A growing body of work has linked key biological activities to the mechanical properties of cellular membranes, and as a means of identification. Here, we present a computational approach to simulate and compare the vibrational spectra in the low- THz region for mammalian and bacterial membranes, investigating the effect of membrane asymmetry and composition, as well as the conserved frequencies of a specific cell. We find that asymmetry does not impact the vibrational spectra, and the impact of sterols depends on the mobility of the components of the membrane. We demonstrate that vibrational spectra can be used to distinguish between membranes and, therefore, could be used in identification of different organisms. The method presented, here, can be immediately extended to other biological structures (e.g., amyloid fibers, polysaccharides, and protein-ligand structures) in order to fingerprint and understand vibrations of numerous biologically-relevant nanoscale structures.

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Biofilms are structurally and functionally complex networks of bacteria and nanoscale macromolecules that play an important role in a myriad of settings from personal health and agriculture to power productions and fuel storage. Amyloid nanofibers are integral components of many biofilms and serve various purposes ranging from virulent to structural. Nonetheless, the precise characterization of bacterial amyloid nanofibers has been elusive, with incomplete and contradicting results. The present work focuses on the molecular details and characteristics of PSMα1 derived functional amyloids present in Staphylococcus aureus biofilms, using a combination of computational and experimental techniques. Results from molecular dynamics simulations, guided and supported by a variety of experiments, show that nanoscale nanofibers present a helical structure formed by two-protofilament PSMα1 amyloid nanofibers. PSMα1 peptides assembles into cross-β sheet structures with an average diameter of about 12 nm, adopting a left-handed helical structure with a periodicity of approximately 72 nm. Strikingly, the chirality of the self assembled nanofibers, an intrinsic geometric property of its constituent peptides, is central in determining the growth and shape of the fibers. The presented findings provide structural insights into the properties of the functional amyloids, hypothesize the role of chirality on the formation of fibers, and aid in strategies for the design of anti-amyloid compounds.

Chiral carbon nanoparticles (CNPs) represent a rapidly evolving area of research for optical and biomedical technologies. Similar to small molecules, applications of CNPs as well as fundamental relationships between their optical activity and structural asymmetry would greatly benefit from their enantioselective separations by chromatography. However, this technique remains in its infancy for chiral carbon and other nanoparticles. The possibility of effective separations using high performance liquid chromatography (HPLC) with chiral stationary phases remains an open question whose answer can also shed light on the components of multiscale chirality of the nanoparticles. Herein, we report a detailed methodology of HPLC for successful separation of chiral CNPs and establish a path for its future optimization. A mobile phase of water/ acetonitrile was able to achieve chiral separation of CNPs derived from L-and D-cysteine denoted as L-CNPs and D-CNPs. Molecular dynamics simulations show that the teicoplanin-based stationary phase has a higher affinity for L-CNPs than for D-CNPs, in agreement with experiments. The experimental and computational findings jointly indicate that chiral centers of chiral CNPs are [This article is part of the Special Issue: Chirality Materials.]