Stochastic Gene Expression in Single Gene Oscillator Variants

It is infeasible to understand all dynamics in cell, but we can aim to understand the impact of design choices under our control. Here we consider a single gene oscillator as a case study to understand the influence of DNA copy number and repressor choice on the resulting dynamics. We first switch the repressor in the oscillator from the originally published lacI to treRL, a chimeric repressor with a lacI DNA binding domain that is inducible by trehalose. This slightly modified system produces faster and more regular oscillations than the original lacI oscillator. We then compare the treRL oscillator at three different DNA copy numbers. The period and amplitude of oscillations increases as the copy number is decreased. We cannot explain the change in period with differential equation models without changing delays or degradation rates. The correlation and phase coherence between daughter cells after cell division also tend to fall off faster for the lower copy oscillator variants. These results suggest that lower copy number variants of our single gene oscillator produce more synchronized oscillations

Stochastic Gene Expression in Single Gene Oscillator Variants

It is infeasible to understand all dynamics in cell, but we can aim to understand the impact of design choices under our control. Here we consider a single gene oscillator as a case study to understand the influence of DNA copy number and repressor choice on the resulting dynamics. We first switch the repressor in the oscillator from the originally published lacI to treRL, a chimeric repressor with a lacI DNA binding domain that is inducible by trehalose. This slightly modified system produces faster and more regular oscillations than the original lacI oscillator. We then compare the treRL oscillator at three different DNA copy numbers. The period and amplitude of oscillations increases as the copy number is decreased. We cannot explain the change in period with differential equation models without changing delays or degradation rates. The correlation and phase coherence between daughter cells after cell division also tend to fall off faster for the lower copy oscillator variants. These results suggest that lower copy number variants of our single gene oscillator produce more synchronized oscillations

AlloRep: A Repository of Sequence, Structural and Mutagenesis Data for the LacI/GalR Transcription Regulators

Protein families evolve functional variation by accumulating point mutations at functionally important amino acid positions. Homologs in the LacI/GalR family of transcription regulators have evolved to bind diverse DNA sequences and allosteric regulatory molecules. In addition to playing key roles in bacterial metabolism, these proteins have been widely used as a model family for benchmarking structural and functional prediction algorithms. We have collected manually curated sequence alignments for >ﾠ3000 sequences, in vivo phenotypic and biochemical data for >ﾠ5750 LacI/GalR mutational variants, and noncovalent residue contact networks for 65 LacI/GalR homolog structures. Using this rich data resource, we compared the noncovalent residue contact networks of the LacI/GalR subfamilies to design and experimentally validate an allosteric mutant of a synthetic LacI/GalR repressor for use in biotechnology. The AlloRep database (freely available at www.AlloRep.org) is a key resource for future evolutionary studies of LacI/GalR homologs and for benchmarking computational predictions of functional change

Modular, Multi-Input Transcriptional Logic Gating with Orthogonal LacI/GalR Family Chimeras

In prokaryotes, the construction of synthetic, multi-input promoters is constrained by the number of transcription factors that can simultaneously regulate a single promoter. This fundamental engineering constraint is an obstacle to synthetic biologists because it limits the computational capacity of engineered gene circuits. Here, we demonstrate that complex multi-input transcriptional logic gating can be achieved through the use of ligand-inducible chimeric transcription factors assembled from the LacI/GalR family. These modular chimeras each contain a ligand-binding domain and a DNA-binding domain, both of which are chosen from a library of possibilities. When two or more chimeras have the same DNA-binding domain, they independently and simultaneously regulate any promoter containing the appropriate operator site. In this manner, simple transcriptional AND gating is possible through the combination of two chimeras, and multiple-input AND gating is possible with the simultaneous use of three or even four chimeras. Furthermore, we demonstrate that orthogonal DNA-binding domains and their cognate operators allow the coexpression of multiple, orthogonal AND gates. Altogether, this work provides synthetic biologists with novel, ligand-inducible logic gates and greatly expands the possibilities for engineering complex synthetic gene circuits

Transcription Factor-Based Screens and Synthetic Selections for Microbial Small-Molecule Biosynthesis

Continued advances in metabolic engineering are increasing the number of small molecules being targeted for microbial production. Pathway yields and productivities, however, are often suboptimal, and strain improvement remains a persistent challenge given that the majority of small molecules are difficult to screen for and their biosynthesis does not improve host fitness. In this work, we have developed a generalized approach to screen or select for improved small-molecule biosynthesis using transcription factor-based biosensors. Using a tetracycline resistance gene 3′ of a small-molecule inducible promoter, host antibiotic resistance, and hence growth rate, was coupled to either small-molecule concentration in the growth medium or a small-molecule production phenotype. Biosensors were constructed for two important chemical classes, dicarboxylic acids and alcohols, using transcription factor-promoter pairs derived from <i>Pseudomonas putida</i>, <i>Thauera butanivorans</i>, or <i>E. coli</i>. Transcription factors were selected for specific activation by either succinate, adipate, or 1-butanol, and we demonstrate product-dependent growth in <i>E. coli</i> using all three compounds. The 1-butanol biosensor was applied in a proof-of-principle liquid culture screen to optimize 1-butanol biosynthesis in engineered <i>E. coli</i>, identifying a pathway variant yielding a 35% increase in 1-butanol specific productivity through optimization of enzyme expression levels. Lastly, to demonstrate the capacity to select for enzymatic activity, the 1-butanol biosensor was applied as synthetic selection, coupling <i>in vivo</i> 1-butanol biosynthesis to <i>E. coli</i> fitness, and an 120-fold enrichment for a 1-butanol production phenotype was observed following a single round of positive selection

Predicting Transcriptional Output of Synthetic Multi-input Promoters

Recent advances in synthetic biology have led to a wealth of well-characterized genetic parts. As parts libraries grow, so too does the potential to create novel multi-input promoters that integrate disparate signals to determine transcriptional output. Our ability to construct such promoters will outpace our ability to characterize promoter performance, due to the vast number of input combinations. In this study, we examine the input–output relations of recently developed synthetic multi-input promoters and describe two methods for predicting their behavior. The first method uses 1-dimensional induction data obtained from experiments on single-input systems to predict the <i>n</i>-dimensional induction responses of systems with <i>n</i> inputs. We demonstrate that this approach accurately predicts Boolean (on/off) responses of multi-input systems consisting of novel chimeric transcription factors and hybrid promoters in <i>Escherichia coli</i>. The second method uses only a small amount of multi-input response data to accurately predict analog system response over the entire landscape of input combinations. Taken together, these methods facilitate the design of synthetic circuits that utilize multi-input promoters

Tuning the dynamic range of bacterial promoters regulated by ligand-inducible transcription factors

For synthetic gene circuits to behave as designed, ligand-inducible promoters should display predictable ON/OFF characteristics. Here the authors design multi-input hybrid promoters to build transcriptional logic gates