Combinatorial promoter design for engineering noisy gene expression

RNAi-based Boolean gates in the yeast Saccharomyces cerevisiae

Boolean gates, the fundamental components of digital circuits, have been widely investigated in synthetic biology because they permit the fabrication of biosensors and facilitate biocomputing. This study was conducted to design and construct Boolean gates in the yeast Saccharomyces cerevisiae, the main component of which was the RNA interference pathway (RNAi) that is naturally absent from the budding yeast cells. We tested different expression cassettes for the siRNA precursor (a giant hairpin sequence, a DNA fragment-flanked by one or two introns-between convergent promoters or transcribed separately in the sense and antisense directions) and placed different components under the control of the circuit inputs (i.e., the siRNA precursor or proteins such as the Dicer and the Argonaute). We found that RNAi-based logic gates are highly sensitive to promoter leakage and, for this reason, challenging to implement in vivo. Convergent-promoter architecture turned out to be the most reliable solution, even though the overall best performance was achieved with the most difficult design based on the siRNA precursor as a giant hairpin.

Biosensor-assisted CRISPRi high-throughput screening to identify genetic targets in Zymomonas mobilis for high d-lactate production

Lactate is an important monomer for the synthesis of poly-lactate (PLA), which is a substitute for the petrochemical plastics. To achieve the goal of high lactate titer, rate, and yield for commercial production, efficient lactate production pathway is needed as well as genetic targets that affect high lactate production and tolerance. In this study, an LldR-based d-lactate biosensor with a broad dynamic range was first applied into Zymomonas mobilis to select mutant strains with strong GFP fluorescence, which could be the mutant strains with increased d-lactate production. Then, LldR-based d-lactate biosensor was combined with a genome-wide CRISPR interference (CRISPRi) library targeting the entire genome to generate thousands of mutants with gRNA targeting different genetic targets across the whole genome. Specifically, two mutant libraries were selected containing 105 and 104 mutants with different interference sites from two rounds of fluorescence-activated cell sorting (FACS), respectively. Two genetic targets of ZMO1323 and ZMO1530 were characterized and confirmed to be associated with the increased d-lactate production, further knockout of ZMO1323 and ZMO1530 resulted in a 15% and 21% increase of d-lactate production, respectively. This work thus not only established a high-throughput approach that combines genome-scale CRISPRi and biosensor-assisted screening to identify genetic targets associated with d-lactate production in Z. mobilis, but also provided a feasible high-throughput screening approach for rapid identification of genetic targets associated with strain performance for other industrial microorganisms.

Engineered Bacillus subtilis as oral probiotics to enhance clearance of blood lactate

Elevated lactate concentrations are implicated in various acute and chronic diseases such as sepsis and mitochondrial dysfunction, respectively. Conversely, ineffective lactate clearance is associated with poor clinical prognoses and high mortality in these diseases. While several groups have proposed using small molecule inhibitors and enzyme replacement to reduce circulating lactate, there are few practical and effective ways to manage this condition. Recent evidence suggests that lactate is exchanged between systemic circulation and the gut, allowing bidirectional modulation between the gut microbiota and peripheral tissues. Inspired by these findings, this work seeks to engineer spore-forming probiotic B. subtilis strains to enable intestinal delivery of lactate oxidase as a therapeutic enzyme. After strain optimization, we showed that oral administration of engineered B. subtilis spores to the gut of mice reduced elevations in blood lactate in two different mouse models involving exogenous challenge or pharmacologic perturbation without disrupting gut microbiota composition, liver function, or immune homeostasis. Taken together, through the oral delivery of engineered probiotic spores to the gastrointestinal tract, our proof-of-concept study offers a practical strategy to aid in the management of disease states with elevated blood lactate and provides a new approach to 'knocking down' circulating metabolites to help understand their roles in host physiological and pathological processes.

Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators

A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.

Development of new binary expression systems for plant synthetic biology

KEY MESSAGE

A novel plant binary expression system was developed from the compactin biosynthetic pathway 27 of Penicillium citrinum ML-236B. The system achieved >fivefold activation of gene expression in 28 transgenic tobacco. A diverse and well-characterized genetic toolset is fundamental to achieve the overall goals of plant synthetic biology. To properly coordinate expression of a multigene pathway, this toolset should include binary systems that control gene expression at the level of transcription. In plants, few highly functional, orthogonal transcriptional regulators have been identified. Here, we describe the process of developing synthetic plant transcription factors using regulatory elements from the Penicillium citrinum ML-236B (compactin) pathway. This pathway contains several genes including mlcA and mlcC that are transcriptionally regulated in a dose-dependent manner by the activator mlcR. In Nicotiana benthamiana, we first expressed mlcR with several cognate synthetic promoters driving expression of GFP. Synthetic promoters contained operator sequences from the compactin gene cluster. Following identification of the most active synthetic promoter, the DNA-binding domain from mlcR was used to generate chimeric transcription factors containing variable activation domains, including QF from the Neurospora crassa Q-system. Activity was measured at both protein and RNA levels which correlated with an R2 value of 0.94. A synthetic transcription factor with a QF activation domain increased gene expression from its synthetic promoter up to sixfold in N. benthamiana. Two systems were characterized in transgenic tobacco plants. The QF-based plants maintained high expression in tobacco, increasing expression from the cognate synthetic promoter by fivefold. Transgenic plants and non-transgenic plants were morphologically indistinguishable. The framework of this study can easily be adopted for other putative transcription factors to continue improvement of the plant synthetic biology toolbox.

Divergent directed evolution of a TetR-type repressor towards aromatic molecules

Reprogramming cellular behaviour is one of the hallmarks of synthetic biology. To this end, prokaryotic allosteric transcription factors (aTF) have been repurposed as versatile tools for processing small molecule signals into cellular responses. Expanding the toolbox of aTFs that recognize new inducer molecules is of considerable interest in many applications. Here, we first establish a resorcinol responsive aTF-based biosensor in Escherichia coli using the TetR-family repressor RolR from Corynebacterium glutamicum. We then perform an iterative walk along the fitness landscape of RolR to identify new inducer specificities, namely catechol, methyl catechol, caffeic acid, protocatechuate, L-DOPA, and the tumour biomarker homovanillic acid. Finally, we demonstrate the versatility of these engineered aTFs by transplanting them into the model eukaryote Saccharomyces cerevisiae. This work provides a framework for efficient aTF engineering to expand ligand specificity towards novel molecules on laboratory timescales, which, more broadly, is invaluable across a wide range of applications such as protein and metabolic engineering, as well as point-of-care diagnostics.

Logic Circuits Based on 2A Peptide Sequences in the Yeast Saccharomyces cerevisiae

Gene digital circuits are the subject of many studies in Synthetic Biology due to their various applications from pollutant detection to medical diagnostics and biocomputing. Complex logic functions are calculated via small genetic components that mimic Boolean gates, i.e., they implement basic logic operations. Gates interact by exchanging proteins or noncoding RNAs. To carry out logic operations in the yeast Saccharomyces cerevisiae, we chose three bacterial repressors commonly used for proofs of concept in Synthetic Biology, namely, TetR, LexA, and LacI. We coexpressed them via synthetic polycistronic cassettes based on 2A peptide sequences. Our initial results highlighted the successful application of four 2A peptides─from Equine rhinitis B virus-1 (ERBV-1 2A), Operophtera brumata cypovirus 18 (OpbuCPV18 2A), Ljungan virus (LV2A), and Thosea asigna virus (T2A)─to the construction of single and two-input Boolean gates. In order to improve protein coexpression, we modified the original 2A peptides with the addition of the glycine-serine-glycine (GSG) prefix or by using two different 2As sequences in tandem. Remarkably, we finally realized a well-working tri-cistronic vector that carried LexA-HBD(hER), TetR, and LacI separated, in the order, by GSG-T2A and ERBV-1 2A. This plasmid led to the implementation of three-input circuits containing AND and OR gates. Taken together, polycistronic constructs simplify the cloning and coexpression of multiple proteins with a dramatic reduction in the complexity of gene digital circuits.

Natural promoters and promoter engineering strategies for metabolic regulation in Saccharomyces cerevisiae

Sharomyces cerevisiae is currently one of the most important foreign gene expression systems. S. cerevisiae is an excellent host for high-value metabolite cell factories due to its advantages of simplicity, safety, and nontoxicity. A promoter, as one of the basic elements of gene transcription, plays an important role in regulating gene expression and optimizing metabolic pathways. Promoters control the direction and intensity of transcription, and the application of promoters with different intensities and performances will largely determine the effect of gene expression and ultimately affect the experimental results. Due to its significant role, there have been many studies on promoters for decades. While some studies have explored and analyzed new promoters with different functions, more studies have focused on artificially modifying promoters to meet their own scientific needs. Thus, this article reviews current research on promoter engineering techniques and related natural promoters in S. cerevisiae. First, we introduce the basic structure of promoters and the classification of natural promoters. Then, the classification of various promoter strategies is reviewed. Finally, by grouping related articles together using various strategies, this review anticipates the future development direction of promoter engineering.

Promoter-proximal introns impact recombinant amylase expression in Saccharomyces cerevisiae

Consolidated bioprocessing (CBP) of starch requires recombinant Saccharomyces cerevisiae strains that produce raw starch-degrading enzymes and ferment the resultant sugars to ethanol in a single step. In this study, the native S. cerevisiae COX4 and RPS25A promoter-proximal introns were evaluated for enhanced expression of amylase genes (ateA, temA or temG_Opt) under the control of an S. cerevisiae promoter (ENO1P, TEF1P, TDH3P, or HXT7P). The results showed that different promoters and promoter-intron combinations differentially affected recombinant amylase production: ENO1P-COX4i and TDH3P-RPS25Ai were the best promoters for AteA, followed closely by HXT7P. The latter was also the best promoter for TemA and TemG production, followed closely by TDH3P-RPS25Ai for both these enzymes. Introducing promoter-proximal introns increased amylase activity up to 62% in Y294[ENO-COX-AteA] and Y294[TDH3-RPS-TemA], a significant improvement relative to the intron-less promoters. Strains co-expressing both an α-amylase and glucoamylase genes yielded up to 56 g/L ethanol from 20% w/v raw starch, with a higher carbon conversion observed with strains co-expressing TDH3P-RPS25Ai-temG_Opt than HXT7P-temG_Opt. The study showed that promoter-proximal introns can enhance amylase activity in S. cerevisiae and suggest that these alternative cassettes may also be considered for expression in more efficient ethanol-producing industrial yeast strains for raw starch CBP.

Engineering a two-gene system to operate as a highly sensitive biosensor or a sharp switch upon induction with β-estradiol

The human estrogen receptor has been used for about thirty years, in the yeast S. cerevisiae, as a component of chimeric transcription factors. Its ligand, β-estradiol, permits to control the protein translocation into the nucleus and, as a consequence, the expression of the gene(s) targeted by the synthetic transcription factor. Activators that are orthogonal to the yeast genome have been realized by fusing the human estrogen receptor to an activation and a DNA-binding domain from bacteria, viruses, or higher eukaryotes. In this work, we optimized the working of a β-estradiol-sensing device-in terms of detection range and maximal output signal-where the human estrogen receptor is flanked by the bacterial protein LexA and either the strong VP64 (from herpes simplex virus) or the weaker B42 (from E. coli) activation domain. We enhanced the biosensor performance by thoroughly engineering both the chimeric activator and the reporter protein expression cassette. In particular, we constructed a synthetic promoter-where transcription is induced by the chimeric activators-based on the core sequence of the yeast CYC1 promoter, by tuning parameters such as the length of the 5' UTR, the distance between adjacent LexA binding sites (operators), and the spacing between the whole operator region and the main promoter TATA box. We found a configuration that works both as a highly sensitive biosensor and a sharp switch depending on the concentration of the chimeric activator and the strength of its activation domain.

A novel Candida glabrata doxycycline-inducible system for in vitro/in vivo use

Candida glabrata is an important pathogen causing superficial to invasive disease in human. Conditional expression systems are helpful in addressing the function of genes and especially when they can be applied to in vivo studies. Tetracycline-dependent regulation systems have been used in diverse fungi to turn-on (Tet-on) or turn-off (Tet-off) gene expression either in vitro but also in vivo in animal models. Up to now, only a Tet-off expression has been constructed for gene expression in C. glabrata. Here, we report a Tet-on gene expression system which can be used in vitro and in vivo in any C. glabrata genetic background. This system was used in a mice model of systemic infection to demonstrate that the general amino acid permease Gap1 is important for C. glabrata virulence.

Stochastic gene transcription with non-competitive transcription regulatory architecture

The transcription factors, such as activators and repressors, can interact with the promoter of gene either in a competitive or non-competitive way. In this paper, we construct a stochastic model with non-competitive transcriptional regulatory architecture and develop an analytical theory that re-establishes the experimental results with an improved data fitting. The analytical expressions in the theory allow us to study the nature of the system corresponding to any of its parameters and hence, enable us to find out the factors that govern the regulation of gene expression for that architecture. We notice that, along with transcriptional reinitiation and repressors, there are other parameters that can control the noisiness of this network. We also observe that, the Fano factor (at mRNA level) varies from sub-Poissonian regime to super-Poissonian regime. In addition to the aforementioned properties, we observe some anomalous characteristics of the Fano factor (at mRNA level) and that of the variance of protein at lower activator concentrations in the presence of repressor molecules. This model is useful to understand the architecture of interactions which may buffer the stochasticity inherent to gene transcription.

A Versatile Transcription Factor Biosensor System Responsive to Multiple Aromatic and Indole Inducers

Allosteric transcription factor (aTF) biosensors are valuable tools for engineering microbes toward a multitude of applications in metabolic engineering, biotechnology, and synthetic biology. One of the challenges toward constructing functional and diverse biosensors in engineered microbes is the limited toolbox of identified and characterized aTFs. To overcome this, extensive bioprospecting of aTFs from sequencing databases, as well as aTF ligand-specificity engineering are essential in order to realize their full potential as biosensors for novel applications. In this work, using the TetR-family repressor CmeR from Campylobacter jejuni, we construct aTF genetic circuits that function as salicylate biosensors in the model organisms Escherichia coli and Saccharomyces cerevisiae. In addition to salicylate, we demonstrate the responsiveness of CmeR-regulated promoters to multiple aromatic and indole inducers. This relaxed ligand specificity of CmeR makes it a useful tool for detecting molecules in many metabolic engineering applications, as well as a good target for directed evolution to engineer proteins that are able to detect new and diverse chemistries.

Synthetic 3'-UTR valves for optimal metabolic flux control in Escherichia coli

As the design of genetic circuitry for synthetic biology becomes more sophisticated, diverse regulatory bioparts are required. Despite their importance, well-characterized 3′-untranslated region (3′-UTR) bioparts are limited. Thus, transcript 3′-ends require further investigation to understand the underlying regulatory role and applications of the 3′-UTR. Here, we revisited the use of Term-Seq in the Escherichia coli strain K-12 MG1655 to enhance our understanding of 3′-UTR regulatory functions and to provide a diverse collection of tunable 3′-UTR bioparts with a wide termination strength range. Comprehensive analysis of 1,629 transcript 3′-end positions revealed multiple 3′-termini classes generated through transcription termination and RNA processing. The examination of individual Rho-independent terminators revealed a reduction in downstream gene expression over a wide range, which led to the design of novel synthetic metabolic valves that control metabolic fluxes in branched pathways. These synthetic metabolic valves determine the optimal balance of heterologous pathways for maximum target biochemical productivity. The regulatory strategy using 3′-UTR bioparts is advantageous over promoter- or 5′-UTR-based transcriptional control as it modulates gene expression at transcription levels without trans-acting element requirements (e.g. transcription factors). Our results provide a foundational platform for 3′-UTR engineering in synthetic biology applications.

Principles for the design of multicellular engineered living systems

Remarkable progress in bioengineering over the past two decades has enabled the formulation of fundamental design principles for a variety of medical and non-medical applications. These advancements have laid the foundation for building multicellular engineered living systems (M-CELS) from biological parts, forming functional modules integrated into living machines. These cognizant design principles for living systems encompass novel genetic circuit manipulation, self-assembly, cell-cell/matrix communication, and artificial tissues/organs enabled through systems biology, bioinformatics, computational biology, genetic engineering, and microfluidics. Here, we introduce design principles and a blueprint for forward production of robust and standardized M-CELS, which may undergo variable reiterations through the classic design-build-test-debug cycle. This Review provides practical and theoretical frameworks to forward-design, control, and optimize novel M-CELS. Potential applications include biopharmaceuticals, bioreactor factories, biofuels, environmental bioremediation, cellular computing, biohybrid digital technology, and experimental investigations into mechanisms of multicellular organisms normally hidden inside the "black box" of living cells.

Independent control of mean and noise by convolution of gene expression distributions

Gene expression noise can reduce cellular fitness or facilitate processes such as alternative metabolism, antibiotic resistance, and differentiation. Unfortunately, efforts to study the impacts of noise have been hampered by a scaling relationship between noise and expression level from individual promoters. Here, we use theory to demonstrate that mean and noise can be controlled independently by expressing two copies of a gene from separate inducible promoters in the same cell. We engineer low and high noise inducible promoters to validate this result in Escherichia coli, and develop a model that predicts the experimental distributions. Finally, we use our method to reveal that the response of a promoter to a repressor is less sensitive with higher repressor noise and explain this result using a law from probability theory. Our approach can be applied to investigate the effects of noise on diverse biological pathways or program cellular heterogeneity for synthetic biology applications.

Competitive dCas9 binding as a mechanism for transcriptional control

Catalytically dead Cas9 (dCas9) is a programmable transcription factor that can be targeted to promoters through the design of small guide RNAs (sgRNAs), where it can function as an activator or repressor. Natural promoters use overlapping binding sites as a mechanism for signal integration, where the binding of one can block, displace, or augment the activity of the other. Here, we implemented this strategy in Escherichia coli using pairs of sgRNAs designed to repress and then derepress transcription through competitive binding. When designed to target a promoter, this led to 27-fold repression and complete derepression. This system was also capable of ratiometric input comparison over two orders of magnitude. Additionally, we used this mechanism for promoter sequence-independent control by adopting it for elongation control, achieving 8-fold repression and 4-fold derepression. This work demonstrates a new genetic control mechanism that could be used to build analog circuit or implement cis-regulatory logic on CRISPRi-targeted native genes.

Engineering of cis-Element in Saccharomyces cerevisiae for Efficient Accumulation of Value-Added Compound Squalene via Downregulation of the Downstream Metabolic Flux

Transcriptional downregulation is widely used for metabolic flux control. Here, marO, a cis-element of Escherichia coli mar operator, was explored to engineer promoters of Saccharomyces cerevisiae for downregulation. First, the ADH1 promoter (P_ADH1) and its enhanced variant P_UADH1 were engineered by insertion of marO into different sites, which resulted in decrease in both gfp5 transcription and GFP fluorescence intensity to various degrees. Then, marO was applied to engineer the native ERG1 and ERG11 promoters due to their importance for accumulation of value-added intermediates squalene and lanosterol. Elevated squalene content (4.9-fold) or lanosterol content (4.8-fold) and 91 or 28% decrease in ergosterol content resulted from the marO-engineered promoter P_ERG1(M5) or P_ERG11(M3), respectively, indicating the validity of the marO-engineered promoters in metabolic flux control. Furthermore, squalene production of 3.53 g/L from cane molasses, a cheap and bulk substrate, suggested the cost-effective and promising potential for squalene production.

Sequence polarity between the promoter and the adjacent gene modulates promoter activity

Promoter engineering has been employed as a strategy to enhance and optimize the production of bio-products. Availability of promoters with predictable activities is needed for downstream application. However, whether promoter activity remains the same in different gene contexts remains unknown. Six consecutive promoters that have previously been determined to have different activity levels were used to construct six different versions of plasmid backbone pTH1227, followed by inserted genes encoding two polymer-producing enzymes. In some cases, promoter activity in the presence of inserted genes did not correspond to the reported activity levels in a previous study. After removing the inserted genes, the activity of these promoters returned to their previously reported level. These changes were further confirmed to occur at the transcriptional level. Polymer production using our newly constructed plasmids showed polymer accumulation levels corresponding to the promoter activity reported in our study. Our study demonstrated the importance of re-assessing promoter activity levels with regard to gene context, which could influence promoter activity, leading to different outcomes in downstream applications.

A precisely adjustable, variation-suppressed eukaryotic transcriptional controller to enable genetic discovery

Conditional expression of genes and observation of phenotype remain central to biological discovery. Current methods enable either on/off or imprecisely controlled graded gene expression. We developed a 'well-tempered' controller, WTC₈₄₆, for precisely adjustable, graded, growth condition independent expression of genes in Saccharomyces cerevisiae. Controlled genes are expressed from a strong semisynthetic promoter repressed by the prokaryotic TetR, which also represses its own synthesis; with basal expression abolished by a second, 'zeroing' repressor. The autorepression loop lowers cell-to-cell variation while enabling precise adjustment of protein expression by a chemical inducer. WTC₈₄₆ allelic strains in which the controller replaced the native promoters recapitulated known null phenotypes (CDC42, TPI1), exhibited novel overexpression phenotypes (IPL1), showed protein dosage-dependent growth rates and morphological phenotypes (CDC28, TOR2, PMA1 and the hitherto uncharacterized PBR1), and enabled cell cycle synchronization (CDC20). WTC₈₄₆ defines an 'expression clamp' allowing protein dosage to be adjusted by the experimenter across the range of cellular protein abundances, with limited variation around the setpoint.

Saccharomyces cerevisiae Promoter Engineering before and during the Synthetic Biology Era

Simple Summary

Promoters are DNA sequences where the process of transcription starts. They can work constitutively or be controlled by environmental signals of different types. The quantity of proteins and RNA present in yeast genetic circuits highly depends on promoter strength. Hence, they have been deeply studied and modified over, at least, the last forty years, especially since the year 2000 when Synthetic Biology was born. Here, we present how promoter engineering changed over these four decades and discuss its possible future directions due to novel computational methods and technology.

Abstract

Synthetic gene circuits are made of DNA sequences, referred to as transcription units, that communicate by exchanging proteins or RNA molecules. Proteins are, mostly, transcription factors that bind promoter sequences to modulate the expression of other molecules. Promoters are, therefore, key components in genetic circuits. In this review, we focus our attention on the construction of artificial promoters for the yeast S. cerevisiae, a popular chassis for gene circuits. We describe the initial techniques and achievements in promoter engineering that predated the start of the Synthetic Biology epoch of about 20 years. We present the main applications of synthetic promoters built via different methods and discuss the latest innovations in the wet-lab engineering of novel promoter sequences.

Interplay between genetic, epigenetic, and gene expression variability: Considering complexity in evolvability

Genetic variability, epigenetic variability, and gene expression variability (noise) are generally considered independently in their relationship with phenotypic variation. However, they appear to be intrinsically interconnected and influence it in combination. The study of the interplay between genetic and epigenetic variability has the longest history. This article rather considers the introduction of gene expression variability in its relationships with the two others and reviews for the first time experimental evidences over the four relationships connected to gene expression noise. They show how introducing this third source of variability complicates the way of thinking evolvability and the emergence of biological novelty. Finally, cancer cells are proposed to be an ideal model to decipher the dynamic interplay between genetic, epigenetic, and gene expression variability when one of them is either experimentally increased or therapeutically targeted. This interplay is also discussed in an evolutionary perspective in the context of cancer cell drug resistance.

Multidimensional Characterization of Parts Enhances Modeling Accuracy in Genetic Circuits

Mathematical models can aid the design of genetic circuits, but may yield inaccurate results if individual parts are not modeled at the appropriate resolution. To illustrate the importance of this concept, we study transcriptional cascades consisting of two inducible synthetic transcription factors connected in series. Despite the simplicity of this design, we find that accurate prediction of circuit behavior requires mapping the dose responses of each circuit component along the dimensions of both its expression level and its inducer concentration. Using this multidimensional characterization, we were able to computationally explore the behavior of 16 different circuit designs. We experimentally verified a subset of these predictions and found substantial agreement. This method of biological part characterization enables the use of models to identify (un)desired circuit behaviors prior to experimental implementation, thus shortening the design-build-test cycle for more complex circuits.

Uncoupling gene expression noise along the central dogma using genome engineered human cell lines

Eukaryotic protein synthesis is an inherently stochastic process. This stochasticity stems not only from variations in cell content between cells but also from thermodynamic fluctuations in a single cell. Ultimately, these inherently stochastic processes manifest as noise in gene expression, where even genetically identical cells in the same environment exhibit variation in their protein abundances. In order to elucidate the underlying sources that contribute to gene expression noise, we quantify the contribution of each step within the process of protein synthesis along the central dogma. We uncouple gene expression at the transcriptional, translational, and post-translational level using custom engineered circuits stably integrated in human cells using CRISPR. We provide a generalized framework to approximate intrinsic and extrinsic noise in a population of cells expressing an unbalanced two-reporter system. Our decomposition shows that the majority of intrinsic fluctuations stem from transcription and that coupling the two genes along the central dogma forces the fluctuations to propagate and accumulate along the same path, resulting in increased observed global correlation between the products.

Buffering noise: KAT2A modular contributions to stabilization of transcription and cell identity in cancer and development

KAT2A is a histone acetyltransferase recently identified as a vulnerability in at least some forms of Acute Myeloid Leukemia (AML). Its loss or inhibition prompts leukemia stem cells out of self-renewal and into differentiation with ultimate exhaustion of the leukemia pool. We have recently linked the Kat2a requirement in AML to control of transcriptional noise, reflecting an evolutionary-conserved role of Kat2a in promoting burst-like promoter activity and stabilizing gene expression. We suggest that through this role, Kat2a contributes to preservation of cell identity. KAT2A exerts its acetyltransferase activity in the context of two macromolecular complexes, Spt-Ada-Gcn5-Acetyltransferase (SAGA) and Ada-Two-A-Containing (ATAC), but the specific contribution of each complex to stabilization of gene expression is currently unknown. By reviewing specific gene targets and requirements of the two complexes in cancer and development, we suggest that SAGA regulates lineage-specific programs, and ATAC maintains biosynthetic activity through control of ribosomal protein and translation-associated genes, on which cells may be differentially dependent. While our data suggest that KAT2A-mediated regulation of transcriptional noise in AML may be exerted through ATAC, we discuss potential caveats and probe general vs. complex-specific contributions of KAT2A to transcriptional stability, with implications for control and perturbation of cell identity.

Promoter Architecture and Promoter Engineering in Saccharomyces cerevisiae

Promoters play an essential role in the regulation of gene expression for fine-tuning genetic circuits and metabolic pathways in Saccharomyces cerevisiae (S. cerevisiae). However, native promoters in S. cerevisiae have several limitations which hinder their applications in metabolic engineering. These limitations include an inadequate number of well-characterized promoters, poor dynamic range, and insufficient orthogonality to endogenous regulations. Therefore, it is necessary to perform promoter engineering to create synthetic promoters with better properties. Here, we review recent advances related to promoter architecture, promoter engineering and synthetic promoter applications in S. cerevisiae. We also provide a perspective of future directions in this field with an emphasis on the recent advances of machine learning based promoter designs.

Orthogonal tuning of gene expression noise using CRISPR-Cas

The control of gene expression noise is important for improving drug treatment and the performance of synthetic biological systems. Previous work has tuned gene expression noise by changing the rate of transcription initiation, mRNA degradation, and mRNA translation. However, these methods are invasive: they require changes to the target genetic components. Here, we create an orthogonal system based on CRISPR-dCas9 to tune gene expression noise. Specifically, we modulate the gene expression noise of a reporter gene in Escherichia coli by incorporating CRISPR activation and repression (CRISPRar) simultaneously in a single cell. The CRISPRar uses a single dCas9 that recognizes two different single guide RNAs (sgRNA). We build a library of sgRNA variants with different expression activation and repression strengths. We find that expression noise and mean of a reporter gene can be tuned independently by CRISPRar. Our results suggest that the expression noise is tuned by the competition between two sgRNAs that modulate the binding of RNA polymerase to promoters. The CRISPRar may change how we tune expression noise at the genomic level. Our work has broad impacts on the study of gene functions, phenotypical heterogeneity, and genetic circuit control.

A Synthetic Malonyl-CoA Metabolic Oscillator in Komagataella phaffii

Malonyl-CoA is a key metabolic molecule that participates in a diverse range of physiological responses and can act as a building block for a variety of value-added pharmaceuticals and chemicals. The cytosolic malonyl-CoA concentration is usually very low, and thus dynamic metabolic control of malonyl-CoA variation will aid its stable formation and efficient consumption. We developed a synthetic malonyl-CoA metabolic oscillator in yeast. A synthetic regulatory protein, Prm1-FapR, was constructed by fusing a yeast transcriptional activator, Prm1, with a bacterial malonyl-CoA-sensitive transcription repressor, FapR. Two oppositely regulated biosensors were then engineered. A total of 18 hybrid promoter variants were designed, each carrying the operator sequence (fapO) of FapR and the core promoter of P_AOX1 (cP_AOX1), which is naturally regulated by Prm1. The promoter activities of these variants, regulated by Prm1-FapR, were tested. Through this process, a sensor for Prm1-FapR/(-52)fapO-P_AOX1 carrying an activation/deactivation regulation module was built. Meanwhile, 24 promoter variants of P_GAP with fapO inserted were designed and tested using the fusion regulator, giving a sensor for Prm1-FapR/P_GAP-(+22) fapO that contained a repression/derepression regulation module. Both sensors were subsequently integrated into a single cell, which exhibited correct metabolic switching of eGFP and mCherry reporters following manipulation of cytosolic malonyl-CoA levels. The Prm1-FapR/(-52)fapO-P_AOX1 and the Prm1-FapR/P_GAP-(+22)fapO were also used to control the malonyl-CoA source and sink pathways, respectively, for the synthesis of 6-methylsalicylic acid. This finally led to an oscillatory metabolic mode of cytosolic malonyl-CoA. Such a metabolator is useful in exploring potential industrial and biomedical applications not limited by natural cellular behavior.

Engineering Life: A Review of Synthetic Biology

Synthetic biology is a field of scientific research that applies engineering principles to living organisms and living systems. It is a field that is increasing in scope with respect to organisms engineered, practical outcomes, and systems integration. There is a commercial dimension as well, where living organisms are engineered as green technologies that could offer alternatives to industrial standards in the pharmaceutical and petroleum-based chemical industries. This review attempts to provide an introduction to this field as well as a consideration of important contributions that exemplify how synthetic biology may be commensurate or even disproportionate with the complexity of living systems. The engineerability of living systems remains a difficult task, yet advancements are reported at an ever-increasing pace.

High-Resolution Scanning of Optimal Biosensor Reporter Promoters in Yeast

Small-molecule binding allosteric transcription factors (aTFs) derived from bacteria enable real-time monitoring of metabolite abundances, high-throughput screening of genetic designs, and dynamic control of metabolism. Yet, engineering of reporter promoter designs of prokaryotic aTF biosensors in eukaryotic cells is complex. Here we investigate the impact of aTF binding site positions at single-nucleotide resolution in >300 reporter promoter designs in Saccharomyces cerevisiae. From this we identify biosensor output landscapes with transient and distinct aTF binding site position effects for aTF repressors and activators, respectively. Next, we present positions for tunable reporter promoter outputs enabling metabolite-responsive designs for a total of four repressor-type and three activator-type aTF biosensors with dynamic output ranges up to 8- and 26-fold, respectively. This study highlights aTF binding site positions in reporter promoters as key for successful biosensor engineering and that repressor-type aTF biosensors allows for more flexibility in terms of choice of binding site positioning compared to activator-type aTF biosensors.

Controlling cell-to-cell variability with synthetic gene circuits

Cell-to-cell variability originating, for example, from the intrinsic stochasticity of gene expression, presents challenges for designing synthetic gene circuits that perform robustly. Conversely, synthetic biology approaches are instrumental in uncovering mechanisms underlying variability in natural systems. With a focus on reducing noise in individual genes, the field has established a broad synthetic toolset. This includes noise control by engineering of transcription and translation mechanisms either individually, or in combination to achieve independent regulation of mean expression and its variability. Synthetic feedback circuits use these components to establish more robust operation in closed-loop, either by drawing on, but also by extending traditional engineering concepts. In this perspective, we argue that major conceptual advances will require new theory of control adapted to biology, extensions from single genes to networks, more systematic considerations of origins of variability other than intrinsic noise, and an exploration of how noise shaping, instead of noise reduction, could establish new synthetic functions or help understanding natural functions.

Gene networks that compensate for crosstalk with crosstalk

Crosstalk is a major challenge to engineering sophisticated synthetic gene networks. A common approach is to insulate signal-transduction pathways by minimizing molecular-level crosstalk between endogenous and synthetic genetic components, but this strategy can be difficult to apply in the context of complex, natural gene networks and unknown interactions. Here, we show that synthetic gene networks can be engineered to compensate for crosstalk by integrating pathway signals, rather than by pathway insulation. We demonstrate this principle using reactive oxygen species (ROS)-responsive gene circuits in Escherichia coli that exhibit concentration-dependent crosstalk with non-cognate ROS. We quantitatively map the degree of crosstalk and design gene circuits that introduce compensatory crosstalk at the gene network level. The resulting gene network exhibits reduced crosstalk in the sensing of the two different ROS. Our results suggest that simple network motifs that compensate for pathway crosstalk can be used by biological networks to accurately interpret environmental signals.

Crosstalk between genetic circuits is a major challenge for engineering sophisticated networks. Here the authors design networks that compensate for crosstalk by integrating, not insulating, pathways.

Synthetic Inducible Regulatory Systems Optimized for the Modulation of Secondary Metabolite Production in Streptomyces

Biosynthesis of secondary metabolites is a highly complex process that often requires tight control of their production, as overproduction of metabolites could be toxic and also may cause metabolic burden to their hosts. Tight control of metabolite production could be achieved by expressing key biosynthetic genes under control of an inducible regulatory system. In this study, we employed the modular design approach to build a high performance synthetic inducible regulatory system that displays a large dynamic range and thus is well-suited for the modulation of secondary metabolite production in Streptomyces. To this end, an inducible regulatory system was divided into three separate functional modules: (1) the induction module, (2) the target expression module, and (3) the repressor expression module. Then, these three separate modules were individually optimized in a stepwise manner and assembled to a new system. First, the cumate (CMT) induction module was chosen as the best performing induction module based on the large dynamic range and moderate inducer sensitivity. Then the CMT induction module maintained its performance when combined with diverse constitutive target expression modules, in which overall dynamic ranges varied depending on maximum promoter strengths. Lastly, the repressor expression module was optimized to achieve complete elimination of leaky expression, further increasing the dynamic range of the system. We also demonstrate that any strong constitutive regulatory system could be converted into an inducible regulatory system by simple CRISPR/Cas9-aided markerless insertion of an operator sequence whenever tight control of gene expression is required. We believe that the synthetic inducible regulatory system we report here would become a useful tool in modulating secondary metabolite production in Streptomyces.

Multiscale effects of heating and cooling on genes and gene networks

Fluctuating environments such as changes in ambient temperature represent a fundamental challenge to life. Cells must protect gene networks that protect them from such stresses, making it difficult to understand how temperature affects gene network function in general. Here, we focus on single genes and small synthetic network modules to reveal four key effects of nonoptimal temperatures at different biological scales: (i) a cell fate choice between arrest and resistance, (ii) slower growth rates, (iii) Arrhenius reaction rates, and (iv) protein structure changes. We develop a multiscale computational modeling framework that captures and predicts all of these effects. These findings promote our understanding of how temperature affects living systems and enables more robust cellular engineering for real-world applications.

Most organisms must cope with temperature changes. This involves genes and gene networks both as subjects and agents of cellular protection, creating difficulties in understanding. Here, we study how heating and cooling affect expression of single genes and synthetic gene circuits in Saccharomyces cerevisiae. We discovered that nonoptimal temperatures induce a cell fate choice between stress resistance and growth arrest. This creates dramatic gene expression bimodality in isogenic cell populations, as arrest abolishes gene expression. Multiscale models incorporating population dynamics, temperature-dependent growth rates, and Arrhenius scaling of reaction rates captured the effects of cooling, but not those of heating in resistant cells. Molecular-dynamics simulations revealed how heating alters the conformational dynamics of the TetR repressor, fully explaining the experimental observations. Overall, nonoptimal temperatures induce a cell fate decision and corrupt gene and gene network function in computationally predictable ways, which may aid future applications of engineered microbes in nonstandard temperatures.

A GRX1 Promoter Variant Confers Constitutive Noisy Bimodal Expression That Increases Oxidative Stress Resistance in Yeast

Higher noise in the expression of stress-related genes was previously shown to confer better resistance in selective conditions. Thus, evolving the promoter of such genes toward higher transcriptional noise appears to be an attractive strategy to engineer microbial strains with enhanced stress resistance. Here we generated hundreds of promoter variants of the GRX1 gene involved in oxidative stress resistance in Saccharomyces cerevisiae and created a yeast library by replacing the native GRX1 promoter by these variants at the native locus. An outlier clone with very strong increase in noise (6-times) at the same mean expression level as the native strain was identified whereas the other noisiest clones were only 3-times increased. This variant provides constitutive bimodal expression and consists in 3 repeated but differently mutated copies of the GRX1 promoter. In spite of the multi-factorial oxidative stress-response in yeast, replacement of the native promoter by this variant is sufficient alone to confer strongly enhanced resistance to H₂O₂ and cumene hydroperoxide. New replacement of this variant by the native promoter in the resistant strain suppresses the resistance. This work shows that increasing noise of target genes in a relevant strategy to engineer microbial strains toward better stress resistance. Multiple promoter replacement could synergize the effect observed here with the sole GRX1 promoter replacement. Finally this work suggests that combining several mutated copies of the target promoter could allow enhancing transcriptional-mediated noise at higher levels than mutating a single copy by providing constitutive bimodal and highly heterogeneous expression distribution.

Fitness effects of altering gene expression noise in Saccharomyces cerevisiae

Gene expression noise is an evolvable property of biological systems that describes differences in expression among genetically identical cells in the same environment. Prior work has shown that expression noise is heritable and can be shaped by selection, but the impact of variation in expression noise on organismal fitness has proven difficult to measure. Here, we quantify the fitness effects of altering expression noise for the TDH3 gene in Saccharomyces cerevisiae. We show that increases in expression noise can be deleterious or beneficial depending on the difference between the average expression level of a genotype and the expression level maximizing fitness. We also show that a simple model relating single-cell expression levels to population growth produces patterns consistent with our empirical data. We use this model to explore a broad range of average expression levels and expression noise, providing additional insight into the fitness effects of variation in expression noise.

Synthetic Toolkit for Complex Genetic Circuit Engineering in Saccharomyces cerevisiae

Sustainable production of chemicals, materials, and pharmaceuticals is increasingly performed by genetically engineered cell factories. Engineering of complex metabolic routes or cell behavior control systems requires robust and predictable gene expression tools. In this challenging task, orthogonality is a fundamental prerequisite for such tools. In this study, we developed and characterized in depth a comprehensive gene expression toolkit that allows accurate control of gene expression in Saccharomyces cerevisiae without marked interference with native cellular regulation. The toolkit comprises a set of transcription factors, designed to function as synthetic activators or repressors, and transcription-factor-dependent promoters, which together provide a broad expression range surpassing, at high end, the strongest native promoters. Modularity of the developed tools is demonstrated by establishing a novel bistable genetic circuit with robust performance to control a heterologous metabolic pathway and enabling on-demand switching between two alternative metabolic branches.

Perspective: Engineering noise in biological systems towards predictive stochastic design

Significant progress has been made towards engineering both single-cell and multi-cellular systems through a combination of synthetic and systems biology, nanobiotechnology, pharmaceutical science, and computational approaches. However, our ability to engineer systems that begin to approach the complexity of natural pathways is severely limited by important challenges, e.g. due to noise, or the fluctuations in gene expression and molecular species at multiple scales (e.g. both intra- and inter-cellular fluctuations). This barrier to engineering requires that biological noise be recognized as a design element with fundamentals that can be actively controlled. Here we highlight studies of an emerging discipline that collectively strives to engineer noise towards predictive stochastic design using interdisciplinary approaches at multiple-scales in diverse living systems.

Identifying and characterizing SCRaMbLEd synthetic yeast using ReSCuES

SCRaMbLE is a novel system implemented in the synthetic yeast genome, enabling massive chromosome rearrangements to produce strains with a large genotypic diversity upon induction. Here we describe a reporter of SCRaMbLEd cells using efficient selection, termed ReSCuES, based on a loxP-mediated switch of two auxotrophic markers. We show that all randomly isolated clones contained rearrangements within the synthetic chromosome, demonstrating high efficiency of selection. Using ReSCuES, we illustrate the ability of SCRaMbLE to generate strains with increased tolerance to several stress factors, such as ethanol, heat and acetic acid. Furthermore, by analyzing the tolerant strains, we are able to identify ACE2, a transcription factor required for septum destruction after cytokinesis, as a negative regulator of ethanol tolerance. Collectively, this work not only establishes a generic platform to rapidly identify strains of interest by SCRaMbLE, but also provides methods to dissect the underlying mechanisms of resistance.

The use of synthetic chromosomes and the recombinase-based SCRaMbLE system could enable rapid strain evolution through massive chromosome rearrangements. Here the authors present ReSCuES, which uses auxotrophic markers to rapidly identify yeast with rearrangements for strain engineering.

Fine-tuning of noise in gene expression with nucleosome remodeling

Engineering stochastic fluctuations of gene expression (or “noise”) is integral to precisely bias cellular-fate decisions and statistical phenotypes in both single-cell and multi-cellular systems. Epigenetic regulation has been shown to constitute a large source of noise, and thus, engineering stochasticity is deeply intertwined with epigenetics. Here, utilizing chromatin remodeling, we report that Caffeic acid phenethyl ester (CA) and Pyrimethamine (PYR), two inhibitors of BAF250a, a subunit of the Brahma-associated factor (BAF) nucleosome remodeling complex, enable differential and tunable control of noise in transcription and translation from the human immunodeficiency virus long terminal repeat promoter in a dose and time-dependent manner. CA conserves noise levels while increasing mean abundance, resulting in direct tuning of the transcriptional burst size, while PYR strictly increases transcriptional initiation frequency while conserving a constant transcriptional burst size. Time-dependent treatment with CA reveals non-continuous tuning with noise oscillating at a constant mean abundance at early time points and the burst size increasing for treatments after 5 h. Treatments combining CA and Protein Kinase C agonists result in an even larger increase of abundance while conserving noise levels with a highly non-linear increase in variance of up to 63× untreated controls. Finally, drug combinations provide non-antagonistic combinatorial tuning of gene expression noise and map a noise phase space for future applications with viral and synthetic gene vectors. Active remodeling of nucleosomes and BAF-mediated control of gene expression noise expand a toolbox for the future design and engineering of stochasticity in living systems.

Construction of hybrid regulated mother-specific yeast promoters for inducible differential gene expression

Engineered promoters with predefined regulation are a key tool for synthetic biology that enable expression on demand and provide the logic for genetic circuits. To expand the availability of synthetic biology tools for S. cerevisiae yeast, we here used hybrid promoter engineering to construct tightly-controlled, externally-inducible promoters that only express in haploid mother cells that have contributed a daughter cell to the population. This is achieved by combining elements from the native HO promoter and from a TetR-repressible synthetic promoter, with the performance of these promoters characterized by both flow cytometry and microfluidics-based fluorescence microscopy. These new engineered promoters are provided as an enabling tool for future synthetic biology applications that seek to exploit differentiation within a yeast population.

Tuning Transcriptional Regulation through Signaling: A Predictive Theory of Allosteric Induction

Allosteric regulation is found across all domains of life, yet we still lack simple, predictive theories that directly link the experimentally tunable parameters of a system to its input-output response. To that end, we present a general theory of allosteric transcriptional regulation using the Monod-Wyman-Changeux model. We rigorously test this model using the ubiquitous simple repression motif in bacteria by first predicting the behavior of strains that span a large range of repressor copy numbers and DNA binding strengths and then constructing and measuring their response. Our model not only accurately captures the induction profiles of these strains, but also enables us to derive analytic expressions for key properties such as the dynamic range and [EC₅₀]. Finally, we derive an expression for the free energy of allosteric repressors that enables us to collapse our experimental data onto a single master curve that captures the diverse phenomenology of the induction profiles.

Emergent Properties in Complex Synthetic Bacterial Promoters

Regulation of gene expression in bacteria results from the interplay between hundreds of transcriptional factors (TFs) at target promoters. However, how the arrangement of binding sites for TFs generates the regulatory logic of promoters is not well-known. Here, we generated and fully characterized a library of synthetic complex promoters for the global regulators, CRP and IHF, in Escherichia coli, which are formed by a weak -35/-10 consensus sequence preceded by four combinatorial binding sites for these two TFs. Using this approach, we found that while cis-elements for CRP preferentially activate promoters when located immediately upstream of the promoter consensus, binding sites for IHF mainly function as "UP" elements and stimulate transcription in several different architectures in the absence of this protein. However, the combination of CRP- and IHF-binding sites resulted in emergent properties in these complex promoters, where the activity of combinatorial promoters cannot be predicted from the individual behavior of its components. Taken together, the results presented here add to the information on architecture-logic of complex promoters in bacteria.

Maximum Caliber Can Characterize Genetic Switches with Multiple Hidden Species

Gene networks with feedback often involve interactions between multiple species of biomolecules, much more than experiments can actually monitor. Coupled with this is the challenge that experiments often measure gene expression in noisy fluorescence instead of protein numbers. How do we infer biophysical information and characterize the underlying circuits from this limited and convoluted data? We address this by building stochastic models using the principle of Maximum Caliber (MaxCal). MaxCal uses the basic information on synthesis, degradation, and feedback-without invoking any other auxiliary species and ad hoc reactions-to generate stochastic trajectories similar to those typically measured in experiments. MaxCal in conjunction with Maximum Likelihood (ML) can infer parameters of the model using fluctuating trajectories of protein expression over time. We demonstrate the success of the MaxCal + ML methodology using synthetic data generated from known circuits of different genetic switches: (i) a single-gene autoactivating circuit involving five species (including mRNA), (ii) a mutually repressing two-gene circuit (toggle switch) with seven species (including mRNA) considering stochastic time traces of two proteins, and (iii) the same toggle switch circuit considering stochastic time traces of only one of the two proteins. To further challenge the MaxCal + ML inference scheme, we repeat our analysis for the second and third scenario with traces expressed in noisy fluorescence instead of protein number to closely mimic typical experiments. We show that, for all of these models with increasing complexity and obfuscation, the minimal model of MaxCal is still able to capture the fluctuations of the trajectory and infer basic underlying rate parameters when benchmarked against the known values used to generate the synthetic data. Importantly, the model also yields an effective feedback parameter that can be used to quantify interactions within these circuits. These applications show the promise of MaxCal's ability to characterize circuits with limited data, and its utility to better understand evolution and advance design strategies for specific functions.

Synthetic gene regulation for independent external induction of the Saccharomyces cerevisiae pseudohyphal growth phenotype

Pseudohyphal growth is a multicellular phenotype naturally performed by wild budding yeast cells in response to stress. Unicellular yeast cells undergo gross changes in their gene regulation and elongate to form branched filament structures consisting of connected cells. Here, we construct synthetic gene regulation systems to enable external induction of pseudohyphal growth in Saccharomyces cerevisiae. By controlling the expression of the natural PHD1 and FLO8 genes we are able to trigger pseudohyphal growth in both diploid and haploid yeast, even in different types of rich media. Using this system, we also investigate how members of the BUD gene family control filamentation in haploid cells. Finally, we employ a synthetic genetic timer network to control pseudohyphal growth and further explore the reversibility of differentiation. Our work demonstrates that synthetic regulation can exert control over a complex multigene phenotype and offers opportunities for rationally modifying the resulting multicellular structure.

Georgios Pothoulakis and Tom Ellis report the construction of a synthetic gene regulation system for inducing pseudohyphal growth in Saccharomyces cerevisiae. This multicellular yeast phenotype can now be switched on and off via external control in a variety of conditions.

Negative Regulation Gene Circuits for Efflux Pump Control

Synthetic biologists aim to design biological systems for a variety of industrial and medical applications, ranging from biofuel to drug production. Synthetic gene circuits regulating efflux pump protein expression can achieve this by driving desired substrates such as biofuels, pharmaceuticals, or other chemicals out of the cell in a precisely controlled manner. However, efflux pumps may introduce implicit negative feedback by pumping out intracellular inducer molecules that control gene circuits, which then can alter gene circuit function. Therefore, synthetic gene circuits must be carefully designed and constructed for precise efflux control. Here, we provide protocols for quantitatively modeling and building synthetic gene constructs for efflux pump regulation.