Non-contiguous protein recombination

Swapping sequence elements among related proteins can produce chimeric proteins with novel behaviors and improved properties such as enhanced stability. Although homologous mutations are much more conservative than random mutations, chimeras of distantly-related proteins have a low probability of retaining fold and function. Here, I introduce a new tool for protein recombination that identifies structural blocks that can be swapped among homologous proteins with minimal disruption. This non-contiguous recombination approach enables design of chimeras and libraries of chimeras with less disruption than can be achieved by swapping blocks of sequence. Less disruption means that one can generate libraries with higher fractions of functional enzymes and enables recombination of more distant homologs.

Using this new tool I design and construct many functional chimeric cellulases. I illustrate the structurally conservative nature of this recombination by creating a functional prokaryotic-eukaryotic chimera and solving its structure. I also show how non-contiguous recombination can be used to efficiently identify stabilizing mutations that have been incorporated into homologs in nature.

Density functional theory embedding for correlated wavefunctions

Methods that exploit the intrinsic locality of molecular interactions show significant promise in making tractable the electronic structure calculation of large-scale systems. In particular, embedded density functional theory (e-DFT) offers a formally exact approach to electronic structure calculations in which the interactions between subsystems are evaluated in terms of their electronic density. In the following dissertation, methodological advances of embedded density functional theory are described, numerically tested, and applied to real chemical systems.

First, we describe an e-DFT protocol in which the non-additive kinetic energy component of the embedding potential is treated exactly. Then, we present a general implementation of the exact calculation of the non-additive kinetic potential (NAKP) and apply it to molecular systems. We demonstrate that the implementation using the exact NAKP is in excellent agreement with reference Kohn-Sham calculations, whereas the approximate functionals lead to qualitative failures in the calculated energies and equilibrium structures.

Next, we introduce density-embedding techniques to enable the accurate and stable calculation of correlated wavefunction (CW) in complex environments. Embedding potentials calculated using e-DFT introduce the effect of the environment on a subsystem for CW calculations (WFT-in-DFT). We demonstrate that WFT-in-DFT calculations are in good agreement with CW calculations performed on the full complex.

We significantly improve the numerics of the algorithm by enforcing orthogonality between subsystems by introduction of a projection operator. Utilizing the projection-based embedding scheme, we rigorously analyze the sources of error in quantum embedding calculations in which an active subsystem is treated using CWs, and the remainder using density functional theory. We show that the embedding potential felt by the electrons in the active subsystem makes only a small contribution to the error of the method, whereas the error in the nonadditive exchange-correlation energy dominates. We develop an algorithm which corrects this term and demonstrate the accuracy of this corrected embedding scheme.

Expanding the Toolkit for Synthetic Biology: Frameworks for Native-like Non-natural Gene Circuits

Synthetic biology combines biological parts from different sources in order to engineer non-native, functional systems. While there is a lot of potential for synthetic biology to revolutionize processes, such as the production of pharmaceuticals, engineering synthetic systems has been challenging. It is oftentimes necessary to explore a large design space to balance the levels of interacting components in the circuit. There are also times where it is desirable to incorporate enzymes that have non-biological functions into a synthetic circuit. Tuning the levels of different components, however, is often restricted to a fixed operating point, and this makes synthetic systems sensitive to changes in the environment. Natural systems are able to respond dynamically to a changing environment by obtaining information relevant to the function of the circuit. This work addresses these problems by establishing frameworks and mechanisms that allow synthetic circuits to communicate with the environment, maintain fixed ratios between components, and potentially add new parts that are outside the realm of current biological function. These frameworks provide a way for synthetic circuits to behave more like natural circuits by enabling a dynamic response, and provide a systematic and rational way to search design space to an experimentally tractable size where likely solutions exist. We hope that the contributions described below will aid in allowing synthetic biology to realize its potential.

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.