Copper Stimulation of Tetrahydrocannabinol and Cannabidiol Production in Hemp (Cannabis sativa L.) Is Copper-Type, Dose, and Cultivar Dependent.

Copper (Cu) is an element widely used as a pesticide for the control of plant diseases. Cu is also known to influence a range of plant secondary metabolisms. However, it is not known whether Cu influences the levels of the major metabolites in hemp (Cannabis sativa L.), tetrahydrocannabinol (THC) and cannabidiol (CBD). This study investigated the impact of Cu on the levels of these cannabinoids in two hemp cultivars, Wife and Merlot, under field conditions, as a function of harvest time (August-September), Cu type (nano, bulk, or ionic), and dose (50, 100, and 500 ppm). In Wife, Cu caused significant temporal increases in THC and CBD production during plant growth, reaching increases of 33% and 31% for THC and 51% and 16.5% for CBD by harvests 3 and 4, respectively. CuO nanoparticles at 50 and 100 ppm significantly increased THC and CBD levels, compared to the control, respectively, by 18% and 27% for THC and 19.9% and 33.6% for CBD. These nanospecific increases coincided with significantly more Cu in the inflorescences (buds) than in the control and bulk CuO treatments. Contrarily, no temporal induction of the cannabinoids by Cu was noticed in Merlot, suggesting a cultivar-specific response to Cu. However, overall, in Merlot, Cu ions, but not particulate Cu, induced THC and CBD levels by 27% and 36%, respectively, compared to the control. Collectively, our findings provide information with contrasting implications in the production of these cannabinoids, where, dependent on the cultivar, metabolite levels may rise above the 0.3% regulatory threshold for THC but to a more profitable level for CBD. Further investigations with a wider range of hemp cultivars, CuO nanoparticle (NP) doses, and harvest times would clarify the significance and broader implications of the findings.

Influence of CuO Nanoparticle Aspect Ratio and Surface Charge on Disease Suppression in Tomato (Solanum lycopersicum).

Nanoparticles (NPs) have been shown to deliver micronutrients to plants to improve health, increase biomass, and suppress disease. Nanoscale properties such as morphology, size, composition, and surface chemistry have all been shown to impact nanomaterial interactions with plant systems. An organic-ligand-free synthesis method was used to prepare positively charged copper oxide (CuO) nanospikes, negatively charged CuO nanospikes, and negatively charged CuO nanosheets with exposed (001) crystal faces. X-ray photoelectron spectroscopy measurements show that the negative charge correlates to increased surface concentration of O on the NP surface, whereas relatively higher Cu concentrations are observed on the positively charged surfaces. The NPs were then used to treat tomato (Solanum lycopersicum) grown in soil infested with Fusarium oxysporum f. sp. lycopersici under greenhouse conditions. The negatively charged CuO significantly reduced disease progression and increased biomass, while the positively charged NPs and a CuSO4 salt control had little impact on the plants. Self-assembled monolayers were used to mimic the leaf surface to understand the intermolecular interactions between the NPs and the plant leaf; the data demonstrate that NP electrostatics and hydrogen-bonding interactions play an important role in adsorption onto leaf surfaces. These findings have important implications for the tunable design of materials as a strategy for the use of nano-enabled agriculture to increase food production.

Machine Learning-Assisted Carbon Dot Synthesis: Prediction of Emission Color and Wavelength.

Carbon dots (CDs) have attracted great attention in a range of applications due to their bright photoluminescence, high photostability, and good biocompatibility. However, it is challenging to design CDs with specific emission properties because the syntheses involve many parameters, and it is not clear how each parameter influences the CD properties. To help bridge this gap, machine learning, specifically an artificial neural network, is employed in this work to characterize the impact of synthesis parameters on and make predictions for the emission color and wavelength for CDs. The machine reveals that the choice of reaction method, purification method, and solvent relate more closely to CD emission characteristics than the reaction temperature or time, which are frequently tuned in experiments. After considering multiple models, the best performing machine learning classification model achieved an accuracy of 94% in predicting relative to actual color. In addition, hybrid (two-stage) models incorporating both color classification and an artificial neural network k-ensemble model for wavelength prediction through regression performed significantly better than either a standard artificial neural network or a single-stage artificial neural network k-ensemble regression model. The accuracy of the model predictions was evaluated against CD emission wavelengths measured from experiments, and the minimum mean average error is 25.8 nm. Overall, the models developed in this work can effectively predict the photoluminescence emission of CDs and help design CDs with targeted optical properties.

Influence of the Spatial Distribution of Cationic Functional Groups at Nanoparticle Surfaces on Bacterial Viability and Membrane Interactions.

While positively charged nanomaterials induce cytotoxicity in many organisms, much less is known about how the spatial distribution and presentation of molecular surface charge impact nanoparticle-biological interactions. We systematically functionalized diamond nanoparticle surfaces with five different cationic surface molecules having different molecular structures and conformations, including four small ligands and one polymer, and we then probed the molecular-level interaction between these nanoparticles and bacterial cells. Shewanella oneidensis MR-1 was used as a model bacterial cell system to investigate how the molecular length and conformation of cationic surface charges influence their interactions with the Gram-negative bacterial membranes. Nuclear magnetic resonance (NMR) and X-ray photoelectron spectroscopy (XPS) demonstrate the covalent modification of the nanoparticle surface with the desired cationic organic monolayers. Surprisingly, bacterial growth-based viability (GBV) and membrane damage assays both show only minimal biological impact by the NPs functionalized with short cationic ligands within the concentration range tested, yet NPs covalently linked to a cationic polymer induce strong cytotoxicity, including reduced cellular viability and significant membrane damage at the same concentration of cationic groups. Transmission electron microscopy (TEM) images of these NP-exposed bacterial cells show that NPs functionalized with cationic polymers induce significant membrane distortion and the production of outer membrane vesicle-like features, while NPs bearing short cationic ligands only exhibit weak membrane association. Our results demonstrate that the spatial distribution of molecular charge plays a key role in controlling the interaction of cationic nanoparticles with bacterial cell membranes and the subsequent biological impact. Nanoparticles functionalized with ligands having different lengths and conformations can have large differences in interactions even while having nearly identical zeta potentials. While the zeta potential is a convenient and commonly used measure of nanoparticle charge, it does not capture essential differences in molecular-level nanoparticle properties that control their biological impact.

Cobalt Release from a Nanoscale Multiphase Lithiated Cobalt Phosphate Dominates Interaction with Shewanella oneidensis MR-1 and Bacillus subtilis SB491.

Cobalt phosphate engineered nanomaterials (ENMs) are an important class of materials that are used as lithium ion battery cathodes, catalysts, and potentially as super capacitors. As production of these nanomaterials increases, so does the likelihood of their environmental release; however, to date, there are relatively few investigations of the impact of nanoscale metal phosphates on biological systems. Furthermore, nanomaterials used in commercial applications are often multiphase materials, and analysis of the toxic potential of mixtures of nanomaterials has been rare. In this work, we studied the interactions of two model environmental bacteria, Shewanella oneidensis MR-1 and Bacillus subtilis, with a multiphase lithiated cobalt phosphate (mLCP) nanomaterial. Using a growth-based viability assay, we found that mLCP was toxic to both bacteria used in this study. To understand the observed toxicity, we screened for production of reactive oxygen species (ROS) and release of Co2+ from mLCP using three abiotic fluorophores. We also used Newport Green DCF dye to show that cobalt was taken up by the bacteria after mLCP exposure. Using transmission electron microscopy, we noted that the mLCP was not associated with the bacterial cell surface. In order for us to further probe the mechanism of interaction of mLCP, the bacteria were exposed to an equivalent dose of cobalt ions that dissolved from mLCP, which recapitulated the changes in viability when the bacteria were exposed to mLCP, and it also recapitulated the observed bacterial uptake of cobalt. Taken together, this implicates the release of cobalt ions and their subsequent uptake by the bacteria as the major toxicity mechanism of mLCP. The properties of the ENM govern the release rate of cobalt, but the toxicity does not arise from nanospecific effects-and importantly, the chemical composition of the ENM may dictate the oxidation state of the metal centers and thus limit ROS production.

Chronic exposure to complex metal oxide nanoparticles elicits rapid resistance in Shewanella oneidensis MR-1.

Engineered nanoparticles are incorporated into numerous emerging technologies because of their unique physical and chemical properties. Many of these properties facilitate novel interactions, including both intentional and accidental effects on biological systems. Silver-containing particles are widely used as antimicrobial agents and recent evidence indicates that bacteria rapidly become resistant to these nanoparticles. Much less studied is the chronic exposure of bacteria to particles that were not designed to interact with microorganisms. For example, previous work has demonstrated that the lithium intercalated battery cathode nanosheet, nickel manganese cobalt oxide (NMC), is cytotoxic and causes a significant delay in growth of Shewanella oneidensis MR-1 upon acute exposure. Here, we report that S. oneidensis MR-1 rapidly adapts to chronic NMC exposure and is subsequently able to survive in much higher concentrations of these particles, providing the first evidence of permanent bacterial resistance following exposure to nanoparticles that were not intended as antibacterial agents. We also found that when NMC-adapted bacteria were subjected to only the metal ions released from this material, their specific growth rates were higher than when exposed to the nanoparticle. As such, we provide here the first demonstration of bacterial resistance to complex metal oxide nanoparticles with an adaptation mechanism that cannot be fully explained by multi-metal adaptation. Importantly, this adaptation persists even after the organism has been grown in pristine media for multiple generations, indicating that S. oneidensis MR-1 has developed permanent resistance to NMC.