The genetics of niche-specific behavioral tendencies in an adaptive radiation of cichlid fishes.

Behavior is critical for animal survival and reproduction, and possibly for diversification and evolutionary radiation. However, the genetics behind adaptive variation in behavior are poorly understood. In this work, we examined a fundamental and widespread behavioral trait, exploratory behavior, in one of the largest adaptive radiations on Earth, the cichlid fishes of Lake Tanganyika. By integrating quantitative behavioral data from 57 cichlid species (702 wild-caught individuals) with high-resolution ecomorphological and genomic information, we show that exploratory behavior is linked to macrohabitat niche adaptations in Tanganyikan cichlids. Furthermore, we uncovered a correlation between the genotypes at a single-nucleotide polymorphism upstream of the AMPA glutamate-receptor regulatory gene cacng5b and variation in exploratory tendency. We validated this association using behavioral predictions with a neural network approach and CRISPR-Cas9 genome editing.

Local Environments Created by the Ligand Coating of Nanoparticles and Their Implications for Sensing and Surface Reactions.

ConspectusThe ligand shells of colloidal nanoparticles (NPs) can serve different purposes. In general, they provide colloidal stability by introducing steric repulsion between NPs. In the context of biological applications, the ligand shell plays a critical role in targeting, enabling NPs to achieve specific biodistributions. However, there is also another important feature of the ligand shell of NPs, namely, the creation of a local environment differing from the bulk of the solvent in which the NPs are dispersed. It is known that charged ligand shells can attract or repel ions and change the effective charge of a NP through Debye-Hückel screening. Positively charged ions, such as H+ (or H3O+) are attracted to negatively charged surfaces, whereas negatively charged ions, such as Cl- are repelled. The distribution of the ions around charged NP surfaces is a radial function of distance from the center of the NP, which is governed by a balance of electrostatic forces and entropy of ions and ligands. As a result, the ion concentration at the NP surface is different from its bulk equilibrium concentration, i.e., the charged ligand shell around the NPs has formed a distinct local environment. This not only applies to charged ligand shells but also follows a more general principle of induced condensation and depletion. Polar/apolar ligand shells, for example, result in a locally increased concentration of polar/apolar molecules. Similar effects can be seen for biocatalysts like enzymes immobilized in nanoporous host structures, which provide a special environment due to their surface chemistry and geometrical nanoconfinement. The formation of a local environment close to the ligand shell of NPs has profound implications for NP sensing applications. As a result, analyte concentrations close to the ligand shell, which are the ones that are measured, may be very different from the analyte concentrations in bulk. Based on previous work describing this effect, it will be discussed herein how such local environments, created by the choice of used ligands, may allow for tailoring the NPs' sensing properties. In general, the ligand shell around NPs can be attractive/repulsive for molecules with distinct properties and thus forms an environment that can modulate the specific response. Such local environments can also be optimized to modulate chemical reactions close to the NP surface (for example, by size filtering within pores) or to attract specific low abundance proteins. The importance hereby is that this is based on interaction with low selectivity between the ligands and the target molecules.

Machine learning of an implicit solvent for dynamic Monte Carlo simulations.

The Bond Fluctuation Model (BFM) is a highly efficient and versatile method for simulating polymers, membranes, and soft matter. Due to its coarse-grained nature, the BFM is employed to understand the universal properties of polymers. Solvent effects are often mediated by explicit solvent particles, while implicit solvent models have had limited use as they may lead to frozen states and, thus, ergodicity-related problems. In simulation setups, such as coagulated multiple homopolymers chains, explicit solvent models are computationally expensive because the region of interest can be localized in a small space compared to the dimension of the periodic box. We introduce an implicit solvent model based on an artificial neural network (NN) that was trained with BFM simulation data for single homopolymers in an explicit solvent. We demonstrate that NN-based simulations that take into account only the information of the local environment of monomers reproduce the expected universal macroscopic properties of the polymer under varying solvent conditions. The homopolymer chains simulated using the NN reproduce the coil-globule transition, the static and dynamic bond autocorrelation, and the mean square displacement of chain monomers. We show that the learned parameters from a single chain system can be transferred to a system containing multiple homopolymers, indicating that the learned parameters are transferable to considerably different systems.

Efficient enumeration-selection computational strategy for adaptive chemistry.

Design problems of finding efficient patterns, adaptation of complex molecules to external environments, affinity of molecules to specific targets, dynamic adaptive behavior of chemical systems, reconstruction of 3D structures from diffraction data are examples of difficult to solve optimal design or inverse search problems. Nature inspires evolution strategies to solve design problems that are based on selection of successful adaptations and heritable traits over generations. To exploit this strategy in the creation of new materials, a concept of adaptive chemistry was proposed to provide a route for synthesis of self-adapting molecules that can fit to their environment. We propose a computational method of an efficient exhaustive search exploiting massive parallelization on modern GPUs, which finds a solution for an inverse problem by solving repetitively a direct problem in the mean field approximation. One example is the search for a composition of a copolymer that allows the polymer to translocate through a lipid membrane at a minimal time. Another example is a search of a copolymer sequence that maximizes the polymer load in the micelle defined by the radial core-shell potentials. The length and the composition of the sequence are adjusted to fit into the restricted environment. Hydrogen bonding is another pathway of adaptation to the environment through reversible links. A linear polymer that interacts with water through hydrogen bonds adjusts the position of hydrogen bonds along the chain as a function of the concentration field around monomers. In the last example, branching of the molecules is adjusted to external fields, providing molecules with annealed topology, that can be flexibly changed by changing external conditions. The method can be generalized and applied to a broad spectrum of design problems in chemistry and physics, where adaptive behavior in multi-parameter space in response to environmental conditions lead to non-trivial patterns or molecule architectures and compositions. It can further be combined with machine learning or other optimization techniques to explore more efficiently the parameter space.

Protein corona modulates interaction of spiky nanoparticles with lipid bilayers.

The impact of protein corona on the interactions of nanoparticles (NPs) with cells remains an open question. This question is particularly relevant to NPs which sizes, ranging from tens to hundreds nanometers, are comparable to the sizes of most abundant proteins in plasma. Protein sizes match with typical thickness of various coatings and ligands layers, usually present at the surfaces of larger NPs. Such size match may affect the properties and the designed function of NPs. We offer a direct demonstration of how protein corona can dramatically change the interaction mode between NPs and lipid bilayers. To this end, we choose the most extreme case of NP surface modification: nanostructures in the form of rigid spikes of 10-20 nm length at the surface of gold nanoparticles. In the absence of proteins we observe the formation of reversible pores when spiky NPs adsorb on lipid bilayers. In contrast, the presence of bovine serum albumin (BSA) proteins adsorbed at the surface of spiked NPs, effectively reduces the length of spikes exposed to the interaction with lipid bilayers. Thus, protein corona changes qualitatively the dynamics of pore formation, which is completely suppressed at high protein concentrations. These results suggest that protein corona can not only be critical for interaction of NPs with membranes, it may change their mode of interaction, thus offsetting the role of surface chemistry and ligands.

Decoding Interaction Patterns from the Chemical Sequence of Polymers Using Neural Networks.

The relation between chemical sequences and the properties of polymers is considered using artificial neural networks with a low-dimensional bottleneck layer of neurons. These encoder-decoder architectures may compress the input information into a meaningful set of physical variables that describe the correlation between distinct types of data. In this work, neural networks were trained to translate a sequence of hydrophilic and hydrophobic segments into the effective free energy landscape of a copolymer interacting with a lipid membrane. The training data were obtained by the sampling of coarse-grained polymer conformations in a given membrane density field. Neural networks that were split into separate channels have learned to decompose the free energy into independent components that are explainable by known concepts from polymer physics. The semantic information in the hidden layers was employed to predict polymer translocation events through a membrane for a more detailed dynamic model via a transfer learning procedure. The search for minimal translocation times in the compressed chemical space underlined that nontrivial sequence motifs may lead to optimal properties.

The multi-faceted mechano-bactericidal mechanism of nanostructured surfaces.

The mechano-bactericidal activity of nanostructured surfaces has become the focus of intensive research toward the development of a new generation of antibacterial surfaces, particularly in the current era of emerging antibiotic resistance. This work demonstrates the effects of an incremental increase of nanopillar height on nanostructure-induced bacterial cell death. We propose that the mechanical lysis of bacterial cells can be influenced by the degree of elasticity and clustering of highly ordered silicon nanopillar arrays. Herein, silicon nanopillar arrays with diameter 35 nm, periodicity 90 nm and increasing heights of 220, 360, and 420 nm were fabricated using deep UV immersion lithography. Nanoarrays of 360-nm-height pillars exhibited the highest degree of bactericidal activity toward both Gram stain-negative Pseudomonas aeruginosa and Gram stain-positive Staphylococcus aureus bacteria, inducing 95 ± 5% and 83 ± 12% cell death, respectively. At heights of 360 nm, increased nanopillar elasticity contributes to the onset of pillar deformation in response to bacterial adhesion to the surface. Theoretical analyses of pillar elasticity confirm that deflection, deformation force, and mechanical energies are more significant for the substrata possessing more flexible pillars. Increased storage and release of mechanical energy may explain the enhanced bactericidal action of these nanopillar arrays toward bacterial cells contacting the surface; however, with further increase of nanopillar height (420 nm), the forces (and tensions) can be partially compensated by irreversible interpillar adhesion that reduces their bactericidal effect. These findings can be used to inform the design of next-generation mechano-responsive surfaces with tuneable bactericidal characteristics for antimicrobial surface technologies.

Unexpected Cholesterol-Induced Destabilization of Lipid Membranes near Transmembrane Carbon Nanotubes.

Cholesterol is a crucial component of mammalian cell membranes that takes part in many vital processes. It is generally accepted that cholesterol stabilizes the membrane and induces transitions into ordered states. In contrast to expectations, we demonstrate that cholesterol can destabilize the membrane by creating a nanodomain around a perpendicularly embedded ultrashort carbon nanotube (CNT), and we show that cholesterol triggers the translocation of an ultrashort CNT through the cell membrane. Using atomistic simulations, we report the existence of a nanoscale domain around an ultrashort carbon nanotube within a crossover distance of 0.9 nm from the surface of the nanotube, where the properties of the bilayer are different from the bulk: the domain is characterized by increased fluctuations, increased thickness, and increased order of the lipids with respect to the bulk. Cholesterol decreases the thickness and order of lipids and increases the fluctuations with respect to a pure lipid bilayer. Experimentally, we confirm that cholesterol nanodomains provoke spontaneous translocation of nanotubes through a lipid bilayer even for low membrane tensions. A specially designed microfluidic device allows us to trace the kinetic pathway of the translocation process and establish the threshold cholesterol concentration of 20% for translocation. The reported nanoscale cholesterol-induced membrane restructuring near the ultrashort CNT in lipid membranes enables precise control and specific targeting of a membrane using cholesterol. As an example, it may allow for specific targeting between cholesterol-rich mammalian cells and cholesterol-poor bacterial cells.

Simulations of Protein Adsorption on Nanostructured Surfaces.

Recent technological advances have allowed the development of a new generation of nanostructured materials, such as those displaying both mechano-bactericidal activity and substrata that favor the growth of mammalian cells. Nanomaterials that come into contact with biological media such as blood first interact with proteins, hence understanding the process of adsorption of proteins onto these surfaces is highly important. The Random Sequential Adsorption (RSA) model for protein adsorption on flat surfaces was modified to account for nanostructured surfaces. Phenomena related to the nanofeature geometry have been revealed during the modelling process; e.g., convex geometries can lead to lower steric hindrance between particles, and hence higher degrees of surface coverage per unit area. These properties become more pronounced when a decrease in the size mismatch between the proteins and the surface nanostructures occurs. This model has been used to analyse the adsorption of human serum albumin (HSA) on a nano-structured black silicon (bSi) surface. This allowed the Blocking Function (the rate of adsorption) to be evaluated. The probability of the protein to adsorb as a function of the occupancy was also calculated.

High-throughput 3D visualization of nanoparticles attached to the surface of red blood cells.

Blood circulation is the main distribution route for systemic delivery and the possibility to manipulate red blood cells (RBCs) by attaching nanoparticles to their surface provides a great opportunity for cargo delivery into tissues. Nanocarriers attached to RBCs can be delivered to specific organs orders of magnitude faster than if injected directly into the bloodstream. Another advantage is a shielding from recognition by the immune system, thereby increasing the efficiency of delivery. We present a high-throughput microfluidic method that can monitor the shape of drifting cells due to interactions with nanoparticles and characterize the 3D dispersion of fluorescent silica nanoparticles at the surface of RBCs. The combination of fluorescence microscopy with image analysis demonstrates that the adsorption of silica nanoparticles onto the surface of RBCs is strongly influenced by electrostatic interactions. A reduced number of intact RBCs with increasing nanoparticle concentration beyond a certain threshold points to a toxicity mechanism associated with the nanoparticle adsorption at the surface of RBCs.

The pyrrolopyrimidine colchicine-binding site agent PP-13 reduces the metastatic dissemination of invasive cancer cells in vitro and in vivo.

Standard chemotherapies that interfere with microtubule dynamics are a chemotherapeutic option used for the patients with advanced malignancies that invariably relapse after targeted therapies. However, major efforts are needed to reduce their toxicity, optimize their efficacy, and reduce cancer chemoresistance to these agents. We previously identified a pyrrolo[2,3d]pyrimidine-based microtubule-depolymerizing agent (PP-13) that binds to the colchicine site of ß-tubulin and exhibits anticancer properties in solid human cancer cells, including chemoresistant subtypes. Here, we investigated the therapeutic potential of PP-13 in vitro and in vivo. PP-13 induced a mitotic blockade and apoptosis in several cancer cells cultured in two-dimensions or three-dimensions spheroids, in conjunction with reduced cell proliferation. Capillary-like tube formation assays using HUVECs showed that PP-13 displayed antiangiogenic properties. It also inhibited cancer cell motility and invasion, in in vitro wound-healing and transwell migration assays. Low concentration PP-13 (130 nmol.L-1) treatment significantly reduced the metastatic invasiveness of human cancer cells engrafts on chicken chorioallantoic membrane. In nude mice, 0.5 or 1 mg.kg-1 PP-13 intraperitoneally administered three-times a week reduced the sizes of paclitaxel-refractory orthotopic breast tumors, delayed the progression of metastasis, and decreased the global metastatic load compared to 0.5 mg.kg-1 paclitaxel or vehicle alone. PP-13 did not show any apparent early adverse effect in vivo. These data suggest that PP-13 is a promising alternative to standard chemotherapy in antimitotic drug-refractory tumors, especially through its impact on metastasis.

Subtle Variations in Surface Properties of Black Silicon Surfaces Influence the Degree of Bactericidal Efficiency.

One of the major challenges faced by the biomedical industry is the development of robust synthetic surfaces that can resist bacterial colonization. Much inspiration has been drawn recently from naturally occurring mechano-bactericidal surfaces such as the wings of cicada (Psaltoda claripennis) and dragonfly (Diplacodes bipunctata) species in fabricating their synthetic analogs. However, the bactericidal activity of nanostructured surfaces is observed in a particular range of parameters reflecting the geometry of nanostructures and surface wettability. Here, several of the nanometer-scale characteristics of black silicon (bSi) surfaces including the density and height of the nanopillars that have the potential to influence the bactericidal efficiency of these nanostructured surfaces have been investigated. The results provide important evidence that minor variations in the nanoarchitecture of substrata can substantially alter their performance as bactericidal surfaces.

Tension-Induced Translocation of an Ultrashort Carbon Nanotube through a Phospholipid Bilayer.

Increasing awareness of bioeffects and toxicity of nanomaterials interacting with cells puts in focus the mechanisms by which nanomaterials can cross lipid membranes. Apart from well-discussed energy-dependent endocytosis for large objects and passive diffusion through membranes by solute molecules, other translocation mechanisms based on physical principles can exist. We show the importance of membrane tension on the translocation through lipid bilayers of ultrashort carbon nanotubes (USCNTs). By using a combination of a microfluidic setup and single chain mean field (SCMF) theory, we observed that, under membrane tension, USCNT inserted into a lipid bilayer may spontaneously nucleate an unstable local pore, allowing it to escape from the bilayer. We demonstrated that stretching of the membrane is essential for triggering this mechanism of translocation, and no translocation is observed at low membrane tension. For this purpose, a quantitative analysis of the kinetic pathway associated with USCNT translocation induced by tension was performed in a specially designed microfluidic device, simultaneously combining optical fluorescence microscopy and electrophysiological measurements. An important outcome of these findings is the identification of the way to control the nanomaterial translocation through the lipid bilayer by membrane tension that can be useful in many practical applications.

Pillars of Life: Is There a Relationship between Lifestyle Factors and the Surface Characteristics of Dragonfly Wings?

Dragonfly wings are of great interest to researchers investigating biomimetic designs for antiwetting and antibacterial surfaces. The waxy epicuticular layer on the membrane of dragonfly wings possesses a unique surface nanoarchitecture that consists of irregular arrays of nanoscale pillars. This architecture confers superhydrophobic, self-cleaning, antiwetting, and antibiofouling behaviors. There is some evidence available that suggests that lifestyle factors may have influenced the evolution of the wing nanostructures and, therefore, the resulting properties of the wings; however, it appears that no systematic studies have been performed that have compared the wing surface features across a range of dragonfly species. Here, we provided a comparison of relevant wing surface characteristics, including chemical composition, wettability, and nanoarchitecture, of seven species of dragonfly from three families including Libellulidae, Aeshnidae, and Gomphidae. The characteristic nanopillar arrays were found to be present, and the chemical composition and the resultant wing surface superhydrophobicity were found to be well-conserved across all of the species studied. However, subtle differences were observed between the height, width, and density of nanofeatures and water droplet bouncing behavior on the wing surfaces. The results of this research will contribute to an understanding of the physical and chemical surface features that are optimal for the design of antiwetting and antibacterial surfaces.

Bridging molecular simulation models and elastic theories for amphiphilic membranes.

The Single Chain Mean Field theory is used to link coarse-grained models of amphiphilic molecules with analytical models for membrane elasticity, where phenomenological parameters are deduced from explicit molecular models and force fields. We estimate the elastic constants based on the free energy of the amphiphilic bilayer in planar and cylindrical geometries on the example of four amphiphilic molecules that differ in length and stiffness. We study how these variations affect the equilibrium bilayer structure, the equilibrium free energy, and the elastic constants. Bending rigidities are obtained within the typical range of experimental values for phospholipid membranes in a liquid state.

Structure and Chemical Organization in Damselfly Calopteryx haemorrhoidalis Wings: A Spatially Resolved FTIR and XRF Analysis with Synchrotron Radiation.

Insects represent the majority of known animal species and exploit a variety of fascinating nanotechnological concepts. We investigated the wings of the damselfly Calopteryx haemorrhoidalis, whose males have dark pigmented wings and females have slightly pigmented wings. We used scanning electron microscopy (SEM) and nanoscale synchrotron X-ray fluorescence (XRF) microscopy analysis for characterizing the nanostructure and the elemental distribution of the wings, respectively. The spatially resolved distribution of the organic constituents was examined by synchrotron Fourier transform infrared (s-FTIR) microspectroscopy and subsequently analyzed using hierarchical cluster analysis. The chemical distribution across the wing was rather uniform with no evidence of melanin in female wings, but with a high content of melanin in male wings. Our data revealed a fiber-like structure of the hairs and confirmed the presence of voids close to its base connecting the hairs to the damselfly wings. Within these voids, all detected elements were found to be locally depleted. Structure and elemental contents varied between wing membranes, hairs and veins. The elemental distribution across the membrane was rather uniform, with higher Ca, Cu and Zn levels in the male damselfly wing membranes.

High Aspect Ratio Nanostructures Kill Bacteria via Storage and Release of Mechanical Energy.

The threat of a global rise in the number of untreatable infections caused by antibiotic-resistant bacteria calls for the design and fabrication of a new generation of bactericidal materials. Here, we report a concept for the design of antibacterial surfaces, whereby cell death results from the ability of the nanofeatures to deflect when in contact with attaching cells. We show, using three-dimensional transmission electron microscopy, that the exceptionally high aspect ratio (100-3000) of vertically aligned carbon nanotubes (VACNTs) imparts extreme flexibility, which enhances the elastic energy storage in CNTs as they bend in contact with bacteria. Our experimental and theoretical analyses demonstrate that, for high aspect ratio structures, the bending energy stored in the CNTs is a substantial factor for the physical rupturing of both Gram-positive and Gram-negative bacteria. The highest bactericidal rates (99.3% for Pseudomonas aeruginosa and 84.9% for Staphylococcus aureus) were obtained by modifying the length of the VACNTs, allowing us to identify the optimal substratum properties to kill different types of bacteria efficiently. This work highlights that the bactericidal activity of high aspect ratio nanofeatures can outperform both natural bactericidal surfaces and other synthetic nanostructured multifunctional surfaces reported in previous studies. The present systems exhibit the highest bactericidal activity of a CNT-based substratum against a Gram-negative bacterium reported to date, suggesting the possibility of achieving close to 100% bacterial inactivation on VACNT-based substrata.

Study of melanin localization in the mature male Calopteryx haemorrhoidalis damselfly wings.

Damselflies Calopteryx haemorrhoidalis exhibiting black wings are found in the western Mediterranean, Algeria, France, Italy, Spain and Monaco. Wing pigmentation is caused by the presence of melanin, which is involved in physiological processes including defence reactions, wound healing and sclerotization of the insect. Despite the important physiological roles of melanin, the presence and colour variation among males and females of the C. haemorrhoidalis species and the localization of the pigment within the wing membrane remain poorly understood. In this study, infrared (IR) microspectroscopy, coupled with the highly collimated synchrotron IR beam, was employed in order to identify the distribution of the pigments in the wings at a high spatial resolution. It was found that the melanin is localized in the procuticle of the C. haemorrhoidalis damselfly wings, distributed homogeneously within this layer, and not associated with the lipids of the epicuticle.

Nanomaterial interactions with biomembranes: Bridging the gap between soft matter models and biological context.

Synthetic polymers, nanoparticles, and carbon-based materials have great potential in applications including drug delivery, gene transfection, in vitro and in vivo imaging, and the alteration of biological function. Nature and humans use different design strategies to create nanomaterials: biological objects have emerged from billions of years of evolution and from adaptation to their environment resulting in high levels of structural complexity; in contrast, synthetic nanomaterials result from minimalistic but controlled design options limited by the authors' current understanding of the biological world. This conceptual mismatch makes it challenging to create synthetic nanomaterials that possess desired functions in biological media. In many biologically relevant applications, nanomaterials must enter the cell interior to perform their functions. An essential transport barrier is the cell-protecting plasma membrane and hence the understanding of its interaction with nanomaterials is a fundamental task in biotechnology. The authors present open questions in the field of nanomaterial interactions with biological membranes, including: how physical mechanisms and molecular forces acting at the nanoscale restrict or inspire design options; which levels of complexity to include next in computational and experimental models to describe how nanomaterials cross barriers via passive or active processes; and how the biological media and protein corona interfere with nanomaterial functionality. In this Perspective, the authors address these questions with the aim of offering guidelines for the development of next-generation nanomaterials that function in biological media.

Formation and stabilization of pores in bilayer membranes by peptide-like amphiphilic polymers.

We study pore formation in models of lipid bilayer membranes interacting with amphiphilic copolymers mimicking anti-microbial peptides using Monte Carlo simulations and we rationalize our results by a simple brush-model for the fluid membrane. In our study a weak tension on the membrane is required to observe pore-formation induced by the adsorption of flexible amphiphilic copolymers. The copolymers enhance the pore stability by decreasing the line tension due to weak adsorption along the rim of the pore. Pore formation is enhanced with increasing length of copolymers or stronger stretching of the membrane. Both solvent and copolymer permeability increase as the pore becomes stable. Pore-formation proceeds via a meta-stable pore-state according to a discontinuous phase transition scenario which lead to finite pore-sizes at once. Our generic model of copolymer-induced pore-formation does not require high polymer concentration at the pores nor any self-organization of the copolymers to open the pore.