Nanoparticles offer clear advantages for both passive and active penetration into biologically important membranes. However, the uptake and localization mechanism of nanoparticles within living plants, plant cells, and organelles has yet to be elucidated.1 Here, we examine the subcellular uptake and kinetic trapping of a wide range of nanoparticles for the first time, using the plant chloroplast as a model system, but validated in vivo in living plants. Confocal visible and near-infrared fluorescent microscopy and single particle tracking of goldcysteine-AF405 (GNP-Cys-AF405), streptavidin-quantum dot (SA-QD), dextran and poly(acrylic acid) nanoceria, and various polymer-wrapped single-walled carbon nanotubes (SWCNTs), including lipid-PEG-SWCNT, chitosan-SWCNT and 30-base (dAdT) sequence of ssDNA (AT) 15 wrapped SWCNTs (hereafter referred to as ss(AT) 15 -SWCNT), are used to demonstrate that particle size and the magnitude, but not the sign, of the zeta potential are key in determining whether a particle is spontaneously and kinetically trapped within the organelle, despite the negative zeta potential of the envelope. We develop a mathematical model of this lipid exchange envelope and penetration (LEEP) mechanism, which agrees well with observations of this size and zeta potential dependence. The theory predicts a critical particle size below which the mechanism fails at all zeta potentials, explaining why nanoparticles are critical for this process. LEEP constitutes a powerful particulate transport and localization mechanism for nanoparticles within the plant system.
Plant nanobionics aims to embed non-native functions to plants by interfacing them with specifically designed nanoparticles. Here, we demonstrate that living spinach plants (Spinacia oleracea) can be engineered to serve as self-powered pre-concentrators and autosamplers of analytes in ambient groundwater and as infrared communication platforms that can send information to a smartphone. The plants employ a pair of near-infrared fluorescent nanosensors-single-walled carbon nanotubes (SWCNTs) conjugated to the peptide Bombolitin II to recognize nitroaromatics via infrared fluorescent emission, and polyvinyl-alcohol functionalized SWCNTs that act as an invariant reference signal-embedded within the plant leaf mesophyll. As contaminant nitroaromatics are transported up the roots and stem into leaf tissues, they accumulate in the mesophyll, resulting in relative changes in emission intensity. The real-time monitoring of embedded SWCNT sensors also allows residence times in the roots, stems and leaves to be estimated, calculated to be 8.3 min (combined residence times of root and stem) and 1.9 min mm leaf, respectively. These results demonstrate the ability of living, wild-type plants to function as chemical monitors of groundwater and communication devices to external electronics at standoff distances.
Advances in the separation and functionalization of single walled carbon nanotubes (SWCNT) by their electronic type have enabled the development of ratiometric fluorescent SWCNT sensors for the first time. Herein, single chirality SWCNT are independently functionalized to recognize either nitric oxide (NO), hydrogen peroxide (H2O2), or no analyte (remaining invariant) to create optical sensor responses from the ratio of distinct emission peaks. This ratiometric approach provides a measure of analyte concentration, invariant to the absolute intensity emitted from the sensors and hence, more stable to external noise and detection geometry. Two distinct ratiometric sensors are demonstrated: one version for H2O2, the other for NO, each using 7,6 emission, and each containing an invariant 6,5 emission wavelength. To functionalize these sensors from SWCNT isolated from the gel separation technique, a method for rapid and efficient coating exchange of single chirality sodium dodecyl sulfate‐SWCNT is introduced. As a proof of concept, spatial and temporal patterns of the ratio sensor response to H2O2 and, separately, NO, are monitored in leaves of living plants in real time. This ratiometric optical sensing platform can enable the detection of trace analytes in complex environments such as strongly scattering media and biological tissues.
The ability to control the subcellular localization of nanoparticles within living plants offers unique advantages for targeted biomolecule delivery and enables important applications in plant bioengineering. However, the mechanism of nanoparticle transport past plant biological membranes is poorly understood. Here, a mechanistic study of nanoparticle cellular uptake into plant protoplasts is presented. An experimentally validated mathematical model of lipid exchange envelope penetration mechanism for protoplasts, which predicts that the subcellular distribution of nanoparticles in plant cells is dictated by the particle size and the magnitude of the zeta potential, is advanced. The mechanism is completely generic, describing nanoparticles ranging from quantum dots, gold and silica nanoparticles, nanoceria, and single-walled carbon nanotubes (SWNTs). In addition, the use of imaging flow cytometry to investigate the influence of protoplasts' morphological characteristics on nanoparticle uptake efficiency is demonstrated. Using DNA-wrapped SWNTs as model nanoparticles, it is found that glycerolipids, the predominant lipids in chloroplast membranes, exhibit stronger lipid-nanoparticle interaction than phospholipids, the major constituent in protoplast membrane. This work can guide the rational design of nanoparticles for targeted delivery into specific compartments within plant cells without the use of chemical or mechanical aid, potentially enabling various plant engineering applications.
The engineering of living plants for visible light emission and sustainable illumination is compelling because plants possess independent energy generation and storage mechanisms and autonomous self-repair. Herein, we demonstrate a plant nanobionic approach that enables exceptional luminosity and lifetime utilizing four chemically interacting nanoparticles, including firefly luciferase conjugated silica (SNP-Luc), D-luciferin releasing poly(lactic-co-glycolic acid) (PLGA-LH 2 ), coenzyme A functionalized chitosan (CS-CoA) and semiconductor nanocrystal phosphors for longer wavelength modulation. An in vitro kinetic model incorporating the release rates of the nanoparticles is developed to maximize the chemiluminescent lifetimes to exceed 21.5 h. In watercress (Nasturtium off icinale) and other species, the nanoparticles circumvent limitations such as luciferin toxicity above 400 μM and colocalization of enzymatic reactions near high adenosine triphosphate (ATP) production. Pressurized bath infusion of nanoparticles (PBIN) is introduced to deliver a mixture of nanoparticles to the entire living plant, well described using a nanofluidic mathematical model. We rationally design nanoparticle size and charge to control localization within distinct tissues compartments with 10 nm nanoparticles localizing within the leaf mesophyll and stomata guard cells, and those larger than 100 nm segregated in the leaf mesophyll. The results are mature watercress plants that emit greater than 1.44 × 10 12 photons/sec or 50% of 1 μW commercial luminescent diodes and modulate "off" and "on" states by chemical addition of dehydroluciferin and coenzyme A, respectively. We show that CdSe nanocrystals can shift the chemiluminescent emission to 760 nm enabling nearinfrared (nIR) signaling. These results advance the viability of nanobionic plants as self-powered photonics, direct and indirect light sources.
Innovative approaches are urgently required to alleviate the growing pressure on agriculture to meet the rising demand for food. A key challenge for plant biology is to bridge the notable knowledge gap between our detailed understanding of model plants grown under laboratory conditions and the agriculturally important crops cultivated in fields or production facilities. This Perspective highlights the recent development of new analytical tools that are rapid and non-destructive and provide tissue-, cell-or organelle-specific information on living plants in real time, with the potential to extend across multiple species in field applications. We evaluate the utility of engineered plant nanosensors and portable Raman spectroscopy to detect biotic and abiotic stresses, monitor plant hormonal signalling as well as characterize the soil, phytobiome and crop health in a non-or minimally invasive manner. We propose leveraging these tools to bridge the aforementioned fundamental gap with new synthesis and integration of expertise from plant biology, engineering and data science. Lastly, we assess the economic potential and discuss implementation strategies that will ensure the acceptance and successful integration of these modern tools in future farming practices in traditional as well as urban agriculture.
The evolution of particle shape is an important consideration in many industrial crystallizations. This article describes the design of temperature-cycling experiments (between alternating positive and negative supersaturations) to substantially change crystal shape with only a small number of cycles. The growth and dissolution of monosodium glutamate crystals of varying shapes were monitored using in-process attenuated total reflection−Fourier transform infrared spectroscopy (ATR-FTIR), focused beam reflectance measurement (FBRM), particle vision and measurement (PVM), and off-line optical microscopy. The growth and dissolution kinetics were estimated in a multidimensional population balance model based on solute concentration and crystal dimension measurements. This model fitted the experimental data with a limited number of parameters of small uncertainty. In addition, with the estimated kinetic parameters, the model predicted the crystal size and shape distribution in a different temperature-cycling experiment reasonably well. In contrast to previous studies that have estimated kinetics along multiple crystal axes in mixed-tank crystallizers, this study implements dissolution terms in the multidimensional population balance model along multiple axes.
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