Artificial Cell Membrane Systems for Biosensing Applications

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Artificial Cell Membrane Systems for Biosensing Applications Toshihisa Osaki, and Shoji Takeuchi Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/acs.analchem.6b04744 • Publication Date (Web): 30 Nov 2016 Downloaded from http://pubs.acs.org on December 2, 2016

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Analytical Chemistry

Artificial Cell Membrane Systems for Biosensing Applications Toshihisa Osaki and Shoji Takeuchi*

Artificial Cell Membrane Systems Group, Kanagawa Academy of 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.

* To whom correspondence should be addressed. E-mail: [email protected]; Fax: +81-3-5452-6649; Tel: +81-3-5452-6650.

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FUNDAMENTALS OF LIPID BILAYER SYSTEMS Lipid Bilayer Platforms Conventional lipid bilayer formation Lipid bilayer formation in microdevices Protein Insertion into Lipid Bilayer Platforms Applications besides Biosensing Characterization of single ion channels Synthetic cell-mimicking systems

CURRENT TOPICS ON MEMBRANE BIOSENSORS Nucleic Acid Analysis and Diagnosis Sequencing of nucleic acids Analysis and diagnosis Exploring Sensor Elements Biological pores Molecular adapters for nanopore assistants Synthetic and semi-synthetic pores Hybrid systems

CONSIDERATIONS FOR BIOSENSOR APPLICATIONS Sensitivity of Single-Molecule Detection Insertion of Sensor Elements into Membranes Membrane Stabilities for Sensing and Storage Membrane Reliability for Sensing and Storage

FUTURE DIRECTIONS


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Biological membranes provide a physical boundary that separates the inside and outside of a cell or organelle. They also mediate signal transduction and transport of various molecules into and out of the cell or organelle. The major constituents of membranes are phospholipids and membrane proteins. The phospholipids form a bilayer membrane structure that creates a hydrophobic barrier for soluble/ionic substances, while the membrane proteins transport signals and substances across the membrane via conformational changes. Because the biological membrane engages in almost every communication between a cell/organelle and its surroundings, membrane-associated proteins and lipid molecules have become a significant focus of efforts to identify new pharmaceutical drug targets. Furthermore, the functionality of the biological membrane makes it ideal for biosensing applications, as it inherently fulfils the necessary conditions of a sensor. Specifically, membranes are capable of detecting stimuli such as mechanical strain, ligand binding, and an electrochemical potential gradient. The input, or stimulus, is then transduced into an output signal with a specific format using the mechanism built into the membrane. The signal is often amplified during transduction, resulting in an enhanced signal-to-noise ratio. Membrane systems have been developed for studying and emulating biological membranes, most commonly using a bottom-up approach with natural and synthetic lipid molecules. Lipid vesicles, which encapsulate an aqueous phase, are one of the representative forms of a membrane system. The other form is a planar membrane system, which can be further classified into supported bilayers, suspended bilayers, and nanodiscs. Among these diverse systems, this review will focus on recent (primarily 2013–2016) development of membrane biosensor platforms that use suspended lipid bilayers coupled with electrical detection technologies. The suspended bilayer, also known as a free-standing bilayer, electrically divides two aqueous chambers. By insertion of transmembrane proteins as the sensing elements, the suspended bilayers form versatile chemical sensing systems that are compatible with electronics. Here, we will introduce the fundamental aspects of membrane platforms, then highlight recent progress on the use of membrane biosensors, and discuss issues and viewpoints directed towards their practical viability. Finally, we will briefly remark on potential directions for the future development of lipid bilayer membrane platforms for use in biosensing applications.



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FUNDAMENTALS OF LIPID BILAYER SYSTEMS Lipid Bilayer Platforms Conventional lipid bilayer formation Phospholipids are amphiphilic molecules that consist of a polar head group(s) and a hydrophobic tail(s). In aqueous solution, the phospholipid molecules self-organize into the form of a bilayer membrane due to a hydrophobic interaction over the hydrocarbon chains at their tails. Typical phospholipids have a molecular weight of approximately 1 kDa, and form a bilayer of 5-nm thickness. Such a thin membrane is able to suppress the permeation of water-soluble molecules, and exhibits a membrane resistance of over 1 MΩ·cm2 and permeability to sodium ions in the order of 10-12 cm/s. The high resistance of the membrane allows detection of a minute increase in conductance caused by the opening of a single ion channel (membrane proteins) at the membrane. The typical conductance of single ion channels and pore-forming proteins is 10 pS to 1 nS, which can be tracked using patch-clamp amplifier equipment. For biosensing applications, the stimulus/response characteristics of membrane proteins have been adopted as the principle of the sensing system, where the response of the proteins is transduced to the variations in ionic current through the membrane. A suspended lipid bilayer, also known as a black lipid membrane, is a bilayer membrane formed at a microaperture in a thin insulating plate that separates two aqueous chambers. Here we briefly introduce two conventional methods of suspended bilayer formation relevant to the development of microdevices that utilize artificial cell membranes. The first of these, known as the painting technique, simply uses a brush to paint a lipid-dispersed organic solvent over the aperture. The solvent is typically a hydrocarbon oil, such as decane or hexadecane. Due to the hydrophobicity of the aperture surface, the oil spreads over the aperture, and lipid monolayers self-assemble on the oil surface. The center of the oil layer spontaneously thins down, causing the monolayers to contact each other and form a lipid bilayer membrane.1 An oil layer remains at the perimeter of the bilayer, the so-called annulus, which helps to stabilize the bilayer and maintain electrical insulation between the divided aqueous solutions. The second method was introduced by Montal and Müller in 1972. Here, lipid monolayers are spread over the air-water interface in each aqueous chamber and the water levels are gradually raised above the aperture. The monolayers are transferred to the separator surface, where they come together and form a lipid bilayer membrane at the aperture.2

Lipid bilayer formation in microdevices Microfabrication technologies have facilitated the development of lipid bilayer platforms, and are aimed at improving the reproducibility of membrane formation, maximizing data throughput, and adapting to sensitive electrical/optical observations. The Behrends group automated the painting method using a polytetrafluoroethylene-coated magnetic bar 4 ACS Paragon Plus Environment

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(Figure 1a). A glass chip composed of 16 microwells with electrodes allowed the bar to be controlled remotely. When the bar was turned on in the wells, it spread the lipid-dispersed oil and formed bilayer membranes. Using this method, they demonstrated parallel electrophysiological recordings of ion channel activities.3,4 The products based on this technology have been commercialized and are distributed by Nanion Technologies.5 Hirano et al. devised a geometrically well-designed aperture within a silicon nitride membrane. The edge of the aperture was smoothly tapered and the surface was modified with a hydrophobic fluoropolymer. Although the bilayer was formed using a Montal-Müller-like method, they succeeded in reconstituting and characterizing a human ether-a-go-go (hERG) ion channel.6 Le Gac and other groups have applied microfluidic systems to bilayer formation.7,8 These systems consist of a microaperture that separates two microchannels or a microchannel–chamber pair. First, the channels are filled with an aqueous solution, and then a lipid-dispersed oil is infused into one of the channels, forming a lipid monolayer at the aperture. By replacing the lipid/oil with an aqueous solution, an oil layer is left at the aperture, which spontaneously thins down and forms a bilayer. This microfluidic procedure has proved to be reproducible at forming a highly parallel bilayer (Figure 1b).9 An alternative key technology for simple, rapid, and reproducible bilayer formation is the droplet contact method, which was firstly reported by Funakoshi et al. (Figure 1c).10 A bilayer membrane is formed by contacting a pair of monolayer-coated aqueous droplets; this method takes advantage of the amphiphilic characteristics of lipid molecules, which result in monolayer self-assembly at the water-oil interface. This bilayer was later named the droplet-interface bilayer (DIB).11 The aqueous droplets can be freely manipulated with manual, fluidic, or electrical actuations,12–15 and can be arbitrarily arranged into groups or two, three or more.16,17 Moreover, the number of DIB pairs can be scaled into a horizontal or a vertical format.18–20 An agarose gel layer can also be used as a counterpart to the droplet for DIB formation.21 Most of the techniques above used a non-volatile organic solvent that electrically insulates the edge of the bilayer membranes and allows electrophysiological observations. However, a small amount of the solvent is known to remain in the bilayer, which can affect the membrane (e.g. thickness and fluidity) and membrane protein function. To avoid this issue, a solvent-free bilayer system was developed using giant lipid vesicles, spanning over sub-μm sized pores.22,23 In summary, microfabrication technologies have contributed substantially to the progress of membrane platforms. Reproducibility has been improved by precise geometrical device design as well as the benefits of miniaturization, such as well-controlled laminar flow. Moreover, spatial freedom in the design has extended the scalability of the bilayer number and has also achieved parallel electrical recordings, sensitive microscopy, and simultaneous electrical/optical observations on chips.9,18,24,25

Protein Insertion into Lipid Bilayer Platforms 5 ACS Paragon Plus Environment


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Membrane-associated proteins and peptides generally take the central role in biosensing, namely target recognition and signal generation in membrane platforms. Insertion of these proteins/peptides into lipid bilayers can be categorized based on solubility in the aqueous media. Pore-forming toxins, such as gramicidin, alamethicin, and α-hemolysin, are soluble as monomers and are simply dissolved into one or both sides of the aqueous solutions, in approximately the nM range. The monomers spontaneously bind to the lipid bilayer membrane and form transmembrane pores. Insoluble proteins are commonly reconstituted into lipid vesicles before insertion into the bilayer membrane, forming structures called proteoliposomes. These proteoliposomes are infused into the aqueous solution, inducing membrane fusion with the bilayer. This is called a vesicle fusion method, and the proteins are typically prepared via overexpression in cultured cells. Alternatively, a cell-free expression system has emerged for preparing membrane proteins. Recent work has incorporated ion channels into DIBs and successfully demonstrated single-channel current monitoring.26,27 A giant plasma membrane vesicle (GPMV) technique, which isolates an intact plasma membrane from live cells using chemical vesiculants, could also be useful, although there is not yet any precedent when combined with DIBs or other platforms.28,29 The vesicle fusion process can be optimized by adjusting the osmotic pressure inside the vesicles, the lipid composition, or vesicle concentration, and efforts to further improve fusion efficiency are ongoing (see also the Section: Consideration for Biosensor Applications).30 Further details can be found in recent reviews.31–33

Applications besides Biosensing Characterization of single ion channels Ion channel characterization has traditionally been an area of interest in the development of artificial cell membrane systems. A patch-clamp technique has traditionally been used to study ion channel function at the single-molecule level, but the procedure demands specific experience and skills and is time-consuming and labor-intensive. Artificial membrane devices are therefore expected to produce reliable data with high throughput and good reproducibility using a systematic procedure. As a result of the intensive development of membrane platforms, recent studies have presented signal features not only of prokaryotic ion channels, but also of eukaryotic channels, including those of human origin.26,34,35 Typically, time-courses of ionic current are observed at different applied voltages.6,36 However, for practical and common use of these systems, the signal data will have to be accumulated and carefully validated by comparing with previous patch-clamp data, in terms of channel conductance, open probability, and dwell time distributions. For ligand-gated ion channels, dose-dependent inhibition/activation characteristics were also investigated to verify whether the system would be feasible as a screening procedure, and whether the incorporated ion channels were intact within the artificial membrane platforms.37,38 For screening tests, device configuration was studied in order to integrate a fluidic channel for ligand exchange.39,40 A parallel screening system would 6 ACS Paragon Plus Environment

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be an alternative solution and would significantly enhance data throughput (Figure 1d).18 Devices for mechanosensitive channels are ongoing.41 We consider that such ion channel studies will be useful not only for fundamental science but also for their potential in drug discovery. Automated whole-cell patch systems are currently being used for high-throughput screening of ion channels. However, the characterization of single ion channels remains less understood. A deeper understanding of how the molecular machinery responds to drug candidates would offer further insight into the drug-development process, and therefore further validation of existing membrane systems is encouraged.

Synthetic cell-mimicking systems Among the suspended bilayer platforms, droplet-interface bilayers (DIBs) have been principally used as models of cells and cellular networks. For example, the morphological transition of a bilayer membrane was traced on cell-sized DIBs; perturbation was induced by water evaporation into the oil in the DIB system, resulting in deformation, buckling and fission of the bilayer.42 DIB systems allow controlled physical and dynamic stimulation of the bilayer, which will help to understand the mechanics of membrane-associated events such as endo/exocytosis. Meanwhile, asymmetric lipid vesicles (liposomes) have been generated from DIB, where the planar membrane was deformed by the application of a pulsed-jet flow.27 Such cell-mimicking systems will be important for elucidating membrane dynamics and interactions between lipids or lipids and their associated proteins. In recent work, droplet network systems have been developed to re-create the sophisticated signatures of cells in synthetic systems, and several assembly techniques have been reported. Aqueous droplets were injected into a lipid/oil bath using a spotting robot and built up layer by layer;43 magnetic beads were loaded into the droplets and a magnetic field was used to assemble a 3D network;17 optical tweezers were used to manipulate and assemble cell-sized droplets.44 The droplets were segregated by bilayers, except when transmembrane pores, such as α-hemolysin, were incorporated for the diffusion of small molecules; molecular and ionic (electrical) routes can be designed within a large droplet cluster by the gizmo. A heterogeneous but controlled osmotic flow of water into the cluster induced a coordinated morphological change (Figure 1e).43 Electrochemical potentials can be charged within part of a droplet using biologically engineered pores.11,45 A multi-step enzymatic reaction was demonstrated in the network as a model of a signaling cascade. Discrete steps of the reaction were isolated within each droplet, and routed to the next step through the pore (Figure 1f).46 This field has only emerged in recent years, but will continue to expand further.



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CURRENT TOPICS ON MEMBRANE BIOSENSORS Nucleic Acid Analysis and Diagnosis Sequencing of nucleic acids Nucleic acid analysis using biological nanopores has shown remarkable progress in the field of artificial cell membrane sensors since the work presented by Kasianowicz and coworkers.47 Similar to the principle of a Coulter counter, nanopore-based sensors detect the size and the number of analytes that translocate through them. The sensor consists of a nanopore embedded in a lipid bilayer membrane, which electrically separates two aqueous phases. An analyte in an aqueous salt solution passes through the nanopore, driven by an electrical potential, and temporally interferes with the ionic current through the pore. The blocking current level, dwell time, and frequency of translocating events provide information about the analyte. In one of the first examples, the mass spectrum of polydisperse poly(ethylene glycol) molecules in an aqueous solution was clearly determined through a nanopore from the mass-dependent conductance level and blocking duration.4,48 Nanopore sensors are a candidate for third generation DNA sequencing technologies.49 For the senor development, the heptameric nanopore-forming protein, α-hemolysin, has traditionally been used as the core of the sensor element. The pore is composed of an extracellular vestibule and a transmembrane β-barrel of approximately 2.5 nm diameter and 5 nm length. The vestibule and β-barrel are connected at a 1.4-nm constriction, which is feasible for single-stranded DNA (ssDNA) translocation but not for double-stranded DNA (dsDNA). Moreover, it was expected that size differences among the four nucleobases could produce specific blocking currents, allowing discrimination between different nucleobases. However, there are two major challenges to using nanopores for DNA sequencing. The first issue is the extremely large translocating velocity of ssDNA through the nanopore, which is estimated to be 1–10 μs per base. The number of ions passing through the interspace between the pore and ssDNA can be calculated in the order of ten to a few hundred, which makes it physically impossible to resolve nucleobase differences. The second issue is a structural drawback in the α-hemolysin nanopore. Approximately 12 nucleotides remain in the β-barrel, which affects to the blocking current level as a series resistance and obscures the specific current signals from the base at the constriction. Among a number of studies reported, the successful approaches were to apply an enzyme coupled to a nanopore. The enzyme, such as a polymerase or helicase, binds to the DNA and “ratchets” the DNA through the nanopore. This significantly slows the translocation velocity down to a few tens of milliseconds per base, which is an adequate dwell time to allow single-nucleobase discrimination. For the second issue, careful examination identified locations in the β-barrel that can specifically differentiate each nucleobase according to the blocking current, and therefore the α-hemolysin nanopore was engineered.50,51 An alternative nanopore, MspA, was introduced to address this issue. MspA is a mutated form of Mycobacterium smegmatis porin A, and comprises a funnel-like pore, thus avoiding the problem of a 8 ACS Paragon Plus Environment

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long-and-narrow transmembrane region. This MspA geometry reduced the sensing region to a short constriction (1.2 nm diameter and 0.6 nm length), which significantly improved separation of the current levels for nucleobases compared to the α-hemolysin nanopore.52 Taken together, the enzymatic process control and the base discrimination using an engineered pore have led to a number of reports demonstrating the use of nanopores for DNA sequencing. For example, the Church group presented a nanopore-based sequencing-by-synthesis (Nanopore-SBS) approach, using a polymerase-coupled nanopore and four nucleotides with specific oligonucleotide-based tags. The polymerase is bound to a complementary nucleotide with a tag, which is captured in the nanopore and provides a tag-specific (i.e. nucleotide-specific) signature of the blocking current. This system was developed on a CMOS (complementary metal oxide semiconductor) chip, enabling 264 parallel measurements with the Nanopore-SBS (Figure 2a).53,54 The Gundlach group demonstrated nanopore sequencing of the bacteriophage phi X 174 genome (4.5 kb) using a combination of the MspA nanopore and phi29 DNA polymerase with two adapters (Figure 2b).55 One adapter (orange), attached at one end of the target dsDNA, consists of a cholesterol tail for intercalating the DNA-polymerase complex into the lipid bilayer membrane and a single-stranded overhang to help insertion into the pore. DNA sequences can then be read through the MspA pore using an unzipping mode (in a cis to trans direction). The second hairpin adapter with a nick (green), attached to the other end of the target DNA, allows the DNA to be re-read by the polymerase’s synthesis mode (in a trans to cis direction). Since 2014, a nanopore-based DNA sequencing device (MinION; Oxford Nanopore Technologies), has been released and updating sequencing results. For example, it is able to perform 48-kb full-length reads of phage λ DNA.56 Further details regarding the historical and technical developments of nanopore-based nucleic acid analysis can be found in recent reviews.57–59

Analysis and diagnosis Nanopores have also been applied to nucleic acid diagnosis, to detect specific sequences in nucleic acid samples. The presence of a target sequence is discriminated using complementary sequences within the nanopore. As mentioned above, single-stranded nucleic acids are able to translocate through the constriction of α-hemolysin nanopore, but double-stranded nucleic acids cannot, thus generating differences in blocking current levels and dwell times. One application of this is in the diagnosis of tumor-derived circulating microRNAs (miRNA), short, non-protein coding RNAs of approximately 22 nucleotides that regulate gene expression.60 Gu et al. demonstrated simultaneous detection of multiplex miRNAs in a single α-hemolysin nanopore using complementary DNA probes with different lengths of poly(ethylene glycol) labeling (Figure 3a). It should be noted that it is important to thoroughly screen multiple miRNA sets for such diagnoses. The target miRNAs specifically bind and form duplexes with their complements in the aqueous solution. The duplex is then captured at the nanopore, unzipped, and translocated to the trans side of the pore due to the 9 ACS Paragon Plus Environment


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electrophoretic force. Differences in the labeled probes discriminate the depth of the current level at the captured stage, and the melting temperature of the duplex reflects the dwell time before the unzipping stage. The concentration of each miRNA, down to 10 pM, was independently proportional to the event frequencies.61,62 Studies from the Zhang and Wang groups reported from a different aspect for discriminating a single-nucleotide mismatch in miRNAs, using locked nucleic acid (LNA) probes. LNA, a nucleic acid analogue that bridges 2’ oxygen and 4’ carbon, significantly increases the melting temperature, resulting in differentiating blocking dwell times for miRNAs with and without a mismatch.63 The White group developed an alternative method with the ability to differentiate mismatched base pairs of CC (cytosine-cytosine) and CA (cytosine-adenine) in a DNA duplex (Figure 3b). They used latch constriction, which is constriction in the vestibule (apart from the central constriction) of the α-hemolysin pore. In the presence of CC and CA mismatches, two distinct state modulating current signatures appear in the current-time trace, probably because of the base-flipping of CC and CA at the latch constriction that interacts with the lysine residues at the site in the vestibule of the α-hemolysin pore. This work has still to be extended to other mismatch types, but immediate identification by simply capturing a single DNA event has great appeal for diagnosing genetic diseases.64

Exploring Sensor Elements Biological pores Pore-based chemical sensor systems are not limited to nucleic acid detection, but can also be used to detect ions, organic molecules, peptides, proteins, and even larger particles such as viruses.65 Their use can therefore be applied to the fields of medicine, food, including agriculture and farming, environment, and safety and security. In order to cover such a wide range of target analytes, a single species of α-hemolysin pore is no longer sufficient, and more diverse sensor elements are required. Similar to nucleic acid assays, the lumen of the β-barrel of the α-hemolysin pore can be specifically engineered to act as the interaction site for the analytes. Specific interactions between analytes and these engineered sites changes the signature of the blocking current level, dwell time, and event frequency.66 For example, selective detection of 2,4,6-trinitrotoluene and nitrogen mustards, both related to the safety and security field, have been demonstrated.67,68 Recent work reported the observation of covalent reaction kinetics in organic molecules, and was even able to track chiral network reactions at the arsenic center at the single-molecule level.69 Other biological pores have been studied for use as sensor candidates.70 Aerolysin, a pore-forming toxin from Aeromonas hydrophila, has been used to detect peptides, proteins, and polymers. Detection of digest fragments of botulinum neurotoxins (BoNTs; lethal toxin; polypeptides) in the sub-nanomolar range was reportedly achieved within minutes using an aerolysin pore. Blocking events were observed with a short C-terminal digest peptide but the pore was insensitive to other native peptides/proteins and serum 10 ACS Paragon Plus Environment

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components.71 In a recent study, single-molecule mass spectrometry of poly(ethylene glycol) was performed using aerolysin. Results indicated that, in contrast to a α-hemolysin pore, the aerolysin pore strongly bound with the nonionic polymers at a high transmembrane voltage, which enhanced mass discrimination, particularly for short polymers (oligomers).72 The mechanism of the interaction was attributed to the geometrical and electrostatic features of the pore, but remains unsolved. The β-barrel of the aerolysin pore contains positively and negatively charged collateral rings at the lumen, while the total net charge is positive.73,74 Pore specificity of aerolysin, such as charge layout and a lack of vestibule structure, was also noted and compared to the α-hemolysin pore used in previous studies.75,76 Conversely, NfpA-NfpB (hetero-oligomeric Nocardia farcinica porin) is cationic selective, with a ring-form of negatively charged residues within the lumen. This pore represents a specific feature of cis-to-trans rectified translocation for cationic peptides. Moreover, the unidirectional translocation can be regulated below a threshold voltage, which is inhibited by peptide binding.77 Such a specific interaction was also found between ampicillin, an antibiotic molecule, and OmpF (porin from the outer membrane of E. coli).78 For native forms of small to medium size proteins, ClyA (cytolysin A from Salmonella typhi with a large cavity of 3.3×5.5×13 nm3) was introduced as a sensor element, and was able to discriminate between human and bovine thrombin based on current blocking signatures.79

Molecular adapters for nanopore assistants Molecular adapters are an additional option to mediate and reinforce nanopore function. One such example is a β-cyclodextrin adapter lodged into the pore lumen, allowing small drug molecules (Mw ~300) to be distinguished in combination with the α-hemolysin pore. Adenosine diphosphate (ADP) can also be detected with OmpG, according to the time-course of current signatures.80,81 In addition to small molecule adapters, proteins, such as Alkb (Alpha-ketoglutarate-dependent dioxygenase from E. coli; 25 kDa) and DHFR (dihydrofolate reductase from E. coli; 19 kDa), were applied and resided in a ClyA pore (Figure 4a). Both protein adapters remained functional within the pore and were successfully utilized for quantitative detection of their ligand molecules.82 For protein analyses, protein sequencing was attempted using protein unfoldase ClpX coupled to the α-hemolysin pore. The unfoldase regulated protein translocation to the trans side of the α-hemolysin pore.83 Aptamers, single-stranded oligonucleic acids that bind specifically to their target molecules, will be applicable as adapters for a range of analytes. Kawano et al. utilized a DNA aptamer for rapid detection of the cocaine molecule. A characteristic signature of deep current blocking and long dwell time indicated the presence of cocaine, because of clogging of the cocaine-aptamer complex in the α-hemolysin pore.84 Proteins could also be detected using a similar strategy.85 In recent work, the roles of analyte recognition and signal generation were divided using a hybridized aptamer with its partly complementary DNA. The partly complementary DNA was released in the presence of the analyte, 11 ACS Paragon Plus Environment


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producing a specific current signature in the nanopore.86 In summary, these examples demonstrate that adapters can be applied to enhance the sensitivity/selectivity of a nanopore, or to help with recognition of target analytes. A more complicated sensory system could be a disadvantage, but also has great potential to improve the function of the sensor.

Synthetic and semi-synthetic pores Synthetic and semi-synthetic nanopores have been developed for various applications.87–90 A pair of biological gA (gramicidin A peptides) forms a β-helix that spans into a lipid bilayer, forming a cation selective ion channel. As the basis of semi-synthetic pores, the relationship between structural variations and channel properties of gA were investigated. Residues at the C- and N-terminus of the channel strongly influence on the conductivity, ion selectivity, and rectification behavior.91,92 These characteristics were applied to detect enzymatic activities in the fM to pM range. The C-terminus of gA was modified with the reacting substrates, and cleavage of the substrates resulted in drastic changes in the current signature.93 Regarding the gA pore, Liu et al. recently synthesized single helically folded polymers that span a lipid bilayer with a pore diameter of 0.5 nm. These synthetic pores exhibit specific conductance, cationic selectivity, and less gating behavior.94 Carbon nanotubes (CNTs) are inherently a type of synthetic nanopore. Recent work showed that CNTs can be incorporated into a lipid bilayer, and their nanopore currents were characterized (Figure 4b).95,96 Short, single-walled CNTs were found to spontaneously penetrate a bilayer membrane, and confirmed that the formed nanopore was able to translocate protons, small ions, water molecules, and DNA. The length and inner diameter of the CNTs was approximately 5–15 nm and 1.5 nm, respectively, both of which are close to the dimensions of the biological α-hemolysin nanopore. Their conductance was in the sub-nano siemens range, and was dependent on pH, probably influenced by carboxylic acid groups at the mouth of the pore, similar to the modified gA pores. In another example of a synthetic pore, metal-organic polyhedra (MOP) was embedded into a lipid bilayer, and characterized according to current signals.97,98 Although both characterization and demonstration of these synthetic pores may not yet match with the biological ones, these results have shown great potential for their application in sensor elements and further improvements are anticipated. DNA has also been used as a structural component of nanopores. Using DNA origami technology, nanochannels of arbitrary shape and size have been assembled, in which chemical modifications can be made at exact geometrical positons. Such a mutated DNA pore displayed channel gating characteristics similar to biological ion channels, and a controllable pore of diameter 2 to 4 nm proved, suitable for both single and double-stranded DNA translocations.99,100 A ligand-gated structure has even been integrated into the DNA pore, together with charge selectivity for the translocation of various substances (Figure 4c).101,102


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The use of additional molecules could therefore extend the application of these synthetic and semi-synthetic nanopores, in the track of the biological nanopores. Matile et al. developed multiplex sensing platforms that are able to differentiate between a series of chemical compounds, including odorants and flavors, using a combination of synthetic/biological molecules.103–105 A set of molecular elements was designed to share individual roles for sensing, for example, enzymes were able to specifically recognize an analyte and convert it to a signal molecule, which could be handed over to a synthetic nanopore to transduce into an electrical output. Signal transportation and amplification can be incorporated into these sequential sensing mechanisms. As mentioned above, the development of synthetic sensing systems is still ongoing, but they have an advantage in robustness for tough assay conditions, and their straightforward mechanism can be altered and adapted to a wide range of analytes by molecular designing.

Hybrid systems Although the application of solid-state nanopores in biosensors is beyond the scope of this review, hybrid systems that comprise a pore with a lipid bilayer or organic molecules offer a different perspective to the development of artificial cell membrane sensors. Mayer et al. reported a solid-state nanopore system combined with a lipid bilayer for peptide/protein detection.106 This system comprised a silicon nitride membrane, with a pore diameter of a few tens of nanometer, that was “coated” with a lipid bilayer using a supported bilayer formation method. By selecting a specific lipid species, typically a few nanometers in length, the nanopore diameter can be altered to fit the size of the target analyte. Receptors tagged to the lipid bilayer specifically concentrate the target analytes over the membrane surface, and deliver the analytes towards the pore one by one, by an applied electric field. It should be noted that a supported bilayer offers moderate lateral diffusion, which slows the translocation rate of analytes, making it more suitable for analysis. In a different system, crown ethers were immobilized onto the surface of a conical nanochannel in a polyimide film, allowing switchable ion selectivity depending on the presence or absence of their “ligands” (K+ and Na+).107



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CONSIDERATIONS FOR BIOSENSOR APPLICATIONS Sensitivity of Single-Molecule Detection Single-molecule detection is an intrinsic characteristic of nanopore-based sensing systems. Translocation of molecules disturbs the ionic current through the pore, and this current blocking event is the fingerprint of the translocated molecule, which is then transduced into output information. The frequency of this event directly relates to the concentration of the molecule. Here we introduce two aspects of nanopore-based single-molecule sensing. The qualitative characterization, i.e. the physical and chemical description, of a translocating molecule is based on interactions between the molecule and the lumen of the nanopore, and the readout quality strongly depends on the tracking resolution of this interaction. The tracking resolution is determined by both spatial features of the pore and translocation velocity of the molecules. As briefly noted in the nucleic acid sequencing section, spatial resolution can be improved by shortening the nanopore length, which limits and specifies the corresponding interaction site to a few nucleotides. For a broad range of analytes, biologically engineering the lumen has also been effective at strengthening the interaction between the pore and the analyte.108,109 To improve temporal resolution, molecular adapters have been applied to actively slow down the translocation velocity of the molecules. Passive control of the velocity has also been studied. For example, Kawano et al. introduced a glycerol/water mixture into the analyte solution to increase the viscosity, and demonstrated a decrease in translocation velocities of the nucleic acids by a factor of approximately 20.110 Wang et al. used TMA (tetramethylammonium) cation in the analyte solution, instead of potassium, and similarly elongated the dwell time of translocation by a factor of about 10, depending on the nucleobase.111 It should be noted that TMA also stabilized the bilayer membrane, and both phenomena may be attributed to the strong interaction of TMA with the negatively charged DNA and polar head groups of the lipids. Alternatively, the resolution can be enhanced by preparing an interface of different aqueous solutions across the pore. For example, Lee et al. showed that the liquid-liquid interface at a solid-state nanopore influenced the translocation of nanoparticles, resulting in an amplification of their signals and dwell times.112 The quantitative characterization, i.e. the concentration calibration and the limit of detection, on nanopore sensing is relied on the frequency of translocation events. The second issue is this event frequency at a low concentration of the analyte/signal molecule. As mentioned by Höfler and Gyurcsányi, single-molecule detection is achieved only when the molecule is delivered to the nanopore sensor.113 By random walk simulations (i.e. by diffusion), a 30-mer DNA molecule at pM concentration encountered a 10-nm diameter pore in the range of 10 min, which is too long to collect a relevant number of events. Using an electrophoretic force could reduce the time 10-fold compared to diffusion, but the Debye length, determined by electrolyte concentration, significantly limited the effective area of the electric field. The concentration gradient of the electrolyte across the nanopore could be a solution to this problem (Figure 5a).114 Under the 14 ACS Paragon Plus Environment

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asymmetric condition of a concentration ratio Ctrans/Ccis = 20 (4 M/0.2 M) together with an external field of trans side positive, the nanopore becomes cationic selective due to the electrochemical potential gradient. This causes cations to diffuse from the trans to cis side, which generates a significant potential gradient with a cationic imbalance in the pore vicinity. The attractive potential for DNA reached as far as several hundreds of nanometers from the pore, allowing observations of picomolar DNA over 1,000 events in 15 min. An alternative solution is dielectrophoretic (DEP) trapping of analytes (Figure 5b).115 Using a gold-coated nanopipette, the analyte (DNA) is salvaged from the order of 10 μm away and concentrated at the tip of the pipette. Using this method, 5 fM DNA was captured at a rate of 315 events/min, approximately a 103 times amplification of the limit of detection. The large effective area of DEP and additional electrothermal flow contributed to this pre-concentration step. One concern is that DEP force strongly depends on the difference in electrical properties between the analyte and the aqueous electrolyte solution, which could limit the experimental conditions. From a different angle, the low event frequencies are compensated by a large number of sensor elements. As demonstrated by DNA sequencing systems, integration of single sensors on an arrayed platform increases the number of the output,53 and the analyte concentration can be digitally counted as the number of the sensors that detected the translocation event.116–118 Note that in this system sensors must be isolated on each platform and must individually readout the signal.

Insertion of Sensor Elements into Membranes One of the most challenging aspects of membrane sensor development is controlling incorporation of the sensor elements into the lipid bilayer. Some pore-forming peptides, such as α-hemolysin, are soluble in aqueous solution and spontaneously incorporate into the membrane. Conversely, insoluble pores, including ion channels, are first incorporated into lipid vesicles, which then fuse with the bilayer. For synthetic and semi-synthetic pores, insertion methods are similar to the above examples, and depend on the materials. For example, DNA pores can be inserted with the help of an electric field and/or a detergent.99,101 For CNTs, a gentle injection flow was applied to the bilayer membrane.96 In all cases, however, incorporation into the lipid bilayer is uncontrollable and often time consuming. The number of incorporated pores and their orientation in the membrane are critical issues for developing sensor devices. The Bayley group developed mechanical probes to physically insert the pores into the membrane.119,120 These probes were made of an agarose-gel tip or a thin glass needle with a flame-treated round tip, and the pore-forming proteins were transferred to the probes by dipping or pipetting. The pore was delivered to the lipid bilayer membrane by engaging the probe with the membrane. Surprisingly, using this method, single pores could be inserted into the membrane within a few seconds. Ide et al. bound an ion channel to a Co2+ affinity bead via a histidine tag, and incorporated an ion channel into a lipid bilayer by simply contacting the bead to the membrane. Note that the use of a tag in this method allowed the ion 15 ACS Paragon Plus Environment


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channel to be oriented in a particular direction.121,122 The grab-and-drop system introduced by the Ces group proved useful for protein insertion (Figure 6). Intact membrane proteins were isolated from cultured cells by close contact with bilayer-coated silica beads, and transferred to a supported lipid bilayer system.123 The White group demonstrated single pore insertion using a controlled pressure difference across the membrane.124 A small positive pressure of up to 200 mmHg at the cis side induced the insertion of a single nanopore, while a negative pressure resulted in removal of the pore. The mechanism is not yet fully confirmed but probably due to the membrane curvature or the area. Wallace et al. reported that membrane area was important in determining the number of incorporated pores.125 All of the abovementioned methods use manually operated insertion procedures, but in future it will be necessary to develop automated/parallel setups for practical applications. To this end, Church et al. showed that pore insertion could be controlled by sequential application of external voltages. A constant 160 mV voltage was applied to the membrane for 1 min, followed by a linear voltage ramp from 50 to 600 mV at 1 mV/s increments, which was expected to guide the proteins to the membrane. With simultaneous monitoring of membrane conductance, multiple pore insertion was prevented by eliminating the voltage after a single pore insertion.54 Such electrical control with a feedback scheme will allow for easier automation and integration, whereas mechanical insertion would be more simple and straightforward.

Membrane Stabilities for Sensing and Storage Mechanical, chemical, and temporal stability are important requirements for practical applications of sensor systems. Among the putative parts of artificial cell membrane sensors, a pristine lipid bilayer membrane is the weakest component to be addressed. Stabilization of the membrane itself has long been studied and reported in the literature.126,127 Strategies include polymerization across the membrane by using crosslinking lipids and scaffold molecules,128 membrane support inside/outside by using proteins/polymers, and the application of amphiphilic block copolymers as alternative membrane materials. In a unique approach, a solid-state nanopore was used to insert the nanopore element, i.e. the nanopores were threaded onto the solid-state nanopore.129 Here, we focus on membrane stabilization by peripheral components. For electrical detection, a lipid bilayer membrane is generally formed at an aperture in a thin plastic film. Whitesides reported the influence of aperture size on electrical stability.130 Breakdown voltage of the membrane was examined at apertures ranging from 2 to 800 μm in diameter, and results indicated significant stabilization below a diameter of 40 μm. An aperture size below 1 μm preserved the lipid bilayer for 120 h, indicating that both mechanical and temporal stability was enhanced by the size reduction.131 The edge of the aperture should also be taken into account. Hirano et al. demonstrated that a smoothly tapered aperture on a silicon chip improved mechanical stability, exhibiting durability with frequent solution exchanges, as well as temporal stability of the membrane for up to 65 h, even at an aperture diameter of 20–60 μm.6 Similar results 16 ACS Paragon Plus Environment

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were obtained using a tapered aperture in a thin polymer film.132 The surface energy of the aperture surface is another factor that affects interactions of lipid molecules at the aperture. The Aspinwall group revealed a relationship between the surface energy and characteristics of a lipid bilayer formed on a glass pipette tip with 30 μm diameter (Figure 7a).133 Perfluorinated modification represents amphiphobic properties (significantly low surface energy) that repel both aqueous solutions and hydrocarbons (apolar solvents). Such modifications produced a 25-fold increase in mechanical stability compared to the more common surface treatment. The same effect was seen in a lipid bilayer formed in a microfluidic device.134 To improve membrane stability, the aqueous media can be replaced with hydrogels, since conventional lipid bilayers are often disturbed by fluctuations in the contacting media. The Schmidt group used a 7.5% poly(ethylene glycol) dimethacrylate (PEG-DMA; 1 kDa) monomer and photoinitiator for the hydrogel material, and UV-induced gelation was applied after membrane formation using the painting method.1 Hydrogel encapsulation considerably stabilized the membrane, lasting up to 5 days (average 48 h), compared to that without the gel (up to 24 h).135 Agarose gels can also be used as hydrogels. Using the Montal-Müller method, a lipid bilayer membrane was formed at 45°C, the temperature at which the agarose (1.5wt%) melted. The agarose was then gelated at a rate of -3°C/min; the gelation point of the agarose was 41°C. The temporal stability of the membrane was significant, and the bilayer was able to be stored for 3 weeks at 4°C with 70% of the success rate. The mechanical stability was also improved. Surprisingly, the incorporated α-hemolysin nanopore remained intact after melting the gel at 85°C.136 Shlm and Gu used agarose with an ultralow gelation point < 17°C, and showed an improvement in temporal stability by a factor of 10 (up to approximately 60 h). It should be noted that the authors demonstrated mechanical stability using a portability test, where an examiner walked around for several minutes while carrying the device containing a prepared membrane with an incorporated ion channel.137 Since droplet interface bilayer (DIB) systems comprise water-in-oil droplets, the solvent surrounding the droplets causes disturbances in the membrane, as for the aqueous media as described above. One solution is to use a plastic or silicone frame to immobilize the droplets.18,138 Venkatesan and Sarles recently introduced organogel

into

a

DIB

system

(Figure

7b).

A

triblock

copolymer

of

poly(styrene-b-(ethylene-co-butylene)-b-styrene) (SEBS; Mw 10,000) exhibits a phase transition from a molten liquid to a soft elastic gel at 40°C. A liquid-in-gel type DIB was generated by contacting two aqueous droplets in molten SEBS/hexadecane (10 mg/mL) at 50°C, followed by gelation of SEBS with cooling to room temperature at -2°C/min. Mechanical and temporal stability was confirmed using this method; the liquid-in-gel DIBs endured up to 6-g acceleration under vibration tests at 50–60 Hz, which was almost 3 times higher durability than liquid-in-liquid DIBs.139 Schmidt et al. developed a lipid bilayer membrane platform available for commercial shipping by freezing the organic solvent.140 The device was composed of a thin plastic film with a 500 μm aperture between two 17 ACS Paragon Plus Environment


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microfluidic channels, and the simple painting method was used to form the membrane.1 A mixture of hexadecane/n-decane (80/20) with 1wt% phospholipid was spread over the aperture and immediately frozen at 4°C for 10 min before proceeding with bilayer formation. The freezing point of the mixture was 14°C. Notably, the bilayer formation process continued after thawing the lipid/oil, although the process took a relatively long time (between 30 min and 24 h). The fraction of successful bilayer formation observed was approximately 50% after shipping events, and similarly 50% recovery after 1 month in storage. The freezing approach bypassed the storage problem by adopting bilayer formation in situ, rather than enhancing the stability of the membrane. However, enhanced reliability will be alternately required for membrane formation, as discussed below. Mechanical and temporal stability of the membrane is, on the other hand, indispensable for biosensing applications with periodical, continuous, and/or mobile monitoring.

Membrane Reliability for Sensing and Storage The reliability of membrane formation has become one of the most critical problems in the development of artificial cell membrane sensors, unless the membrane is sufficiently robust during delivery and storage. As noted above, the freezing approach has the potential to overcome the distribution of the sensor device, while the conventional painting method limited the success rate of on-demand membrane formation.140 For those devices, a lipid bilayer membrane was suspended at the microaperture in a thin polymer film via the annulus, an oil-containing layer surrounding the bilayer. In equilibrium at the Plateau-Gibbs border between the bilayer and the annulus, the interfacial bilayer tension is balanced with the lipid-monolayer tensions on two sides of the annulus–water interface.141 Thus, the properties of the lipid molecules, oil, aqueous media, and aperture surface have to be taken into account based on the geometrical design of the aperture, i.e. diameter and thickness, and temperature conditions. In principle, the same theoretical speculation could be applied to DIBs (Figure 8a).142 In addition, applications of DC and AC electric fields to the membrane allow active control of surface tension through the electrowetting phenomenon.143,144 Alternatively, the vectors of the surface tensions at the annulus–water interface were controlled by controlling the amount of oil in the annulus through a microchannel tunneled into the thin film (Figure 8b).145 Moreover, automated systems have improved the reliability of membrane formation.3,7 From a different aspect, the number of membranes potentially covers the reproducibility of the formation process. In the laboratory, 10 to 100 lipid bilayer membranes have been produced in parallel, from which the examiner is able to select the appropriate channels.18,20,146–148 In the commercial product MinION, it was reported that 512 membranes were selected out of 2,048.57 Differently, a method for repetitive membrane formation has also been developed, where an aqueous droplet in contact with the membrane was successively exchanged by using mechanical movement of the droplet frame or controlled flow in a microfluidic channel (Figure 8c, 8d).12,149,150 For example, 64 nanopore signals were obtained in a single 18 ACS Paragon Plus Environment

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device in a 30 min operation (an average of 1 signal recorded every 30 s) although the reproducibility of membrane formation was approximately 50%. A rapid screening test with 6 concentrations of inhibitor added to the nanopore was demonstrated using this system.



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FUTURE DIRECTIONS Microfabrication technologies have contributed significantly to the recent development of lipid bilayer membrane platforms, which are now actively utilized in both fundamental and applied studies. The efforts have shown great success in the functional analyses of ion channels and DNA sequencing, both leading to the generation of commercial products. In future biosensing applications, the target analytes will be extended from nucleic acids to include a broad range of organic/biological molecules. In particular, the applications could be used to detect biomarkers from body fluids and for VOC (volatile organic compound) analysis, including exhaled gas diagnostics, odorant sensors, explosives, noxious gas, and illegal drug detectors. Together with the expansion of target molecules, however, comprehensive strategies should be planned for the entire sensor device, including the sensor elements, the design of the membrane platform, and housing, including electronics and software, as briefly noted below. For diagnostic use, both target specificity among mixed compounds and quantification with a low detection limit may be necessary for the sensing elements, whereas a differential sensing platform that recognizes a large variety of molecules will be required for odorant sensors. Ligand-gated ion channels will become one of the model sensor elements, since they can recognize single molecules with a given specificity and sensitivity, and transduce molecular binding events to an ionic current that is compatible with electronic devices. In nature, the selection of such ion channels is known to cover a considerably wide range of ligands, e.g. the insect olfactory systems.151–153 Thus, ion channels represent a potential candidate for next generation elements to be explored, as an alternative to nanopores. In this regard, however, protein expression and purification present additional challenges due to their structural complexity, and the additional technologies will have to be developed for protein orientation and stabilization within the membrane platform. Synthetic ligand-gated channels are another prospective candidate as a prototype has recently been reported using DNA origami technology.101 Most importantly, the varieties of both biological and synthetic sensing elements are insufficient to accommodate the wide range of target analytes, for which cooperative sensing ensembles may have to be developed to generate specific signal patterns.103,104 Finally, considering competitive sensing technologies such as mass spectrometry, the need for a mobile or tabletop type platform with a simple, rapid, and cost-effective procedure highlights the importance of artificial cell membrane sensors, for which further development of the peripheral components will be required. Some introductory and inspiring work has been reported regarding device configuration for VOC detection,154, a scalable electronic platform,155,156 a field test with a mobile device,157 and open source software.158,159


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Notes The authors declare no competing financial interest.

Acknowledgments We thank Ms. Akiko Sato (Univ. Tokyo) for the TOC artwork. This work was partly supported by KAKENHI (No. 25246017), JSPS, Strategic Advancement of Multi-Purpose Ultra-Human Robot and Artificial Intelligence Technologies Project of NEDO, and Regional Innovation Strategy Support Program of MEXT, Japan.



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References (1)

Mueller, P.; Rudin, D. O.; Tien, H. T.; Wescott, W. C. J. Phys. Chem. 1963, 67, 534–535.

(2)

Montal, M.; Mueller, P. Proc. Natl. Acad. Sci. 1972, 69, 3561–3566.

(3)

del Rio Martinez, J. M.; Zaitseva, E.; Petersen, S.; Baaken, G.; Behrends, J. C. Small 2015, 11, 119– 125.

(4)

Baaken, G.; Ankri, N.; Schuler, A.-K.; Rühe, J.; Behrends, J. C. ACS Nano 2011, 5, 8080–8088.

(5)

Weichbrodt, C.; Bajaj, H.; Baaken, G.; Wang, J.; Guinot, S.; Kreir, M.; Behrends, J. C.; Winterhalter, M.; Fertig, N. Analyst 2015, 140, 4874–4881.

(6)

Oshima, A.; Hirano-Iwata, A.; Mozumi, H.; Ishinari, Y.; Kimura, Y.; Niwano, M. Anal. Chem. 2013, 85, 4363–4369.

(7)

Stimberg, V. C.; Bomer, J. G.; van Uitert, I.; van den Berg, A.; Le Gac, S. Small 2013, 9, 1076–1085.

(8)

Bomer, J. G.; Prokofyev, A. V; van den Berg, A.; Le Gac, S. Lab Chip 2014, 14, 4461–4464.

(9)

Watanabe, R.; Soga, N.; Fujita, D.; Tabata, K. V; Yamauchi, L.; Hyeon Kim, S.; Asanuma, D.; Kamiya, M.; Urano, Y.; Suga, H.; Noji, H. Nat. Commun. 2014, 5, 4519.

(10)

Funakoshi, K.; Suzuki, H.; Takeuchi, S. Anal. Chem. 2006, 78, 8169–8174.

(11)

Holden, M. A.; Needham, D.; Bayley, H. J. Am. Chem. Soc. 2007, 129, 8650–8655.

(12)

Czekalska, M. a; Kaminski, T. S.; Jakiela, S.; Tanuj Sapra, K.; Bayley, H.; Garstecki, P. Lab Chip 2015, 15, 541–548.

(13)

Fan, S.-K.; Chen, C.-W.; Lin, Y.-Y.; Chen, L.-C.; Tseng, F.-G.; Pan, R.-L. Biomicrofluidics 2014, 8, 52006.

(14)

Aghdaei, S.; Sandison, M. E.; Zagnoni, M.; Green, N. G.; Morgan, H. Lab Chip 2008, 8, 1617–1620.

(15)

Poulos, J. L.; Nelson, W. C.; Jeon, T.-J.; Kim, C.-J.; Schmidt, J. J. Appl. Phys. Lett. 2009, 95, 013706.

(16)

Schlicht, B.; Zagnoni, M. Sci. Rep. 2015, 5, 9951.

(17)

Wauer, T.; Gerlach, H.; Mantri, S.; Hill, J.; Bayley, H.; Sapra, K. T. ACS Nano 2014, 8, 771–779.

(18)

Kawano, R.; Tsuji, Y.; Sato, K.; Osaki, T.; Kamiya, K.; Hirano, M.; Ide, T.; Miki, N.; Takeuchi, S. Sci. Rep. 2013, 3, 1995.

(19)

Thapliyal, T.; Poulos, J. L.; Schmidt, J. J. Biosens. Bioelectron. 2011, 26, 2651–2654.

(20)

Poulos, J. L.; Jeon, T.-J.; Damoiseaux, R.; Gillespie, E. J.; Bradley, K. A.; Schmidt, J. J. Biosens. Bioelectron. 2009, 24, 1806–1810.

(21)

Leptihn, S.; Castell, O. K.; Cronin, B.; Lee, E.-H.; Gross, L. C. M.; Marshall, D. P.; Thompson, J. R.; Holden, M.; Wallace, M. I. Nat. Protoc. 2013, 8, 1048–1057.

(22)

Kresák, S.; Hianik, T.; Naumann, R. L. C. Soft Matter 2009, 5 (20), 4021–4032.

(23)

Schmidt, C.; Mayer, M.; Vogel, H. Angew. Chemie 2000, 39, 3137–3140.

(24)

Huang, S.; Romero-Ruiz, M.; Castell, O. K.; Bayley, H.; Wallace, M. I. Nat. Nanotechnol. 2015, 10, 986–991.

(25)

Heron, A. J.; Thompson, J. R.; Cronin, B.; Bayley, H.; Wallace, M. I. J. Am. Chem. Soc. 2009, 131, 1652–1653.

(26)

Friddin, M. S.; Smithers, N. P.; Beaugrand, M.; Marcotte, I.; Williamson, P. T. F.; Morgan, H.; de Planque, M. R. R. Analyst 2013, 138, 7294–7298. 22 ACS Paragon Plus Environment

Page 23 of 39

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(27)


Kamiya, K.; Kawano, R.; Osaki, T.; Akiyoshi, K.; Takeuchi, S. Nat. Chem. 2016, 8, 881–889.

(28) Sengupta, P.; Hammond, A.; Holowka, D.; Baird, B. Biochim. Biophys. Acta - Biomembr. 2008, 1778, 20–32. (29)

Sezgin, E.; Kaiser, H.-J.; Baumgart, T.; Schwille, P.; Simons, K.; Levental, I. Nat. Protoc. 2012, 7, 1042–1051.

(30)

Hirano-Iwata, A.; Ishinari, Y.; Yoshida, M.; Araki, S.; Tadaki, D.; Miyata, R.; Ishibashi, K.; Yamamoto, H.; Kimura, Y.; Niwano, M. Biophys. J. 2016, 110, 2207–2215.

(31)

Demarche, S.; Sugihara, K.; Zambelli, T.; Tiefenauer, L.; Vörös, J. Analyst 2011, 136, 1077–1089.

(32)

Hirano-Iwata, A.; Ishinari, Y.; Yamamoto, H.; Niwano, M. Chem. - An Asian J. 2015, 10, 1266–1274.

(33)

Hirano-Iwata, A.; Niwano, M.; Sugawara, M. TrAC Trends Anal. Chem. 2008, 27, 512–520.

(34)

Ide, T.; Kobayashi, T.; Hirano, M. Anal. Chem. 2008, 80, 7792–7795.

(35)

Heron, A. J.; Thompson, J. R.; Mason, A. E.; Wallace, M. I. J. Am. Chem. Soc. 2007, 129, 16042– 16047.

(36)

Leptihn, S.; Thompson, J. R.; Ellory, J. C.; Tucker, S. J.; Wallace, M. I. J. Am. Chem. Soc. 2011, 133, 9370–9375.

(37)

El-Arabi, A. M.; Salazar, C. S.; Schmidt, J. J. Lab Chip 2012, 12, 2409–2413.

(38)

Saha, S. C.; Henderson, A. J.; Powl, A. M.; Wallace, B. A.; de Planque, M. R. R.; Morgan, H. PLoS One 2015, 10, e0131286.

(39)

Saha, S. C.; Powl, A. M.; Wallace, B. A.; de Planque, M. R. R.; Morgan, H. Biomicrofluidics 2015, 9, 014103.

(40)

Tsuji, Y.; Kawano, R.; Osaki, T.; Kamiya, K.; Miki, N.; Takeuchi, S. Lab Chip 2013, 13, 1476–1481.

(41)

Charalambous, K.; Booth, P. J.; Woscholski, R.; Seddon, J. M.; Templer, R. H.; Law, R. V; Barter, L. M. C.; Ces, O. J. Am. Chem. Soc. 2012, 134, 5746–5749.

(42)

Boreyko, J. B.; Mruetusatorn, P.; Sarles, S. A.; Retterer, S. T.; Collier, C. P. J. Am. Chem. Soc. 2013, 135, 5545–5548.

(43)

Villar, G.; Graham, A. D.; Bayley, H. Science 2013, 340, 48–52.

(44)

Friddin, M. S.; Bolognesi, G.; Elani, Y.; Brooks, N. J.; Law, R. V.; Seddon, J. M.; Neil, M. A. A.; Ces, O. Soft Matter 2016, 12, 7731–7734.

(45)

Maglia, G.; Heron, A. J.; Hwang, W. L.; Holden, M. a; Mikhailova, E.; Li, Q.; Cheley, S.; Bayley, H. Nat. Nanotechnol. 2009, 4, 437–440.

(46)

Elani, Y.; Law, R. V; Ces, O. Nat. Commun. 2014, 5, 5305.

(47)

Kasianowicz, J. J.; Brandin, E.; Branton, D.; Deamer, D. W. Proc. Natl. Acad. Sci. 1996, 93, 13770– 13773.

(48)

Robertson, J. W. F.; Rodrigues, C. G.; Stanford, V. M.; Rubinson, K. A.; Krasilnikov, O. V; Kasianowicz, J. J. Proc. Natl. Acad. Sci. U. S. A. 2007, 104, 8207–8211.

(49)

Venkatesan, B. M.; Bashir, R. Nat. Nanotechnol. 2011, 6, 615–624.

(50)

Stoddart, D.; Heron, A. J.; Mikhailova, E.; Maglia, G.; Bayley, H. Proc. Natl. Acad. Sci. 2009, 106, 7702–7707.

(51)

Purnell, R. F.; Schmidt, J. J. ACS Nano 2009, 3, 2533–2538. 23 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 24 of 39

(52) Derrington, I. M.; Butler, T. Z.; Collins, M. D.; Manrao, E.; Pavlenok, M.; Niederweis, M.; Gundlach, J. H. Proc. Natl. Acad. Sci. 2010, 107, 16060–16065. (53)

Fuller, C. W.; Kumar, S.; Porel, M.; Chien, M.; Bibillo, A.; Stranges, P. B.; Dorwart, M.; Tao, C.; Li, Z.; Guo, W.; Shi, S.; Korenblum, D.; Trans, A.; Aguirre, A.; Liu, E.; Harada, E. T.; Pollard, J.; Bhat, A.; Cech, C.; Yang, A.; Arnold, C.; Palla, M.; Hovis, J.; Chen, R.; Morozova, I.; Kalachikov, S.; Russo, J. J.; Kasianowicz, J. J.; Davis, R.; Roever, S.; Church, G. M.; Ju, J. Proc. Natl. Acad. Sci. 2016, 113, 5233–5238.

(54)

Stranges, P. B.; Palla, M.; Kalachikov, S.; Nivala, J.; Dorwart, M.; Trans, A.; Kumar, S.; Porel, M.; Chien, M.; Tao, C.; Morozova, I.; Li, Z.; Shi, S.; Aberra, A.; Arnold, C.; Yang, A.; Aguirre, A.; Harada, E. T.; Korenblum, D.; Pollard, J.; Bhat, A.; Gremyachinskiy, D.; Bibillo, A.; Chen, R.; Davis, R.; Russo, J. J.; Fuller, C. W.; Roever, S.; Ju, J.; Church, G. M. Proc. Natl. Acad. Sci. 2016, 113, E6749–E6756.

(55)

Laszlo, A. H.; Derrington, I. M.; Ross, B. C.; Brinkerhoff, H.; Adey, A.; Nova, I. C.; Craig, J. M.; Langford, K. W.; Samson, J. M.; Daza, R.; Doering, K.; Shendure, J.; Gundlach, J. H. Nat. Biotechnol. 2014, 32, 829–833.

(56)

Jain, M.; Fiddes, I. T.; Miga, K. H.; Olsen, H. E.; Paten, B.; Akeson, M. Nat. Methods 2015, 12, 351– 356.

(57)

Deamer, D.; Akeson, M.; Branton, D. Nat. Biotechnol. 2016, 34, 518–524.

(58)

Schmidt, J. Curr. Opin. Biotechnol. 2016, 39, 17–27.

(59)

Laszlo, A. H.; Derrington, I. M.; Gundlach, J. H. Methods 2016, 105, 75–89.

(60)

Graybill, R. M.; Bailey, R. C. Anal. Chem. 2016, 88, 431–450.

(61)

Wang, Y.; Zheng, D.; Tan, Q.; Wang, M. X.; Gu, L.-Q. Nat. Nanotechnol. 2011, 6, 668–674.

(62)

Zhang, X.; Wang, Y.; Fricke, B. L.; Gu, L. ACS Nano 2014, 8, 3444–3450.

(63)

Xi, D.; Shang, J.; Fan, E.; You, J.; Zhang, S.; Wang, H. Anal. Chem. 2016, 88, 10540–10546.

(64)

Johnson, R. P.; Fleming, A. M.; Beuth, L. R.; Burrows, C. J.; White, H. S. J. Am. Chem. Soc. 2016, 138, 594–603.

(65)

Howorka, S.; Siwy, Z. Chem. Soc. Rev. 2009, 38, 2360–2384.

(66)

Bayley, H.; Cremer, P. S. Nature 2001, 413, 226–230.

(67)

Guan, X.; Gu, L.-Q.; Cheley, S.; Braha, O.; Bayley, H. ChemBioChem 2005, 6, 1875–1881.

(68)

Wu, H.-C.; Bayley, H. J. Am. Chem. Soc. 2008, 130, 6813–6819.

(69)

Steffensen, M. B.; Rotem, D.; Bayley, H. Nat. Chem. 2014, 6, 603–607.

(70)

Majd, S.; Yusko, E. C.; Billeh, Y. N.; Macrae, M. X.; Yang, J.; Mayer, M. Curr. Opin. Biotechnol. 2010, 21, 439–476.

(71)

Wang, Y.; Montana, V.; Grubišić, V.; Stout, R. F.; Parpura, V.; Gu, L.-Q. ACS Appl. Mater. Interfaces 2015, 7, 184–192.

(72)

Baaken, G.; Halimeh, I.; Bacri, L.; Pelta, J.; Oukhaled, A.; Behrends, J. C. ACS Nano 2015, 9, 6443– 6449.

(73) Degiacomi, M. T.; Iacovache, I.; Pernot, L.; Chami, M.; Kudryashev, M.; Stahlberg, H.; van der Goot, F. G.; Dal Peraro, M. Nat. Chem. Biol. 2013, 9, 623–629. 24 ACS Paragon Plus Environment

Page 25 of 39

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

(74)


Maglia, G.; Restrepo, M. R.; Mikhailova, E.; Bayley, H. Proc. Natl. Acad. Sci. 2008, 105, 19720– 19725.

(75)

Pastoriza-Gallego, M.; Rabah, L.; Gibrat, G.; Thiebot, B.; van der Goot, F. G.; Auvray, L.; Betton, J.-M.; Pelta, J. J. Am. Chem. Soc. 2011, 133, 2923–2931.

(76)

Stefureac, R.; Waldner, L.; Howard, P.; Lee, J. S. Small 2008, 4, 59–63.

(77)

Singh, P. R.; Bárcena-Uribarri, I.; Modi, N.; Kleinekathöfer, U.; Benz, R.; Winterhalter, M.; Mahendran, K. R. ACS Nano 2012, 6, 10699–10707.

(78)

Nestorovich, E. M.; Danelon, C.; Winterhalter, M.; Bezrukov, S. M. Proc. Natl. Acad. Sci. 2002, 99, 9789–9794.

(79)

Soskine, M.; Biesemans, A.; Moeyaert, B.; Cheley, S.; Bayley, H.; Maglia, G. Nano Lett. 2012, 12, 4895–4900.

(80)

Braha, O.; Bayley, H.; Gu, L.-Q.; Conlan, S.; Cheley, S. Nature 1999, 398, 686–690.

(81)

Chen, M.; Khalid, S.; Sansom, M. S. P.; Bayley, H. Proc. Natl. Acad. Sci. 2008, 105, 6272–6277.

(82)

Soskine, M.; Biesemans, A.; Maglia, G. J. Am. Chem. Soc. 2015, 137 (17), 5793–5797.

(83)

Nivala, J.; Marks, D. B.; Akeson, M. Nat. Biotechnol. 2013, 31, 247–250.

(84)

Kawano, R.; Osaki, T.; Sasaki, H.; Takinoue, M.; Yoshizawa, S.; Takeuchi, S. J. Am. Chem. Soc. 2011, 133, 8474–8477.

(85)

Rotem, D.; Jayasinghe, L.; Salichou, M.; Bayley, H. J. Am. Chem. Soc. 2012, 134, 2781–2787.

(86)

Li, T.; Liu, L.; Li, Y.; Xie, J.; Wu, H.-C. Angew. Chemie Int. Ed. 2015, 54, 7568–7571.

(87)

Vargas Jentzsch, A.; Hennig, A.; Mareda, J.; Matile, S. Acc. Chem. Res. 2013, 46, 2791–2800.

(88)

Matile, S.; Vargas Jentzsch, A.; Montenegro, J.; Fin, A. Chem. Soc. Rev. 2011, 40, 2453–2474.

(89)

Mayer, M.; Yang, J. Acc. Chem. Res. 2013, 46, 2998–3008.

(90)

Gokel, G. W.; Negin, S. Acc. Chem. Res. 2013, 46, 2824–2833.

(91)

Capone, R.; Blake, S.; Rincon Restrepo, M.; Yang, J.; Mayer, M. J. Am. Chem. Soc. 2007, 129, 9737–9745.

(92)

Su, G.; Zhang, M.; Si, W.; Li, Z.; Hou, J. Angew. Chemie Int. Ed. 2016, 55, 14678–14682.

(93)

Macrae, M. X.; Blake, S.; Jiang, X.; Capone, R.; Estes, D. J.; Mayer, M.; Yang, J. ACS Nano 2009, 3, 3567–3580.

(94)

Lang, C.; Li, W.; Dong, Z.; Zhang, X.; Yang, F.; Yang, B.; Deng, X.; Zhang, C.; Xu, J.; Liu, J. Angew. Chemie Int. Ed. 2016, 55, 9723–9727.

(95)

Geng, J.; Kim, K.; Zhang, J.; Escalada, A.; Tunuguntla, R.; Comolli, L. R.; Allen, F. I.; Shnyrova, A. V; Cho, K. R.; Munoz, D.; Wang, Y. M.; Grigoropoulos, C. P.; Ajo-Franklin, C. M.; Frolov, V. A.; Noy, A. Nature 2014, 514, 612–615.

(96)

Liu, L.; Yang, C.; Zhao, K.; Li, J.; Wu, H.-C. Nat. Commun. 2013, 4, 2989.

(97)

Kulikov, O. V.; Li, R.; Gokel, G. W. Angew. Chemie Int. Ed. 2009, 48, 375–377.

(98)

Jung, M.; Kim, H.; Baek, K.; Kim, K. Angew. Chemie Int. Ed. 2008, 47, 5755–5757.

(99)

Krishnan, S.; Ziegler, D.; Arnaut, V.; Martin, T. G.; Kapsner, K.; Henneberg, K.; Bausch, A. R.; Dietz, H.; Simmel, F. C. Nat. Commun. 2016, 7, 12787.

(100) Langecker, M.; Arnaut, V.; Martin, T. G.; List, J.; Renner, S.; Mayer, M.; Dietz, H.; Simmel, F. C. 25 ACS Paragon Plus Environment


1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60

Page 26 of 39

Science 2012, 338, 932–936. (101) Burns, J. R.; Seifert, A.; Fertig, N.; Howorka, S. Nat. Nanotechnol. 2016, 11, 152–156. (102) Burns, J. R.; Stulz, E.; Howorka, S. Nano Lett. 2013, 13, 2351–2356. (103) Litvinchuk, S.; Tanaka, H.; Miyatake, T.; Pasini, D.; Tanaka, T.; Bollot, G.; Mareda, J.; Matile, S. Nat. Mater. 2007, 6, 576–580. (104) Takeuchi, T.; Montenegro, J.; Hennig, A.; Matile, S. Chemcal Sci. 2011, 2, 303–307. (105) Takeuchi, T.; Matile, S. Chem. Commun. 2013, 49, 19–29. (106) Yusko, E. C.; Johnson, J. M.; Majd, S.; Prangkio, P.; Rollings, R. C.; Li, J.; Yang, J.; Mayer, M. Nat. Nanotechnol. 2011, 6, 253–260. (107) Liu, Q.; Xiao, K.; Wen, L.; Lu, H.; Liu, Y.; Kong, X.-Y.; Xie, G.; Zhang, Z.; Bo, Z.; Jiang, L. J. Am. Chem. Soc. 2015, 137, 11976–11983. (108) Rincon-Restrepo, M.; Mikhailova, E.; Bayley, H.; Maglia, G. Nano Lett. 2011, 11, 746–750. (109) Asandei, A.; Chinappi, M.; Lee, J.; Ho Seo, C.; Mereuta, L.; Park, Y.; Luchian, T. Sci. Rep. 2015, 5, 10419. (110) Kawano, R.; Schibel, A. E. P.; Cauley, C.; White, H. S. Langmuir 2009, 25, 1233–1237. (111) Wang, Y.; Yao, F.; Kang, X. Anal. Chem. 2015, 87, 9991–9997. (112) Lee, S. J.; Kang, J. Y.; Choi, W.; Kwak, R. Small 2016, DOI: 10.1002/smll.201601725. (113) Höfler, L.; Gyurcsányi, R. E. Anal. Chim. Acta 2012, 722, 119–126. (114) Wanunu, M.; Morrison, W.; Rabin, Y.; Grosberg, A. Y.; Meller, A. Nat. Nanotechnol. 2010, 5, 160– 165. (115) Freedman, K. J.; Otto, L. M.; Ivanov, A. P.; Barik, A.; Oh, S.-H.; Edel, J. B. Nat. Commun. 2016, 7, 10217. (116) Witters, D.; Sun, B.; Begolo, S.; Rodriguez-Manzano, J.; Robles, W.; Ismagilov, R. F. Lab Chip 2014, 14, 3225–3232. (117) Kim, S. H.; Iwai, S.; Araki, S.; Sakakihara, S.; Iino, R.; Noji, H. Lab Chip 2012, 12, 4986–4991. (118) Rissin, D. M.; Kan, C. W.; Campbell, T. G.; Howes, S. C.; Fournier, D. R.; Song, L.; Piech, T.; Patel, P. P.; Chang, L.; Rivnak, A. J.; Ferrell, E. P.; Randall, J. D.; Provuncher, G. K.; Walt, D. R.; Duffy, D. C. Nat. Biotechnol. 2010, 28, 595–599. (119) Holden, M. a; Bayley, H. J. Am. Chem. Soc. 2005, 127, 6502–6503. (120) Holden, M. a; Jayasinghe, L.; Daltrop, O.; Mason, A.; Bayley, H. Nat. Chem. Biol. 2006, 2, 314–318. (121) Hirano, M.; Takeuchi, Y.; Aoki, T.; Yanagida, T.; Ide, T. Anal. Chem. 2009, 81, 3151–3154. (122) Frank, P.; Siebenhofer, B.; Hanzer, T.; Geiss, A. F.; Schadauer, F.; Reiner-Rozman, C.; Durham, B.; Loew, L. M.; Ludwig, B.; Richter, O.-M. H.; Nowak, C.; Naumann, R. L. C. Soft Matter 2015, 11, 2906–2908. (123) Schrems, A.; Phillips, J.; Casey, D.; Wylie, D.; Novakova, M.; Sleytr, U. B.; Klug, D.; Neil, M. A. A.; Schuster, B.; Ces, O. Analyst 2014, 139, 3296–3304. (124) White, R. J.; Ervin, E. N.; Yang, T.; Chen, X.; Daniel, S.; Cremer, P. S.; White, H. S. J. Am. Chem. Soc. 2007, 129, 11766–11775. (125) Gross, L. C. M.; Castell, O. K.; Wallace, M. I. Nano Lett. 2011, 11, 3324–3328. 26 ACS Paragon Plus Environment

Page 27 of 39

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60


(126) Nielsen, C. H. Anal. Bioanal. Chem. 2009, 395, 697–718. (127) Polymer Membranes/Biomembranes; Meier, W. P., Knoll, W., Eds.; Advances in Polymer Science; Springer Berlin Heidelberg: Berlin, Heidelberg, 2010; Vol. 224. (128) Bright, L. K.; Baker, C. A.; Bränström, R.; Saavedra, S. S.; Aspinwall, C. A. ACS Biomater. Sci. Eng. 2015, 1, 955–963. (129) Hall, A. R.; Scott, A.; Rotem, D.; Mehta, K. K.; Bayley, H.; Dekker, C. Nat. Nanotechnol. 2010, 5, 874–877. (130) Mayer, M.; Kriebel, J. K.; Tosteson, M. T.; Whitesides, G. M. Biophys. J. 2003, 85, 2684–2695. (131) Kawano, R.; Osaki, T.; Sasaki, H.; Takeuchi, S. Small 2010, 6, 2100–2104. (132) Kalsi, S.; Powl, A. M.; Wallace, B. A.; Morgan, H.; de Planque, M. R. R. Biophys. J. 2014, 106, 1650–1659. (133) Bright, L. K.; Baker, C. A.; Agasid, M. T.; Ma, L.; Aspinwall, C. A. ACS Appl. Mater. Interfaces 2013, 5, 11918–11926. (134) Marin, V.; Kieffer, R.; Padmos, R.; Aubin-Tam, M.-E. Anal. Chem. 2016, 88, 7466–7470. (135) Jeon, T.-J.; Malmstadt, N.; Schmidt, J. J. J. Am. Chem. Soc. 2006, 128, 42–43. (136) Kang, X.; Cheley, S.; Rice-Ficht, A. C.; Bayley, H. J. Am. Chem. Soc. 2007, 129, 4701–4705. (137) Shim, J. W.; Gu, L. Q. Anal. Chem. 2007, 79, 2207–2213. (138) Sarles, S. a; Leo, D. J. Lab Chip 2010, 10, 710–717. (139) Venkatesan, G. A.; Sarles, S. A. Lab Chip 2016, 16, 2116–2125. (140) Jeon, T.-J.; Poulos, J. L.; Schmidt, J. J. Lab Chip 2008, 8, 1742–1744. (141) Needham, D.; Haydon, D. A. Biophys. J. 1983, 41, 251–257. (142) Taylor, G. J.; Venkatesan, G. A.; Collier, C. P.; Sarles, S. A. Soft Matter 2015, 11, 7592–7605. (143) Punnamaraju, S.; Steckl, A. J. Langmuir 2011, 27, 618–626. (144) White, S. H.; Chang, W. Biophys. J. 1981, 36, 449–453. (145) Beltramo, P. J.; Van Hooghten, R.; Vermant, J. Soft Matter 2016, 12, 4324–4331. (146) Barlow, N. E.; Bolognesi, G.; Flemming, A. J.; Brooks, N. J.; Barter, L. M. C.; Ces, O. Lab Chip 2016, DOI: 10.1039/c6lc01011c. (147) Osaki, T.; Suzuki, H.; Le Pioufle, B.; Takeuchi, S. Anal. Chem. 2009, 81, 9866–9870. (148) Zagnoni, M.; Sandison, M. E.; Morgan, H. Biosens. Bioelectron. 2009, 24, 1235–1240. (149) Tomoike, F.; Tonooka, T.; Osaki, T.; Takeuchi, S. Lab Chip 2016, 16, 2423–2426. (150) Tsuji, Y.; Kawano, R.; Osaki, T.; Kamiya, K.; Miki, N.; Takeuchi, S. Anal. Chem. 2013, 85, 10913– 10919. (151) Hallem, E. A.; Carlson, J. R. Cell 2006, 125, 143–160. (152) Glatz, R.; Bailey-Hill, K. Prog. Neurobiol. 2011, 93, 270–296. (153) Wang, G.; Carey, A. F.; Carlson, J. R.; Zwiebel, L. J. Proc. Natl. Acad. Sci. 2010, 107, 4418–4423. (154) Sato, K.; Takeuchi, S. Angew. Chemie Int. Ed. 2014, 53, 11798–11802. (155) Crescentini, M.; Thei, F.; Bennati, M.; Saha, S.; de Planque, M. R. R.; Morgan, H.; Tartagni, M. IEEE Trans. Biomed. Circuits Syst. 2015, 9, 334–344. (156) Saha, S. C.; Thei, F.; de Planque, M. R. R.; Morgan, H. Sensors Actuators B Chem. 2014, 199, 76–82. 27 ACS Paragon Plus Environment


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Page 28 of 39

(157) Kawano, R.; Tsuji, Y.; Kamiya, K.; Kodama, T.; Osaki, T.; Miki, N.; Takeuchi, S. PLoS One 2014, 9, e102427. (158) Forstater, J. H.; Briggs, K.; Robertson, J. W. F.; Ettedgui, J.; Marie-Rose, O.; Vaz, C.; Kasianowicz, J. J.; Tabard-Cossa, V.; Balijepalli, A. Anal. Chem. 2016, DOI: 10.1021/acs.analchem.6b03725. (159) Marx, V. Nat. Methods 2015, 12, 1015–1018.


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Biographies Toshihisa Osaki received his Dr. Eng. degree in organic and polymeric materials in 2002 from Tokyo Institute of Technology. He worked as a postdoctoral researcher at Leibniz-Institute of Polymer Research Dresden, Germany (2002–2006), at National Institute of Advanced Industrial Science and Technology, Japan (2006–2007), and at LIMMS/CNRS-IIS, The University of Tokyo (2007–2009). He is currently working at Kanagawa Academy of Science and Technology as a project assistant leader. His current research is focused on developing artificial cell membrane systems for fundamental studies of membrane proteins and for sensor applications.

Shoji Takeuchi received the B.E, M.E., and Dr. Eng. degrees in mechanical engineering from the University of Tokyo, Tokyo, Japan, in 1995, 1997, and 2000, respectively. He is currently a Professor in the Center for International Research on Integrative Biomedical Systems (CIBiS), Institute of Industrial Science (IIS), The University of Tokyo. His current research interests include bottom-up tissue engineering, membrane protein chips and biohybrid MEMS.



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Figure 1

Figure 1 (a) 16-channel microchip with the chip holder (a1). Magnified view of the microwells on the chip (a2), and its cross-sectional schematic (a3). Reproduced from Baaken, G.; Ankri, N.; Schuler, A.-K.; Rühe, J.; Behrends, J. C. ACS Nano 2011, 5, 8080–8088 (ref 4). Copyright 2011 American Chemical Society. (b) Lipid bilayer formation in a microfluidic channel (b1). Encapsulation of Alexa 488 in 4-μm diameter microchambers by lipid membranes. Reprinted by permission from Macmillan Publishers Ltd: Watanabe, R.; Soga, N.; Fujita, D.; Tabata, K. V; Yamauchi, L.; Hyeon Kim, S.; Asanuma, D.; Kamiya, M.; Urano, Y.; Suga, H.; Noji, H. Nat. Commun. 2014, 5, 4519 (ref 9), copyright 2014. (c) Lipid bilayer formation by the droplet contact method (Schematic and procedures). (d) Current recordings of various ion channels using the 30 ACS Paragon Plus Environment

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droplet contact device. Reproduced from Kawano, R.; Tsuji, Y.; Sato, K.; Osaki, T.; Kamiya, K.; Hirano, M.; Ide, T.; Miki, N.; Takeuchi, S. Sci. Rep. 2013, 3, 1995 (ref 18). Copyright 2013 Nature Publishing Group. (e) Folding process of a flower-shaped droplet-network to a hollow sphere by osmotic flow from the upper (blue) to the bottom (orange) layer. The time-lapse images for 8 h. Scale bar: 200μm. From Villar, G.; Graham, A. D.; Bayley, H. Science 2013, 340, 48–52 (ref 43). Reprinted with permission from AAAS. (f) Sequential reactions using segregation of aqueous droplets via a lipid bilayer. The multi-step reaction (f1) was respectively demonstrated in three systems (f2-4) in the presence/absence of the key elements. Reproduced from Elani, Y.; Law, R. V; Ces, O. Nat. Commun. 2014, 5, 5305 (ref 46). Copyright 2014 Nature Publishing Group.



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Figure 2

Figure 2 (a) Schematic of DNA sequencing method using four polymer tags for each nucleotide that exhibit unique blockade signatures. Reproduced from Stranges, P. B.; Palla, M.; Kalachikov, S.; Nivala, J.; Dorwart, M.; Trans, A.; Kumar, S.; Porel, M.; Chien, M.; Tao, C.; Morozova, I.; Li, Z.; Shi, S.; Aberra, A.; Arnold, C.; Yang, A.; Aguirre, A.; Harada, E. T.; Korenblum, D.; Pollard, J.; Bhat, A.; Gremyachinskiy, D.; Bibillo, A.; Chen, R.; Davis, R.; Russo, J. J.; Fuller, C. W.; Roever, S.; Ju, J.; Church, G. M. Proc. Natl. Acad. Sci. 2016, 113, E6749–E6756 (ref 54). Copyright 2016 National Academy of Sciences. (b) Schematics of DNA sequencing method using MspA nanopore and phi29 DNA polymerase (b1-2). The raw data (b3) are processed using an algorithm to identify the transition level (b4), and compared with the predicted levels from the reference sequence (b5). Reprinted by permission from Macmillan Publishers Ltd: Laszlo, A. H.; Derrington, I. M.; Ross, B. C.; Brinkerhoff, H.; Adey, A.; Nova, I. C.; Craig, J. M.; Langford, K. W.; Samson, J. M.; Daza, R.; Doering, K.; Shendure, J.; Gundlach, J. H. Nat. Biotechnol. 2014, 32, 829–833 (ref 55), copyright 2014.


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Figure 3

Figure 3 (a) Multiplex detection of microRNA using poly(ethylene glycol) labeling. Individual labels on DNA probes generate different blockade levels, enabling the discrimination of the target microRNAs (a1-3). The event frequencies vs. miR155 concentration while other 3 miRNAs are at 75 nM (a4), and the event frequencies of each microRNA at the same concentrations (a5). Results of multiplex detection. Reproduced from Zhang, X.; Wang, Y.; Fricke, B. L.; Gu, L. ACS Nano 2014, 8, 3444–3450 (ref 62). Copyright 2014 American Chemical Society. (b) Identification of CC and CA mismatches using the latch constriction. With the mismatches, two distinct state modulating signatures were observed by the current traces (b2). Reproduced from Johnson, R. P.; Fleming, A. M.; Beuth, L. R.; Burrows, C. J.; White, H. S. J. Am. Chem. Soc. 2016, 138, 594–603 (ref 64). Copyright 2016 American Chemical Society.



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Figure 4

Figure 4 (a) Alkb-Fe2+-trapped ClyA-AS nanopore (a1). Blockade events depending on the ligands. Reproduced from Soskine, M.; Biesemans, A.; Maglia, G. J. Am. Chem. Soc. 2015, 137, 5793–5797 (ref 82). Copyright 2015 American Chemical Society. (b) Ionic current traces of single/multiple CNT pores incorporated in a lipid bilayer. Reprinted by permission from Macmillan Publishers Ltd: Geng, J.; Kim, K.; Zhang, J.; Escalada, A.; Tunuguntla, R.; Comolli, L. R.; Allen, F. I.; Shnyrova, A. V; Cho, K. R.; Munoz, D.; Wang, Y. M.; Grigoropoulos, C. P.; Ajo-Franklin, C. M.; Frolov, V. A.; Noy, A. Nature 2014, 514, 612–615 (ref 95), copyright 2014. (c) DNA-triggered molecular release with charge selectivity. DNA pore opened with a key DNA (NP-C to NP-O; c1), and selectively released sulpho-rhodamine B (SRB; green) to outside of vesicles but carboxy-fluorescein (CF; red) (c2-4). Reprinted by permission from Macmillan Publishers Ltd: Burns, J. R.; Seifert, A.; Fertig, N.; Howorka, S. Nat. Nanotechnol. 2016, 11, 152–156 (ref 101), copyright 2016.


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Figure 5

Figure 5 (a) Enhancement of capture rate by a salt concentration gradient. Dependency of DNA capture rate on Ctrans/Ccis at 3.5-nm pore (a1-2). Schematics of K+ ion selective pumping (a3), and numerical simulation of the electric potentials of the cis side chamber at different Ctrans/Ccis concentrations (a4). Reprinted by permission from Macmillan Publishers Ltd: Wanunu, M.; Morrison, W.; Rabin, Y.; Grosberg, A. Y.; Meller, A. Nat. Nanotechnol. 2010, 5, 160–165 (ref 114), copyright (2009). (b) Enhanced DNA capture on a gold-coated nanopipette using AC field. Schematic (b1) and the capture rate vs. 10 kbp DNA concentration (b2). Reproduced from Freedman, K. J.; Otto, L. M.; Ivanov, A. P.; Barik, A.; Oh, S.-H.; Edel, J. B. Nat. Commun. 2016, 7, 10217 (ref 115). Copyright 2016 Nature Publishing Group.



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Figure 6

Figure 6 Illustration of the grab-and-drop method; transfer intact proteins in a cell to a supported lipid bilayer. Reproduced from Schrems, A.; Phillips, J.; Casey, D.; Wylie, D.; Novakova, M.; Sleytr, U. B.; Klug, D.; Neil, M. A. A.; Schuster, B.; Ces, O. Analyst 2014, 139, 3296–3304 (ref 123) with permission of The Royal Society of Chemistry.


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Figure 7

Figure 7 (a) The relationship between the surface treatment and the bilayer stabilities. Reproduced from Bright, L. K.; Baker, C. A.; Agasid, M. T.; Ma, L.; Aspinwall, C. A. ACS Appl. Mater. Interfaces 2013, 5, 11918–11926 (ref 133). Copyright 2013 American Chemical Society. (b) Portability and handling ability of organogel-encapsulated DIB. DIB was stable on a flexible, open substrate, under water, and under indirect force (b1-3). Reproduced from Venkatesan, G. A.; Sarles, S. A. Lab Chip 2016, 16, 2116–2125 (ref 139) with permission of The Royal Society of Chemistry.



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Figure 8

Figure 8 (a) Schematics representing the equilibrium of three surface tensions. Reproduced from Taylor, G. J.; Venkatesan, G. A.; Collier, C. P.; Sarles, S. A. Soft Matter 2015, 11, 7592–7605 (ref 142) with permission of The Royal Society of Chemistry. (b) Bilayer formation by draining the excessive oil. Bottom images represent the bilayer formation process. Scale bar: 200 μm. Reproduced from Beltramo, P. J.; Van Hooghten, R.; Vermant, J. Soft Matter 2016, 12, 4324–4331 (ref 145) with permission of The Royal Society of Chemistry. (c) Repetitive bilayer formation by rotating motion on an aperture. Scale bar: 20 μm. Reproduced from Tomoike, F.; Tonooka, T.; Osaki, T.; Takeuchi, S. Lab Chip 2016, 16, 2423–2426 (ref 149) with permission of The Royal Society of Chemistry. (d) DIB reformation by exchanging one of the droplets in a microfluidic trap. Scale bar: 200 μm. Reproduced from Czekalska, M. a; Kaminski, T. S.; Jakiela, S.; Tanuj Sapra, K.; Bayley, H.; Garstecki, P. Lab Chip 2015, 15, 541–548 (ref 12) –Published by The Royal Society of Chemistry.


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Artificial Cell Membrane Systems for Biosensing Applications

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