Purification-Free MicroRNA Detection by Using Magnetically

Publication Date (Web): August 9, 2018. Copyright © 2018 American Chemical Society. *E-mail: [email protected]. Cite this:Anal. Chem. 2018, ...
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Purification-Free MicroRNA Detection By Using Magnetically Immobilized Nanopores On Liposome Membrane Satoshi Fujii, Koki Kamiya, Toshihisa Osaki, Nobuo Misawa, Masatoshi Hayakawa, and Shoji Takeuchi Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.8b01443 • Publication Date (Web): 09 Aug 2018 Downloaded from http://pubs.acs.org on August 10, 2018

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Analytical Chemistry

Purification-Free MicroRNA Detection By Using Magnetically Immobilized Nanopores On Liposome Membrane Satoshi Fujii†, Koki Kamiya†, Toshihisa Osaki†,‡, Nobuo Misawa†, Masatoshi Hayakawa§, Shoji Takeuchi†, ‡,*. † Artificial Cell Membrane Systems Group, Kanagawa Institute of Industrial Science and Technology, 3-2-1 Sakado, Takatsu, 213-0012 Kawasaki, Japan ‡ Institute of Industrial Science, The University of Tokyo, 4-6-1 Komaba, Meguro, 153-8505 Tokyo, Japan § Research and Development Department, Kanagawa Institute of Industrial Science and Technology, 3-2-1 Sakado, Takatsu, 213-0012 Kawasaki, Japan ABSTRACT: MicroRNAs have critical roles in a number of serious diseases and, as a result, are of major interest as clinical diagnostic targets. Conventionally, microRNAs are collected from blood and urine samples, and are measured by either quantitative reverse transcription polymerase chain reaction or microarray. Recently, nanopore sensing techniques have been applied for measuring microRNAs at the single molecule level. However, existing techniques are technically complex, needing several tools and requiring purification and/or labelling of microRNA samples prior to use. Here we report a method for microRNA detection in a simple procedure requiring neither purification nor labelling. This system utilizes magnetic beads anchored with DNA and nanopores on a liposome membrane. In the presence of the target microRNA, it forms a duplex with complementary DNA, which is then cleaved by a duplex-specific nuclease (DSN). The cleaved DNA, which harbors a liposome on its terminus, is subsequently released from the magnetic bead, fuses to the lipid bilayer on chip, and emits an electrical signal derived from the formation of a nanopore. Because of a property of the DSN, the signals derived from microRNAs are expected to be amplified in an isothermal reaction. Our system possesses the specificity to detect target microRNAs from mixtures containing >106 different microRNA sequences and readily uses blood or urine samples. Although the limit of detection is above 10 nM and need to be improved for practical diagnosis, as purification and labelling are not required, the presented system proposes a possible schematic for the development of easy and on-site diagnosis.

MicroRNAs are non-coding RNAs that regulate gene expression in various biological processes, including the development and suppression of cancer1. The sequences of several microRNAs have been shown to up- or down-regulate in different types of cancer, Alzheimer’s disease, Parkinson’s disease, and Huntington’s disease 2. Thus, microRNAs are considered strong candidate biomarkers and as potential therapeutic drugs for the diagnosis and treatment of several diseases. Since microRNAs can be collected from body fluids, such as blood and urine3, development of an easy method to measure the microRNA levels within body fluids would enable the useful diagnosis of several diseases, compared to conventional but complicated methods, such as X-ray irradiation, computed tomography scanning, and positron emission tomography3. Today, microRNAs are generally analyzed by quantitative reverse-transcription polymerase chain reaction (qRT-PCR), microarray, Northern blotting, or microRNA cloning4. In these methods, microRNA samples are purified, labelled, amplified in most cases, and then detected by fluorescence, radiation, or sequencing5. Nanopore sensing, which utilizes techniques from next-generation sequencing, has recently been applied towards microRNA detection6. The microRNA is detected by electrical measurement obtained from monitoring the dynamics of current flow through a nanopore integrated in a lipid bilayer. Small hydrophilic chemicals less than 2 kDa7 and single-stranded DNA and RNA pass through the nanopore, block the ionic current,

and are identified by analysis of the blocking ratio and/or duration of the current8. As nanopore sensing can measure the microRNA at the single molecule level without the need of labelling, several approaches have been developed and used based on this technique. For example, DNA probes with identifiable barcode sequences have been designed to distinguish multiple microRNA sequences9. Each of these DNA probes uniquely hybridize to different microRNAs based on sequence complementarity, pass through a nanopore, and emit a different blocking signal. Another study demonstrated that the gradient of ionic concentration surrounding the nanopore can enhance the passage frequency of the microRNA through the nanopore, thus enabling rapid and sensitive detection10. Nanopore sensing confers several major advantages over conventional approaches including the fact that a labelling procedure is not required, and because of properties of the electrical measurement, equipment for thermal cycling and fluorescent imagers are unnecessary11. However, a remaining limitation is that samples still require purification prior to nanopore sensing. This step is necessary because considerable background noise, which is technically difficult to distinguish from those signals emitted by target microRNA, is generated because of the diverse length of nucleotides and from the many types of small compounds present in body fluids12. Currently, sample purification is commonly performed using columns, buffers, and centrifuges, requiring several handling procedures.

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In this study, we develop and test an electrical measurement system that does not require sample labeling and purification. Although the blocking of ionic currents in nanopore sensing are derived from various contaminating compounds, such as small chemicals and any single-stranded DNA or RNA sequence, signals in our system are only derived by the presence of the target microRNA. This advancement was achieved by using magnetic beads and a magnet on a lipid bilayer system designed to hold the nanopore to the wall away from the droplet interface bilayer (DIB), which suppresses signal emission derived from contaminants in unpurified samples. Nanopores are released from magnetic entrapment only by addition of the target microRNA, which derives by formation of an RNA/DNA duplex and a resulting enzymatic reaction of a duplex specific nuclease (DSN). Our assay system is sufficiently robust to directly measure the target microRNA from unpurified blood and urine samples, thus enabling the development of easy on-site diagnostic applications in the future.

Figure 1. The device and nanopore-DNA-magnetic bead construction. (a) A turbid solution of magnetic beads applied to the device (left) cleared within a minute (right) with the collection of the beads on the inner wall of the well (illustrations are shown below images of the device). (b) The device used for electrical measurement is based on a sensor chip and patch-amplifier. (c) Magnetic beads are complexed with the nanoporeliposome via an oligo-DNA.

EXPERIMENTAL SECTION Reagents and chemicals The microRNAs, miRNA-713, miRNA-1614, miRNA-2115, miRNA-14116, and miRNA-22117 were obtained from Eurofins Genomics (Tokyo, Japan), the sequences of which are provided

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in Table S1. Four oligo-DNAs modified with cholesterol and biotin on their 5′ and 3′ terminus respectively, were synthesized by Eurofins Genomics. The sequence of each unique oligo-DNA was designed as the complementary sequence to miRNA-7, miRNA-21, miRNA-141, and miRNA-221. A mixture containing over a million different microRNA sequences were designed using the mixed base (N) in the following sequence template: 5′-AUCNNNGUGNNNUGCNNNNAUC3′ (GeneDesign, Osaka, Japan). Chloroform, n-decane, and Lalpha-phosphatidylcholine from egg yolk (EggPC) were obtained from Sigma-Aldrich (St. Louis, MO, USA), and cholesterol was obtained from Nacalai Tesque (Kyoto, Japan). The phospholipids, 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), 1,2-dioleoyl-sn-glycero-3-phosphoethanolamine (DOPE), and 1,2-dioleoyl-sn-glycero-3-phospho-L-serine (sodium salt) (DOPS) were obtained from Avanti Polar Lipids (Alabaster, AL, USA). The cell-free translation system, PUREfrex 2.0, was obtained from GeneFrontier (Chiba, Japan), and the DNA encoding alpha hemolysin was designed as previously reported18. A Recombinant RNase Inhibitor was obtained from Takara Bio Inc. (Shiga, Japan), and magnetic beads coated with streptavidin (Dynabeads MyOne Streptavidin C1) were obtained from Thermo Fisher Scientific (Waltham, MA, USA). DSN was supplied by Evrogen (Moscow, Russia). Human blood and urine samples were obtained from Tennessee Blood Services (Memphis, TN, USA) and BioreclamationIVT (Westbuty, NY, USA), respectively. Nanopore-DNA-magnetic bead construction Lipids dissolved in chloroform were mixed in a composition of EggPC:DOPC:DOPE:DOPS:cholesterol:oligo-DNA (modified with biotin and cholesterol) at a weight ratio of 400:700:100:100:500:0.5 respectively, and flushed by argon gas to form a lipid-film in a glass tube. Next, a liposome inner solution consisting of 10 mM HEPES-KOH (pH 7.6) and 500 mM sucrose was added to the lipid film to construct liposomes by hydration19, and the constructed liposomes were then mixed with PUREfrex 2.0 and 5 nM of alpha hemolysin DNA. Incubation of this mixture at 37 C resulted in synthesis of alpha hemolysin, which was integrated into the lipid membrane forming heptameric complexes (nanopores). To reduce the size of the liposomes, which increases fusion efficiency to the DIB, the solution was passed through a film extruder with 100-nm pores. As nanopores are integrated to this liposome membrane, we termed this solution “nanopore-liposome”. Because of the incorporation of cholesterol in the liposome membrane, oligoDNA containing biotin at its terminus is positioned on the liposome surface. Finally, this nanopore-liposome complex was incubated with magnetic beads coated with streptavidin for 1 h at 37 C to produce “nanopore-liposome-magnetic bead” complexes. Unbound solution was removed by washing using DSN buffer, which contains 50 mM Tris-HCl (pH 7.0), 20 mM MgCl2, and 1 mM DTT. Device setup and sensing schematic Our device was fabricated essentially following our previous report that describes production of a double-well chip for DIB formation20,21 , with an additional magnet sheet embedded next to one well (Fig. 1). To accumulate magnetic beads to the inner wall of the well, the magnet is localized peripherally to the well.

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Figure 2. Schematic of microRNA sensing. (a) Magnetic beads accumulate on the inner wall of the well, and (b) the target microRNA hybridizes to oligo-DNA, (c) which is then cleaved by DSN. (d) DNA and the nanopore-liposome complex are released from the magnetic bead, fuse to the lipid bilayer (DIB), and (e) generate stepwise signals due to the formation of nanopores on the DIB. A patch amplifier is then connected to electrodes positioned on the wells to measure ionic current through the DIB. We first added 4.2 μL lipid-dispersed oil (20 mg/mL of DOPC:DOPE at a weight ratio of 3:1 dissolved in n-decane) to both wells. Following the addition of oil, we applied 21 μL DSN buffer to the well furthest from the magnet. Next, we applied 21 μL mixture solution to the well nearest to magnet. This mixture, composed of DSN buffer including microRNAs, nanopore-DNA-

magnetic bead complexes, and 0.2 U/μL DSN, was pre-incubated at 50 C for 30 min before use. This incubation could be performed in the well by using the heater to maintain the double-well chip at 50 C (Fig. S1). We added 0.4 U/μL RNase inhibitor when measuring blood or urine samples. The schematic of microRNA detection is illustrated in Fig. 2. First, the microRNA forms a duplex with oligo-DNA. Following duplex formation, DSN cleaves the DNA. DSN is an enzyme derived from crab, which cleaves the duplex of DNA or the DNA in DNA-RNA duplex22. As DSN can distinguish the perfect and imperfect matching of duplex sequences in a single base-pair level, this enzyme has been used for several bioanalysis, including the detection of single nucleotide polymorphism (SNP)22,23. The length required for cleavage is 15 bp DNA/RNA duplex, which is shorter than the length of general microRNAs (22-25 bp), therefore could be applied to our sensing schematic as well. The cleaved DNA with the nanopore-liposome at its terminus is then released from the magnetic bead and diffuses into solution. Next, the nanopore-liposome fuses to the DIB, incorporates the nanopore proteins in the DIB, and generates electrical signals because of the resulting conductance of the nanopore. As DSNs specifically digest DNA, a microRNA repeatedly forms the duplex with DNA after the DSN reaction, therefore the signal is expected to be amplified in isothermal reaction23. Electrical measurement Ionic current signals emitted by nanopore generation on the DIB were measured using a multi-patch-clamp amplifier in the sampling period of 5 kHz, with a 1 kHz low-pass filter. Data were analyzed by pCLAMP 10.4 (Molecular Devices, San Jose, CA, USA). If the DIB was ruptured because of the generation of excess nanopores, it was reformed using a hydrophobic needle11. For signal analysis, the slope of the stepwise signals was calculated by dividing the elevation of ionic current (pA) over duration (min). RESULTS AND DISCUSSION MicroRNA detection

Figure 3. Evaluation of the system. (a) Background noise was not detected without addition of microRNA, and (b) signal emission was derived by freely diffusing nanopore-liposome complexes. (c) Signals were not detected with the addition of mock miRNA-16 (10 μM). (d) Signals were detected with the addition of the target microRNA, miRNA-141 (10 μM). (e) Signal slope was plotted against microRNA concentration. cont., control; miRNA, microRNA; n.a., not applicable; ns, not significant; *P106 types of synthetic microRNA sequences (100 μM) and (f) this pool of microRNAs with the target microRNA, miR-141 (10 μM). (g, h) Signal slopes were plotted from measurements of (g) four microRNAs or (h) miRNA-141 spiked in a mock microRNA mixture. n.a., not applicable. observed variation was large, these four experiments demonstrated a negative correlation between signal slope and the melting temperature of the oligo-DNA (Fig. S2). As the melting temperature of all the oligo-DNAs is above 50 C, it is anticipated that all tested microRNAs form a duplex with the target oligo-DNA in our experimental conditions. However, the dissociation rate of microRNA/DNA duplexes after DNA cleavage may differ because of differences in the melting temperature. For example, DSN cleavage of a single DNA nucleotide enables a microRNA to partially form a duplex with the remaining oligo-DNA. This partial duplex may dissociate more easily at a lower melting temperature, which leads to more frequent release of nanopore-liposome complexes from magnetic entrapment, thus resulting in increased signal emission and a higher slope. Other possible factor which affect the signal slope will be the efficiency of liposome formation. As oligo-DNA is anchored on liposome surface, it may interact with the negatively charged lipids such as DOPS, therefore affect the stability of liposome, or the nanopore formation on its membrane. Alt-

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hough the molecular mechanism is not clearly revealed, we experimentally found the preference of the target microRNA sequence. This means that standard curve should be drawn for each target microRNA of interest. Next, we tested the specificity of our system. As humans express a few thousand different microRNA sequences, sequencespecific detection is critically important for precise diagnosis using commonly obtained body fluid samples27,28. We constructed a mixture of different mock microRNA sequences using mixed bases (A+C+G+U) in 10 ribonucleic acid positions (Table S1). Theoretically, this mixture contains 410 (>1,000,000) different synthetic microRNA sequences. It is important to note that the sequences of target microRNAs used for detection in this study are not included in these mock microRNA sequences. We did not detect a significant signal using this artificial mock microRNA mixture in our system. However, when the target miRNA-141 was included in this microRNA mixture, we observed stepwise signals, which indicates our system can detect microRNAs not only in a sequence-specific manner, but in a pool containing many different microRNAs. Importantly, as the average of the slope signal did not decrease compared to our previous findings (shown in Fig. 4g), inhibitory effects of the mock microRNAs were not observed using our system. We assume that this high specificity is because of the ability of the DSN to distinguish between a duplex with a perfect match and a duplex containing at least one sequence mismatch 22. MicroRNA detection from unpurified samples As a final proof of concept, we tested the applicability of our system using unpurified blood and urine samples (Fig. 5). As RNA extraction and purification require several laboratory procedures and equipment, the direct detection of microRNAs from commonly obtained clinical samples is important for practical and easy diagnosis in a clinical setting. We mixed the target miRNA-141 in blood and urine samples, which then underwent analysis. Prior to sample loading, we heated the body fluid containing the target microRNA at 98 °C for 2 min to denature possible inhibitory factors present in the sample as well as to ensure the collapse of extracellular vesicles (EVs). EVs are enriched with microRNAs, but it is technically difficult to collect total EVs without bias because there are two subtypes of EVs, which differ in size29. Because our system does not require the isolation and enrichment of EVs from clinical samples, our direct detection of microRNAs may enable more precise microRNA-based diagnosis. Following denaturation, samples were then mixed with the nanopore-DNA-magnetic bead complexes and DSN, incubated, and analyzed by electrical measurement. When we applied blood without the addition of target microRNA, we did not detect any signals (Fig. 5a). In the case of blood sample, we observed a sedimentation, which is expected to include denatured cells and proteins. However, this sedimentation did not interfere with the DIB further ensuring noise-free detection of the system. When we mixed 10 μM target microRNA (miRNA-141) to the blood, we observed the signals, which showed the detection of microRNA without the purification of blood components (Fig. 5b). Next, we applied urine, and did not detect the background noise signals (Fig. 5c). In contrast, when we mixed the 10 μM miRNA-141 in urine, we detected signals (Fig. 5d). These results demonstrate that targeted microRNA detection was possible without prior purification or labelling of body fluid samples. As body fluids lacking

microRNA did not show background noise (Fig. 5a, c), we posit that potentially inhibitory cells and proteins are deactivated in our system and do not contribute as background noise. Nevertheless, ions and small compounds may still diffuse and interfere with the system. In fact, we did not observe signals frequently enough from the body fluids to quantitatively compare with the data obtained by purified microRNAs (Fig. 3). This lower frequency of signal emission in body fluids indicate that there may be compounds in body fluids that can affect the formation of the microRNA/DNA duplex, DSN reaction, and/or fusion of the nanopore-liposome to the DIB. As the DSN has a narrow optimum concentration range for ions for nuclease activity, optimization of the buffer solution may be required for each type of body fluid samples. As the concentration of microRNAs in plasma are in the tens of femtomolar range30, we need to improve the sensitivity of our developed system for practical diagnostic applications. In our system, the microRNA are expected to repeatedly releases the nanopore-liposome complex. Thus, extending the incubation time in the optimum buffer condition may be useful to increase the sensitivity. Nevertheless, using blood and urine samples as example body fluids, our system succeeded in the detection of microRNAs simply requiring a brief denaturation prior to sample loading and using electrical measurement. Because electrical measurement systems can be readily adapted as mobile equipment11, the entire system can be easily deployed not only in conventional medical settings, but also in any desired location providing robust and informative on-site diagnosis.

Figure 5. Background noise from unpurified samples was analyzed from (a) blood or (c) urine samples. Following addition of target miRNA-141 (10 μM) to (b) blood or (d) urine samples, target-specific signals were detected. CONCLUSIONS Taking advantage of DSNs and a magnetic field, we demonstrated the noise-free and sequence-specific measurement of microRNAs using blood and urine samples as well as a complex mixture of over a million microRNA sequences. In addition to conferring a label-free advantage using electrical measurement, we succeeded in developing a purification-free process enabling samples to quickly undergo loading. Although further confirmation should be required, the signal emission in our system is also expected to be amplified. Our system does not require specialized or complex equipment, and moreover, does not require detailed and lengthy sample preprocessing, such as

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purification and labeling. As cancer diagnosis is an important global issue, this easy handling method for accurate microRNA detection will be useful for diagnostic applications in the future.

ASSOCIATED CONTENT Supporting Information Sequences of microRNA used in this work is provided in Table S1. Halogen lamp for incubating the chip is explained in Text 1 and shown in Fig. S1. Plot of the signal slope obtained by electrical measurement against the melting temperature of the corresponding complementary oligo-DNA is shown in Fig. S2.

AUTHOR INFORMATION Corresponding Author *E-mail: [email protected] ORCID Shoji Takeuchi: 0000-0001-6946-0409.

ACKNOWLEDGMENT This work was partly supported by the Regional Innovation Strategy Support Program of MEXT, the Strategic Advancement of Multi-Purpose Ultra-Human Robot and Artificial Intelligence Technologies Project of NEDO, Japan, and JSPS KAKENHI Grant Number JP16H06329, JP17H00888 Japan. We thank Ms. Inagaki (KISTEC) for the technical support.

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