Designer Gene Networks: Towards Fundamental Cellular Control

The engineered control of cellular function through the design of synthetic genetic networks is becoming plausible. Here we show how a naturally occurring network can be used as a parts list for artificial network design, and how model formulation leads to computational and analytical approaches relevant to nonlinear dynamics and statistical physics.Comment: 35 pages, 8 figure

Programming microbes to treat superbug infection

Superbug infection is one of the greatest public health threat with grave implications across all levels of society. Towards a new solution to combat infection by multi-drug resistant bacteria, this thesis presents an engineering framework and genetic tools applied to repurpose commensal bacteria into “micro-robots” for the treatment of superbug infection. Specifically, a prototype of designer probiotic was developed using the human commensal bacteria Escherichia coli. The engineered commensal was reprogrammed with user-specified functions to sense superbug, produced pathogen-specific killing molecules and released the killing molecules via a lytic mechanism. The engineered commensal was effective in suppressing ~99% of planktonic Pseudomonas and preventing ~ 90% of biofilm formation. To enhance the sensing capabilities of engineered commensal, genetic interfaces comprising orthogonal AND & OR logic devices were developed to mediate the integration and interpretation of binary input signals. Finally, AND, OR and NOT logic gates were networked to generate a myriad of cellular logic operations including half adder and half subtractor. The creation of half adder logic represents a significant advancement of engineering human commensal to be biological equivalent of microprocessor chips in programmable computer with the ability to process input signals into diversified actions. Importantly, this thesis provides exemplary case studies to the attenuation of cellular and genetic context dependent effects through principles elucidated herein, thereby advancing our capability to engineer commensal bacteria.Open Acces

Single-Cell and Single-Molecule Studies of Bacteriophage Lambda Post-Infection Decision-Making

Cellular decision making is a ubiquitous process among all life forms, and a key step that organisms take to integrate the environmental signals to choose an optimal response to improve their overall fitness. The genetic circuits selected to carry out this task determine the cell fate in a seemingly probabilistic way, either due to the inherent stochasticity of the system, or our inability to characterize the factors with deterministic impacts. To gain a better understanding of the mechanisms underlying cell-fate selection, we utilize a well-established system for cellular decision-making, the paradigm of bacteriophage lambda infection, which leads to two distinct outcomes – lysis and lysogeny. Recent studies of this system using higher resolution techniques suggested that different phage decisions are partially determined by pre-existing difference and the complex in vivo phage-phage interactions. Therefore, characterizing more ‘hidden’ deterministic factors and dissecting the intracellular behaviors of phage components, such as DNA, RNA and proteins are central to a more complete understanding of the phage decision-making strategies. One commonly overlooked but potentially important factor is phage DNA replication, which could result in not only more templates for gene expression but also introduce gene copy number variations. Meanwhile, although theoretical work has long predicted that noise arising from stochastic gene expression can be propagated through the gene networks to result in phenotypic variance, experimental characterization is still lacking, impeding the assessment of its contributions to phage decision-making. In this work, we provided direct experimental evidence that different phage DNAs are capable of making decisions independently. DNA integration, a characteristic event for phage lysogenization, can also be detected in lytic cells. Moreover, through single phage DNA labeling technique, we revealed great heterogeneity in intracellular DNA motions, which could partially explain the complex phage-phage interactions. Furthermore, we found that DNA replication is important for the enforcement of decisions. Instead of affecting the transcription of early lysis-lysogeny decision-making genes, DNA replication exerts its effect on the expression of the decision effectors, CI. Lastly, a mathematical model is built to provide comprehensive understanding of the decision making network

Dynamic control of endogenous metabolism with combinatorial logic circuits

Controlling gene expression during a bioprocess enables real-time metabolic control, coordinated cellular responses, and staging order-of-operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by-product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18-h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post-translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.Synthetic Biology Engineering Research Center (SynBERC EEC0540879)United States. Office of Naval Research. Multidisciplinary University Research Initiative (N00014‐13‐1‐0074)United States. Department of Energy (DE‐SC0018368

To Lyse or Not to Lyse: Transient-Mediated Stochastic Fate Determination in Cells Infected by Bacteriophages

Cell fate determination is usually described as the result of the stochastic dynamics of gene regulatory networks (GRNs) reaching one of multiple steady-states each of which corresponds to a specific decision. However, the fate of a cell is determined in finite time suggesting the importance of transient dynamics in cellular decision making. Here we consider cellular decision making as resulting from first passage processes of regulatory proteins and examine the effect of transient dynamics within the initial lysis-lysogeny switch of phage λ. Importantly, the fate of an infected cell depends, in part, on the number of coinfecting phages. Using a quantitative model of the phage λ GRN, we find that changes in the likelihood of lysis and lysogeny can be driven by changes in phage co-infection number regardless of whether or not there exists steady-state bistability within the GRN. Furthermore, two GRNs which yield qualitatively distinct steady state behaviors as a function of phage infection number can show similar transient responses, sufficient for alternative cell fate determination. We compare our model results to a recent experimental study of cell fate determination in single cell assays of multiply infected bacteria. Whereas the experimental study proposed a “quasi-independent” hypothesis for cell fate determination consistent with an observed data collapse, we demonstrate that observed cell fate results are compatible with an alternative form of data collapse consistent with a partial gene dosage compensation mechanism. We show that including partial gene dosage compensation at the mRNA level in our stochastic model of fate determination leads to the same data collapse observed in the single cell study. Our findings elucidate the importance of transient gene regulatory dynamics in fate determination, and present a novel alternative hypothesis to explain single-cell level heterogeneity within the phage λ lysis-lysogeny decision switch