scholarly journals Stochastic Simulations as a Tool for Assessing Signal Fidelity in Gene Expression in Synthetic Promoter Design

Biology ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 724
Author(s):  
Elena Righetti ◽  
Cansu Uluşeker ◽  
Ozan Kahramanoğulları
Keyword(s):  
Synthetic Biology ◽  
Computer Aided Design ◽  
Reaction Network ◽  
Intrinsic Noise ◽  
Stochastic Simulations ◽  
Fine Tuning ◽  
Promoter Strength ◽  
Synthetic Promoter ◽  
Synthetic Promoters ◽  
Noise Characteristics

The design and development of synthetic biology applications in a workflow often involve connecting modular components. Whereas computer-aided design tools are picking up in synthetic biology as in other areas of engineering, the methods for verifying the correct functioning of living technologies are still in their infancy. Especially, fine-tuning for the right promoter strength to match the design specifications is often a lengthy and expensive experimental process. In particular, the relationship between signal fidelity and noise in synthetic promoter design can be a key parameter that can affect the healthy functioning of the engineered organism. To this end, based on our previous work on synthetic promoters for the E. coli PhoBR two-component system, we make a case for using chemical reaction network models for computational verification of various promoter designs before a lab implementation. We provide an analysis of this system with extensive stochastic simulations at a single-cell level to assess the signal fidelity and noise relationship. We then show how quasi-steady-state analysis via ordinary differential equations can be used to navigate between models with different levels of detail. We compare stochastic simulations with our full and reduced models by using various metrics for assessing noise. Our analysis suggests that strong promoters with low unbinding rates can act as control tools for filtering out intrinsic noise in the PhoBR context. Our results confirm that even simpler models can be used to determine promoters with specific signal to noise characteristics.

scholarly journals Fast and flexible simulation and parameter estimation for synthetic biology using bioscrape

2017 ◽  
Author(s):  
Anandh Swaminathan ◽  
William Poole ◽  
Victoria Hsiao ◽  
Richard M. Murray
Keyword(s):  
Parameter Estimation ◽  
Cell Growth ◽  
Synthetic Biology ◽  
Chemical Reaction ◽  
Growth Models ◽  
Dna Recombination ◽  
Reaction Network ◽  
Stochastic Simulations ◽  
Delay Cell ◽  
Computational Bottleneck

AbstractIn systems and synthetic biology, it is common to build chemical reaction network (CRN) models of biochemical circuits and networks. Although automation and other high-throughput techniques have led to an abundance of data enabling data-driven quantitative modeling and parameter estimation, the intense amount of simulation needed for these methods still frequently results in a computational bottleneck. Here we present bioscrape (Bio-circuit Stochastic Single-cell Reaction Analysis and Parameter Estimation) - a Python package for fast and flexible modeling and simulation of highly customizable chemical reaction networks. Specifically, bioscrape supports deterministic and stochastic simulations, which can incorporate delay, cell growth, and cell division. All functionalities - reaction models, simulation algorithms, cell growth models, and partioning models - are implemented as interfaces in an easily extensible and modular object-oriented framework. Models can be constructed via Systems Biology Markup Language (SBML), a simple internal XML language, or specified programmatically via a Python API. Simulation run times obtained with the package are comparable to those obtained using C code - this is particularly advantageous for computationally expensive applications such as Bayesian inference or simulation of cell lineages. We first show the package’s simulation capabilities on a variety of example simulations of stochastic gene expression. We then further demonstrate the package by using it to do parameter inference on a model of integrase enzyme-mediated DNA recombination dynamics with experimental data. The bioscrape package is publicly available online (https://github.com/ananswam/bioscrape) along with more detailed documentation and examples.

scholarly journals RetroPath2.0: a retrosynthesis workflow for metabolic engineers

2017 ◽  
Author(s):  
Baudoin Delépine ◽  
Thomas Duigou ◽  
Pablo Carbonell ◽  
Jean-Loup Faulon
Keyword(s):  
Synthetic Biology ◽  
Open Source ◽  
Computer Aided Design ◽  
Reaction Network ◽  
Ease Of Use ◽  
Chemical Diversity ◽  
Industrial Biotechnology ◽  
List Type ◽  
Enzyme Promiscuity ◽  
Main Challenge

AbstractSynthetic biology applied to industrial biotechnology is transforming the way we produce chemicals. However, despite advances in the scale and scope of metabolic engineering, the bioproduction process still remains costly. In order to expand the chemical repertoire for the production of next generation compounds, a major engineering biology effort is required in the development of novel design tools that target chemical diversity through rapid and predictable protocols. Addressing that goal involves retrosynthesis approaches that explore the chemical biosynthetic space. However, the complexity associated with the large combinatorial retrosynthesis design space has often been recognized as the main challenge hindering the approach. Here, we provide RetroPath2.0, an automated open source workflow for retrosynthesis based on generalized reaction rules that perform the retrosynthesis search from chassis to target through an efficient and well-controlled protocol. Its easiness of use and the versatility of its applications make of this tool a valuable addition into the biological engineer bench desk. We show through several examples the application of the workflow to biotechnological relevant problems, including the identification of alternative biosynthetic routes through enzyme promiscuity; or the development of biosensors. We demonstrate in that way the ability of the workflow to streamline retrosynthesis pathway design and its major role in reshaping the design, build, test and learn pipeline by driving the process toward the objective of optimizing bioproduction. The RetroPath2.0 workflow is built using tools developed by the bioinformatics and cheminformatics community, because it is open source we anticipate community contributions will likely expand further the features of the workflow.HighlightsState-of-the-art Computer-Aided Design retrosynthesis solutions lack open source and ease of useWe propose RetroPath2.0 a modular and open-source workflow to perform retrosynthesisRetroPath2.0 computes reaction network between Source and Sink sets of compoundsRetroPath2.0 is distributed as a KNIME workflow for desktop computersRetroPath2.0 is ready-for-use and distributed with reaction rulesFundingThis work was supported by the French National Research Agency [ANR-15-CE1-0008], the Biotechnology and Biological Sciences Research Council, Centre for synthetic biology of fine and speciality chemicals [BB/M017702/1]; Synthetic Biology Applications for Protective Materials [EP/N025504/1], and GIP Genopole.

scholarly journals A synthetic promoter library for constitutive gene expression in Lactobacillus plantarum

Microbiology ◽  
2006 ◽  
Vol 152 (4) ◽  
pp. 1011-1019 ◽  
Author(s):  
Ida Rud ◽  
Peter Ruhdal Jensen ◽  
Kristine Naterstad ◽  
Lars Axelsson
Keyword(s):  
Gene Expression ◽  
Lactobacillus Plantarum ◽  
Protein Production ◽  
Consensus Sequence ◽  
Fine Tuning ◽  
Stable Gene ◽  
Synthetic Promoter ◽  
Synthetic Promoters ◽  
Promoter Library ◽  
Wide Range

A synthetic promoter library (SPL) for Lactobacillus plantarum has been developed, which generalizes the approach for obtaining synthetic promoters. The consensus sequence, derived from rRNA promoters extracted from the L. plantarum WCFS1 genome, was kept constant, and the non-consensus sequences were randomized. Construction of the SPL was performed in a vector (pSIP409) previously developed for high-level, inducible gene expression in L. plantarum and Lactobacillus sakei. A wide range of promoter strengths was obtained with the approach, covering 3–4 logs of expression levels in small increments of activity. The SPL was evaluated for the ability to drive β-glucuronidase (GusA) and aminopeptidase N (PepN) expression. Protein production from the synthetic promoters was constitutive, and the most potent promoters gave high protein production with levels comparable to those of native rRNA promoters, and production of PepN protein corresponding to approximately 10–15 % of the total cellular protein. High correlation was obtained between the activities of promoters when tested in L. sakei and L. plantarum, which indicates the potential of the SPL for other Lactobacillus species. The SPL enables fine-tuning of stable gene expression for various applications in L. plantarum.

scholarly journals Refactoring of a synthetic raspberry ketone pathway with EcoFlex

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Simon J. Moore ◽  
Yonek B. Hleba ◽  
Sarah Bischoff ◽  
David Bell ◽  
Karen M. Polizzi ◽  
...  
Keyword(s):  
Gene Expression ◽  
Synthetic Biology ◽  
Combinatorial Libraries ◽  
Value Added ◽  
Microtiter Plate ◽  
Fine Tuning ◽  
Golden Gate ◽  
E Coli ◽  
Fine Chemical ◽  
Raspberry Ketone

Abstract Background  A key focus of synthetic biology is to develop microbial or cell-free based biobased routes to value-added chemicals such as fragrances. Originally, we developed the EcoFlex system, a Golden Gate toolkit, to study genes/pathways flexibly using Escherichia coli heterologous expression. In this current work, we sought to use EcoFlex to optimise a synthetic raspberry ketone biosynthetic pathway. Raspberry ketone is a high-value (~ £20,000 kg−1) fine chemical farmed from raspberry (Rubeus rubrum) fruit. Results  By applying a synthetic biology led design-build-test-learn cycle approach, we refactor the raspberry ketone pathway from a low level of productivity (0.2 mg/L), to achieve a 65-fold (12.9 mg/L) improvement in production. We perform this optimisation at the prototype level (using microtiter plate cultures) with E. coli DH10β, as a routine cloning host. The use of E. coli DH10β facilitates the Golden Gate cloning process for the screening of combinatorial libraries. In addition, we also newly establish a novel colour-based phenotypic screen to identify productive clones quickly from solid/liquid culture. Conclusions  Our findings provide a stable raspberry ketone pathway that relies upon a natural feedstock (L-tyrosine) and uses only constitutive promoters to control gene expression. In conclusion we demonstrate the capability of EcoFlex for fine-tuning a model fine chemical pathway and provide a range of newly characterised promoter tools gene expression in E. coli.

scholarly journals Differential ability of proximal and remote element pairs to cooperate in activating RNA polymerase II transcription.

1991 ◽  
Vol 11 (9) ◽  
pp. 4561-4571 ◽  
Author(s):  
W D Wang ◽  
J D Gralla
Keyword(s):  
Rna Polymerase Ii ◽  
Binding Sites ◽  
Tandem Repeats ◽  
Simian Virus 40 ◽  
Simian Virus ◽  
Cooperative Interaction ◽  
Promoter Strength ◽  
Synthetic Promoters ◽  
Major Late Promoter ◽  
Test Gene

To investigate the synergism or cooperative interaction between transcription elements, we have designed and constructed a series of synthetic polymerase II promoters with different combinations of elements. These include three different CCAAT boxes, which correspond to the binding sites for CP1, CP2, and NFI, a GC box, a CACCC box, and an ATF/CREB-binding site. The synthetic promoters containing these elements in proximal positions were linked to a test gene (CAT). Tandem repeats of AP1- and AP2-binding sites, the simian virus 40 enhancer, and DNA-binding sites for GAL-estrogen receptor were cloned downstream of the test gene. The strength of these promoters was then tested in transient-expression assays in HeLa TK- cells. In the context of the adenovirus major late promoter TATA box, the promoters containing only certain combinations of elements are active in this assay. Some elements appear to cooperate nearly universally, but others exhibit strong selectivity. These results indicate strongly selective synergistic interactions between elements and suggest that levels of promoter strength may be determined by the extent of compatibility between factors bound to proximal and enhancer sites.

Fine Tuning of Rational B-Spline Motions

1998 ◽  
Vol 120 (1) ◽  
pp. 46-51 ◽  
Author(s):  
L. N. Srinivasan ◽  
Q. Jeffrey Ge
Keyword(s):  
Computer Aided Design ◽  
Rate Of Change ◽  
Fine Tuning ◽  
Smoothing Algorithm ◽  
Third Order ◽  
B Spline ◽  
Key Points ◽  
Geometric Discontinuities ◽  
Aided Design ◽  
Three Space

This paper presents two algorithms for fine-tuning rational B-spline motions suitable for Computer Aided Design. The problem of fine-tuning of rational motions is studied as that of fine-tuning rational curves in a projective dual three-space, called the image curves. The path-smoothing algorithm automatically detects and smoothes out the third order geometric discontinuities in the path of a cubic rational B-spline image curve. The speed-smoothing algorithm uses a quintic rational spline image curve to obtain a second-order geometric approximation of the path of a cubic rational B-spline image curve while allowing specification of the speed and the rate of change of speed at the key points to obtain a near constant kinetic energy parameterization. The results have applications in Cartesian trajectory planning in robotics, spatial navigation in visualization and virtual reality systems, as well as mechanical system simulation.

scholarly journals Fine-tuning anti-tumor immunotherapies via stochastic simulations

2012 ◽  
Vol 13 (Suppl 4) ◽  
pp. S8 ◽  
Author(s):  
Giulio Caravagna ◽  
Roberto Barbuti ◽  
Alberto d'Onofrio
Keyword(s):  
Stochastic Simulations ◽  
Fine Tuning

scholarly journals Trends in Synthetic Biology in the Bioeconomy of Non-food-Competing Biofuels

2021 ◽  
Author(s):  
Antônio Luiz Fantinel ◽  
Rogério Margis ◽  
Edson Talamini ◽  
Homero Dewes
Keyword(s):  
Los Angeles ◽  
Synthetic Biology ◽  
Raw Materials ◽  
Renewable Energy Sources ◽  
Redox Balance ◽  
The United States ◽  
Biofuel Production ◽  
Bioenergy Production ◽  
Synthetic Promoters ◽  
Interdisciplinary Field

Despite the acknowledged relevance of renewable energy sources, biofuel production supported by food-related agriculture has faced severe criticism. One way to minimize the considered negative impacts is the use of sources of non-food biomass or wastes. Synthetic biology (SB) embraces a promising complex of technologies for biofuel production from non-edible and sustainable raw materials. Therefore, it is pertinent to identify the global evolution of investments, concepts, and techniques underlying the field in support of policy formulations for sustainable bioenergy production. We mapped the SB scientific knowledge related to biofuels using software that combines information visualization methods, bibliometrics, and data mining algorithms. The United States and China have been the leading countries in developing SB technologies. Technical University of Denmark and Tsinghua University are the institutions with higher centrality and have played prominent roles besides UC-Los Angeles and Delft University Technology. We identified six knowledge clusters under the terms: versatile sugar dehydrogenase, redox balance principle, sesquiterpene production, Saccharomyces cerevisiae, recombinant xylose-fermenting strain, and Clostridium saccharoperbutylacetonicum N1-4. The emerging trends refer to specific microorganisms, processes, and products. Yarrowia lipolytica, Oleaginous yeast, E. coli, Klebsiella pneumoniae, Phaeodactylum tricornutum, and Microalgae are the most prominent microorganisms, mainly from the year 2016 onwards. Anaerobic digestion, synthetic promoters, and genetic analysis appear as the most relevant platforms of new processes. Improved biofuels, bioethanol, and N-butanol are at the frontier of the development of SB-derived products. Synthetic biology is a dynamic interdisciplinary field in environmentally friendly bioenergy production pushed by growing social concerns and the emergent bioeconomy.

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