Periodic Reporting for period 4 - RetroNets (Reverse Engineering Gene Regulatory Networks)
Período documentado: 2021-10-01 hasta 2022-09-30
Gene regulatory networks are an important cellular signal processing mechanism for translating input signals into appropriate phenotypes by modulating expression of the genome. The quantitative details of how cells process information through gene regulatory networks are still poorly understood, but of central importance in a large number of biological processes. Considerable progress has been made in mapping the topology of gene regulatory networks and more recently in deciphering the relationship between promoter sequence and function. Nonetheless, it is not yet possible to computationally predict the output of most native promoters, nor is it trivial to build promoters that integrate signals in a novel and predictive manner. Developing a quantitative understanding of transcriptional regulation, ultimately leading to the ability to predict entire gene regulatory networks will be a significant achievement and a prerequisite for our ability to engineer biological systems.
Gene regulatory networks are at the core of all biological processes, including disease states such as cancer. Furthermore, biotechnology heavily relies on engineered gene regulatory networks for pharmaceutical and other product syntheses. In the near future it can be expected that gene regulatory networks will play an increasingly important and central role in the development of smart and ultra-low-cost diagnostic assays. Despite the obvious importance of gene regulatory networks, they remain relatively poorly understood, limiting our ability to engineer novel complex gene regulatory networks or decipher the regulation or mis-regulation of native gene regulatory networks. Current gene regulatory network engineering still heavily relies on inefficient trial and error approaches. Other engineering disciplines such as electrical and mechanical are much more advanced, allowing the creation of complex systems that can be expected to work as designed (a building, bridge, computer, cell phone, etc.). Our project will provide useful insights into the basic biology and physics of gene regulatory networks, which will hopefully make the process of engineering biological systems such as gene regulatory networks much more robust and efficient.
We are employing a multi-disciplinary approach incorporating biology, engineering, and computational modelling to improve our quantitative understanding of gene regulatory networks by reverse engineering a native GRNs from S. cerevisiae. My research group has developed a powerful set of unique, high-throughput microfluidic technologies that enable the quantitative analysis of gene regulatory networks in vitro and in vivo. Specifically we are quantitatively investigating the yeast phosphate regulatory network under various inorganic phosphate concentrations, developing novel approaches for modulating gene regulatory networks using engineered Zn-finger transcription factors (TF), linking gene regulatory network output to fitness in order to develop an understanding of how networks are optimized and evolve, and reverse engineering an exact functional copy of the native phosphate regulatory network with orthogonal components.
Gene regulatory networks are at the core of all biological processes, including disease states such as cancer. Furthermore, biotechnology heavily relies on engineered gene regulatory networks for pharmaceutical and other product syntheses. In the near future it can be expected that gene regulatory networks will play an increasingly important and central role in the development of smart and ultra-low-cost diagnostic assays. Despite the obvious importance of gene regulatory networks, they remain relatively poorly understood, limiting our ability to engineer novel complex gene regulatory networks or decipher the regulation or mis-regulation of native gene regulatory networks. Current gene regulatory network engineering still heavily relies on inefficient trial and error approaches. Other engineering disciplines such as electrical and mechanical are much more advanced, allowing the creation of complex systems that can be expected to work as designed (a building, bridge, computer, cell phone, etc.). Our project will provide useful insights into the basic biology and physics of gene regulatory networks, which will hopefully make the process of engineering biological systems such as gene regulatory networks much more robust and efficient.
We are employing a multi-disciplinary approach incorporating biology, engineering, and computational modelling to improve our quantitative understanding of gene regulatory networks by reverse engineering a native GRNs from S. cerevisiae. My research group has developed a powerful set of unique, high-throughput microfluidic technologies that enable the quantitative analysis of gene regulatory networks in vitro and in vivo. Specifically we are quantitatively investigating the yeast phosphate regulatory network under various inorganic phosphate concentrations, developing novel approaches for modulating gene regulatory networks using engineered Zn-finger transcription factors (TF), linking gene regulatory network output to fitness in order to develop an understanding of how networks are optimized and evolve, and reverse engineering an exact functional copy of the native phosphate regulatory network with orthogonal components.
The team worked on developing a library of yeast strains, new microfluidic devices for single cell analysis, in vitro transcription factor (TF) protein biochemistry, and in vivo synthetic gene induction systems. We generated a library of yeast strains that enabled us to quantitatively analyze the output of the entire inorganic phosphate regulatory network in yeast. These strains allowed us to precisely map the response of the entire gene regulatory network under different inorganic phosphate starvation conditions. To cope with the large number of strains the team also implemented and further improved a microfluidic technology that allowed us to measure 1152 yeast strains in parallel in a single experiment. Each strain was quantified on the single cell level, with high temporal resolution. Improving on the platform, the team developed an automated a dilution generator that allowed us to measure 96 yeast strains under 12 phosphate conditions. To better understand the biophysics of the master regulator of the inorganic phosphate gene regulatory network, which is the TF Pho4, we developed a high-throughput microfluidic method that allowed us to measure the affinity of TFs to clusters of binding sites. Previous measurements were only able to assess the affinity to a single binding site. Finally, the team has implemented a synthetic gene induction system capable of regulating the expression level of a target gene.
The project resulted in a complete overhaul of how we think about the pho-regulon and how its regulation is achieved. We discovered a previously unknown transcription factor localization state. This discovery now readily explains the observed programmatic states of the pho-regulon. This discovery solves a long standing problem in the field. It also allowed us to put forth a hypothesis that explains how the 3 distinct localization states of the master regulator can be achieved. Unlike previous hypothesis that assumed that the observed systems behavior is achieved through a complex system of positive and negative feedback loops, we propose that simple transporter biophysics in a two-transporter system can give rise to the same phenotypes. We also were able to explore in detail the importance and functional relevance of clusters of low affinity binding sites, showing that these are highly functional with a comprehensive in vivo and in vitro analysis. Finally, we demonstrated that complex gene regulatory networks can be built from the bottom up with entirely synthetic components, and these systems can be predictively engineered. Together these deliverables significantly push the state-of-the-art of gene regulatory network systems and synthetic biology, and provide a foundation for further developments and applications of gene regulatory networks.
The project resulted in a complete overhaul of how we think about the pho-regulon and how its regulation is achieved. We discovered a previously unknown transcription factor localization state. This discovery now readily explains the observed programmatic states of the pho-regulon. This discovery solves a long standing problem in the field. It also allowed us to put forth a hypothesis that explains how the 3 distinct localization states of the master regulator can be achieved. Unlike previous hypothesis that assumed that the observed systems behavior is achieved through a complex system of positive and negative feedback loops, we propose that simple transporter biophysics in a two-transporter system can give rise to the same phenotypes. We also were able to explore in detail the importance and functional relevance of clusters of low affinity binding sites, showing that these are highly functional with a comprehensive in vivo and in vitro analysis. Finally, we demonstrated that complex gene regulatory networks can be built from the bottom up with entirely synthetic components, and these systems can be predictively engineered. Together these deliverables significantly push the state-of-the-art of gene regulatory network systems and synthetic biology, and provide a foundation for further developments and applications of gene regulatory networks.
With this ERC funded project we were able to provide insights into the function of a native eukaryotic gene regulatory network and improve our ability to engineer gene regulatory networks from the bottom up. We mapped the entire functional space of a native gene regulatory network. This provided insights into the specific characteristics that native gene regulatory networks fulfill both in terms of the precise output functions they are able to produce, as well as how precise the upstream input transducers need to be regulated for robust network function. Together these insights provided guidelines on how to engineer robust gene regulatory networks. Our efforts in building gene regulatory networks provided both know-how and tools for building gene regulatory networks. On the one hand the project provided insights on how to design promoters that can give rise to complex output functions approaching those of native promoters. In order to build novel gene regulatory networks the project delivered new synthetic transcriptional regulators and promoters that can be integrated into novel gene regulatory networks.