Biology subjects

Landry, M. P.

Publications and source records attributed to Landry, M. P..

At least 37 records · Page 2Linked to original sources

bioRxiv2022

Near Infrared Nanosensors Enable Optical Imaging of Oxytocin with Selectivity over Vasopressin in Acute Mouse Brain Slices

Oxytocin plays a critical role in regulating social behaviors, yet our understanding of its role in both neurological health and disease remains incomplete. Real-time oxytocin imaging probes with the spatiotemporal resolution relevant to its endogenous signaling are required to fully elucidate oxytocin function in the brain. Herein we describe a near-infrared oxytocin nanosensor (nIROx), a synthetic probe capable of imaging oxytocin in the brain without interference from its structural analogue, vasopressin. nIROx leverages the inherent tissue-transparent fluorescence of single-walled carbon nanotubes (SWCNT) and the molecular recognition capacity of an oxytocin receptor peptide fragment (OXTp) to selectively and reversibly image oxytocin. We employ these nanosensors to monitor electrically stimulated oxytocin release in brain tissue, revealing oxytocin release sites with a median size of 3 m which putatively represents the spatial diffusion of oxytocin from its point of release. These data demonstrate that covalent SWCNT constructs such as nIROx are powerful optical tools that can be leveraged to measure neuropeptide release in brain tissue.

bioengineering↗

bioRxiv2022

Synaptic scale dopamine disruption in Huntington's Disease model mice imaged with near infrared catecholamine nanosensors

Dopamine neuromodulation is a critical process that facilitates learning, motivation, and motor control. Disruption of these processes has been implicated in several neurological and psychiatric disorders including Huntingtons Disease (HD). While several treatments for physical and psychiatric HD symptoms target dopaminergic neuromodulation, the mechanism by which dopaminergic dysfunction occurs during HD is unknown. This is partly due to limited capability to visualize dopamine dynamics at the spatiotemporal resolution of both neuromodulator release (ms) and dopaminergic boutons ({micro}m). Here we employ near-infrared fluorescent catecholamine nanosensors (nIRCats) to image dopamine release within the brain striatum of R6/2 Huntingtons Disease Model (R6/2) mice. We find that stimulated dorsal striatal dopamine release decreases with progressive motor degeneration and that these decreases are primarily driven by a decrease in the number of dopamine hotspots combined with decreased release intensity and decreased release fidelity. Using nIRCats high spatial resolution, we show that dopamine hotspots in late HD show increased ability to add new dopamine hotspots at high extracellular calcium concentrations and track individual dopamine hotspots over repeated stimulations and pharmacological wash to measure dopamine hotspots release fidelity. Compellingly, we demonstrate that antagonism of D2-autoreceptors using Sulpiride and direct blocking of Kv1.2 channels using 4-Aminopyradine (4-AP) increases the fidelity of dopamine hotspot activity in WT striatum but not in late HD striatum, indicating that D2-autoreceptor regulation of dopamine release through Kv1.2 channels is compromised in late HD. These findings, enabled by nIRCats, provide a more detailed look into how dopamine release is disrupted and dysregulated during Huntingtons Disease to alter the coverage of dopamine modulation across the dorsal striatum. SIGNIFICANCE STATEMENTHuntingtons Disease (HD) is a neurodegenerative disorder with no cure. Dysfunction of dopamine signaling is known to deteriorate in HD but has not been studied at the spatial level of individual release sites. Here, we image dopamine release from individual hotspots in brain slices from R6/2 HD mice at early and late disease timepoints with dopamine nanosensors. We track single dopamine hotspots and find that dopamine hotspot number, release intensity, and release fidelity decrease in HD, and demonstrate that changes in D2-autoreceptor regulation manifest through changes in hotspot release fidelity thus compromising dopamine coverage across the dorsal lateral striatum. These findings highlight dopaminergic neurons in cortico-striatal signaling during HD as a promising new therapeutic target for HD treatment.

neuroscience↗

bioRxiv2022

Quantification of cell penetrating peptide mediated delivery of proteins in plant leaves

Protein delivery to plants offers many opportunities for plant bioengineering via gene editing and through direction of protein-protein interactions. However, the delivery and confirmation of successful protein delivery to plants presents both practical and analytical challenges. We present a GFP bimolecular fluorescence complementation-based tool, delivered complementation in planta (DCIP), which allows for unambiguous and quantitative measurement of protein delivery in leaves. Using DCIP, we demonstrate cell-penetrating peptide mediated cytosolic delivery of peptides and recombinant proteins in Nicotiana benthamiana. We show that DCIP enables measurement of delivery efficiency and enables functional screening of cell penetrating peptide efficacies for in-plant protein delivery. Finally, we demonstrate that DCIP detects cell penetrating peptide mediated delivery of recombinantly expressed proteins such as mCherry and Lifeact into intact leaves. Finally, we also demonstrate, for the first time, delivery of a recombinant plant transcription factor, WUSCHEL (AtWUS), in N. benthamiana. RT-qPCR analysis of AtWUS delivery in Arabidopsis seedlings also suggests delivered WUS can recapitulate AtWUS-overexpression transcriptional changes. All combined, DCIP offers a new and powerful tool for interrogating cytosolic delivery of proteins in plants and highlights future avenues for engineering plant physiology.

plant biology↗

bioRxiv2021

Machine learning enables discovery of DNA-carbon nanotube sensors for serotonin

DNA-wrapped single walled carbon nanotube (SWNT) conjugates have remarkable optical properties leading to their use in biosensing and imaging applications. A critical limitation in the development of DNA-SWNT sensors is the current inability to predict unique DNA sequences that confer a strong analyte-specific optical response to these sensors. Here, near-infrared (nIR) fluorescence response datasets for ~100 DNA-SWNT conjugates, narrowed down by a selective evolution protocol starting from a pool of ~1010 unique DNA-SWNT candidates, are used to train machine learning (ML) models to predict new unique DNA sequences with strong optical response to neurotransmitter serotonin. First, classifier models based on convolutional neural networks (CNN) are trained on sequence features to classify DNA ligands as either high response or low response to serotonin. Second, support vector machine (SVM) regression models are trained to predict relative optical response values for DNA sequences. Finally, we demonstrate with validation experiments that integrating the predictions of ensembles of the highest quality CNN classifiers and SVM regression models leads to the best predictions of both high and low response sequences. With our ML approaches, we discovered five new DNA-SWNT sensors with higher fluorescence intensity response to serotonin than obtained previously. Overall, the explored ML approaches introduce an important new tool to predict useful DNA sequences, which can be used for discovery of new DNA-based sensors and nanobiotechnologies. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=100 SRC="FIGDIR/small/457145v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@9e1a2corg.highwire.dtl.DTLVardef@1c84e68org.highwire.dtl.DTLVardef@1939d1eorg.highwire.dtl.DTLVardef@30424e_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2021

Carbon nanotube biocompatibility in plants is determined by their surface chemistry

Agriculture faces significant global challenges including climate change and an increasing food demand due to a growing population. Addressing these challenges will require the adoption of transformative innovations into biotechnology practice, such as nanotechnology. Recently, nanomaterials have emerged as unmatched tools for their use as biosensors, or as biomolecule delivery vehicles. Despite their increasingly prolific use, plant-nanomaterial interactions remain poorly characterized, drawing into question the breadth of their utility and their broader environmental compatibility. Herein, we characterize Arabidopsis thaliana transcriptional response to single walled carbon nanotubes (SWNTs) with two different surface chemistries commonly used for biosensing and nucleic acid delivery: oligonucleotide adsorbed-pristine SWNTs, and polyethyleneimine-SWNTs loaded with plasmid DNA (PEI-SWNTs), both introduced by leaf infiltration. We observed that SWNTs elicit a mild stress response almost undistinguishable from the infiltration process, indicating that these nanomaterials are well-tolerated by the plant. However, PEI-SWNTs induce a much larger transcriptional reprogramming that involves stress, immunity, and senescence responses. PEI-SWNT-induced transcriptional profile is very similar to that of mutant plants displaying a constitutive immune response or treated with stress-priming agrochemicals. We selected molecular markers from our transcriptomic analysis and identified PEI as the main cause of this reaction. We show that PEI-SWNT response is concentration-dependent and, when persistent over time, leads to cell death. We probed a panel of PEI variant-functionalized SWNTs across two plant species and identified biocompatible SWNT surface functionalizations. Our results highlight the importance of nanoparticle surface chemistry on their biocompatibility and will facilitate the use of functionalized nanomaterials for agricultural improvement. Significance statementNanomaterials can be used in agriculture as biosensors to monitor plant health, as fertilizers or growth regulators, and as delivery vehicles for genome engineering reagents to improve crops. However, the interactions between nanoparticles and plant cells are not well understood. Here, we characterize the plant transcriptomic response to single-walled carbon nanotubes (SWNTs) commonly used for sensing and nucleic acid delivery. While SWNTs themselves are well tolerated by plants, SWNTs surface-functionalized with positively charged polymers become toxic and produce cell death. We identify molecular markers of this toxic response to create biocompatible SWNT formulations. These results highlight the significance of nanoparticle surface chemistry, perhaps more than the nanoparticles themselves, on downstream interactions of nanoparticles with the environment.

plant biology↗

bioRxiv2021

Polymer-Conjugated Carbon Nanotubes for Biomolecule Loading

Nanomaterials have emerged as an invaluable tool for the delivery of biomolecules such as DNA and RNA, with various applications in genetic engineering and post-transcriptional genetic manipulation. Alongside this development, there has been an increasing use of polymer-based techniques, such as polyethyleneimine (PEI), to electrostatically load polynucleotide cargoes onto nanomaterial carriers. However, there remains a need to assess nanomaterial properties, conjugation conditions, and biocompatibility of these nanomaterial-polymer constructs, particularly for use in plant systems. In this work, we develop mechanisms to optimize DNA loading on single-walled carbon nanotubes (SWNTs) with a library of polymer-SWNT constructs and assess DNA loading ability, polydispersity, and both chemical and colloidal stability. Counterintuitively, we demonstrate that polymer hydrolysis from nanomaterial surfaces can occur depending on polymer properties and attachment chemistries, and describe mitigation strategies against construct degradation. Given the growing interest in delivery applications in plant systems, we also assess the toxicity of polymer-based nanomaterials in plants and provide recommendations for future design of nanomaterial-based polynucleotide delivery strategies.

biochemistry↗

bioRxiv2021

Supervised Learning Model Predicts Protein Adsorption to Nanotubes

Engineered nanoparticles are advantageous for numerous biotechnology applications, including biomolecular sensing and delivery. However, testing the compatibility and function of nanotechnologies in biological systems requires a heuristic approach, where unpredictable biofouling via protein corona formation often prevents effective implementation. Moreover, rational design of biomolecule-nanoparticle conjugates requires prior knowledge of such interactions or extensive experimental testing. Toward better applying engineered nanoparticles in biological systems, herein, we develop a random forest classifier (RFC) trained with proteomic mass spectrometry data that identifies proteins that adsorb to nanoparticles, based solely on the proteins amino acid sequence. We model proteins that populate the corona of a single-walled carbon nanotube (SWCNT)-based optical nanosensor and study whether there is a relationship between the proteins amino acid-based properties and the proteins adsorption to SWCNTs. We optimize the classifier and characterize the classifier performance against other models. To evaluate the predictive power of our model, we apply the classifier to rapidly identify proteins with high binding affinity to SWCNTs, followed by experimental validation. We further determine protein features associated with increased likelihood of SWCNT binding: high content of solvent-exposed glycine residues and non-secondary structure-associated amino acids. Conversely, proteins with high content of leucine residues and beta-sheet-associated amino acids are less likely to form the SWCNT protein corona. The classifier presented herein provides a step toward undertaking the otherwise intractable problem of predicting protein-nanoparticle interactions, which is needed for more rapid and effective translation of nanobiotechnologies from in vitro synthesis to in vivo use. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=66 SRC="FIGDIR/small/449132v2_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@bbc175org.highwire.dtl.DTLVardef@9a0b94org.highwire.dtl.DTLVardef@16e22e1org.highwire.dtl.DTLVardef@1b40a84_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2021

A ratiometric dual color luciferase reporter for fast characterization of transcriptional regulatory elements

Plant synthetic biology requires precise characterization of genetic elements to construct complex genetic circuits that can improve plant traits or confer them new characteristics. Transcriptional reporter assays are essential to quantify the effect of gene expression regulator elements. Therefore, transcriptional reporter systems are a key tool in understanding control of gene expression in biology. In this work we construct and characterize a dual-color luciferase ratiometric reporter system that possesses several advantages over currently used reporters. It is ratiometric, reducing variability and increasing consistency between experiments; it is fast, as both reporters can be measured at the same time in a single reaction, and it is cheaper to perform than current dual-luciferase reporter assays. We have validated our system quantifying the transcriptional capability of a panel of promoters and terminators commonly used in synthetic biology with a broad range of expression magnitudes, and in a biologically relevant system, nitrate response.

synthetic biology↗

bioRxiv2021

Nanoparticle Cellular Internalization is Not Required for RNA Delivery to Mature Plant Leaves

Rapidly growing interest in nanoparticle-mediated delivery of DNA and RNA to plants requires a better understanding of how nanoparticles and their cargoes translocate in plant tissues and into plant cells. However, little is known about how the size and shape of nanoparticles influences transport in plants and use of their cargoes, limiting development and deployment of nanotechnology in plant systems. Here, we employ non-biolistically delivered DNA-modified gold nanoparticles (AuNP) spanning various sizes (5 - 20 nm) and shapes (spheres and rods) to systematically investigate their transport following infiltration into Nicotiana benthamiana (Nb) leaves. Generally, smaller AuNPs demonstrate more rapid, higher, and longer-lasting levels of association with plant cell walls compared to larger AuNPs. We observe internalization of rod-shaped but not spherical AuNPs into plant cells, yet surprisingly, 10 nm spherical AuNP functionalized with small-interfering RNA (siRNA) are most efficient at siRNA delivery and inducing gene silencing in mature plant leaves. These results indicate the importance of nanoparticle size in efficient biomolecule delivery, and, counterintuitively, demonstrate that efficient cargo delivery is possible and potentially optimal in the absence of nanoparticle cellular internalization. Our results highlight nanoparticle features of importance for transport within plant tissues, providing a mechanistic overview of how nanoparticles can be designed to achieve efficacious bio-cargo delivery for future developments in plant nanobiotechnology.

bioengineering↗

bioRxiv2021

Gold nanocluster mediated delivery of siRNA to intact plant cells for efficient gene knockdown

RNA interference (RNAi), which involves the delivery of small interfering RNA molecules (siRNA), has been used to validate target genes in plants, to understand and control cellular metabolic pathways, and as a green alternative for crop pest tolerance. Conventional siRNA delivery methods such as viruses and Agrobacterium-mediated delivery exhibit limitations in host plant species range and their use can result in uncontrolled DNA integration into the plant host genome. Here, we synthesize polyethyleneimine functionalized gold nanoclusters (PEI-AuNCs) to mediate siRNA delivery into intact plant cells and show these constructs enable efficient gene knockdown. We demonstrate that functionalized AuNCs protect siRNA from RNase degradation and are small enough (~2 nm) to bypass the plant cell wall which exhibits a size exclusion limit of 5-20 nm. These AuNCs in turn enable up to 76.5 {+/-} 5.9% GFP mRNA knockdown efficiency with no cellular toxicity. Our data suggest this simple and biocompatible platform for passive delivery of siRNA into intact plant cells could have broad applications in plant biotechnology.

bioengineering↗

bioRxiv2020

Transcriptomic and morphological response of SIM-A9 mouse microglia to carbon nanotube neuro-sensors

Single-walled carbon nanotubes (SWCNT) are used in neuroscience for deep-brain imaging, neuron activity recording, measuring brain morphology, and imaging neuromodulation. However, the extent to which SWCNT-based probes impact brain tissue is not well understood. Here, we study the impact of (GT)6-SWCNT dopamine nanosensors on SIM-A9 mouse microglial cells and show SWCNT-induced morphological and transcriptomic changes in these brain immune cells. Next, we introduce a strategy to passivate (GT)6-SWCNT nanosensors with PEGylated phospholipids to improve both biocompatibility and dopamine imaging quality. We apply these passivated dopamine nanosensors to image electrically stimulated striatal dopamine release in acute mouse brain slices, and show that slices labeled with passivated nanosensor exhibit higher fluorescence response to dopamine and measure more putative dopamine release sites. Hence, this facile modification to SWCNT-based dopamine probes provides immediate improvements to both biocompatibility and dopamine imaging functionality with an approach that is readily translatable to other SWCNT-based neurotechnologies.Competing Interest StatementThe authors have declared no competing interest.View Full Text

bioengineering↗

bioRxiv2020

Binding affinity and conformational preferences influence kinetic stability of short oligonucleotides on carbon nanotubes

DNA-wrapped single walled carbon nanotubes (SWNTs) have found a widespread use in a variety of nanotechnology applications. Yet, the relationship between structural conformation, binding affinity and kinetic stability of these polymers on SWNTs remains poorly understood. Here, we used molecular dynamics (MD) simulations and experiments to explore this relationship for short oligonucleotides adsorbed on SWNTs. First, using classical MD simulations of oligonucleotide-(9,4)-SWNT hybrid complexes, we explored the relationship between ssDNA and ssRNA surface conformation and sequence chemistry. We screened the conformation of 36 sequences of short ssDNA and ssRNA polymers on (9,4) SWNT, where the contour lengths were selected so the polymers can, to a first approximation, wrap once around the SWNT circumference. From these screens, we identified structural motifs that we broadly classified into "rings" and "non-rings." Then, several sequences were selected for detailed investigations. We used temperature replica exchange MD calculations to compute two-dimensional free energy landscapes characterizing the conformations of select sequences. "Ring" conformations seemed to be driven primarily by sequence chemistry. Specifically, strong (n,n+2) nucleotide interactions and the ability of the polymer to form compact structures, as for example, through sharp bends in the nucleotide backbone, correlated with ring-forming propensity. However, ring-formation probability was found to be uncorrelated with free energy of oligonucleotide binding to SWNTs ({Delta}Gbind). Conformational analyses of oligonucleotides, computed free energy of binding of oligonucleotides to SWNTs, and experimentally determined kinetic stability measurements show that {Delta}Gbind is the primary correlate for kinetic stability. The probability of the sequence to adopt a compact, ring-like conformation is shown to play a secondary role that still contributes measurably to kinetic stability. For example, sequences that form stable compact rings (C-rich sequences) could compensate for their relatively lower {Delta}Gbind and exhibit kinetic stability, while sequences with strong {Delta}Gbind (such as (TG)3(GT)3) were found to be kinetically stable despite their low ring formation propensity. We conclude that the stability of adsorbed oligonucleotides is primarily driven by its free energy of binding and that if ring-like structural motifs form, they would contribute positively to stability. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=104 SRC="FIGDIR/small/939918v1_ufig1.gif" ALT="Figure 1"> View larger version (22K): org.highwire.dtl.DTLVardef@6483e6org.highwire.dtl.DTLVardef@10f9e60org.highwire.dtl.DTLVardef@66c8c3org.highwire.dtl.DTLVardef@68ff4_HPS_FORMAT_FIGEXP M_FIG C_FIG

biophysics↗

bioRxiv2020

Protein Corona Composition and Dynamics on Carbon Nanotubes in Blood Plasma and Cerebrospinal Fluid

When a nanoparticle enters a biological environment, the surface is rapidly coated with proteins to form a "protein corona". Presence of the protein corona surrounding the nanoparticle has significant implications for applying nanotechnologies within biological systems, affecting outcomes such as biodistribution and toxicity. Herein, we measure protein corona formation on single-stranded DNA wrapped single-walled carbon nanotubes (ssDNA-SWCNTs), a high-aspect ratio nanoparticle ideal for sensing and delivery applications, and polystyrene nanoparticles, a model nanoparticle system. The protein corona of each nanoparticle is studied in human blood plasma and cerebrospinal fluid. We characterize corona composition by proteomic mass spectrometry to determine abundant and differentially enriched vs. depleted corona proteins. High-binding corona proteins on ssDNA-SWCNTs include proteins involved in lipid binding and transport (clusterin and apolipoprotein A-I), complement activation (complement C3), and blood coagulation (fibrinogen). Of note, albumin is the most common blood protein (55% w/v), yet exhibits low-binding affinity towards ssDNA-SWCNTs, displaying 1300-fold lower bound concentration relative to native plasma. We investigate the role of electrostatic and entropic interactions driving selective protein corona formation, and find that hydrophobic interactions drive inner corona formation, while shielding of electrostatic interactions allows for outer corona formation. Lastly, we study real-time binding of proteins on ssDNA-SWCNTs and find relative agreement between proteins that are enriched and bind strongly, such as fibrinogen, and proteins that are depleted and bind marginally, such as albumin. Interestingly, certain proteins express contrary behavior in single-protein experiments than within the whole biofluid, highlighting the importance of cooperative mechanisms driving selective corona adsorption on the SWCNT surface. Knowledge of the protein corona composition, dynamics, and structure informs translation of engineered nanoparticles from in vitro design to effective in vivo application.

bioengineering↗

bioRxiv2019

Surface Modification Effects on Single-Walled Carbon Nanotubes for Multimodal Optical Applications

Optical nanoscale technologies often implement covalent or noncovalent strategies for the modification of nanoparticles, whereby both functionalizations are leveraged for multimodal applications but can affect the intrinsic fluorescence of nanoparticles. Specifically, single-walled carbon nanotubes (SWCNTs) can enable real-time imaging and cellular delivery; however, the introduction of covalent SWCNT sidewall functionalizations often attenuates SWCNT fluorescence. Herein, we leverage recent advances in SWCNT covalent functionalization chemistries that preserve the SWCNTs pristine graphitic lattice and intrinsic fluorescence and demonstrate that such covalently functionalized SWCNTs maintain fluorescence-based molecular recognition of neurotransmitter and protein analytes. We show that the covalently modified SWCNT nanosensor fluorescence response towards its analyte is preserved for certain nanosensors, presumably dependent on the steric hindrance introduced by the covalent functionalization that hinders noncovalent interactions with the SWCNT surface. We further demonstrate that these SWCNT nanosensors can be functionalized via their covalent handles to self-assemble on passivated microscopy slides, and discuss future use of these dual-functionalized SWCNT materials for multiplexed applications.

bioengineering↗

bioRxiv2019

Corona exchange dynamics on carbon nanotubes by multiplexed fluorescence monitoring

Noncovalent adsorption of DNA on nanoparticles has led to their widespread implementation as gene delivery tools and optical probes. Yet, the behavior and stability of DNA-nanoparticle complexes once applied in biomolecule-rich, in vivo environments remains unpredictable, whereby biocompatibility testing usually occurs in serum. Here, we demonstrate time-resolved measurements of exchange dynamics between solution-phase and adsorbed corona-phase DNA and protein biomolecules on single-walled carbon nanotubes (SWCNTs). We capture real-time binding of fluorophore-labeled biomolecules, utilizing the SWCNT surface as a fluorescence quencher, and apply this corona exchange assay to study protein corona dynamics on ssDNA-SWCNT-based dopamine sensors. We study exchange of two blood proteins, albumin and fibrinogen, adsorbing to and competitively displacing (GT)6 vs. (GT)15 ssDNA from ssDNA-SWCNTs. We find that (GT)15 binds to SWCNTs with a higher affinity than (GT)6 and that fibrinogen interacts with ssDNA-SWCNTs more strongly than albumin. Albumin and fibrinogen cause a 52.2% and 78.2% attenuation of the dopamine nanosensor response, coinciding with 0.5% and 3.7% desorption of (GT)6, respectively. Concurrently, the total surface-adsorbed fibrinogen mass is 168% greater than that of albumin. Binding profiles are fit to a competitive surface exchange model which recapitulates the experimental observation that fibrinogen has a higher affinity for SWCNTs than albumin, with a fibrinogen on-rate constant 1.61-fold greater and an off-rate constant 0.563-fold smaller than that of albumin. Our methodology presents a generic route to assess real-time corona exchange on nanoparticles in solution phase, and more broadly motivates testing of nanoparticle-based technologies in blood plasma rather than the more ubiquitously-tested serum conditions.

bioengineering↗

bioRxiv2019

Nanotubes effectively deliver siRNA to intact plant cells and protect siRNA against nuclease degradation

Post-transcriptional gene silencing (PTGS) is a powerful tool to understand and control plant metabolic pathways, which is central to plant biotechnology. PTGS is commonly accomplished through delivery of small interfering RNA (siRNA) into cells. While siRNA delivery has been optimized for mammalian systems, it remains a significant challenge for plants due to the plant cell wall. Standard plant siRNA delivery methods (Agrobacterium and viruses) involve coding siRNA into DNA vectors, and are only tractable for certain plant species. Herein, we develop a nanotube-based platform for direct delivery of siRNA, and show high silencing efficiency in intact plant cells. We demonstrate that nanotubes successfully deliver siRNA and silence endogenous genes owing to effective intracellular delivery and nanotube-induced protection of siRNA from nuclease degradation. This study establishes that nanotubes, which are below the size exclusion limit of the plant cell wall, could enable a myriad of plant biotechnology applications that rely on RNA delivery.

plant biology↗

bioRxiv2018

CHEMOMETRIC APPROACHES FOR DEVELOPING INFRARED NANOSENSORS TO IMAGE ANTHRACYCLINES

Generation, identification, and validation of optical probes to image molecular targets in a biological milieu remains a challenge. Synthetic molecular recognition approaches leveraging the intrinsic near-infrared fluorescence of single-walled carbon nanotubes is a promising approach for chronic biochemical imaging in tissues. However, generation of nanosensors for selective imaging of molecular targets requires a heuristic approach. Here, we present a chemometric platform for rapidly screening libraries of candidate single-walled carbon nanotube nanosensors against biochemical analytes to quantify fluorescence response to small molecules including vitamins, neurotransmitters, and chemotherapeutics. We further show this approach can be leveraged to identify biochemical analytes that selectively modulate the intrinsic near-infrared fluorescence of candidate nanosensors. Chemometric analysis thus enables identification of nanosensor-analyte hits and also nanosensor fluorescence signaling modalities such as wavelength-shifts that are optimal for translation to biological imaging. Through this approach, we identify and characterize a nanosensor for the chemotherapeutic anthracycline doxorubicin, which provides an up to 17 nm fluorescence red-shift and exhibits an 8 {micro}M limit of detection, compatible with peak circulatory concentrations of doxorubicin common in therapeutic administration. We demonstrate selectivity of this nanosensor over dacarbazine, a chemotherapeutic commonly co-injected with DOX. Lastly, we demonstrate nanosensor tissue compatibility for imaging of doxorubicin in muscle tissue by incorporating nanosensors into the mouse hindlimb and measuring nanosensor response to exogenous DOX administration. Our results motivate chemometric approaches to nanosensor discovery for chronic imaging of drug partitioning into tissues and towards real-time monitoring of drug accumulation.

biochemistry↗

bioRxiv2018

Imaging Striatal Dopamine Release Using a Non-Genetically Encoded Near-Infrared Fluorescent Catecholamine Nanosensor

Neuromodulation plays a critical role in brain function in both health and disease. New optical tools, and their validation in biological tissues, are needed that can image neuromodulation with high spatial and temporal resolution, which will add an important new dimension of information to neuroscience research. Here, we demonstrate the use of a catecholamine nanosensor with fluorescent emission in the 1000-1300 nm near-infrared window to measure dopamine transmission in ex vivo brain slices. These near-infrared catecholamine nanosensors (nIRCats) represent a broader class of nanosensors that can be synthesized from non-covalent conjugation of single wall carbon nanotubes (SWNT) with single strand oligonucleotides. We show that nIRCats can be used to detect catecholamine efflux in brain tissue driven by both electrical stimulation or optogenetic stimulation. Spatial analysis of electrically-evoked signals revealed dynamic regions of interest approximately 2 microns in size in which transients scaled with simulation intensity. Optogenetic stimulation of dopaminergic terminals produced similar transients, whereas optogenetic stimulation of glutamatergic terminals showed no effect on nIRCat signal. Bath application of nomifensine prolonged nIRCat fluorescence signal, consistent with reuptake blockade of dopamine. We further show that the chemically synthetic molecular recognition elements of nIRCats permit measurement of dopamine dynamics in the presence of dopamine receptor agonists and antagonists. These nIRCat nanosensors may be advantageous for future use because i) they do not require virus delivery, gene delivery, or protein expression, ii) their near-infrared fluorescence facilitates imaging in optically scattering brain tissue and is compatible for use in conjunction with other optical neuroscience tool sets, iii) the broad availability of unique near-infrared colors have the potential for simultaneous detection of multiple neurochemical signals, and iv) they are compatible with pharmacology. Together, these data suggest nIRCats and other nanosensors of this class can serve as versatile new optical tools to report dynamics of extracellular neuromodulation in the brain.

neuroscience↗