Synthetic molecular machines for active self-assembly : prototype algorithms, designs, and experimental study

Computer science and electrical engineering have been the great success story of the twentieth century. The neat modularity and mapping of a language onto circuits has led to robots on Mars, desktop computers and smartphones. But these devices are not yet able to do some of the things that life takes for granted: repair a scratch, reproduce, regenerate, or grow exponentially fast–all while remaining functional.

This thesis explores and develops algorithms, molecular implementations, and theoretical proofs in the context of “active self-assembly” of molecular systems. The long-term vision of active self-assembly is the theoretical and physical implementation of materials that are composed of reconfigurable units with the programmability and adaptability of biology’s numerous molecular machines. En route to this goal, we must first find a way to overcome the memory limitations of molecular systems, and to discover the limits of complexity that can be achieved with individual molecules.

One of the main thrusts in molecular programming is to use computer science as a tool for figuring out what can be achieved. While molecular systems that are Turing-complete have been demonstrated [Winfree, 1996], these systems still cannot achieve some of the feats biology has achieved.

One might think that because a system is Turing-complete, capable of computing “anything,” that it can do any arbitrary task. But while it can simulate any digital computational problem, there are many behaviors that are not “computations” in a classical sense, and cannot be directly implemented. Examples include exponential growth and molecular motion relative to a surface.

Passive self-assembly systems cannot implement these behaviors because (a) molecular motion relative to a surface requires a source of fuel that is external to the system, and (b) passive systems are too slow to assemble exponentially-fast-growing structures. We call these behaviors “energetically incomplete” programmable behaviors. This class of behaviors includes any behavior where a passive physical system simply does not have enough physical energy to perform the specified tasks in the requisite amount of time.

As we will demonstrate and prove, a sufficiently expressive implementation of an “active” molecular self-assembly approach can achieve these behaviors. Using an external source of fuel solves part of the the problem, so the system is not “energetically incomplete.” But the programmable system also needs to have sufficient expressive power to achieve the specified behaviors. Perhaps surprisingly, some of these systems do not even require Turing completeness to be sufficiently expressive.

Building on a large variety of work by other scientists in the fields of DNA nanotechnology, chemistry and reconfigurable robotics, this thesis introduces several research contributions in the context of active self-assembly.

We show that simple primitives such as insertion and deletion are able to generate complex and interesting results such as the growth of a linear polymer in logarithmic time and the ability of a linear polymer to treadmill. To this end we developed a formal model for active-self assembly that is directly implementable with DNA molecules. We show that this model is computationally equivalent to a machine capable of producing strings that are stronger than regular languages and, at most, as strong as context-free grammars. This is a great advance in the theory of active self- assembly as prior models were either entirely theoretical or only implementable in the context of macro-scale robotics.

We developed a chain reaction method for the autonomous exponential growth of a linear DNA polymer. Our method is based on the insertion of molecules into the assembly, which generates two new insertion sites for every initial one employed. The building of a line in logarithmic time is a first step toward building a shape in logarithmic time. We demonstrate the first construction of a synthetic linear polymer that grows exponentially fast via insertion. We show that monomer molecules are converted into the polymer in logarithmic time via spectrofluorimetry and gel electrophoresis experiments. We also demonstrate the division of these polymers via the addition of a single DNA complex that competes with the insertion mechanism. This shows the growth of a population of polymers in logarithmic time. We characterize the DNA insertion mechanism that we utilize in Chapter 4. We experimentally demonstrate that we can control the kinetics of this re- action over at least seven orders of magnitude, by programming the sequences of DNA that initiate the reaction.

In addition, we review co-authored work on programming molecular robots using prescriptive landscapes of DNA origami; this was the first microscopic demonstration of programming a molec- ular robot to walk on a 2-dimensional surface. We developed a snapshot method for imaging these random walking molecular robots and a CAPTCHA-like analysis method for difficult-to-interpret imaging data.

The effect of the incident relative phase on the four-wave mixing field and the electromagnetically induced transparency

In a A-type system employing a two-photon pump field, a four-wave mixing field can be generated simultaneously and, hence, a closed-loop system forms. We study theoretically the effect of the relative phase between the two incident fields on the generated four-wave mixing field and the electromagnetically induced transparency. It is found that the phase of the generated four-wave mixing field is the sum of the incident relative phase and a fixed phase that is irrelative to the incident relative phase. Hence, the total phase of the closed-loop system is independent of the incident relative phase. As a result, the incident relative phase has no effect on the electromagnetically induced transparency, which is different from the case of a A-type loop system closed by a third incident field. (c) 2005 Pleiades Publishing, Inc.

Proteomic analysis of the Cdc48/Ubx network identifies a role for Ubx2 in the regulation of lipid biosynthesis

Cdc48/p97 is an essential, highly abundant hexameric member of the AAA (ATPase associated with various cellular activities) family. It has been linked to a variety of processes throughout the cell but it is best known for its role in the ubiquitin proteasome pathway. In this system it is believed that Cdc48 behaves as a segregase, transducing the chemical energy of ATP hydrolysis into mechanical force to separate ubiquitin-conjugated proteins from their tightly-bound partners.

Current models posit that Cdc48 is linked to its substrates through a variety of adaptor proteins, including a family of seven proteins (13 in humans) that contain a Cdc48-binding UBX domain. As such, due to the complexity of the network of adaptor proteins for which it serves as the hub, Cdc48/p97 has the potential to exert a profound influence on the ubiquitin proteasome pathway. However, the number of known substrates of Cdc48/p97 remains relatively small, and smaller still is the number of substrates that have been linked to a specific UBX domain protein. As such, the goal of this dissertation research has been to discover new substrates and better understand the functions of the Cdc48 network. With this objective in mind, we established a proteomic screen to assemble a catalog of candidate substrate/targets of the Ubx adaptor system.

Here we describe the implementation and optimization of a cutting-edge quantitative mass spectrometry method to measure relative changes in the Saccharomyces cerevisiae proteome. Utilizing this technology, and in order to better understand the breadth of function of Cdc48 and its adaptors, we then performed a global screen to identify accumulating ubiquitin conjugates in cdc48-3 and ubxΔ mutants. In this screen different ubx mutants exhibited reproducible patterns of conjugate accumulation that differed greatly from each other, pointing to various unexpected functional specializations of the individual Ubx proteins.

As validation of our mass spectrometry findings, we then examined in detail the endoplasmic-reticulum bound transcription factor Spt23, which we identified as a putative Ubx2 substrate. In these studies ubx2Δ cells were deficient in processing of Spt23 to its active p90 form, and in localizing p90 to the nucleus. Additionally, consistent with reduced processing of Spt23, ubx2Δ cells demonstrated a defect in expression of their target gene OLE1, a fatty acid desaturase. Overall, this work demonstrates the power of proteomics as a tool to identify new targets of various pathways and reveals Ubx2 as a key regulator lipid membrane biosynthesis.

Directed evolution of terpene synthases for non-natural substrates

Terpenes represent about half of known natural products, with terpene synthases catalyzing reactions to increase the complexity of substrates and generate cyclizations of the linear diphosphate substrates, therefore forming rings and stereocenters. With their diverse functionality, terpene synthases may be highly evolvable, with the ability to accept a wide range of non-natural compounds and with high product selectivity. Our hypothesis is that directed evolution of terpene synthases can be used to increase selectivity of the synthase on a specific substrate. In the first part of the work presented herein, three natural terpene synthases, Cop2, BcBOT2, and SSCG_02150, were tested for activity against the natural substrate and a non-natural substrate, called Surrogate 1, and the relative activities on both the natural and non-natural substrates were compared. In the second part of this work, a terpene synthase variant of BcBOT2 that has been evolved for thermostability, was used for directed evolution for increased activity and selectivity on the non-natural substrate referred to as Surrogate 2. Mutations for this evolution were introduced using random mutagenesis, with error prone polymerase chain reactions, and using site-specific saturation mutagenesis, in which an NNK library is designed with a specific active site amino acid targeted for mutation. The mutant enzymes were then screened and selected for enhancement of the desired functionality. Two neutral mutants, 19B7 W367F and 19B7 W118Q, were found to maintain activity on Surrogate 2, as measured by the screen.

Relative mirror symmetry and ramifications of a formula for Gromov-Witten invariants

For a toric Del Pezzo surface S, a new instance of mirror symmetry, said relative, is introduced and developed. On the A-model, this relative mirror symmetry conjecture concerns genus 0 relative Gromov-Witten of maximal tangency of S. These correspond, on the B-model, to relative periods of the mirror to S. Furthermore, for S not necessarily toric, two conjectures for BPS state counts are related. It is proven that the integrality of BPS state counts of the total space of the canonical bundle on S implies the integrality for the relative BPS state counts of S. Finally, a prediction of homological mirror symmetry for the open complement is explored. The B-model prediction is calculated in all cases and matches the known A-model computation for the projective plane.

Enhancement and broadening of extreme-ultraviolet supercontinuum in a relative phase controlled two-color laser field

We experimentally demonstrate the generation of an extreme-ultraviolet (XUV) supercontinuum in argon with a two-color laser field consisting of an intense 7 fs pulse at 800 nm and a relatively weak 37 fs pulse at 400 nm. By controlling the relative time delay between the two laser pulses, we observe enhanced high-order harmonic generation as well as spectral broadening of the supercontinuum. A method to produce isolated attosecond pulses with variable width and intensity is proposed. (C) 2008 Optical Society of America.

Studies of ambient organic and inorganic aerosol in Southern California

The negative impacts of ambient aerosol particles, or particulate matter (PM), on human health and climate are well recognized. However, owing to the complexity of aerosol particle formation and chemical evolution, emissions control strategies remain difficult to develop in a cost effective manner. In this work, three studies are presented to address several key issues currently stymieing California's efforts to continue improving its air quality.

Gas-phase organic mass (GPOM) and CO emission factors are used in conjunction with measured enhancements in oxygenated organic aerosol (OOA) relative to CO to quantify the significant lack of closure between expected and observed organic aerosol concentrations attributable to fossil-fuel emissions. Two possible conclusions emerge from the analysis to yield consistency with the ambient organic data: (1) vehicular emissions are not a dominant source of anthropogenic fossil SOA in the Los Angeles Basin, or (2) the ambient SOA mass yields used to determine the SOA formation potential of vehicular emissions are substantially higher than those derived from laboratory chamber studies. Additional laboratory chamber studies confirm that, owing to vapor-phase wall loss, the SOA mass yields currently used in virtually all 3D chemical transport models are biased low by as much as a factor of 4. Furthermore, predictions from the Statistical Oxidation Model suggest that this bias could be as high as a factor of 8 if the influence of the chamber walls could be removed entirely.

Once vapor-phase wall loss has been accounted for in a new suite of laboratory chamber experiments, the SOA parameterizations within atmospheric chemical transport models should also be updated. To address the numerical challenges of implementing the next generation of SOA models in atmospheric chemical transport models, a novel mathematical framework, termed the Moment Method, is designed and presented. Assessment of the Moment Method strengths and weaknesses provide valuable insight that can guide future development of SOA modules for atmospheric CTMs.

Finally, regional inorganic aerosol formation and evolution is investigated via detailed comparison of predictions from the Community Multiscale Air Quality (CMAQ version 4.7.1) model against a suite of airborne and ground-based meteorological measurements, gas- and aerosol-phase inorganic measurements, and black carbon (BC) measurements over Southern California during the CalNex field campaign in May/June 2010. Results suggests that continuing to target sulfur emissions with the hopes of reducing ambient PM concentrations may not the most effective strategy for Southern California. Instead, targeting dairy emissions is likely to be an effective strategy for substantially reducing ammonium nitrate concentrations in the eastern part of the Los Angeles Basin.

Effects of relative phase in an open ladder system without incoherent pumping

We studied effects of the relative phase between the probe and driving fields on the absorption and dispersion properties in an open three-level ladder system with spontaneously generated coherence but without incoherent pumping. It is shown that by the phase controlling, switching from absorption to lasing without inversion (LWI) and enhancing remarkablely LWI gain can be realized; large index of refraction with zero absorption and the electromagnetically induced transparency can be obtained. We also find that varying the atomic injection and exit rates has a considerable influence on the phase dependent-absorption property of the probe field, existent of the atomic injection and exit rates gives the necessary condition of the realization of LWI, getting LWI is impossible in the corresponding closed system without incoherent pumping. We studied effects of the relative phase between the probe and driving fields on the absorption and dispersion properties in an open three-level ladder system with spontaneously generated coherence but without incoherent pumping. It is shown that by the phase controlling, switching from absorption to lasing without inversion (LWI) and enhancing remarkablely LWI gain can be realized; large index of refraction with zero absorption and the electromagnetically induced transparency can be obtained. We also find that varying the atomic injection and exit rates has a considerable influence on the phase dependent-absorption property of the probe field, existent of the atomic injection and exit rates gives the necessary condition of the realization of LWI, getting LWI is impossible in the corresponding closed system without incoherent pumping.

Efficient methods for empirical tests of behavioral economics theories in laboratory and field experiments

In the quest for a descriptive theory of decision-making, the rational actor model in economics imposes rather unrealistic expectations and abilities on human decision makers. The further we move from idealized scenarios, such as perfectly competitive markets, and ambitiously extend the reach of the theory to describe everyday decision making situations, the less sense these assumptions make. Behavioural economics has instead proposed models based on assumptions that are more psychologically realistic, with the aim of gaining more precision and descriptive power. Increased psychological realism, however, comes at the cost of a greater number of parameters and model complexity. Now there are a plethora of models, based on different assumptions, applicable in differing contextual settings, and selecting the right model to use tends to be an ad-hoc process. In this thesis, we develop optimal experimental design methods and evaluate different behavioral theories against evidence from lab and field experiments.

We look at evidence from controlled laboratory experiments. Subjects are presented with choices between monetary gambles or lotteries. Different decision-making theories evaluate the choices differently and would make distinct predictions about the subjects' choices. Theories whose predictions are inconsistent with the actual choices can be systematically eliminated. Behavioural theories can have multiple parameters requiring complex experimental designs with a very large number of possible choice tests. This imposes computational and economic constraints on using classical experimental design methods. We develop a methodology of adaptive tests: Bayesian Rapid Optimal Adaptive Designs (BROAD) that sequentially chooses the "most informative" test at each stage, and based on the response updates its posterior beliefs over the theories, which informs the next most informative test to run. BROAD utilizes the Equivalent Class Edge Cutting (EC²) criteria to select tests. We prove that the EC² criteria is adaptively submodular, which allows us to prove theoretical guarantees against the Bayes-optimal testing sequence even in the presence of noisy responses. In simulated ground-truth experiments, we find that the EC² criteria recovers the true hypotheses with significantly fewer tests than more widely used criteria such as Information Gain and Generalized Binary Search. We show, theoretically as well as experimentally, that surprisingly these popular criteria can perform poorly in the presence of noise, or subject errors. Furthermore, we use the adaptive submodular property of EC² to implement an accelerated greedy version of BROAD which leads to orders of magnitude speedup over other methods.

We use BROAD to perform two experiments. First, we compare the main classes of theories for decision-making under risk, namely: expected value, prospect theory, constant relative risk aversion (CRRA) and moments models. Subjects are given an initial endowment, and sequentially presented choices between two lotteries, with the possibility of losses. The lotteries are selected using BROAD, and 57 subjects from Caltech and UCLA are incentivized by randomly realizing one of the lotteries chosen. Aggregate posterior probabilities over the theories show limited evidence in favour of CRRA and moments' models. Classifying the subjects into types showed that most subjects are described by prospect theory, followed by expected value. Adaptive experimental design raises the possibility that subjects could engage in strategic manipulation, i.e. subjects could mask their true preferences and choose differently in order to obtain more favourable tests in later rounds thereby increasing their payoffs. We pay close attention to this problem; strategic manipulation is ruled out since it is infeasible in practice, and also since we do not find any signatures of it in our data.

In the second experiment, we compare the main theories of time preference: exponential discounting, hyperbolic discounting, "present bias" models: quasi-hyperbolic (α, β) discounting and fixed cost discounting, and generalized-hyperbolic discounting. 40 subjects from UCLA were given choices between 2 options: a smaller but more immediate payoff versus a larger but later payoff. We found very limited evidence for present bias models and hyperbolic discounting, and most subjects were classified as generalized hyperbolic discounting types, followed by exponential discounting.

In these models the passage of time is linear. We instead consider a psychological model where the perception of time is subjective. We prove that when the biological (subjective) time is positively dependent, it gives rise to hyperbolic discounting and temporal choice inconsistency.

We also test the predictions of behavioral theories in the "wild". We pay attention to prospect theory, which emerged as the dominant theory in our lab experiments of risky choice. Loss aversion and reference dependence predicts that consumers will behave in a uniquely distinct way than the standard rational model predicts. Specifically, loss aversion predicts that when an item is being offered at a discount, the demand for it will be greater than that explained by its price elasticity. Even more importantly, when the item is no longer discounted, demand for its close substitute would increase excessively. We tested this prediction using a discrete choice model with loss-averse utility function on data from a large eCommerce retailer. Not only did we identify loss aversion, but we also found that the effect decreased with consumers' experience. We outline the policy implications that consumer loss aversion entails, and strategies for competitive pricing.

In future work, BROAD can be widely applicable for testing different behavioural models, e.g. in social preference and game theory, and in different contextual settings. Additional measurements beyond choice data, including biological measurements such as skin conductance, can be used to more rapidly eliminate hypothesis and speed up model comparison. Discrete choice models also provide a framework for testing behavioural models with field data, and encourage combined lab-field experiments.