Most animal species operate according to a 24-h period set by the suprachiasmatic nucleus (SCN) of the hypothalamus. The rhythmic activity of the SCN modulates hippocampal-dependent memory, but the molecular and cellular mechanisms that account for this effect remain largely unknown. Here, we identify cell-type-specific structural and functional changes that occur with circadian rhythmicity in neurons and astrocytes in hippocampal area CA1. Pyramidal neurons change the surface expression of NMDA receptors. Astrocytes change their proximity to synapses. Together, these phenomena alter glutamate clearance, receptor activation, and integration of temporally clustered excitatory synaptic inputs, ultimately shaping hippocampal-dependent learning in vivo. We identify corticosterone as a key contributor to changes in synaptic strength. These findings highlight important mechanisms through which neurons and astrocytes modify the molecular composition and structure of the synaptic environment, contribute to the local storage of information in the hippocampus, and alter the temporal dynamics of cognitive processing.

Recent in vivo studies have established ultrasmall (<3 nm) gold nanoparticles coated with glutathione (AuGSH) as a promising platform for applications in nanomedicine. However, systematic in vitro investigations to gain a more fundamental understanding of the particles’ biointeractions are still lacking. Herein we examined the behavior of ultrasmall AuGSH in vitro, focusing on their ability to resist aggregation and adsorption from serum proteins. Despite having net negative charge, AuGSH particles were colloidally stable in biological media and able to resist binding from serum proteins, in agreement with the favorable bioresponses reported for AuGSH in vivo. However, our results revealed disparate behaviors depending on nanoparticle size: particles between 2 and 3 nm in core diameter were found to readily aggregate in biological media, whereas those strictly under 2 nm were exceptionally stable. Molecular dynamics simulations provided microscopic insight into interparticle interactions leading to aggregation and their sensitivity to the solution composition and particle size. These results have important implications, in that seemingly small variations in size can impact the biointeractions of ultrasmall AuGSH, and potentially of other ultrasmall nanoparticles as well.

The use of nanoparticles (NPs) in biomedicine has made a gradual transition from proof-of-concept to clinical applications, with several NP types meeting regulatory approval or undergoing clinical trials. A new type of metallic nanostructures called ultrasmall nanoparticles (usNPs) and nanoclusters (NCs), while retaining essential properties of the larger (classical) NPs, have features common to bioactive proteins. This combination expands the potential use of usNPs and NCs to areas of diagnosis and therapy traditionally reserved for small-molecule medicine. Their distinctive physicochemical properties can lead to unique in vivo behaviors, including improved renal clearance and tumor distribution. Both the beneficial and potentially deleterious outcomes (cytotoxicity, inflammation) can, in principle, be controlled through a judicious choice of the nanocore shape and size, as well as the chemical ligands attached to the surface. At present, the ability to control the behavior of usNPs is limited, partly because advances are still needed in nanoengineering and chemical synthesis to manufacture and characterize ultrasmall nanostructures and partly because our understanding of their interactions in biological environments is incomplete. This review addresses the second limitation. We review experimental and computational methods currently available to understand molecular mechanisms, with particular attention to usNP–protein complexation, and highlight areas where further progress is needed. We discuss approaches that we find most promising to provide relevant molecular-level insight for designing usNPs with specific behaviors and pave the way to translational applications.

Synthetic ultrasmall nanoparticles (NPs) can be designed to interact with biologically active proteins in a controlled manner. However, the rational design of NPs requires a clear understanding of their interactions with proteins and the precise molecular mechanisms that lead to association/dissociation in biological media. Although much effort has been devoted to the study of the kinetics mechanism of protein corona formation on large NPs, the nature of NP–protein interactions in the ultrasmall regime is radically different and poorly understood. Using a combination of experimental and computational approaches, we studied the interactions of a model protein, CrataBL, with ultrasmall gold NPs passivated with p-mercaptobenzoic acid (AuMBA) and glutathione (AuGSH). We have identified this system as an ideal in vitro platform to understand the dependence of binding affinity and kinetics on NP surface chemistry. We found that the structural and chemical complexity of the passivating NP layer leads to quite different association kinetics, from slow and reaction-limited (AuGSH) to fast and diffusion-limited (AuMBA). We also found that the otherwise weak and slow AuGSH–protein interactions measured in buffer solution are enhanced in macromolecular crowded solutions. These findings advance our mechanistic understanding of biomimetic NP–protein interactions in the ultrasmall regime and have implications for the design and use of NPs in the crowded conditions common to all biological media.

The catalytic activity of enzymes can be regulated by interactions with synthetic nanoparticles (NPs) in a number of ways. To date, however, the potential use of NPs as allosteric effectors has not been investigated in detail. Importantly, targeting allosteric (distal) sites on the enzyme surface could afford unique ways to modulate the activity, allowing for either enzyme activation, partial or full inhibition. Using p-mercaptobenzoic acid-coated ultrasmall gold NPs (AuMBA) and human α-thrombin as a model system, here we experimentally tested the hypothesis that enzyme activity could be regulated through ultrasmall NP interactions at allosteric sites. We show that AuMBA interacted selectively and reversibly around two positively charged regions of the thrombin surface (exosites 1 and 2) and away from the active site. NP complexation at the exosites transmitted long-range structural changes over to the active site, altering both substrate binding affinity and catalysis. Significantly, thrombin activity was partially reduced – but not completely inhibited – by interactions with AuMBA. These findings indicate that interactions of proteins with ultrasmall NPs may mimic a typical biomolecular complexation event, and suggest the prospect of using ultrasmall particles as synthetic receptors to allosterically regulate protein function.

The robust characterization of lipid nanoparticles (LNPs) encapsulating therapeutics or vaccines is an important and multifaceted translational problem. Sedimentation velocity analytical ultracentrifugation (SV-AUC) has proven to be a powerful approach in the characterization of size-distribution, interactions, and composition of various types of nanoparticles across a large size range, including metal nanoparticles (NPs), polymeric NPs, and also nucleic acid loaded viral capsids. Similar potential of SV-AUC can be expected for the characterization of LNPs, but is hindered by the flotation of LNPs being incompatible with common sedimentation analysis models. To address this gap, we developed a high-resolution, diffusion-deconvoluted sedimentation/flotation distribution analysis approach analogous to the most widely used sedimentation analysis model c(s). The approach takes advantage of independent measurements of the average particle size or diffusion coefficient, which can be conveniently determined, for example, by dynamic light scattering (DLS). We demonstrate the application to an experimental model of extruded liposomes as well as a commercial LNP product and discuss experimental potential and limitations of SV-AUC. The method is implemented analogously to the sedimentation models in the free, widely used SEDFIT software.