Inverse Molecular Sentinel-Integrated Fiberoptic Sensor for Direct and

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Inverse Molecular Sentinel-Integrated Fiberoptics Sensor for Direct and In Situ Detection of miRNA Targets Pietro Strobbia, Yang Ran, Bridget M Crawford, Vanessa Cupil-Garcia, Rodolfo Zentella, Hsin-Neng Wang, Tai-Ping Sun, and Tuan Vo-Dinh Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.9b01350 • Publication Date (Web): 27 Mar 2019 Downloaded from http://pubs.acs.org on March 28, 2019

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Analytical Chemistry

Inverse Molecular Sentinel-Integrated Fiberoptics Sensor for Direct and In Situ Detection of miRNA Targets Pietro Strobbiaab#, Yang Ranac#, Bridget M. Crawfordab, Vanessa Cupil-Garciaad, Rodolfo Zentellae, Hsin-Neng Wangab, Tai-Ping Sune, Tuan Vo-Dinhabd* a. Fitzpatrick Institute for Photonics, Duke University, Durham, NC 27708, USA b. Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA c. Guangdong Provincial Key Laboratory of Optical Fiber Sensing and Communications, Institute of Photonics Technology, Jinan University, Guangzhou 510632, China d. Department of Chemistry, Duke University, Durham, NC 27708, USA e. Department of Biology, Duke University, Durham, NC 27708, USA # P.S. and Y.R. contributed equally to this work * Corresponding author: [email protected] Abstract Molecular advances have been made in analysis systems for a wide variety of applications ranging from bio-diagnostics, bio-safety, bio-engineering and biofuel research applications. There are, however, limited practical tools necessary for in situ and accurate detection of nucleic acid targets during field work. New technology is needed to translate these molecular advances from laboratory settings into the real-life practical monitoring realm. The exquisite characteristics (e.g., sensitivity and adaptability) of plasmonic nanosensors have made them attractive candidates for field-ready sensing applications. Herein, we have developed a fiber-based plasmonic sensor capable of direct detection (i.e., no washing steps required) of nucleic acid targets, which can be detected simply by immerging the sensor in the sample solution. This sensor is composed of an optical fiber that is decorated with plasmonic nanoprobes based on silver-coated gold nanostars (AuNS@Ag) to detect target nucleic acids using the surface-enhanced Raman scattering (SERS) sensing mechanism of nanoprobes referred to as inverse molecular sentinels (iMS). These fiber-optrodes can be reused for several detection-regeneration cycles (> 6). The usefulness and applicability of the iMS fiber-sensors was tested by detecting target miRNA in extracts from leaves of plants that were induced to have different expression levels of miRNA targets. These fiber-optrodes enable direct detection of miRNA in plant tissue extract without the need for complex assays by simply immersing the fiber in the sample solution. The results indicate the fiber-based sensors developed herein have the potential to be a powerful tool for field and in situ analysis of nucleic acid samples. Keywords: surface-enhanced Raman scattering (SERS), sensor, miRNA, optrode, plasmonics, molecular sensor, fiberoptics, nanoprobes

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Introduction The knowledge of genomic and transcriptional information of plants is of key importance for the fields of bioanalysis, bio-safety, bio-engineering and biofuel research. For example, to meet food safety standard, genetically modified organisms (GMO) have to be identified in a screening process performed via PCR in laboratory settings.1, 2 In bio-engineering plant biology and biofuel research, quantitative reverse transcriptase-PCR (qRT-PCR) is also routinely used to study transcriptional changes in plants.3, 4 Such changes can be associated with external stimuli through RNA-dependent pathways activated in plants. Among other purposes, this information can be used to design modification in the plant’s genome, as well as in the plant’s environment, for more efficient biomass production. In spite of the advancements made in these fields, bio-safety and bio-engineering research still lack the instrumentation necessary for the accurate detection of nucleic acid targets in the field. Without the development of such instrumentation, the key task of nucleic acid detection will be limited to laboratory settings, hindering rapid translation of bio-safety and bio-engineering research into the field. In recent years, there has been a significant effort to develop assays for the detection of target nucleic acids without the need of complicated PCR machinery. This effort has led to many different sensing strategies.5-9 Among them, promising applications are those that utilize plasmonic nanoparticles in surface-enhanced Raman sensors.10-12 These sensors exploit the unique properties of metallic nanoparticles to enhance the Raman signal of molecules in close proximity to the metal surface, due to a phenomenon called surface-enhanced Raman scattering (SERS).13-18 SERS is an analytical spectroscopic method based on vibrational characteristics of molecules, which gives several advantages over other detection methods. The narrow bandwidth of Raman peaks allows for highly multiplexed detection of targets. Furthermore, the nature of Raman and SERS enable the direct identification of chemical species through their vibrational fingerprint. These advantages have made researchers pursue SERS sensing in applications ranging from chemical sensing to biomedicine and biodefense.16-25 Our group has developed a unique class of SERS sensors capable of direct detection of nucleic acids biotargets (e.g., DNA, mRNA and miRNA), referred to as molecular sentinels (MS) and inverse molecular sentinels (iMS).26-29 The basic unit of these biosensors is the MS sequence, a single-strand nucleic acid probe bound to a plasmonic-active surface and terminated with a Raman reporter molecule. The MS sequence is designed to form a stem-loop, which controls the distance between the reporter and the surface of the nanoparticle and therefore the SERS signal. The target sequence forms a hybrid with its complementary strand on the MS, which causes the Raman reporter to move farther away from the plasmonic-active surface (‘OFF’ SERS signal), exploiting the steep distance dependence of SERS as a transduction mechanism. This ‘ON-to-OFF’ signal detection scheme was reversed in the development of iMS sensors to increase the limit of detection (LOD) and accuracy of the sensor by avoiding false-positive responses.28, 29 The iMS sensing mechanism utilizes a placeholder DNA strand (complementary to the target sequence) that binds a portion of the molecular sentinel strand to hold the probe in an open (SERS ‘OFF’) position. In the presence of the target sequence, the stem-loop closes due to non-enzymatic strand displacement of the placeholder-probe hybrid. The diagnostic capabilities of these sensors have been demonstrated detecting variations in expression of miRNA in cancer cell lines,28 as well as in a “smart tattoo” biosensor where iMS sensors were used to detect synthetic nucleic acid targets in a large animal model in vivo.30 This technology is a significant advantage over other plasmonic nanosensors by providing homogenous direct sensing (i.e., no need of washing steps). While nanoparticle-based assays are powerful tools for nucleic acid detection, this class of sensors commonly requires the mixing of the nanosensors with the sample under analysis and, in most cases, several washing steps. These processes require complex sample preparation and reduce the robustness of ACS Paragon Plus Environment

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the method. Furthermore, the mixing process is irreversible, resulting in a single-use analytical method. To overcome issues of sample preparation and sample accessibility, SERS-based plasmonic fiber sensors have been developed.31-40 Fiber-based sensors, also called fiber-optrodes, are optical sensors built at the end of a fiber in order to deliver both sensor and light stimulus directly in situ. This strategy allows to interrogate samples not easily accessible as well as to avoid background signal from regions in the sample not under analysis. Furthermore, due to the sensors being integrated on the surface of a fiber, these detection methods do not require sample preparation and avoid disturbing the sample under analysis. Fiber-based in situ detection has been used for the direct detection of bio-analytes, as well as with tapered fiber to analyze target species in micro-environment.41 Fiber-based sensors can be integrated in portable instruments as long as the output and input are coupled to a fiber.39 Thus, the development of fiber-based sensors for the direct detection of nucleic acid biotargets will significantly contribute to the fields of biosafety and bio-engineering by providing tools that do not require laboratory settings and that can detect the target species in situ. In this paper, we first report the integration of iMS nanoprobes onto a fiber optic for the development of a fiber-based plasmonic sensor. In this study, we demonstrate the successful functionalization of the end of a fiber optic with iMS nanoprobes and their utility in multiple detection cycles, demonstrating the recyclability of the miRNA target-specific sensing mechanism. These sensors were demonstrated to retain the calibrated response throughout regeneration cycles and among different fibers fabricated simultaneously. Finally, we used the sensors to detect miR156 in RNA extracted from N. benthamiana leaf tissues, comparing a plant overexpressing miR156 with a control overexpressing miR319, a different miRNA sequence. The target miRNA (i.e., miR156) was selected because of its involvement in the flowering regulation pathways, which is an important aspect to control during plant growth for optimizing biomass production.42 This work represents the first development of a reusable SERS-based fiber biosensor for direct detection of miRNA targets for use in bio-engineering applications. Experimental Section Materials The optical fiber used in this study is the multimode silica fiber (400/440) with a numerical aperture (NA) of 0.25, which was purchased from CeramOptec Industries Inc. (Bonn, Germany). All chemicals were purchased from Sigma-Aldrich (St. Louis, MO) unless otherwise specified. Ammonium hydroxide (NH4OH, 29%) and pure 100%-ethanol were acquired through VWR (Radnor, PA). The silver nitrate was obtained from Alfa Aesar (Haverhill, MA). All the chemicals and reagents were at the highest purity grade available and used as received. Deionized (DI) water (18 MΩ cm) was used throughout the experiment. UV/Vis Measurements UV/Vis extinction spectra were acquired with a FLUOstar Omega plate reader (BMG LABTECH GmbH; Germany). Using a Cornstar 96-well plate (Corning; Corning, NY), 100 µL volume and 200 flashes. Transmission Electron Microscopy Measurements The structural features and morphology of the silver-coated gold nanostars were visualized using transmission electron microscopy. The samples were cast on Formvar carbon coated copper grids and imaged with a FEI Tecnai G2 Twin transmission electron microscope (Fisher Scientific, USA) at 160 kV. Scanning Electron Microscopy Measurements ACS Paragon Plus Environment


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Scanning electron microscopy (SEM) micrographs were obtained using a XL30 SEM-FEG (FEI; Hillsboro, OR), 3 kV and a TV-scan mode (average of 32 images). The fast scanning mode was performed to avoid charging on the insulating fiber. Silver-Coated Gold Nanostar Synthesis The AuNS were synthesized as previously reported using a seed-mediated method.43 Briefly, 12 nm citrate gold seed solution was prepared by use of a previously reported method.44 A 10 mL solution of 0.25 mM HAuCl4 containing 10 μL of 1 N HCl was prepared in a 20 mL scintillation vial. With rapid stirring, 100 µL of 12 nm gold seed was quickly added to the above solution. After even dispersion of the gold seed, 50 µL of 0.1 M ascorbic acid (AA) and 50 µL of 2 mM AgNO3 were rapidly and simultaneously added, and the color of the solution changed from a pale red to deep blue. The process was completed in less than 1 minute. The silver coating of the AuNS was obtained by the rapid addition of 50 µL of 0.1 M AgNO3 and 10 µL of NH4OH, within minutes of the AuNS synthesis being completed. Such synthesized silver-coated gold nanostars (AuNS@Ag) were used 2 hr after the synthesis. Fresh batches of AuNS@Ag were used for fabrication of the fiber-optrodes. The spectra for the AuNS and AuNS@Ag, as well as for the Raman reporter molecule (Cy5), are reported in Figure S1 (in the Supporting Information). Figure S2A and B (in the Supporting Information) reports the TEM micrographs of the AuNS and AuNS@Ag, respectively. Fiber-Optrode Fabrication A piece of fiber with a length of 25 cm was cut off from the original coil. The coating on both ends of the optical fiber was removed by flame-heating for a length of 1 cm. One end was immobilized into a fiber adaptor with glue to fit the optical setup, as the laserguiding end. Afterwards, the facet of the fiber at the adaptor end was polished by two abrasive papers of increasinglyfine roughness, to provide a flat surface to collect the laser effectively. The free end of the fiber, which is adopted as the fiber-optrode end, was immersed into a 10% APTES solution lasting for 3 hours. After being washed in pure ethanol, the optrode end was moved into the prepared AuNS@Ag solution and left under moderate shaking

Figure 1. A. Schematic representation of the optical detection system used with the fiber-optrodes. In the inset, a schematic representation of the functionalized fiber surface and a scanning electron micrograph of the functionalized surface of a fiber-optrode. B. Schematic representation of the iMS sensing mechanism on the surface of the fiber-optrode.


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overnight. The fiber-optrode was then washed numerous times with DI water to get rid of the residual unbound AuNS@Ag particles. A schematics of the fiber optrode is shown in the inset of Figure 1A with an SEM micrograph of the functionalized fiber surface. An SEM micrograph of the functionalized fiber surface is also shown in Figure S3 (in the Supporting Information). Inverse Molecular Sentinels-Integrated Fiber-Optrode Fabrication The iMS probes were integrated by immersing the fiber-optrodes as fabricated in a solution containing 0.25 mM MgCl2 and 0.2 µM probe strand overnight. The probe strand used herein was designed to detect miR156 and purchased from IDT (Coralville, IA), same strands for all the other DNA synthetic products. The probe strand sequence and modification were HS-CH2(6)- (5’) AAA AAT CTC TTA AAA AAA AAA TGA CAG AAG AGA (3’) -Cy5. After careful washing using Tris-HCl 10 mM buffer, the fiberoptrodes were immerged for 10 min in mercaptohexanol 0.1 mM. Then washed again in Tris-HCl 10 mM buffer and immersed in a solution containing 0.2 µM placeholder strand in PBS overnight. The placeholder strand sequence was (3') TTT TTA CTG TCT TCT CTC ACT C (5'). The integrated fiberoptrodes are carefully washed 3 times in PBS and stored in PBS. The synthetic target miR156 sequence used in the experiments was (5’) TGA CAG AAG AGA GTG AGC AC (3’). The hybrids calculated between the sequences used for the sensor are shown in Figure S4A and B (in the Supporting Information). A schematic representation of the mechanism by which the iMS works is depicted in Figure 1B. SERS Measurements A backscattered Raman setup was used to measure the SERS signal from the fibers (Figure 1). A 633 nm HeNe laser (Melles-Girot; Carlsbad, CA) was passed through a laser line filter (Thorlabs; Newton, NJ), a 10% transmission neutral density filter (Thorlabs; power at fiber tip = 0.5 mW) and reflected on a 633 nm notch filter (Thorlabs). The light was launched in the fiber sensors using a collimator NA = 0.25 (Thorlabs). The light scattered from the fiber tip was collected through the same optics, passed through an additional notch filter and collected into the spectrometer using a lens (f/4; Thorlabs). The spectrometer used was an Acton 2300 (Princeton Instruments; Acton, MA) coupled to a PiMAX CCD camera (Princeton Instruments). The spectra acquisition was controlled using Winspec 32 (Roper Scientific; Trenton, NJ). Each spectrum was measured with a total integration time of 2.5 s and avalanche gain of 2000. To detect the Cy5 reference spectrum, we used a fiber probe (InPhotonics; Norwood, MA) connected to a 100 mW 785 nm excitation laser (Optoengine; Midvale, UT) and a Raman detection system (LS785 and Pixis100; Princeton Instrument). Plasmid Construction Genomic DNA of Arabidopsis thaliana ecotype Columbia-0 was used as template to amplify miR319a and miR156f genes by PCR. The resulting PCR products were cloned into pCR8/GW/TOPO (Thermo Fisher; Waltham, MA) and sequenced to verify accuracy. Finally, the miRNA genes were transferred to the plant expression vector pEarlyGate100 by Gateway recombination. The resulting plasmids pEG100miR319a and pEG100-miR156f were transformed into Agrobacterium tumefaciens strain GV3101 pMP90. Nicotiana benthamiana Transient Transformation Leaf agro-infiltration procedures were performed as previously described.45 Agrobacterium cultures were diluted to an OD600 = 0.4 prior to infiltration. Small RNA Extraction and RT-qPCR Analysis



N. benthamiana leaves were harvested 48 h after agroinfiltration, flash-frozen and pulverized in liquid nitrogen with mortar and pestle. Total RNA was extracted from 100 mg of leaf powder with Quick-RNA MiniPrep kit (Zymo Research; Irvine, CA), according to the manufacturer instructions. Total RNA was further separated into small and large RNA with the same RNA kit. First strand cDNA was synthesized using the Transcriptor First Strand cDNA Synthesis kit (Roche Applied Science; Germany). For qPCR, the FastStart Essential DNA Green Master mix was used on a LigthCycler 96 Instrument (Roche Applied Science). The housekeeping gene PP2A from N. benthamiana was used as internal control.46 Results and Discussion Sensor Mechanism and Integration The iMS nanoprobes were integrated on the optical fiber by chemically linking the AuNS@Ag onto the fiber surface, producing the fiber-optrode (see FiberOptrodes Fabrication). The developed sensor combines the in situ measurement capabilities of fiber sensing with the miRNA detection capabilities of the iMS nanoprobes. Figure 2A shows an example of the spectra obtained from the iMS before and after the target miRNA (i.e., miR156) addition. In the presence of the target, the peak at 558 cm-1, which is characteristic of the Raman reporter molecule Cy5, is clearly visible in the spectrum (Figure 2A). The Raman measurements were performed with a 633 nm laser to take advantage of resonance Raman effect for the Raman reporter. Due to the absorption characteristic of Cy5, the fiber sensor exhibited a strong fluorescence background from the reporter. We used the fluorescence background to normalize the SERS response of the iMS by normalizing all spectra for the highest intensity wavelength of the fluorescence peak of Cy5. The sensor response was then calculated as the difference in intensity between the latter wavelength and the Raman peak at 558 cm-1 normalized for the fluorescence intensity. The normalization method is represented by the dotted lines in Figure 2A. This normalization methodology allowed for the results to account for variations in the delivered and collected light due to the coupling of the fiber with free-space optics and for the possible photobleaching of the dye on the fiber surface.

Figure 2. A. Raman spectra of the iMS sensors in the ON state (in target miR156) and in the OFF state (in PBS). The vertical dotted line represents the wavelength of the Cy5 Raman peak. The horizontal dotted line represents the reference intensity point used for the calculation of the normalized peak intensity. B. Comparison of a reference Cy5 spectrum with the blank-subtracted spectrum of the iMS ON from panel A. C. Sensor response for a fiber-optrode immersed first in PBS, then in a solution containing miR155 and finally in a solution containing miR156 target. The error bars represent the standard error (n = 3).


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To verify that the signal change was due to the Raman reporter, we compare the signal change observed with a reference Cy5 spectrum. The signal change from the sensor was obtained by subtracting the blank spectrum (iMS OFF) to the iMS ON spectrum, both from Figure 2A. The reference spectrum for Cy5 was measured by coating AuNS@Ag with the MS and detecting the SERS signal using a 785 nm laser. This spectrum was blank subtracted to remove the contributions of optics and glass container. The use of a different excitation (i.e., 785 nm instead of 633 nm) permitted to avoid fluorescence signal and the absence of the fiber to avoid background signal from the fiber. The spectra were both backgroundsubtracted for visualization purposes and are plotted offset in respect to the Y axis in Figure 2B. As it can be observed from the figure, the spectra show the same Raman peaks, demonstrating the correct functioning of the iMS on the fiber-optrode. To evaluate the efficacy and specificity of the sensing method, the fiber-optrodes were tested in three different solutions: -1- PBS, -2- a solution containing 200 nM synthetic miR155 (i.e., a noncomplementary strand) and -3- a solution containing 200 nM synthetic miR156 (i.e., the target miRNA). Figure 2C depicts the sensor response of a fiber-optrode immersed in the three solutions for 30 min. The sensor response is given as the normalized peak intensity, following the process described above. As it can be observed, the fiber-optrode has no response to miR155 and its signal is statistically identical to the signal observed in PBS. It was observed that the sensor turned ‘ON’ in the presence of the miRNA target. These results demonstrate the successful sensing of synthetic miRNA using the developed fiberoptrodes, as well as the specificity of the miRNA detection mechanism. Fiber-Optrode Sensor Reusability An important aspect for the application of this fiber-optrodes is the possibility of re-using a sensor for multiple cycles. This possibility allows for the pre-calibration of the sensor response, while also improving the field-applicability of the sensor. To demonstrate the recyclability of the sensing mechanism, three different fiber-optrodes were used through six detection-regeneration cycles. Figure 3A depicts the mechanism of a single detection-regeneration cycle. The cycles consisted of using the sensor to detect 200 nM target then regenerating the sensing mechanism by exposing the fiber-optrodes to the placeholder strand (also at a 200 nM concentration) overnight. The sensor responses for three different fibers during various detection-regeneration cycles are reported in Figure 3B. As can be observed, the fiber-optrodes retain their function even following six cycles. These results demonstrate the sensor reusability and also suggest that the plasmonic nanoparticles used in the fiber-optrodes are stable for over one week. Additionally, the stability of the fiber-optrodes was further demonstrated by

Figure 3. A. Schematic representation of theACS mechanism cycle. B. Sensor response for 3 Paragonfor Plusa detection-regeneration Environment different fiber-optrodes (Fiber# 1,2,3) in PBS (blank) and in 200 nM target miR156, through multiple detectionregeneration cycles.


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observing the retention of the detection capability after one 30 days (see Figure S5 in the Supporting Information). Although the sensing mechanism was observed to be regenerated after each cycle, the total response of the sensor changed over multiple cycles. Figure 4 depicts the change in total response of the fiberoptrodes by plotting the percent change (i.e., signal change between blank and target) of the different fiber-optrodes relative to the initial signal change (cycle #1) as a function of the cycle number. We observed a general trend characterized by a loss of signal change for increasing detection-regeneration cycles. The trend was quantified with a linear regression over the average percent change of the three fiber-optrodes as a function of cycle number. From the gradient of the average linear change, it can be determined that the fiber-optrodes exhibit a loss of 8% of the total signal change per cycle. While this factor limits the maximum number of regeneration cycles obtainable for a single fiberoptrode, the decrease in percent change does not influence its sensing characteristics. In fact, the loss in total signal change can be attributed to the irreversible photobleaching of the Raman reporters. This effect is prominent on fiber-optrodes as the Raman reporter dyes are continuously exposed to Figure 4. Normalized total signal change for three the laser, unlike in solution-based assays. fiber-optrodes over multiple detection-regeneration Photobleaching causes the loss of the resonance cycles. The dashed line represents a linear regression for the average normalized total signal Raman and therefore of the signal change calculated change for the three fibers (m = -8%). contribution from certain reporters. However, due to the fact that nucleic acid probes themselves are not involved in this photodegradation process, the binding properties of the sensor surface are not affected (see Calibration and Limit of Detection section) and only the total signal intensity changes. Calibration and Limit of Detection As mention above, an important aspect in the development of the fiber-optrodes is the recyclability of the sensing mechanism for pre-calibration purposes. To observe the binding characteristics of the fiberoptrodes and demonstrate the possibility of pre-calibration, we investigated the concentration-dependent sensor response for two different fiber-optrodes by dipping the fibers in a solution containing target at concentrations ranging from 1 to 200 nM for 30 min. It is noteworthy that the graphs below show 366 nM as the highest concentration because it takes into account the additive response of the sensor. For example, the response from a sensor first tested in a 1-nM solution and then immersed in a 5-nM solution is graphed at a concentration equal to 6 nM. Figure 5A shows the background-subtracted spectra around the peak used for the sensor response from a fiber-optrode exposed to various concentrations of target miRNA (i.e., miR156). As it can be observed, the peak around 558 cm-1 increases with increasing target concentrations. Figure 5B and 5C show the fiber-optrodes response as a function of target concentration for two different fibers (1 and 2, respectively in 5B and 5C), while Figure 5D shows the response of fiber 2 after a detection-regeneration cycle. The sensor response is given as percent change, which is calculated by taking the signal change from a specific fiber-optrode (calculated as 𝑠𝑖𝑔𝑛𝑎𝑙 𝑐ℎ𝑎𝑛𝑔𝑒 = 𝑠𝑖𝑔𝑛𝑎𝑙[𝑥] ― 𝑠𝑖𝑔𝑛𝑎𝑙𝑃𝐵𝑆, as explained in Sensor Mechanism and Integration) and normalizing for the maximum signal

(

change observed for that specific fiber-optrode 𝑝𝑒𝑟𝑐𝑒𝑛𝑡 𝑐ℎ𝑎𝑛𝑔𝑒 = ACS Paragon Plus Environment

(

𝑠𝑖𝑔𝑛𝑎𝑙[𝑥] ― 𝑠𝑖𝑔𝑛𝑎𝑙𝑃𝐵𝑆

𝑠𝑖𝑔𝑛𝑎𝑙[𝑀𝐴𝑋] ― 𝑠𝑖𝑔𝑛𝑎𝑙𝑃𝐵𝑆

) ∙ 100). This

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strategy was used to take into account changes in the total signal change observed over multiple detection-regeneration cycles.

Figure 5. A. Raman peak at 558 cm-1 of a fiber-optrode immersed in solution of increasing target concentration (0 -200 nM). The vertical dotted line represents the wavelength of the Cy5 Raman peak used for the sensor response. The inset reports the blank subtracted peaks. Normalized sensor response as a function of target miRNA concentration, for respectively Fiber 1 (B), Fiber 2 (C) and Fiber 2 cycle 2(D). The response was fitted with a surface saturation function and the dissociation constants found were of 19 ± 2, 18 ± 2 and 14 ± 3 nM, in respectively A, B and C. Error bars represent the standard error (n=3). The insets show the linear region of the sensor response fitted to a line.

A surface saturation function (𝑓(𝑥) =

(𝑥 +𝑥 𝑘) ∙ 100) was used to fit the responses of the different fiber-

optrodes. The dissociation constants (k) calculated for the different sensors were of 19 ± 2, 18 ± 2 and 14 ± 3 nM, for respectively Fiber 1, Fiber 2 and Fiber 2 Cycle 2. The dissociation constants were found to be statistically identical (p > 0.12), both in the case of two fibers fabricated in the same batch and tested separately or for the same fiber tested after a detection-regeneration cycle. The agreement in dissociation constants shows how by normalizing the signal is possible to obtain comparable signal changes in different fibers and cycles. Furthermore, these results agree with the previously formulated hypothesis (see Sensors Reusability), according to which the decay of total signal change in the sensors over multiple cycle does not influence the binding affinity of the sensor but only the observable signal change. This study demonstrates that by normalizing for the maximum signal change it is possible to calibrate a fiber prior to its use on the sample under analysis. In addition, we also calculated the LOD for the fiber-optrodes by fitting a linear regression in the region of linear response of the sensor shown in the insets in Figure 5BCD. The LOD for the fiber-optrodes was determined to be of 1.6 nM. ACS Paragon Plus Environment


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Detection of Overexpressed miR156 in RNA Extracts from Leaf Tissue To test the applicability of the fiber-optrodes to real-life samples, we evaluated the use of the sensors on RNA extracted from leaf tissue of a control plant and a plant transformed to overexpress the target miRNA. N. benthamiana, a close relative of tobacco, was selected for these studies because it is routinely use in plant biology research and has an extremely low spontaneous expression of miR156. The procedures to induce expression of miRNA in N. benthamiana are discussed in detail in the experimental section (Plasmid Construction and Nicotiana benthamiana Transient Transformation) and schematically Figure 6. Schematic depiction of the transient transformation process. Plasmid containing a plant depicted in Figure 6.

expression vector and a sequence associated to specific miRNAs were transformed into Agrobacterium tumefaciens. The Agrobacterium was then infiltrated into N. benthamiana leaves, inducing the expression of the target miRNA in the cell nucleus.

Figure 7A shows a representation of the experimental procedure for these studies, in which we compared the results obtained with the fiber sensors and with qPCR analysis. The sensor response was detected by immerging the fiber-optrode for 30 min in a 40 ng/µL solutions of small RNA extract diluted in PBS. The first RNA sample was extracted from a leaf transformed with a bacterial-vector to overexpress miR319 (control plant, overexpressing a miRNA with a different sequence), while the second was extracted from a leaf induced to overexpress miR156 (i.e., the target miRNA). Figure 7B shows a comparison of sensor response from the two samples. As it can be observed, the sensor responds to the presence of miR156, showing a significantly different signal for the miR156transformed leaf as compared to the control (p = 0.06). To confirm the difference in miR156 concentration, we detected pri-miR156 using RT-qPCR on the extracted-RNA samples. We used the precursor of miRNA, which is proportional to the expression of miR156, due to its longer sequence with respect to the mature miRNA making the PCR results more accurate. The expression of miR156 was

Figure 7. A. Schematic representation of the experimental procedure. B. Sensor response from a fiber-optrode immerged in a solution of small RNA extracted from an N. benthamiana leaf induced to overexpress miR319 and a leaf induced to overexpress miR156. Error bars represent the standard error (n=3). C. RT-PCR data reporting the expression of pri-miR156 relative to the PP2A N. benthamiana-gene. Error bars represent the standard error (n=3). ACS Paragon Plus Environment

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reported relative to PP2A, an endogenous housekeeping gene of N. benthamiana and consistently expressed at moderate levels. This analysis showed a 150000-fold (217.41) change in expression of miR156 between the two leaves (Figure 7C). The large difference in expression between the RNA is due to the fact that N. benthamiana express extremely low levels of miR156, which is a miRNA sequence involved in the developmental stage of a plant. The low levels of endogenous miR156 cause the baseline level of the target sequence to be approximately zero in the control plant, and thus exponentially increase the fold change. The PCR results confirmed a large difference in miR156 expression between the leaves, in agreement with the difference in signal response from the extracted RNA measured with the developed fiber sensor. Conclusion In summary, we have developed a new type of fiber-optrode biosensor for specific and direct detection of miRNA targets using SERS-based iMS nanobiosensors. The biosensors can be reused for numerous detection-regeneration cycles (> 6). The normalized sensor response was observed to be stable and unchanged by the detection-regeneration cycles, allowing for the pre-calibration of the sensors. Finally, the fiber-optrodes were successfully tested on RNA samples from genetically-transformed plant leaves. The development of these novel fiber-optrodes enable the detection of miRNA in plant tissue samples without the need for complex assays but by simply immerging the optrodes in the RNA extract solution. Whereas this study was focused on plant bioassays, the fiber-optrode technology has the potential to be a useful tool for field analysis in other areas involving nucleic acid samples. The iMS fiber-optrode biosensor platform will move molecular analysis from the traditional lab-based qRT-PCR assay scheme to a novel molecular platform that is simpler and more cost effective for bioanalysis research capable to enhance biosensing in the areas of molecular screening, and ultimately better suited for field applications. Acknowledgements This research is supported by the U.S. Department of Energy Offices of Science, under award number DE-SC0014077 and DE-SC0019393. Y. R. acknowledges the support of the China Scholarship Council (visiting scholar grant), National Natural Science Foundation of China (grant number 61775082) and Pearl River S&T Nova Program of Guangzhou (grant number 201610010151). B. M. C. acknowledges the support of the National Science Foundation Graduate Research Fellowship (grant number 1106401). Associated Content: UV-Vis spectra of Raman reporter, AuNS and AuNS@Ag; TEM micrographs of AuNS and AuNS@Ag; SEM micrograph of the functionalized fiber surface; calculated hybrids formed by the DNA strands used in the sensing mechanism; response of fiber sensors after being stored for 30 days. References 1. Holst-Jensen, A.; Rønning, S. B.; Løvseth, A.; Berdal, K. G., PCR technology for screening and quantification of genetically modified organisms (GMOs). Anal Bioanal Chem 2003, 375, 985993. 2. Debode, F.; Huber, I.; Macarthur, R.; Rischitor, P.; Mazzara, M.; Herau, V.; Sebah, D.; Dobnik, D.; Broeders, S.; Roosens, N., Inter-laboratory studies for the validation of two singleplex (tE9 and pea lectin) and one duplex (pat/bar) real-time PCR methods for GMO detection. Food Control 2017, 73, 452-461. 3. Springer, A.; Acker, G.; Bartsch, S.; Bauerschmitt, H.; Reinbothe, S.; Reinbothe, C., Differences in gene expression between natural and artificially induced leaf senescence in barley. Journal of plant physiology 2015, 176, 180-191.



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Inverse Molecular Sentinel-Integrated Fiberoptic Sensor for Direct and

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