Resetting asynchronous QDI systems

Quasi Delay-Insensitive (QDI) systems must be reset into a valid initial state before normal operation can start. Otherwise, deadlock may occur due to wrong handshake communication between processes. This thesis first reviews the traditional Global Reset Schemes (GRS). It then proposes a new Wave Reset Schemes (WRS). By utilizing the third possible value of QDI data codes - reset value, WRS propagates the data with reset value and triggers Local Reset (LR) sequentially. The global reset network for GRS can be removed and all reset signals are generated locally for each process. Circuits templates as well as some special blocks are modified to accommodate the reset value in WRS. An algorithm is proposed to choose the proper Local Reset Input (LRI) in order to shorten reset time. WRS is then applied to an iterative multiplier. The multiplier is proved working under different operating conditions.

Beyond Watson and Crick : programming the self-assembly and reconfiguration of DNA nanostructures based on stacking interactions

Life is the result of the execution of molecular programs: like how an embryo is fated to become a human or a whale, or how a person’s appearance is inherited from their parents, many biological phenomena are governed by genetic programs written in DNA molecules. At the core of such programs is the highly reliable base pairing interaction between nucleic acids. DNA nanotechnology exploits the programming power of DNA to build artificial nanostructures, molecular computers, and nanomachines. In particular, DNA origami—which is a simple yet versatile technique that allows one to create various nanoscale shapes and patterns—is at the heart of the technology. In this thesis, I describe the development of programmable self-assembly and reconfiguration of DNA origami nanostructures based on a unique strategy: rather than relying on Watson-Crick base pairing, we developed programmable bonds via the geometric arrangement of stacking interactions, which we termed stacking bonds. We further demonstrated that such bonds can be dynamically reconfigurable.

The first part of this thesis describes the design and implementation of stacking bonds. Our work addresses the fundamental question of whether one can create diverse bond types out of a single kind of attractive interaction—a question first posed implicitly by Francis Crick while seeking a deeper understanding of the origin of life and primitive genetic code. For the creation of multiple specific bonds, we used two different approaches: binary coding and shape coding of geometric arrangement of stacking interaction units, which are called blunt ends. To construct a bond space for each approach, we performed a systematic search using a computer algorithm. We used orthogonal bonds to experimentally implement the connection of five distinct DNA origami nanostructures. We also programmed the bonds to control cis/trans configuration between asymmetric nanostructures.

The second part of this thesis describes the large-scale self-assembly of DNA origami into two-dimensional checkerboard-pattern crystals via surface diffusion. We developed a protocol where the diffusion of DNA origami occurs on a substrate and is dynamically controlled by changing the cationic condition of the system. We used stacking interactions to mediate connections between the origami, because of their potential for reconfiguring during the assembly process. Assembling DNA nanostructures directly on substrate surfaces can benefit nano/microfabrication processes by eliminating a pattern transfer step. At the same time, the use of DNA origami allows high complexity and unique addressability with six-nanometer resolution within each structural unit.

The third part of this thesis describes the use of stacking bonds as dynamically breakable bonds. To break the bonds, we used biological machinery called the ParMRC system extracted from bacteria. The system ensures that, when a cell divides, each daughter cell gets one copy of the cell’s DNA by actively pushing each copy to the opposite poles of the cell. We demonstrate dynamically expandable nanostructures, which makes stacking bonds a promising candidate for reconfigurable connectors for nanoscale machine parts.

Distributed optimization in power networks and general multi-agent systems

The dissertation studies the general area of complex networked systems that consist of interconnected and active heterogeneous components and usually operate in uncertain environments and with incomplete information. Problems associated with those systems are typically large-scale and computationally intractable, yet they are also very well-structured and have features that can be exploited by appropriate modeling and computational methods. The goal of this thesis is to develop foundational theories and tools to exploit those structures that can lead to computationally-efficient and distributed solutions, and apply them to improve systems operations and architecture.

Specifically, the thesis focuses on two concrete areas. The first one is to design distributed rules to manage distributed energy resources in the power network. The power network is undergoing a fundamental transformation. The future smart grid, especially on the distribution system, will be a large-scale network of distributed energy resources (DERs), each introducing random and rapid fluctuations in power supply, demand, voltage and frequency. These DERs provide a tremendous opportunity for sustainability, efficiency, and power reliability. However, there are daunting technical challenges in managing these DERs and optimizing their operation. The focus of this dissertation is to develop scalable, distributed, and real-time control and optimization to achieve system-wide efficiency, reliability, and robustness for the future power grid. In particular, we will present how to explore the power network structure to design efficient and distributed market and algorithms for the energy management. We will also show how to connect the algorithms with physical dynamics and existing control mechanisms for real-time control in power networks.

The second focus is to develop distributed optimization rules for general multi-agent engineering systems. A central goal in multiagent systems is to design local control laws for the individual agents to ensure that the emergent global behavior is desirable with respect to the given system level objective. Ideally, a system designer seeks to satisfy this goal while conditioning each agent’s control on the least amount of information possible. Our work focused on achieving this goal using the framework of game theory. In particular, we derived a systematic methodology for designing local agent objective functions that guarantees (i) an equivalence between the resulting game-theoretic equilibria and the system level design objective and (ii) that the resulting game possesses an inherent structure that can be exploited for distributed learning, e.g., potential games. The control design can then be completed by applying any distributed learning algorithm that guarantees convergence to the game-theoretic equilibrium. One main advantage of this game theoretic approach is that it provides a hierarchical decomposition between the decomposition of the systemic objective (game design) and the specific local decision rules (distributed learning algorithms). This decomposition provides the system designer with tremendous flexibility to meet the design objectives and constraints inherent in a broad class of multiagent systems. Furthermore, in many settings the resulting controllers will be inherently robust to a host of uncertainties including asynchronous clock rates, delays in information, and component failures.

Randomness-efficient curve sampling

Curve samplers are sampling algorithms that proceed by viewing the domain as a vector space over a finite field, and randomly picking a low-degree curve in it as the sample. Curve samplers exhibit a nice property besides the sampling property: the restriction of low-degree polynomials over the domain to the sampled curve is still low-degree. This property is often used in combination with the sampling property and has found many applications, including PCP constructions, local decoding of codes, and algebraic PRG constructions.

The randomness complexity of curve samplers is a crucial parameter for its applications. It is known that (non-explicit) curve samplers using O(log N + log(1/δ)) random bits exist, where N is the domain size and δ is the confidence error. The question of explicitly constructing randomness-efficient curve samplers was first raised in [TU06] where they obtained curve samplers with near-optimal randomness complexity.

In this thesis, we present an explicit construction of low-degree curve samplers with optimal randomness complexity (up to a constant factor) that sample curves of degree (m log_q(1/δ))^O(1) in F_q^m. Our construction is a delicate combination of several components, including extractor machinery, limited independence, iterated sampling, and list-recoverable codes.

Temporal and spacial control of RNA stability in the early embryo of Drosophila melanogaster

Early embryogenesis in metazoa is controlled by maternally synthesized products. Among these products, the mature egg is loaded with transcripts representing approximately two thirds of the genome. A subset of this maternal RNA pool is degraded prior to the transition to zygotic control of development. This transfer of control of development from maternal to zygotic products is referred to as the midblastula transition (or MBT). It is believed that the degradation of maternal transcripts is required to terminate maternal control of development and to allow zygotic control of development to begin. Until now this process of maternal transcript degradation and the subsequent timing of the MBT has been poorly understood. I have demonstrated that in the early embryo there are two independent RNA degradation pathways, either of which is sufficient for transcript elimination. However, only the concerted action of both pathways leads to elimination of transcripts with the correct timing, at the MBT. The first pathway is maternally encoded, is triggered by egg activation, and is targeted to specific classes of mRNAs through cis-acting elements in the 3' untranslated region (UTR}. The second pathway is activated 2 hr after fertilization and functions together with the maternal pathway to ensure that transcripts are degraded by the MBT. In addition, some transcripts fail to degrade at select subcellular locations adding an element of spatial control to RNA degradation. The spatial control of RNA degradation is achieved by protecting, or masking, transcripts from the degradation machinery. The RNA degradation and protection events are regulated by distinct cis-elements in the 3' untranslated region (UTR). These results provide the first systematic dissection of this highly conserved process in development and demonstrate that RNA degradation is a novel mechanism used for both temporal and spatial control of development.

Characterization of the human SCF ubiquitin ligases - structure, function, and regulation

The SCF ubiquitin ligase complex of budding yeast triggers DNA replication by cata lyzi ng ubiquitination of the S phase CDK inhibitor SIC1. SCF is composed of several evolutionarily conserved proteins, including ySKP1, CDC53 (Cullin), and the F-box protein CDC4. We isolated hSKP1 in a two-hybrid screen with hCUL1, the human homologue of CDC53. We showed that hCUL1 associates with hSKP1 in vivo and directly interacts with hSKP1 and the human F-box protein SKP2 in vitro, forming an SCF-Iike particle. Moreover, hCUL1 complements the growth defect of yeast CDC53^(ts) mutants, associates with ubiquitination-promoting activity in human cell extracts, and can assemble into functional, chimeric ubiquitin ligase complexes with yeast SCF components. These data demonstrated that hCUL1 functions as part of an SCF ubiquitin ligase complex in human cells. However, purified human SCF complexes consisting of CUL1, SKP1, and SKP2 are inactive in vitro, suggesting that additional factors are required.

Subsequently, mammalian SCF ubiquitin ligases were shown to regulate various physiological processes by targeting important cellular regulators, like lĸBα, β-catenin, and p27, for ubiquitin-dependent proteolysis by the 26S proteasome. Little, however, is known about the regulation of various SCF complexes. By using sequential immunoaffinity purification and mass spectrometry, we identified proteins that interact with human SCF components SKP2 and CUL1 in vivo. Among them we identified two additional SCF subunits: HRT1, present in all SCF complexes, and CKS1, that binds to SKP2 and is likely to be a subunit of SCF5^(SKP2) complexes. Subsequent work by others demonstrated that these proteins are essential for SCF activity. We also discovered that COP9 Signalosome (CSN), previously described in plants as a suppressor of photomorphogenesis, associates with CUL1 and other SCF subunits in vivo. This interaction is evolutionarily conserved and is also observed with other Cullins, suggesting that all Cullin based ubiquitin ligases are regulated by CSN. CSN regulates Cullin Neddylation presumably through CSNS/JAB1, a stochiometric Signalosome subunit and a putative deneddylating enzyme. This work sheds light onto an intricate connection that exists between signal transduction pathways and protein degradation machinery inside the cell and sets stage for gaining further insights into regulation of protein degradation.

Characterizing the regulation of mitochondrial nucleoids

Mitochondria contain a 16.6 kb circular genome encoding 13 proteins as well as mitochondrial tRNAs and rRNAs. Copies of the genome are organized into nucleoids containing both DNA and proteins, including the machinery required for mtDNA replication and transcription. Although mtDNA integrity is essential for cellular and organismal viability, regulation of proliferation of the mitochondrial genome is poorly understood. To elucidate the mechanisms behind this, we chose to study the interplay between mtDNA copy number and the proteins involved in mitochondrial fusion, another required function in cells. Strikingly, we found that mouse embryonic fibroblasts lacking fusion also had a mtDNA copy number deficit. To understand this phenomenon further, we analyzed the binding of mitochondrial transcription factor A, whose role in transcription, replication, and packaging of the genome is well-established and crucial for cellular maintenance. Using ChIP-seq, we were able to detect largely uniform, non-specific binding across the genome, with no occupancy in the known specific binding sites in the regulatory region. We did detect a single binding site directly upstream of a known origin of replication, suggesting that TFAM may play a direct role in replication. Finally, although TFAM has been previously shown to localize to the nuclear genome, we found no evidence for such binding sites in our system.

To further understand the regulation of mtDNA by other proteins, we analyzed publicly available ChIP-seq datasets from ENCODE, modENCODE, and mouseENCODE for evidence of nuclear transcription factor binding to the mitochondrial genome. We identified eight human transcription factors and three mouse transcription factors that demonstrated binding events with the classical strand asymmetrical morphology of classical binding sites. ChIP-seq is a powerful tool for understanding the interactions between proteins and the mitochondrial genome, and future studies promise to further the understanding of how mtDNA is regulated within the nucleoid.

Mechanisms of substrate selection by the signal recognition particle

The signal recognition particle (SRP) targets membrane and secretory proteins to their correct cellular destination with remarkably high fidelity. Previous studies have shown that multiple checkpoints exist within this targeting pathway that allows ‘correct cargo’ to be quickly and efficiently targeted and for ‘incorrect cargo’ to be promptly rejected. In this work, we delved further into understanding the mechanisms of how substrates are selected or discarded by the SRP. First, we discovered the role of the SRP fingerloop and how it activates the SRP and SRP receptor (SR) GTPases to target and unload cargo in response to signal sequence binding. Second, we learned how an ‘avoidance signal’ found in the bacterial autotransporter, EspP, allows this protein to escape the SRP pathway by causing the SRP and SR to form a ‘distorted’ complex that is inefficient in delivering the cargo to the membrane. Lastly, we determined how Trigger Factor, a co-translational chaperone, helps SRP discriminate against ‘incorrect cargo’ at three distinct stages: SRP binding to RNC; targeting of RNC to the membrane via SRP-FtsY assembly; and stronger antagonism of SRP targeting of ribosomes bearing nascent polypeptides that exceed a critical length. Overall, results delineate the rich underlying mechanisms by which SRP recognizes its substrates, which in turn activates the targeting pathway and provides a conceptual foundation to understand how timely and accurate selection of substrates is achieved by this protein targeting machinery.

Quantitative, Time-Resolved Proteomic Analysis Using Bio-Orthogonal Non-Canonical Amino Acid Tagging

Bio-orthogonal non-canonical amino acid tagging (BONCAT) is an analytical method that allows the selective analysis of the subset of newly synthesized cellular proteins produced in response to a biological stimulus. In BONCAT, cells are treated with the non-canonical amino acid L-azidohomoalanine (Aha), which is utilized in protein synthesis in place of methionine by wild-type translational machinery. Nascent, Aha-labeled proteins are selectively ligated to affinity tags for enrichment and subsequently identified via mass spectrometry. The work presented in this thesis exhibits advancements in and applications of the BONCAT technology that establishes it as an effective tool for analyzing proteome dynamics with time-resolved precision.

Chapter 1 introduces the BONCAT method and serves as an outline for the thesis as a whole. I discuss motivations behind the methodological advancements in Chapter 2 and the biological applications in Chapters 2 and 3.

Chapter 2 presents methodological developments that make BONCAT a proteomic tool capable of, in addition to identifying newly synthesized proteins, accurately quantifying rates of protein synthesis. I demonstrate that this quantitative BONCAT approach can measure proteome-wide patterns of protein synthesis at time scales inaccessible to alternative techniques.

In Chapter 3, I use BONCAT to study the biological function of the small RNA regulator CyaR in Escherichia coli. I correctly identify previously known CyaR targets, and validate several new CyaR targets, expanding the functional roles of the sRNA regulator.

In Chapter 4, I use BONCAT to measure the proteomic profile of the quorum sensing bacterium Vibrio harveyi during the time-dependent transition from individual- to group-behaviors. My analysis reveals new quorum-sensing-regulated proteins with diverse functions, including transcription factors, chemotaxis proteins, transport proteins, and proteins involved in iron homeostasis.

Overall, this work describes how to use BONCAT to perform quantitative, time-resolved proteomic analysis and demonstrates that these measurements can be used to study a broad range of biological processes.

Biological Activity of Rhodium Metalloinsertors and the Design of Bifunctional Conjugates

The Barton laboratory has established that octahedral rhodium complexes bearing the sterically expansive 5,6-chrysene diimine ligand can target thermodynamically destabilized sites, such as base pair mismatches, in DNA with high affinity and selectivity. These complexes approach DNA from the minor groove, ejecting the mismatched base pairs from the duplex in a binding mode termed metalloinsertion. In recent years, we have shown that these metalloinsertor complexes also exhibit cytotoxicity preferentially in cancer cells that are deficient in the mismatch repair (MMR) machinery.

Here, we establish that a sensitive structure-activity relationship exists for rhodium metalloinsertors. We studied the relationship between the chemical structures of metalloinsertors and their effect on biological activity for ten complexes with similar DNA binding affinities, but wide variation in their lipophilicity. Drastic differences were observed in the selectivities of the complexes for MMR-deficient cells. Compounds with hydrophilic ligands were highly selective, exhibiting preferential cytotoxicity in MMR-deficient cells at low concentrations and short incubation periods, whereas complexes with lipophilic ligands displayed poor cell-selectivity. It was discovered that all of the complexes localized to the nucleus in concentrations sufficient for mismatch binding; however, highly lipophilic complexes also exhibited high mitochondrial uptake. Significantly, these results support the notion that mitochondrial DNA is not the desired target for our metalloinsertor complexes; instead, selectivity stems from targeting mismatches in genomic DNA.

We have also explored the potential for metalloinsertors to be developed into more complex structures with multiple functionalities that could either enhance their overall potency or impart mismatch selectivity onto other therapeutic cargo. We have constructed a family of bifunctional metalloinsertor conjugates incorporating cis-platinum, each unique in its chemical structure, DNA binding interactions, and biological activity. The study of these complexes in MMR-deficient cells has established that the cell-selective biological activity of rhodium metalloinsertors proceeds through a critical cellular pathway leading to necrosis.

We further explored the underlying mechanisms surrounding the biological response to mismatch recognition by metalloinsertors in the genome. Immunofluorescence assays of MMR-deficient and MMR-proficient cells revealed that a critical biomarker for DNA damage, phosphorylation of histone H2AX (γH2AX) rapidly accumulates in response to metalloinsertor treatment, signifying the induction of double strand breaks in the genome. Significantly, we have discovered that our metalloinsertor complexes selectively inhibit transcription in MMR-deficient cells, which may be a crucial checkpoint in the eventual breakdown of the cell via necrosis. Additionally, preliminary in vivo studies have revealed the capability of these compounds to traverse the complex environments of multicellular organisms and accumulate in MMR-deficient tumors. Our ever-increasing understanding of metalloinsertors, as well as the development of new generations of complexes both monofunctional and bifunctional, enables their continued progress into the clinic as promising new chemotherapeutic agents.