Multifaceted Effects of Resource Competition on Gene Expression and Noise

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Description
A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a…

A notable challenge when assembling synthetic gene circuits is that modularity often fails to function as intended. A crucial underlying reason for this modularity failure is the existence of competition for shared and limited gene expression resources. By designing a synthetic cascading bistable switches (Syn-CBS) circuit in a single strain with two coupled self-activation modules to achieve successive cell fate transitions, nonlinear resource competition within synthetic gene circuits is unveiled. However, in vivo it can be seen that the transition path was redirected with the activation of one switch always prevailing over that of the other, contradictory to coactivation theoretically expected. This behavior is a result of resource competition between genes and follows a ‘winner-takes-all’ rule, where the winner is determined by the relative connection strength between the two modules. Despite investigation demonstrating that resource competition between gene modules can significantly alter circuit deterministic behaviors, how resource competition contributes to gene expression noise and how this noise can be controlled is still an open issue of fundamental importance in systems biology and biological physics. By utilizing a two-gene circuit, the effects of resource competition on protein expression noise levels can be closely studied. A surprising double-edged role is discovered: the competition for these resources decreases noise while the constraint on resource availability adds its own term of noise into the system, denoted “resource competitive” noise. Noise reduction effects are then studied using orthogonal resources. Results indicate that orthogonal resources are a good strategy for eliminating the contribution of resource competition to gene expression noise. Noise propagation through a cascading circuit has been considered without resource competition. It has been noted that the noise from upstream genes can be transmitted downstream. However, resource competition’s effects on this cascading noise have yet to be studied. When studied, it is found that resource competition can induce stochastic state switching and perturb noise propagation. Orthogonal resources can remove some of the resource competitive behavior and allow for a system with less noise.
Date Created
2022
Agent

Detection and Manipulation of Extrachromosomal Circular DNA in Yeast

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Description
Extrachromosomal circular DNA (eccDNA) has become an increasingly popular subject of study in eukaryotic cell biology due to its prevalence in human cancer. Though the literature reports a consensus regarding DNA break repair as a driver of eccDNA formation, there…

Extrachromosomal circular DNA (eccDNA) has become an increasingly popular subject of study in eukaryotic cell biology due to its prevalence in human cancer. Though the literature reports a consensus regarding DNA break repair as a driver of eccDNA formation, there remains a lack of knowledge surrounding the exact mechanisms for eccDNA formation and the selective dynamics that promote their retainment in a cell or population. A central issue to studying eccDNA is the inability to distinguish between linear and circular DNA of homologous sequence. The work presented here describes an adapted eccDNA enrichment and detection assay, specifically for investigating the effects of manipulating a known eccDNA-forming locus in the budding yeast Saccharomyces cerevisiae. First, a galactose inducible GFP reporter was integrated within the copper inducible CUP1 tandem repeat locus of yeast cells. The eccDNA enrichment and detection assay was first applied to wildtype yeast to demonstrate the presence of CUP1 eccDNA in copper induced cells by qPCR. Although subsequent sequencing analysis failed to validate this result, it indicated the presence of various other known and previously un-reported eccDNA species. Finally, application of the enrichment protocol and qPCR detection assay to CUP1-GFP reporter cells yielded inconclusive results, suggesting the assay requires further optimization to sensitively detect eccDNA from this altered locus. While more work is necessary to draw conclusions regarding the limits of eccDNA production at a manipulated eccDNA-forming locus, this knowledge will lend to the potential for therapeutically targeting eccDNA at the point of de novo formation.
Date Created
2022
Agent

Bioprocess Monitoring Technology for the Biomanufacturing of Regenerative Medicine Tissue Products

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Description

Regenerative medicine utilizes living cells as therapeutics to replace or repair damaged or diseased tissue, but the manufacturing processes to produce cell-based tissue products require customized biounit operations that do not currently exist as conventional biochemical and biopharma manufacturing processes.…

Regenerative medicine utilizes living cells as therapeutics to replace or repair damaged or diseased tissue, but the manufacturing processes to produce cell-based tissue products require customized biounit operations that do not currently exist as conventional biochemical and biopharma manufacturing processes. Living cells are constantly changing and reacting to their environment, which in the case of cells isolated from their hosts, are utilized as living bioreactor components that, by themselves, are manipulated to biomanufacturer selected tissue products. Therefore, specialized technology is required to assure that cellular products produce the phenotypical tissue characteristics that the final product is designated to have, while also maintaining sterility of the culture. Because of this, FDA guidelines encourage the use of Process Analytical Technology (PAT – see Ref ) to be integrated into manufacturing systems of biologics to ensure quality and safety. To address the need for evaluation of sensor technologies for potential use in PAT, a literature review of both existing sensing technologies and biomarkers was conducted. After a thorough assessment of the sensor technologies that were most applicable to biomanufacturing, spectrophotometry was selected to monitor the metabolic components glucose and lactate of living cells in culture in real time. Initially, spectrophotometric measurements were taken of mock solutions of glucose and lactate solutions at concentrations relevant to human cell culture and physiology. With that data, a mathematical model was developed to predict a solution’s glucose and lactate concentration. This model was then integrated into a Matlab program that was used to continuously monitor and estimate solutions of glucose and lactate concentrations in real time. After testing the accuracy of this program in different solutions, it was determined that calibration curves and models must be made for each media type and estimates of glucose and lactate were found accurate only at higher concentrations. This program was successfully utilized to monitor in real time glucose and lactate production and consumption trends of Mesenchymal Stem Cells (MSCs) in culture, demonstrating proof-of-concept of the proposed bioprocess monitoring schema.

Date Created
2022-05
Agent

Spatial Temporal Patterning and Dynamics of E. Coli Growth with Nutrient Variation

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Description
Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not…

Synthetic biology (SB) has become an important field of science focusing on designing and engineering new biological parts and systems, or re-designing existing biological systems for useful purposes. The dramatic growth of SB throughout the past two decades has not only provided us numerous achievements, but also brought us more timely and underexplored problems. In SB's entire history, mathematical modeling has always been an indispensable approach to predict the experimental outcomes, improve experimental design and obtain mechanism-understanding of the biological systems. \textit{Escherichia coli} (\textit{E. coli}) is one of the most important experimental platforms, its growth dynamics is the major research objective in this dissertation. Chapter 2 employs a reaction-diffusion model to predict the \textit{E. coli} colony growth on a semi-solid agar plate under multiple controls. In that chapter, a density-dependent diffusion model with non-monotonic growth to capture the colony's non-linear growth profile is introduced. Findings of the new model to experimental data are compared and contrasted with those from other proposed models. In addition, the cross-sectional profile of the colony are computed and compared with experimental data. \textit{E. coli} colony is also used to perform spatial patterns driven by designed gene circuits. In Chapter 3, a gene circuit (MINPAC) and its corresponding pattern formation results are presented. Specifically, a series of partial differential equation (PDE) models are developed to describe the pattern formation driven by the MINPAC circuit. Model simulations of the patterns based on different experimental conditions and numerical analysis of the models to obtain a deeper understanding of the mechanisms are performed and discussed. Mathematical analysis of the simplified models, including traveling wave analysis and local stability analysis, is also presented and used to explore the control strategies of the pattern formation. The interaction between the gene circuit and the host \textit{E. coli} may be crucial and even greatly affect the experimental outcomes. Chapter 4 focuses on the growth feedback between the circuit and the host cell under different nutrient conditions. Two ordinary differential equation (ODE) models are developed to describe such feedback with nutrient variation. Preliminary results on data fitting using both two models and the model dynamical analysis are included.
Date Created
2021
Agent

Control of Tissue Homeostasis, Tumorigenesis, and Degeneration by Coupled Bidirectional Bistable Switches

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Description
The Hippo-YAP/TAZ signaling pathway plays a critical role in tissue homeostasis, tumorigenesis, and degeneration disorders. The regulation of YAP/TAZ levels is controlled by a complex regulatory network, where several feedback loops have been identified. However, it remains elusive how these…

The Hippo-YAP/TAZ signaling pathway plays a critical role in tissue homeostasis, tumorigenesis, and degeneration disorders. The regulation of YAP/TAZ levels is controlled by a complex regulatory network, where several feedback loops have been identified. However, it remains elusive how these feedback loops contain the YAP/TAZ levels and maintain the system in a healthy physiological state or trap the system into pathological conditions. Here, a mathematical model was developed to represent the YAP/TAZ regulatory network. Through theoretical analyses, three distinct states that designate the three physiological and pathological outcomes were found. The transition from the physiological state to the two pathological states is mechanistically controlled by coupled bidirectional bistable switches, which are robust to parametric variation and stochastic fluctuations at the molecular level. This work provides a mechanistic understanding of the regulation and dysregulation of YAP/TAZ levels in tissue state transitions.
Date Created
2021
Agent

Investigating the Role of APOE2 in Alzheimer's Disease Using Human Induced Pluripotent Stem Cell Derived Neurons and Astrocytes

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Description
Genome wide association studies (GWAS) have identified polymorphism in the Apolipoprotein E (APOE) gene to be the most prominent risk factor for Alzheimer’s disease (AD). Compared to individuals homozygous for the APOE3 variant, individuals with the APOE4 variant have a…

Genome wide association studies (GWAS) have identified polymorphism in the Apolipoprotein E (APOE) gene to be the most prominent risk factor for Alzheimer’s disease (AD). Compared to individuals homozygous for the APOE3 variant, individuals with the APOE4 variant have a significantly elevated risk of AD. On the other hand, longitudinal studies have shown that the presence of the APOE2 variant reduces lifetime risk of developing AD by 40 percent. While there has been significant research that has identified the risk-inducing effects of APOE4, the underlying mechanisms by which APOE2 influences AD onset and progression have not been extensively explored. The hallmarks of AD pathology manifest in human neurons in the form of extracellular amyloid deposits and intracellular neurofibrillary tangles, whereas astrocytes are the primary source of the APOE protein in the brain. In this study, an isogenic human induced pluripotent stem cell (hiPSC)-based system is utilized to demonstrate that conversion of APOE3 to APOE2 greatly reduced the production of amyloid-beta (Aβ) peptides in hiPSC-derived neural cultures. Mechanistically, analysis of pure populations of neurons and astrocytes derived from these neural cultures revealed that mitigating effects of APOE2 is mediated by cell autonomous and non-autonomous effects. In particular, it was demonstrated the reduction in Aβ and pathogenic β-C-terminal fragments (APP-βCTF) is potentially driven by a mechanism related to non-amyloidogenic processing of amyloid precursor protein (APP), suggesting a gain of protective function of the APOE2 variant. Together, this study provides insights into the risk-modifying effects associated with the APOE2 allele and establishes a platform to probe the mechanisms by which APOE2 enhances neuroprotection against AD.
Date Created
2021
Agent

An Investigation of the Formation, Function, and Future of Extrachromosomal Circular DNA

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Description

Extrachromosomal circular DNA (eccDNA) has been identified in a broad range of eukaryotes and have been shown to carry genes and regulatory sequences. Additionally, they can amplify within a cell by autonomous replication or reintegration into the genome, effectively influencing…

Extrachromosomal circular DNA (eccDNA) has been identified in a broad range of eukaryotes and have been shown to carry genes and regulatory sequences. Additionally, they can amplify within a cell by autonomous replication or reintegration into the genome, effectively influencing copy number in cells. This has significant implications for cancer, where oncogenes are frequently amplified on eccDNA. However, little is known about the exact molecular mechanisms governing eccDNA functionality. To this end, we constructed a fluorescent reporter at an eccDNA-prone locus of the yeast genome, CUP1. It is our hope that this reporter will contribute to a better understanding of eccDNA formation and amplification within a cell.

Date Created
2021-05
Agent

Engineering of Synthetic DNA/RNA Modules for Manipulating Gene Expression and Circuit Dynamics

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Description
Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture…

Gene circuit engineering facilitates the discovery and understanding of fundamental biology and has been widely used in various biological applications. In synthetic biology, gene circuits are often constructed by two main strategies: either monocistronic or polycistronic constructions. The Latter architecture can be commonly found in prokaryotes, eukaryotes, and viruses and has been largely applied in gene circuit engineering. In this work, the effect of adjacent genes and noncoding regions are systematically investigated through the construction of batteries of gene circuits in diverse scenarios. Data-driven analysis yields a protein expression metric that strongly correlates with the features of adjacent transcriptional regions (ATRs). This novel mathematical tool helps the guide for circuit construction and has the implication for the design of synthetic ATRs to tune gene expression, illustrating its potential to facilitate engineering complex gene networks. The ability to tune RNA dynamics is greatly needed for biotech applications, including therapeutics and diagnostics. Diverse methods have been developed to tune gene expression through transcriptional or translational manipulation. Control of RNA stability/degradation is often overlooked and can be the lightweight alternative to regulate protein yields. To further extend the utility of engineered ATRs to regulate gene expression, a library of RNA modules named degradation-tuning RNAs (dtRNAs) are designed with the ability to form specific 5’ secondary structures prior to RBS. These modules can modulate transcript stability while having a minimal interference on translation initiation. Optimization of their functional structural features enables gene expression level to be tuned over a wide dynamic range. These engineered dtRNAs are capable of regulating gene circuit dynamics as well as noncoding RNA levels and can be further expanded into cell-free system for gene expression control in vitro. Finally, integrating dtRNA with synthetic toehold sensor enables improved paper-based viral diagnostics, illustrating the potential of using synthetic dtRNAs for biomedical applications.
Date Created
2020
Agent

Nanoplasmonic Sensing of Disease-associated Extracellular Vesicles - An Ultrasensitive Diagnosis and Prognosis Approach

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Description
Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated…

Extracellular vesicles (EVs) are membranous particles that are abundantly secreted in the circulation system by most cells and can be found in most biological fluids. Among different EV subtypes, exosomes are small particles (30 – 150 nm) that are generated through the double invagination of the lipid bilayer membrane of cell. Therefore, they mirror the cell membrane proteins and contain proteins, RNAs, and DNAs that can represent the phenotypic state of their cell of origin, hence considered promising biomarker candidates. Importantly, in most pathological conditions, such as cancer and infection, diseased cells secrete more EVs and the disease associated exosomes have shown great potential to serve as biomarkers for early diagnosis, disease staging, and treatment monitoring. However, using EVs as diagnostic or prognostic tools in the clinic is hindered by the lack of a rapid, sensitive, purification-free technique for their isolation and characterization. Developing standardized assays that can translate the emerging academic EV biomarker discoveries to clinically relevant procedures is a bottleneck that have slowed down advancements in medical research. Integrating widely known immunoassays with plasmonic sensors has shown the promise to detect minute amounts of antigen present in biological sample, based on changes of ambient optical refractive index, and achieve ultra-sensitivity. Plasmonic sensors take advantage of the enhanced interaction of electromagnetic radiations with electron clouds of plasmonic materials at the dielectric-metal interface in tunable wavelengths.
Date Created
2020
Agent

Landscape of Gene Regulatory Network Motifs

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Description
The human transcriptional regulatory machine utilizes hundreds of transcription factors which bind to specific genic sites resulting in either activation or repression of targeted genes. Networks comprised of nodes and edges can be constructed to model the relationships of regulators…

The human transcriptional regulatory machine utilizes hundreds of transcription factors which bind to specific genic sites resulting in either activation or repression of targeted genes. Networks comprised of nodes and edges can be constructed to model the relationships of regulators and their targets. Within these biological networks small enriched structural patterns containing at least three nodes can be identified as potential building blocks from which a network is organized. A first iteration computational pipeline was designed to generate a disease specific gene regulatory network for motif detection using established computational tools. The first goal was to identify motifs that can express themselves in a state that results in differential patient survival in one of the 32 different cancer types studied. This study identified issues for detecting strongly correlated motifs that also effect patient survival, yielding preliminary results for possible driving cancer etiology. Second, a comparison was performed for the topology of network motifs across multiple different data types to identify possible divergence from a conserved enrichment pattern in network perturbing diseases. The topology of enriched motifs across all the datasets converged upon a single conserved pattern reported in a previous study which did not appear to diverge dependent upon the type of disease. This report highlights possible methods to improve detection of disease driving motifs that can aid in identifying possible treatment targets in cancer. Finally, networks where only minimally perturbed, suggesting that regulatory programs were run from evolved circuits into a cancer context.
Date Created
2020
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