지질 이중층 상 플라즈모닉 나노입자 기반 나노바이오 검지 및 컴퓨팅

학위논문 (박사)-- 서울대학교 대학원 : 자연과학대학 화학부, 2019. 2. 남좌민.Supported lipid bilayer is a two-dimensional lipid bilayer self-assembled on a hydrophilic substrate with two-dimensional fluidity. By introducing plasmonic nanoparticles with strong scattering signals into the supported lipid bilayer, it is possible to observe and track thousands of nanoparticles and their interactions at a single-nanoparticle level in real time. In this thesis, I expand the nanoparticle-lipid bilayer platform by engineering plasmonic nanoparticles to construct a complex nanoparticle network system and develop multiplexed bio-detection and bio-computing strategies. Chapter 1 describes a supported lipid bilayer platform incorporating plasmonic nanoparticles. Section 1 introduces the optical properties and biosensing application of plasmonic nanoparticles, and Section 2 introduces tethering technique, characteristics, and advantages for introducing nanoparticles into supported lipid bilayer platforms. In Chapter 2, I introduce a system that can distinguish nine types of nanoparticle assembly reactions occurring simultaneously by introducing optically encoded plasmonic nanoparticles that scatter red, blue, and green light into supported lipid bilayers. I performed multiplexed detection of nine types of microRNAs, which are important gene regulators and cancer cell biomarker. In Chapter 3, I develop a bio-computing platform that recognizes molecular inputs, performs logic circuits, and generates nanoparticle assembly/disassembly output signals. Complex logic circuits are designed and implemented by combining two strategies: (i) interfacial design that constructs a logic circuit through DNA functionalization of the interface of nanoparticles, and (ii) a network design that connects assembly/disassembly reactions. In Chapter 4, I develop a bio-computing calculator capable of performing arithmetic logic operations. I use the nanoparticle-lipid bilayer platform as the hardware that stores, processes, and outputs information, and constructs software that contains logic circuit functions through DNA solution. An information storage nanoparticle stores solution-phase molecular input signals on the surface of nanoparticles. The bio-computing lipid nanotablet recognizes an arithmetic logic circuit programmed with DNA information and generates outputs a result of a kinetic difference between nanoparticle assembly reaction according to the storage state of the input signal.지지형 지질 이중층은 친수성 기판 위에 조립된 2차원의 지질 이중층으로 2차원 상의 유동성을 가진다. 지지형 지질 이중층에 강한 산란 신호를 지니는 플라즈모닉 나노입자를 도입하면 수천 개의 나노입자와 그 상호작용을 단일 나노입자 수준으로 실시간 관찰이 가능하다. 본 학위논문에서는 나노입자-지질 이중층 플랫폼에서의 나노입자 종류 및 개질 방법을 확장하여 복잡한 나노입자 네트워크 시스템을 구성하고, 바이오 검지, 바이오 컴퓨팅 응용을 개발한다. 1장에서는 플라즈모닉 나노입자가 도입된 지지형 지질 이중층 플랫폼을 설명한다. 1절에서 플라즈모닉 나노입자의 광학적 특성과 산란신호를 이용한 바이오센싱 응용 연구를 소개하고 2절에서는 지지형 지질 이중층 플랫폼에 나노입자의 도입 방법, 특징, 장점, 분석방법 등을 소개한다. 2장에서는 빨강, 초록, 파랑 빛을 산란하는 플라즈모닉 나노입자를 합성하고, 지지형 지질 이중층에 도입하여 동시에 일어나는 9종류의 나노입자 결합 반응을 각각 구분할 수 있는 플랫폼을 개발한다. 이를 이용하여 세포 내 중요한 단백질 번역 조절물질이자 암 바이오마커인 마이크로RNA를 동시 다중 검지한다. 3장에서는 지지형 지질 이중층 상에 도입된 나노입자를 다종의 DNA로 기능화하여 특정 DNA 분자 입력 신호 인식, 논리회로 수행, 나노입자 결합/분리 출력 신호 생성하는 바이오 컴퓨팅 플랫폼을 개발한다. 나노입자의 계면을 DNA로 디자인하여 논리 회로를 구성하는 인터페이스 프로그래밍과 나노입자의 결합/분리 반응을 연결하여 네트워크를 디자인하여 논리 회로를 집적하는 네트워크 프로그래밍을 조합하여 복잡한 논리 회로를 설계하고 수행한다. 4장에서는 지지형 지질 이중층에 도입된 나노입자 표면에 용액 상 분자 입력신호를 저장하는 정보 저장 장치를 개발하고 모든 종류의 산술논리연산을 수행할 수 있는 생분자 계산기을 개발한다. 나노입자-지질 이중층 플랫폼을 정보저장, 수행, 출력하는 매체인 하드웨어로 이용하고, DNA 분자 조합 용액을 산술논리회로 기능을 담고있는 소프트웨어로 구성한다. 바이오 컴퓨팅 칩은 DNA 정보로 프로그래밍된 산술논리회로를 인식하여 입력신호의 저장 상태에 따라 나노입자 결합 반응에 반응속도에 차이를 일으키고 결과를 출력한다.Chapter 1. Introduction: Plasmonic Nanoparticle-Tethered Supported Lipid Bilayer Platform 1 1.1. Plasmonic Nanoparticles and Their Bio-Applications 2 1.1.1. Introduction 4 1.1.2. Fundamentals of Plasmonic Nanoparticles 8 1.1.3. Plasmonic Nanoparticle Engineering for Biological Application 11 1.1.4. Plasmonic Nanoparticles for Rayleigh Scattering-Based Biosensing 16 1.1.5. References 21 1. 2. Supported Lipid Bilayer as a Dynamic Platform 24 1.2.1. Introduction 26 1.2.2. Basic Setups and Strategies 29 1.2.3. Nanoparticle-Tethering Techniques 33 1.2.4. Real-Time Imaging and Tracking of Single Nanoparticles on SLB 39 1.2.5. Observation of Interactions between Single Nanoparticles 44 1.2.6. References 50 Chapter 2. Multiplexed Biomolecular Detection Strategy 53 2.1. Introduction 55 2.2. Experimental Section 60 2.3. Results and Discussion 66 2.4. Conclusion 77 2.5. Supporting Information 79 2.6. References 83 Chapter 3. Nano-Bio Computing on Lipid Bilayer 84 3.1. Introduction 85 3.2. Experimental Section 88 3.3. Results and Discussion 98 3.4. Conclusion 120 3.5. Supporting Information 124 3.6. References 161 Chapter 4. Development of Nanoparticle Architecture for Biomolecular Arithmetic Logic Operation 163 4.1. Introduction 165 4.2. Experimental Section 167 4.3. Results and Discussion 171 4.4. Conclusion 177 4.5. References 179 Abstract in Korean 180Docto

Rational Design of DNA Sequences with Non-Orthogonal Binding Interactions

Molecular computation involving promiscuous, or non-orthogonal, binding interactions between system components is found commonly in natural biological systems, as well as some proposed human-made molecular computers. Such systems are characterized by the fact that each computational unit, such as a domain within a DNA strand, may bind to several different partners with distinct, prescribed binding strengths. Unfortunately, implementing systems of molecular computation that incorporate non-orthogonal binding is difficult, because researchers lack a robust, general-purpose method for designing molecules with this type of behavior. In this work, we describe and demonstrate a process for the rational design of DNA sequences with prescribed non-orthogonal binding behavior. This process makes use of a model that represents large sets of non-orthogonal DNA sequences using fixed-length binary strings, and estimates the differential binding affinity between pairs of sequences through the Hamming distance between their corresponding binary strings. The real-world applicability of this model is supported by simulations and some experimental data. We then select two previously described systems of molecular computation involving non-orthogonal interactions, and apply our sequence design process to implement them using DNA strand displacement. Our simulated results on these two systems demonstrate both digital and analog computation. We hope that this work motivates the development and implementation of new computational paradigms based on non-orthogonal binding

DNA Matrix Operation Based on the Mechanism of the DNAzyme Binding to Auxiliary Strands to Cleave the Substrate

Numerical computation is a focus of DNA computing, and matrix operations are among the most basic and frequently used operations in numerical computation. As an important computing tool, matrix operations are often used to deal with intensive computing tasks. During calculation, the speed and accuracy of matrix operations directly affect the performance of the entire computing system. Therefore, it is important to find a way to perform matrix calculations that can ensure the speed of calculations and improve the accuracy. This paper proposes a DNA matrix operation method based on the mechanism of the DNAzyme binding to auxiliary strands to cleave the substrate. In this mechanism, the DNAzyme binding substrate requires the connection of two auxiliary strands. Without any of the two auxiliary strands, the DNAzyme does not cleave the substrate. Based on this mechanism, the multiplication operation of two matrices is realized; the two types of auxiliary strands are used as elements of the two matrices, to participate in the operation, and then are combined with the DNAzyme to cut the substrate and output the result of the matrix operation. This research provides a new method of matrix operations and provides ideas for more complex computing systems

Probabilistic reasoning with a bayesian DNA device based on strand displacement

We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes? Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro

Design Of Dna Strand Displacement Based Circuits

DNA is the basic building block of any living organism. DNA is considered a popular candidate for future biological devices and circuits for solving genetic disorders and several other medical problems. With this objective in mind, this research aims at developing novel approaches for the design of DNA based circuits. There are many recent developments in the medical field such as the development of biological nanorobots, SMART drugs, and CRISPR-Cas9 technologies. There is a strong need for circuits that can work with these technologies and devices. DNA is considered a suitable candidate for designing such circuits because of the programmability of the DNA strands, small size, lightweight, known thermodynamics, higher parallelism, and exponentially reducing the cost of synthesizing techniques. The DNA strand displacement operation is useful in developing circuits with DNA strands. The circuit can be either a digital circuit, in which the logic high and logic low states of the DNA strand concentrations are considered as the signal, or it can be an analog circuit in which the concentration of the DNA strands itself will act as the signal. We developed novel approaches in this research for the design of digital, as well as analog circuits keeping in view of the number of DNA strands required for the circuit design. Towards this goal in the digital domain, we developed spatially localized DNA majority logic gates and an inverter logic gate that can be used with the existing seesaw based logic gates. The majority logic gates proposed in this research can considerably reduce the number of strands required in the design. The introduction of the logic inverter operation can translate the dual rail circuit architecture into a monorail architecture for the seesaw based logic circuits. It can also reduce the number of unique strands required for the design into approximately half. The reduction in the number of unique strands will consequently reduce the leakage reactions, circuit complexity, and cost associated with the DNA circuits. The real world biological inputs are analog in nature. If we can use those analog signals directly in the circuits, it can considerably reduce the resources required. Even though analog circuits are highly prone to noise, they are a perfect candidate for performing computations in the resource-limited environments, such as inside the cell. In the analog domain, we are developing a novel fuzzy inference engine using analog circuits such as the minimum gate, maximum gate, and fan-out gates. All the circuits discussed in this research were designed and tested in the Visual DSD software. The biological inputs are inherently fuzzy in nature, hence a fuzzy based system can play a vital role in future decision-making circuits. We hope that our research will be the first step towards realizing these larger goals. The ultimate aim of our research is to develop novel approaches for the design of circuits which can be used with the future biological devices to tackle many medical problems such as genetic disorders

Investigating the dynamics of surface-immobilized DNA nanomachines

Surface-immobilization of molecules can have a profound influence on their structure, function and dynamics. Toehold-mediated strand displacement is often used in solution to drive synthetic nanomachines made from DNA, but the effects of surface-immobilization on the mechanism and kinetics of this reaction have not yet been fully elucidated. Here we show that the kinetics of strand displacement in surface-immobilized nanomachines are significantly different to those of the solution phase reaction, and we attribute this to the effects of intermolecular interactions within the DNA layer. We demonstrate that the dynamics of strand displacement can be manipulated by changing strand length, concentration and G/C content. By inserting mismatched bases it is also possible to tune the rates of the constituent displacement processes (toehold-binding and branch migration) independently, and information can be encoded in the time-dependence of the overall reaction. Our findings will facilitate the rational design of surface-immobilized dynamic DNA nanomachines, including computing devices and track-based motors

Pathways to cellular supremacy in biocomputing

Synthetic biology uses living cells as the substrate for performing human-defined computations. Many current implementations of cellular computing are based on the “genetic circuit” metaphor, an approximation of the operation of silicon-based computers. Although this conceptual mapping has been relatively successful, we argue that it fundamentally limits the types of computation that may be engineered inside the cell, and fails to exploit the rich and diverse functionality available in natural living systems. We propose the notion of “cellular supremacy” to focus attention on domains in which biocomputing might offer superior performance over traditional computers. We consider potential pathways toward cellular supremacy, and suggest application areas in which it may be found.A.G.-M. was supported by the SynBio3D project of the UK Engineering and Physical Sciences Research Council (EP/R019002/1) and the European CSA on biological standardization BIOROBOOST (EU grant number 820699). T.E.G. was supported by a Royal Society University Research Fellowship (grant UF160357) and BrisSynBio, a BBSRC/ EPSRC Synthetic Biology Research Centre (grant BB/L01386X/1). P.Z. was supported by the EPSRC Portabolomics project (grant EP/N031962/1). P.C. was supported by SynBioChem, a BBSRC/EPSRC Centre for Synthetic Biology of Fine and Specialty Chemicals (grant BB/M017702/1) and the ShikiFactory100 project of the European Union’s Horizon 2020 research and innovation programme under grant agreement 814408

Probabilistic reasoning with an enzyme-driven DNA device

We present a biomolecular probabilistic model driven by the action of a DNA toolbox made of a set of DNA templates and enzymes that is able to perform Bayesian inference. The model will take single-stranded DNA as input data, representing the presence or absence of a specific molecular signal (the evidence). The program logic uses different DNA templates and their relative concentration ratios to encode the prior probability of a disease and the conditional probability of a signal given the disease. When the input and program molecules interact, an enzyme-driven cascade of reactions (DNA polymerase extension, nicking and degradation) is triggered, producing a different pair of single-stranded DNA species. Once the system reaches equilibrium, the ratio between the output species will represent the application of Bayes? law: the conditional probability of the disease given the signal. In other words, a qualitative diagnosis plus a quantitative degree of belief in that diagno- sis. Thanks to the inherent amplification capability of this DNA toolbox, the resulting system will be able to to scale up (with longer cascades and thus more input signals) a Bayesian biosensor that we designed previously