Tissue engineering active biological machines : bio-inspired design, directed self-assembly, and characterization of muscular pumps simulating the embryonic heart

Biological machines are active devices that are comprised of cells and other biological components. These functional devices are best suited for physiological environments that support cellular function and survival. Biological machines have the potential to revolutionize the engineering of biomedical devices intended for implantation, where the human body can provide the required physiological environment. For engineering such cell-based machines, bio-inspired design can serve as a guiding platform as it provides functionally proven designs that are attainable by living cells. In the present work, a systematic approach was used to tissue engineer one such machine by exclusively using biological building blocks and by employing a bio-inspired design. Valveless impedance pumps were constructed based on the working principles of the embryonic vertebrate heart and by using cells and tissue derived from rats. The function of these tissue-engineered muscular pumps was characterized by exploring their spatiotemporal and flow behavior in order to better understand the capabilities and limitations of cells when used as the engines of biological machines.

Engineering thermostable fungal cellobiohydrolases

Meeting the world's growing energy demands while protecting our fragile environment is a challenging issue. Second generation biofuels are liquid fuels like long-chain alcohols produced from lignocellulosic biomass. To reduce the cost of biofuel production, we engineered fungal family 6 cellobiohydrolases (Cel6A) for enhanced thermostability using random mutagenesis and recombination of beneficial mutations. During long-time hydrolysis, engineered thermostable cellulases hydrolyze more sugars than wild-type Cel6A as single enzymes and binary mixtures at their respective optimum temperatures. Engineered thermostable cellulases exhibit synergy in binary mixtures similar to wild-type cellulases, demonstrating the utility of engineering individual cellulases to produce novel thermostable mixtures. Crystal structures of the engineered thermostable cellulases indicate that the stabilization comes from improved hydrophobic interactions and restricted loop conformations by proline substitutions. At high temperature, free cysteines contribute to irreversible thermal inactivation in engineered thermostable Cel6A and wild-type Cel6A. The mechanism of thermal inactivation in this cellulase family is consistent with disulfide bond degradation and thiol-disulfide exchange. Enhancing the thermostability of Cel6A also increases tolerance to pretreatment chemicals, demonstrated by the strong correlation between thermostability and tolerance to 1-ethyl-3-methylimidazolium acetate. Several semi-rational protein engineering approaches – on the basis of consensus sequence analysis, proline stabilization, FoldX energy calculation, and high B-factors – were evaluated to further enhance the thermostability of Cel6A.

Engineering nucleic acid mechanisms for regulation and readout of gene expression : conditional Dicer substrate formation and sensitive multiplexed northern blots

Nucleic acids are most commonly associated with the genetic code, transcription and gene expression. Recently, interest has grown in engineering nucleic acids for biological applications such as controlling or detecting gene expression. The natural presence and functionality of nucleic acids within living organisms coupled with their thermodynamic properties of base-pairing make them ideal for interfacing (and possibly altering) biological systems. We use engineered small conditional RNA or DNA (scRNA, scDNA, respectively) molecules to control and detect gene expression. Three novel systems are presented: two for conditional down-regulation of gene expression via RNA interference (RNAi) and a third system for simultaneous sensitive detection of multiple RNAs using labeled scRNAs.

RNAi is a powerful tool to study genetic circuits by knocking down a gene of interest. RNAi executes the logic: If gene Y is detected, silence gene Y. The fact that detection and silencing are restricted to the same gene means that RNAi is constitutively on. This poses a significant limitation when spatiotemporal control is needed. In this work, we engineered small nucleic acid molecules that execute the logic: If mRNA X is detected, form a Dicer substrate that targets independent mRNA Y for silencing. This is a step towards implementing the logic of conditional RNAi: If gene X is detected, silence gene Y. We use scRNAs and scDNAs to engineer signal transduction cascades that produce an RNAi effector molecule in response to hybridization to a nucleic acid target X. The first mechanism is solely based on hybridization cascades and uses scRNAs to produce a double-stranded RNA (dsRNA) Dicer substrate against target gene Y. The second mechanism is based on hybridization of scDNAs to detect a nucleic acid target and produce a template for transcription of a short hairpin RNA (shRNA) Dicer substrate against target gene Y. Test-tube studies for both mechanisms demonstrate that the output Dicer substrate is produced predominantly in the presence of a correct input target and is cleaved by Dicer to produce a small interfering RNA (siRNA). Both output products can lead to gene knockdown in tissue culture. To date, signal transduction is not observed in cells; possible reasons are explored.

Signal transduction cascades are composed of multiple scRNAs (or scDNAs). The need to study multiple molecules simultaneously has motivated the development of a highly sensitive method for multiplexed northern blots. The core technology of our system is the utilization of a hybridization chain reaction (HCR) of scRNAs as the detection signal for a northern blot. To achieve multiplexing (simultaneous detection of multiple genes), we use fluorescently tagged scRNAs. Moreover, by using radioactive labeling of scRNAs, the system exhibits a five-fold increase, compared to the literature, in detection sensitivity. Sensitive multiplexed northern blot detection provides an avenue for exploring the fate of scRNAs and scDNAs in tissue culture.

Coupled effects of mechanics, geometry, and chemistry on bio-membrane behavior

Lipid bilayer membranes are models for cell membranes--the structure that helps regulate cell function. Cell membranes are heterogeneous, and the coupling between composition and shape gives rise to complex behaviors that are important to regulation. This thesis seeks to systematically build and analyze complete models to understand the behavior of multi-component membranes.

We propose a model and use it to derive the equilibrium and stability conditions for a general class of closed multi-component biological membranes. Our analysis shows that the critical modes of these membranes have high frequencies, unlike single-component vesicles, and their stability depends on system size, unlike in systems undergoing spinodal decomposition in flat space. An important implication is that small perturbations may nucleate localized but very large deformations. We compare these results with experimental observations.

We also study open membranes to gain insight into long tubular membranes that arise for example in nerve cells. We derive a complete system of equations for open membranes by using the principle of virtual work. Our linear stability analysis predicts that the tubular membranes tend to have coiling shapes if the tension is small, cylindrical shapes if the tension is moderate, and beading shapes if the tension is large. This is consistent with experimental observations reported in the literature in nerve fibers. Further, we provide numerical solutions to the fully nonlinear equilibrium equations in some problems, and show that the observed mode shapes are consistent with those suggested by linear stability. Our work also proves that beadings of nerve fibers can appear purely as a mechanical response of the membrane.

Engineering multi-step electron tunneling systems in proteins

Multi-step electron tunneling, or “hopping,” has become a fast-developing research field with studies ranging from theoretical modeling systems, inorganic complexes, to biological systems. In particular, the field is exploring hopping mechanisms in new proteins and protein complexes, as well as further understanding the classical biological hopping systems such as ribonuclease reductase, DNA photolyases, and photosystem II. Despite the plethora of natural systems, only a few biologically engineered systems exist. Engineered hopping systems can provide valuable information on key structural and electronic features, just like other kinds of biological model systems. Also, engineered systems can harness common biologic processes and utilize them for alternative reactions. In this thesis, two new hopping systems are engineered and characterized.

The protein Pseudomonas aeruginosa azurin is used as a building block to create the two new hopping systems. Besides being well studied and amenable to mutation, azurin already has been used to successfully engineer a hopping system. The two hopping systems presented in this thesis have a histidine-attached high potential rhenium 4,7-dimethyl-1,10-phenanthroline tricarbonyl [Re(dmp)(CO)3] + label which, when excited, acts as the initial electron acceptor. The metal donor is the type I copper of the azurin protein. The hopping intermediates are all tryptophan, an amino acid mutated into the azurin at select sites between the photoactive metal label and the protein metal site. One system exhibits an inter-molecular hopping through a protein dimer interface; the other system undergoes intra-molecular multi-hopping utilizing a tryptophan “wire.” The electron transfer reactions are triggered by excitation of the rhenium label and monitored by UV-Visible transient absorption, luminescence decays measurements, and time-resolved Infrared spectroscopy (TRIR). Both systems were structurally characterized by protein X-ray crystallography.

Engineering enzyme systems by recombination

Homologous recombination is a source of diversity in both natural and directed evolution. Standing genetic variation that has passed the test of natural selection is combined in new ways, generating functional and sometimes unexpected changes. In this work we evaluate the utility of homologous recombination as a protein engineering tool, both in comparison with and combined with other protein engineering techniques, and apply it to an industrially important enzyme: Hypocrea jecorina Cel5a.

Chapter 1 reviews work over the last five years on protein engineering by recombination. Chapter 2 describes the recombination of Hypocrea jecorina Cel5a endoglucanase with homologous enzymes in order to improve its activity at high temperatures. A chimeric Cel5a that is 10.1 °C more stable than wild-type and hydrolyzes 25% more cellulose at elevated temperatures is reported. Chapter 3 describes an investigation into the synergy of thermostable cellulases that have been engineered by recombination and other methods. An engineered endoglucanase and two engineered cellobiohydrolases synergistically hydrolyzed cellulose at high temperatures, releasing over 200% more reducing sugars over 60 h at their optimal mixture relative to the best mixture of wild-type enzymes. These results provide a framework for engineering cellulolytic enzyme mixtures for the industrial conditions of high temperatures and long incubation times.

In addition to this work on recombination, we explored three other problems in protein engineering. Chapter 4 describes an investigation into replacing enzymes with complex cofactors with simple cofactors, using an E. coli enolase as a model system. Chapter 5 describes engineering broad-spectrum aldehyde resistance in Saccharomyces cerevisiae by evolving an alcohol dehydrogenase simultaneously for activity and promiscuity. Chapter 6 describes an attempt to engineer gene-targeted hypermutagenesis into E. coli to facilitate continuous in vivo selection systems.

Nonstationary response of structures and its application to earthquake engineering

This thesis presents a simplified state-variable method to solve for the nonstationary response of linear MDOF systems subjected to a modulated stationary excitation in both time and frequency domains. The resulting covariance matrix and evolutionary spectral density matrix of the response may be expressed as a product of a constant system matrix and a time-dependent matrix, the latter can be explicitly evaluated for most envelopes currently prevailing in engineering. The stationary correlation matrix of the response may be found by taking the limit of the covariance response when a unit step envelope is used. The reliability analysis can then be performed based on the first two moments of the response obtained.

The method presented facilitates obtaining explicit solutions for general linear MDOF systems and is flexible enough to be applied to different stochastic models of excitation such as the stationary models, modulated stationary models, filtered stationary models, and filtered modulated stationary models and their stochastic equivalents including the random pulse train model, filtered shot noise, and some ARMA models in earthquake engineering. This approach may also be readily incorporated into finite element codes for random vibration analysis of linear structures.

A set of explicit solutions for the response of simple linear structures subjected to modulated white noise earthquake models with four different envelopes are presented as illustration. In addition, the method has been applied to three selected topics of interest in earthquake engineering, namely, nonstationary analysis of primary-secondary systems with classical or nonclassical dampings, soil layer response and related structural reliability analysis, and the effect of the vertical components on seismic performance of structures. For all the three cases, explicit solutions are obtained, dynamic characteristics of structures are investigated, and some suggestions are given for aseismic design of structures.

Innovations of wide-field optical-sectioning fluorescence microscopy : toward high-speed volumetric bio-imaging with simplicity

Optical microscopy has become an indispensable tool for biological researches since its invention, mostly owing to its sub-cellular spatial resolutions, non-invasiveness, instrumental simplicity, and the intuitive observations it provides. Nonetheless, obtaining reliable, quantitative spatial information from conventional wide-field optical microscopy is not always intuitive as it appears to be. This is because in the acquired images of optical microscopy the information about out-of-focus regions is spatially blurred and mixed with in-focus information. In other words, conventional wide-field optical microscopy transforms the three-dimensional spatial information, or volumetric information about the objects into a two-dimensional form in each acquired image, and therefore distorts the spatial information about the object. Several fluorescence holography-based methods have demonstrated the ability to obtain three-dimensional information about the objects, but these methods generally rely on decomposing stereoscopic visualizations to extract volumetric information and are unable to resolve complex 3-dimensional structures such as a multi-layer sphere.

The concept of optical-sectioning techniques, on the other hand, is to detect only two-dimensional information about an object at each acquisition. Specifically, each image obtained by optical-sectioning techniques contains mainly the information about an optically thin layer inside the object, as if only a thin histological section is being observed at a time. Using such a methodology, obtaining undistorted volumetric information about the object simply requires taking images of the object at sequential depths.

Among existing methods of obtaining volumetric information, the practicability of optical sectioning has made it the most commonly used and most powerful one in biological science. However, when applied to imaging living biological systems, conventional single-point-scanning optical-sectioning techniques often result in certain degrees of photo-damages because of the high focal intensity at the scanning point. In order to overcome such an issue, several wide-field optical-sectioning techniques have been proposed and demonstrated, although not without introducing new limitations and compromises such as low signal-to-background ratios and reduced axial resolutions. As a result, single-point-scanning optical-sectioning techniques remain the most widely used instrumentations for volumetric imaging of living biological systems to date.

In order to develop wide-field optical-sectioning techniques that has equivalent optical performance as single-point-scanning ones, this thesis first introduces the mechanisms and limitations of existing wide-field optical-sectioning techniques, and then brings in our innovations that aim to overcome these limitations. We demonstrate, theoretically and experimentally, that our proposed wide-field optical-sectioning techniques can achieve diffraction-limited optical sectioning, low out-of-focus excitation and high-frame-rate imaging in living biological systems. In addition to such imaging capabilities, our proposed techniques can be instrumentally simple and economic, and are straightforward for implementation on conventional wide-field microscopes. These advantages together show the potential of our innovations to be widely used for high-speed, volumetric fluorescence imaging of living biological systems.

Engineering and Characterization of Cytochrome P450 Enzymes for Nitrogen-Atom Transfer Reactions

The creation of novel enzyme activity is a great challenge to protein engineers, but nature has done so repeatedly throughout the process of natural selection. I begin by outlining the multitude of distinct reactions catalyzed by a single enzyme class, cytochrome P450 monooxygenases. I discuss the ability of cytochrome P450 to generate reactive intermediates capable of diverse reactivity, suggesting this enzyme can also be used to generate novel reactive intermediates in the form of metal-carbenoid and nitrenoid species. I then show that cytochrome P450 from Bacillus megaterium (P450_BM3) and its isolated cofactor can catalyze metal-nitrenoid transfer in the form of intramolecular C–H bond amination. Mutations to the protein sequence can enhance the reactivity and selectivity of this transformation significantly beyond that of the free cofactor. Next, I demonstrate an intermolecular nitrene transfer reaction catalyzed by P450_BM3 in the form of sulfide imidation. Understanding that sulfur heteroatoms are strong nucleophiles, I show that increasing the sulfide nucleophilicity through substituents on the aryl sulfide ring can dramatically increase reaction productivity. To explore engineering nitrenoid transfer in P450BM3, active site mutagenesis is employed to tune the regioselectivity intramolecular C–H amination catalysts. The solution of the crystal structure of a highly selective variant demonstrates that hydrophobic residues in the active site strongly modulate reactivity and regioselectivity. Finally, I use a similar strategy to develop P450-based catalysts for intermolecular olefin aziridination, demonstrating that active site mutagenesis can greatly enhance this nitrene transfer reaction. The resulting variant can catalyze intermolecular aziridination with more than 1000 total turnovers and enantioselectivity of up to 99% ee.

Band Engineering in Thermoelectric Materials Using Optical, Electronic, and Ab-Initio Computed Properties

Thermoelectric materials have demanded a significant amount of attention for their ability to convert waste heat directly to electricity with no moving parts. A resurgence in thermoelectrics research has led to significant enhancements in the thermoelectric figure of merit, zT, even for materials that were already well studied. This thesis approaches thermoelectric zT optimization by developing a detailed understanding of the electronic structure using a combination of electronic/thermoelectric properties, optical properties, and ab-initio computed electronic band structures. This is accomplished by applying these techniques to three important classes of thermoelectric materials: IV-VI materials (the lead chalcogenides), Half-Heusler’s (XNiSn where X=Zr, Ti, Hf), and CoSb₃ skutterudites.

In the IV-VI materials (PbTe, PbSe, PbS) I present a shifting temperature-dependent optical absorption edge which correlates well to the computed ab-initio molecular dynamics result. Contrary to prior literature that suggests convergence of the primary and secondary bands at 400 K, I suggest a higher convergence temperature of 700, 900, and 1000 K for PbTe, PbSe, and PbS, respectively. This finding can help guide electronic properties modelling by providing a concrete value for the band gap and valence band offset as a function of temperature.

Another important thermoelectric material, ZrNiSn (half-Heusler), is analyzed for both its optical and electronic properties; transport properties indicate a largely different band gap depending on whether the material is doped n-type or p-type. By measuring and reporting the optical band gap value of 0.13 eV, I resolve the discrepancy in the gap calculated from electronic properties (maximum Seebeck and resistivity) by correlating these estimates to the electron-to-hole weighted mobility ratio, A, in narrow gap materials (A is found to be approximately 5.0 in ZrNiSn).

I also show that CoSb₃ contains multiple conduction bands that contribute to the thermoelectric properties. These bands are also observed to shift towards each other with temperature, eventually reaching effective convergence for T>500 K. This implies that the electronic structure in CoSb₃ is critically important (and possibly engineerable) with regards to its high thermoelectric figure of merit.

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.

Programming chemical kinetics: engineering dynamic reaction networks with DNA strand displacement

Over the last century, the silicon revolution has enabled us to build faster, smaller and more sophisticated computers. Today, these computers control phones, cars, satellites, assembly lines, and other electromechanical devices. Just as electrical wiring controls electromechanical devices, living organisms employ "chemical wiring" to make decisions about their environment and control physical processes. Currently, the big difference between these two substrates is that while we have the abstractions, design principles, verification and fabrication techniques in place for programming with silicon, we have no comparable understanding or expertise for programming chemistry.

In this thesis we take a small step towards the goal of learning how to systematically engineer prescribed non-equilibrium dynamical behaviors in chemical systems. We use the formalism of chemical reaction networks (CRNs), combined with mass-action kinetics, as our programming language for specifying dynamical behaviors. Leveraging the tools of nucleic acid nanotechnology (introduced in Chapter 1), we employ synthetic DNA molecules as our molecular architecture and toehold-mediated DNA strand displacement as our reaction primitive.

Abstraction, modular design and systematic fabrication can work only with well-understood and quantitatively characterized tools. Therefore, we embark on a detailed study of the "device physics" of DNA strand displacement (Chapter 2). We present a unified view of strand displacement biophysics and kinetics by studying the process at multiple levels of detail, using an intuitive model of a random walk on a 1-dimensional energy landscape, a secondary structure kinetics model with single base-pair steps, and a coarse-grained molecular model that incorporates three-dimensional geometric and steric effects. Further, we experimentally investigate the thermodynamics of three-way branch migration. Our findings are consistent with previously measured or inferred rates for hybridization, fraying, and branch migration, and provide a biophysical explanation of strand displacement kinetics. Our work paves the way for accurate modeling of strand displacement cascades, which would facilitate the simulation and construction of more complex molecular systems.

In Chapters 3 and 4, we identify and overcome the crucial experimental challenges involved in using our general DNA-based technology for engineering dynamical behaviors in the test tube. In this process, we identify important design rules that inform our choice of molecular motifs and our algorithms for designing and verifying DNA sequences for our molecular implementation. We also develop flexible molecular strategies for "tuning" our reaction rates and stoichiometries in order to compensate for unavoidable non-idealities in the molecular implementation, such as imperfectly synthesized molecules and spurious "leak" pathways that compete with desired pathways.

We successfully implement three distinct autocatalytic reactions, which we then combine into a de novo chemical oscillator. Unlike biological networks, which use sophisticated evolved molecules (like proteins) to realize such behavior, our test tube realization is the first to demonstrate that Watson-Crick base pairing interactions alone suffice for oscillatory dynamics. Since our design pipeline is general and applicable to any CRN, our experimental demonstration of a de novo chemical oscillator could enable the systematic construction of CRNs with other dynamic behaviors.

A brief study of economic Penstock design : Supplementary to Course 800, Department of Civil Engineering

No abstract.