopy. Experimental results are compared with the predictions of an analytical theory that couples the deformation of the vesicle to a full description of the statistical mechanics of mobile linkers. With at most one fitting parameter, our theory is capable of semi-quantitatively matching experimental data, confirming the quality of the underlying assumptions.