Name: assembly and characterization of biomolecular memristors consisting of ion channel-doped lipid membranes
Uploaded: 2019-03-09T15:00:00
Description: Watch this Scientific Journal Video about Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes at JoVE.com

Financial support was provided by the National Science Foundation Grant NSF ECCS-1631472. Research for G.J.T., C.D.S., A.B., and C.P.C. was partially sponsored by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy. A portion of this research was conducted at the Center for Nanophase Materials Sciences, which is a DOE Office of Science User Facility.&#160;

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This paper presents a protocol for assembling and characterizing biomolecular memristors based on ion channel-doped synthetic biomembranes formed between two droplets of water in oil. The soft-matter, two-terminal device is designed and studied to: 1) overcome constraints that are associated with solid-state technology, such as high noise, high energy consumption, and high switching voltages, 2) more closely mimic the composition, structure, switching mechanisms of biological synapses, and 3) explore the mechanisms and f...

It is widely recognized that biological synapses are responsible for the high efficiency and enormous parallelism of the brain due to their ability to learn and process information in highly adaptive ways. This coordinated functionality emerges from multiple, highly complex molecular mechanisms that drive both short-term and long-term synaptic plasticity1,2,3,4,5. Neuromorphic computing systems aim to emulate synaptic functionalities at levels approaching the density, complexity, and energy efficiency of the brain, which are needed for the next generation of brain-like computers6,7,8. However, reproducing synaptic features using traditional electronic circuit elements is virtually impossible9, instead requiring the design and fabrication of new hardware elements that can adapt to incoming signals and remember information histories9. These types of synapse-inspired hardware are known as mem-elements9,10,11 (short for memory elements), which, according to Di Ventra et al.9,11, are passive, two-terminal devices whose resistance, capacitance, or inductance can be reconfigured in response to external stimuli, and which can remember prior states11. To achieve energy consumption levels approaching those in the brain, these elements should employ similar materials and mechanisms for synaptic plasticity12.
To date, two-terminal memristors13,14,15 have predominantly been built using complementary metal-oxide-semiconductor (CMOS) technology, characterized by high-switching voltages and high noise. This technology does not scale well due to high power consumption and low density. To address these limitations, multiple organic and polymeric memristors have been recently built. However, these devices exhibit significantly slower switching dynamics due to time-consuming ion diffusion through a conductive polymer matrix16,17. As a result, the mechanisms by which both CMOS-based and organic memristive devices emulate synapse-inspired functionalities are highly phenomenological, encompassing only a few synaptic functionalities such as Spike Timing Dependent Plasticity (STDP)18, while overlooking other key features that also play essential roles in making the brain a powerful and efficient computer, such as pre-synaptic, short-term plasticity19.&#160;
Recently, we introduced a new class of memristive devices12 featuring voltage-activated peptides incorporated in biomimetic lipid membranes that mimics the biomolecular composition, membrane structure, and ion channel triggered switching mechanisms of biological synapses20.&#160; Here, we describe how to assemble and electrically interrogate these two-terminal devices, with specific focus on how to evaluate short-term plasticity for implementation in online learning applications12. Device assembly is based on the droplet interface bilayer (DIB)21 method, which has been used extensively in recent years to study the biophysics of model membranes21 and membrane-bound ion channels22,23,24, and as building blocks for the development of stimuli-responsive materials25,26. We describe the membrane assembly and interrogation process in detail for those interested in neuromorphic applications but have limited experience in biomaterials or membrane biology. The protocol also includes a full description of the characterization procedure, which is as important as the assembly process, given the dynamic and reconfigurable electrical properties of the device27. The procedure and representative results described here are foundations for a new class of low-cost, low-power, soft mem-elements based on lipid interfaces and other biomolecules for applications in neuromorphic computing, autonomous structures and systems, and even adaptive brain-computer interfaces.

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			<td style="width:183px;">850356P/850356C</td>
			<td style="width:663px;">Purchased as lyophilized powder (P) or in chloroform (C)&#160;</td>
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			<td style="width:183px;">610000</td>
			<td>This includes a mini-extruder, 2 syringes, 100 PC membranes, 100 filter supports, and 1 holder/heating block</td>
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assembly and characterization of biomolecular memristors consisting of ion channel-doped lipid membranes

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the cognitive powers of the brain with comparable efficiency and density. To date, silicon-based three-terminal transistors and two-terminal memristors have been widely used in neuromorphic circuits, in large part due to their ability to co-locate information processing and memory. Yet these devices cannot achieve the interconnectivity and complexity of the brain because they are power-hungry, fail to mimic key synaptic functionalities, and suffer from high noise and high switching voltages. To overcome these limitations, we have developed and characterized a biomolecular memristor that mimics the composition, structure, and switching characteristics of biological synapses. Here, we describe the process of assembling and characterizing biomolecular memristors consisting of a 5 nm-thick lipid bilayer formed between lipid-functionalized water droplets in oil and doped with voltage-activated alamethicin peptides. While similar assembly protocols have been used to investigate biophysical properties of droplet-supported lipid membranes and membrane-bound ion channels, this article focuses on key modifications of the droplet interface bilayer method essential for achieving consistent memristor performance. Specifically, we describe the liposome preparation process and the incorporation of alamethicin peptides in lipid bilayer membranes, and the appropriate concentrations of each constituent as well as their impact on the overall response of the memristors. We also detail the characterization process of biomolecular memristors, including measurement and analysis of memristive current-voltage relationships obtained via cyclic voltammetry, as well as short-term plasticity and learning in response to step-wise voltage pulse trains.

Figure 1 displays the experimental setup used to assemble and characterize the biomolecular memristor. Lowering the free ends of the electrodes to the bottom of the oil reservoir, as shown in Figure 1b, was found helpful to minimize vibrations of the electrodes and droplets that can result in variations in measured current and bilayer area, especially in cases where heating the oil can generate convective flow in the oil. Figure 2 s...

Watch this Scientific Journal Video about Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes at JoVE.com

Assembly and Characterization of Biomolecular Memristors Consisting of Ion Channel-doped Lipid Membranes

Soft, low-power, biomolecular memristors leverage similar composition, structure, and switching mechanisms of bio-synapses. Presented here is a protocol to assemble and characterize biomolecular memristors obtained from insulating lipid bilayers formed between water droplets in oil. The incorporation of voltage-activated alamethicin peptides results in memristive ionic conductance across the membrane.

The ability to recreate synaptic functionalities in synthetic circuit elements is essential for neuromorphic computing systems that seek to emulate the ...

Our protocol describes how to assemble and electrically characterize a peptide-doped biomembrane that closely mimics the composition, structure, and transport properties of biological synapses and which exhibits tunable memory resistance. This technique empowers users to assess activity-dependent, memory resistance and short-term plasticity in engineered systems at time scales and excitation levels relevant to biological synapses and ion channels. This technique provides a framework for characterizing biomimetic membranes containing voltage-activated ion channels, making it applicable to characterization of a variety of cellular transport processes, including those in neurons.Our suggestion to new researchers is to first become proficient at preparing liposome solutions and assembling a droplet interface bilayer on wire-type electrodes. Seeing firsthand the process for droplet dispensing and positioning on electrodes simplifies this technique for bilayer formation, making it immediately accessible to all. Demonstrating this procedure will be Dr.Joseph Najem, a postdoc from my laboratory.To begin, prepare the alamethicin stock solution in the microcentrifuge tube by dissolving the alamethicin peptides powder in ethanol to a final concentration of 2.5 milligram per milliliter. Vortex the tube briefly to mix well, and store the stock solution in a minus 20 degree Celsius freezer. In a 1.5 milliliter Safe-Lock tube, add one microliter of alamethicin stock solution to 99 microliters of solution A to achieve a final alamethicin concentration of 13 micromolar in the liposome suspension.Vortex to mix well. The resulting peptide liposome solution is solution B.Mix 117 microliters of solution A with 10 microliters of solution B to achieve a final alamethicin concentration of one micromolar, and then vortex to mix well. Refer to the resulting solution as C.Store the solutions B and C at four degrees Celsius.Place a one-millimeter thick 25 times 75 millimeters glass side on the stage of an inverted microscope. Dispense a few drops of hexadecane oil onto the center of the glass slide, and then place the oil reservoir directly onto the oil on the glass slide. Completely fill the oil reservoir with hexadecane oil.Make sure the reservoir is positioned above the objective lens. Then plug the electrode holder to the head stage of a current amplifier mounted on a micromanipulator. The micromanipulator minimizes electrode length and electrical noise.Then, mount the glass micropipette holder with the second silver-silver-chloride wire onto another micromanipulator. Using the micromanipulators, position the electrodes such that the agarose-coated tips of the silver-silver-chloride wires are fully submerged into the oil reservoir at a similar vertical plane. Align the two electrodes and separate them by a few millimeters.To form the lipid bilayer, move the electrodes vertically into the oil phase. Use the micropipette to deposit 200 nanoliters of lipid solution A on each of the wires. Wait for three to five minutes to allow for spontaneous lipid monolayer assembly to occur at the water oil interface.Droplets might sag if the surrounding oil is sufficiently less dense. After that, lower the electrodes to re-submerge until the ends of both electrodes barely touch the bottom of the oil reservoir. Then to form the bilayer, move the electrodes horizontally to bring the droplets into contact.To obtain the pinched, hysteretic, current-voltage relationship, use a function generator to apply triangular or sinusoidal voltage waveform to an alamethicin-free lipid membrane assembled with droplets of solution A.Record the induced current response across multiple frequencies. To record the size of the interfacial lipid bilayer, either measure the diameter of the lipid membrane on computer or record the peak-to-peak current amplitude resulting from the 10 hertz, 10 millivolts triangular wave to calculate the area of the membrane. Take the wires out of the oil phase to remove the droplets that contain no alamethicin.Add new aqueous droplets using solution C and form a lipid bilayer. Based on the square wave current amplitude, use the micromanipulators to adjust contact between droplets, such that the bilayer has a similar area as the one formed earlier. Then apply a 10-hertz and 10-millivolts voltage wave form, and record the induced current response as previously.To conduct pulse experiments using a custom programming software and analog voltage source, generate voltage pulses with specific high and low amplitudes on time and off time. Record the current in response to applied pulses. The plot of current versus voltage shows the non-zero current response upon application of a voltage bias to an alamethicin-free lipid bilayer.Add 0.017 hertz, a frequency where the impedance is dominated by membrane resistance. A low ohmic current response is shown for the highly insulating membrane. The plot of a lipid bilayer formed between two droplets containing alamethicin peptides shows exponentially increasing currents at voltages higher than the insertion threshold of 100 millivolts.At high voltage, alamethicin peptides residing at the surface of the lipid bilayer insert into the membrane and aggregate to form conductive pores. The symmetric current responses at both polarities is due to the insertion and aggregation of separate populations of peptides from opposite sides of the membrane. The capacitive current must be subtracted from the total current to obtain only the memristive, pinched hysteresis current-voltage response.The biomolecular memristor response to subsequent voltage pulses with an increase in conductance during the on time, despite intermittently restoring an insulating state during each off time. Both the present stimulus and prior stimuli contribute to the current increase. Cohesive monolayers on both droplets must form before bringing them together to form the bilayer.If the droplets are brought together too early, they coalesce and no bilayer is formed. We are now designing and fabricating, microfluidic base neural networks consisting of solid state neurons connected by membrane-based synapses supported by network assimilation optimization of high-performance supercomputers at ORNL. These memristors are the first to have the composition, structure, switching mechanism, and ion transport of biological synapses.They thus provide a biomolecular basis furnished adding brain-like computing and memory.

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