Using yeast counter-selection for the improved development of ligand-stabilized biosensors
Matt Rich (former lab member)
Yeast and other microbes can be used to produce many small molecules, but optimization of the metabolic pathways involved is a non-trivial undertaking. Strains optimized to produce a small molecule of interest can be selected through the use of suitable biosensors, but few of these are currently available. As such, we must design new sensors for use in strain engineering contexts. We have previously shown that ligand-stabilized transcription factors are a viable, and likely general, biosensor platform. In this approach (Figure 1), an unstable transcription factor can induce expression of a reporter gene only in the presence of a stabilizing ligand. Optimization of this stabilizing interaction can be difficult, and would be aided by an in vivo selection and counter-selection strategy that enables the use of large populations of protein variants.
We have implemented such a strategy using the yeast CAN1 gene. CAN1 encodes an arginine transporter that also imports canavanine, a toxic arginine analog, into the cell. Because evidence has shown that low expression of CAN1 is not fully toxic in the presence of canavanine, we hypothesized that this gene could be used as a counter-selectable marker for ligand-stabilized transcription factor optimization. Indeed, increased biosensor stabilization causes a growth defect in the presence of canavanine (Figure 2). We are currently testing selection methods in which we initially positively select for HIS3 expression in the presence of ligand, followed by counter-selection in canavanine in the absence of ligand.
The use of CAN1 has drawbacks, though. For instance, the mutation rate at the CAN1 locus is relatively high, and loss-of-function mutations in CAN1 break the counter-selection. We are exploring the use of diploid reporter strains, which should diminish this problem. CAN1 seems to require a higher expression level for phenotypic effects when compared to the positive selectable marker, HIS3.
E. coli biosensors based on ligand-dependent stability
Ben Brandsen
Biosensors are genetically encoded proteins or nucleic acids that enable cells to sense and respond to stimuli. They can be used to control gene expression, to construct genetic circuits, and to detect metabolic products for genome engineering. Many bacterial biosensors are based on natural allosteric transcriptional repressors, which after binding ligand, no longer repress a reporter gene and result in increased gene expression. Engineering allosteric transcription factors to bind new ligands is challenging, however, because engineered transcription factors often have broken allostery.
One general strategy to new biosensors relies upon ligand-dependent protein stabilization. In this biosensor design, a protein that binds to ligand is destabilized with mutations, such that it is rapidly degraded in the absence of ligand, but stabilized in the presence of ligand (Figure 1A). We constructed E. coli transcriptional biosensors based on ligand-dependent stabilization by fusing the LacI ligand-binding domain between the Zif268 DNA-binding domain and the RpoZ transcription-activating domain. We generated an error-prone PCR library of LacI ligand-binding domains between Zif268 and RpoZ, and subjected this library to a positive selection for growth with ligand (Figure 1B). The biosensor was coupled to the selectable marker HIS3, which was required for growth in the absence of histidine. Variants that survived selection were replica-plated onto minimal media with and without IPTG (ligand for LacI), and variants that grew better with ligand compared to without ligand were selected for further analysis
One general strategy to new biosensors relies upon ligand-dependent protein stabilization. In this biosensor design, a protein that binds to ligand is destabilized with mutations, such that it is rapidly degraded in the absence of ligand, but stabilized in the presence of ligand (Figure 1A). We constructed E. coli transcriptional biosensors based on ligand-dependent stabilization by fusing the LacI ligand-binding domain between the Zif268 DNA-binding domain and the RpoZ transcription-activating domain. We generated an error-prone PCR library of LacI ligand-binding domains between Zif268 and RpoZ, and subjected this library to a positive selection for growth with ligand (Figure 1B). The biosensor was coupled to the selectable marker HIS3, which was required for growth in the absence of histidine. Variants that survived selection were replica-plated onto minimal media with and without IPTG (ligand for LacI), and variants that grew better with ligand compared to without ligand were selected for further analysis
Figure 1. (A) Design of biosensors based on ligand-dependent stabilization. The LacI ligand-binding domain is fused between the Zif268 DNA-binding domain and RpoZ transcription-activating domain and destabilized by mutation, such that in the absence of ligand, the biosensor is degraded, but in the presence of ligand, the biosensor is stabilized by binding ligand. This biosensor is coupled to a HIS3 reporter gene downstream of a Zif268 binding site. (B) Selection strategy to identify new biosensors. An error-prone PCR library of ligand-binding domain variants is subjected to positive selection with ligand in minimal media lacking histidine, such that only variants able to activate HIS3 expression grow. Biosensors that show ligand-dependent stabilization are subsequently identified by replica-plating on minimal media with and without ligand.
We identified a single biosensor, L1.0, that contains six amino acid mutations in the LacI ligand-binding domain, and is able to drive HIS3 expression in an IPTG-dependent manner (Figure 2). L1.0 shows an ~3-fold increase in growth rate with 100 mM IPTG compared to without ligand. To determine which amino acid mutations are required for biosensor behavior, we reverted each mutation back to the WT amino acid. All amino acid revertants except one, G272R, showed activity similar to L1.0, while reverting G272R abolished biosensor activity. We assessed the biosensor with LacI G272R (named L1.7), and found it showed a similar ligand-dependent response to L1.0 (Figure 2), establishing that a single amino acid mutation is sufficient to confer biosensor behavior. We additionally assessed the equivalent mutation to G272R in two structurally related solute-binding proteins, AlsB and RbsB. However, these biosensor variants did not show any ligand-dependent response, suggesting that the equivalent G272R mutation is not generally destabilizing.
Figure 2. Biosensor L1.0, with six amino acid mutations, shows approximately three-fold increase in growth rate with 100 mM IPTG compared to no IPTG. Reversion of each single amino acid mutation revealed that G272R is primarily responsible for biosensor behavior. Biosensor L1.7, containing only the G272R mutation, shows similar biosensor activity to L1.0.
Engineering Natural Product Biosynthetic Pathways with Multiplexed Mutagenesis and Biosensor-Based Selection
Ben Brandsen
Antibiotic resistance is a serious and growing problem. In 2013, the U.S. Centers for Disease Control reported that antibiotic resistance is responsible for more than 23,000 deaths and 2 million infections each year, costing approximately $20 billion. The problem of increasing antibiotic resistance is compounded by the small number of new antibiotics approved by the FDA in the past decade and a dearth of new antibiotic drug candidates in clinical trials. One rich source of antibiotic lead compounds is natural products, but isolation of new natural products has slowed, significantly hampered by the rediscovery of known compounds. If the biosynthetic pathways that synthesize therapeutically useful natural products can be efficiently engineered in a laboratory, then new, natural product-like compounds would be accessible.
Polyketides are a class of natural products from which many important antibiotic compounds have been identified, including erythromycin, azithromycin, and clarithromycin. Polyketides are biosynthesized by polyketide synthase (PKS) enzymes, which consist of several modular protein domains that iteratively add small extender substrates together. One of the most well-studied polyketide biosynthetic pathways produces the antibiotic erythromycin A (Figure 1). It consists of three synthases, named DEBS1-3. The synthases contains two modules, each of which incorporates a single extender substrate. A thioesterase domain on DEBS3 cyclizes the polyketide to form 6-deoxyerythronolide B, and additional tailoring enzymes convert 6-deoxyerythronolide B (6-dEB) to erythromycin A.
Polyketides are a class of natural products from which many important antibiotic compounds have been identified, including erythromycin, azithromycin, and clarithromycin. Polyketides are biosynthesized by polyketide synthase (PKS) enzymes, which consist of several modular protein domains that iteratively add small extender substrates together. One of the most well-studied polyketide biosynthetic pathways produces the antibiotic erythromycin A (Figure 1). It consists of three synthases, named DEBS1-3. The synthases contains two modules, each of which incorporates a single extender substrate. A thioesterase domain on DEBS3 cyclizes the polyketide to form 6-deoxyerythronolide B, and additional tailoring enzymes convert 6-deoxyerythronolide B (6-dEB) to erythromycin A.
Figure 1. Biosynthesis of erythromycin by DEBS1-3. 6-dEB is modified by additional tailoring enzymes to generate the natural product antibiotic erythromycin A.
Because of the iterative manner by which polyketides are built and the modular nature of the PKS enzymes, engineering the biosynthetic pathways to produce new compounds is an appealing prospect. Efforts have primarily focused on changing the order of protein domains, substituting exogenous enzyme domains, and supplying unique extender substrates. However, technical challenges, such as poor interaction between non-native protein domains and reduced enzymatic activity, have stalled these efforts.
I hope to overcome many of these challenges by using high-throughput DNA mutagenesis and biosensor-based selection to improve the activity of chimeric PKS enzymes. I have established that allosteric transcription factor MphR, which activates expression of a downstream gene in the presence of erythromycin, can be used for ligand-dependent expression of a HIS3 reporter gene. I plan to build a library of chimeric DEBS pathways with acyltransferase domains from other polyketide pathways (as shown in Figure 2), which control the substrates that are incorporated into the growing polyketide, and connect production of their macrolide ligand to the response of MphR.
I hope to overcome many of these challenges by using high-throughput DNA mutagenesis and biosensor-based selection to improve the activity of chimeric PKS enzymes. I have established that allosteric transcription factor MphR, which activates expression of a downstream gene in the presence of erythromycin, can be used for ligand-dependent expression of a HIS3 reporter gene. I plan to build a library of chimeric DEBS pathways with acyltransferase domains from other polyketide pathways (as shown in Figure 2), which control the substrates that are incorporated into the growing polyketide, and connect production of their macrolide ligand to the response of MphR.
Figure 2. Strategy for constructing DEBS chimeras. Acyltransferase (AT) domains from several other polyketide biosynthetic pathways that incorporate different substrates into the polyketide natural product are swapped for the native AT domain, to generate a library of chimeric synthases.
Finally, I will use multiplexed genome engineering in E. coli to introduce mutations near the substitute AT domain, and select for active pathway variants using the MphR biosensor to detect product formation (Figure 3). This strategy of high-throughput mutagenesis and biosensor-based selection could also be applied to other biosynthetic pathways that produce valuable small molecule or protein products.
Figure 3. Biosensor-based strategy to improve biosynthetic pathway production. DEBS production is coupled to the MphR transcription factor, which in the presence of ligand, increases expression of the HIS3 and URA3 reporter genes required for growth in minimal media lacking histidine and uracil. After in vivo mutagenesis using DNA oligos, pathway variants able to produce the macrolide product will grow faster than those that produce no product or less product, such that after selection, active pathway variants make up a large fraction of the cell population. These will be scored by deep sequencing, to identify the best mutations, and subjected to additional rounds of mutagenesis and selection.
Genetic sensors for the detection of biosynthetic products
Ben Jester (former lab member)
Model microorganisms such as E. coli and S. cerevisiae are valuable tools for the production of small molecules, such as therapeutics and biofuels, but the optimization of biosynthetic pathways in a new host is non-trivial. Identifying genetic modifications that enhance metabolite synthesis can be an exceptionally laborious process, particularly in the absence of a method to easily determine product yields. Genetically encoded biosensors that couple small molecule recognition to a readily measured output allow more rapid identification of cells with enhanced biosynthetic production or conditions that promote enhanced production. One of Nature’s most common mechanisms for detecting the presence of a small molecule – be it a metabolite or an environmental agent – has been to evolve biosensors that regulate the transcription of one or more genes upon binding of the relevant ligand. The goal of this project is to design a transcription factor (TF)-based strategy for biosensors that may provide a general solution to the problem of small molecule detection.
Our strategy is to use destabilizing mutations that impair functional expression of the biosensor until it binds its cognate ligand. It should be possible to design a protein-based biosensor for any ligand as long as a ligand-binding domain (LBD) exists – or can be designed – for the desired small molecule. By fusing an unstable LBD to a TF, we couple ligand-dependent stabilization to reporter gene expression. As a proof of principle, we chose to use a de novo designed LBD, DIG10.3, which binds digoxigenin, a steroid similar to drugs used to treat heart failure. By fusing this protein to a DNA-binding domain (DBD) and a transcriptional activation domain (TAD), we were able to generate a ligand-dependent TF, which we designated GDVP. From a library of mutants, FACS analysis allowed us to identify destabilizing mutations that improved sensor function by >10-fold (GDVP.1 and GDVP.2).
Our strategy is to use destabilizing mutations that impair functional expression of the biosensor until it binds its cognate ligand. It should be possible to design a protein-based biosensor for any ligand as long as a ligand-binding domain (LBD) exists – or can be designed – for the desired small molecule. By fusing an unstable LBD to a TF, we couple ligand-dependent stabilization to reporter gene expression. As a proof of principle, we chose to use a de novo designed LBD, DIG10.3, which binds digoxigenin, a steroid similar to drugs used to treat heart failure. By fusing this protein to a DNA-binding domain (DBD) and a transcriptional activation domain (TAD), we were able to generate a ligand-dependent TF, which we designated GDVP. From a library of mutants, FACS analysis allowed us to identify destabilizing mutations that improved sensor function by >10-fold (GDVP.1 and GDVP.2).
In order to tune the sensor for selections using a HIS3 reporter, we fused the degron from the Mata protein to GDVP to increase degradation. The fusion generated a sensor that leads to growth in histidine-deficient media more than 3 orders of magnitude better when the ligand (digoxigenin) is present. Sensitivity to digoxigenin can be further improved by deleting yeast efflux pumps, like Pdr5.
While the biosynthetic pathway required to produce digoxigenin is not known, other steroids such as progesterone have been successfully produced by yeast. An additional round of mutagenesis and screening allowed us to create a sensor that is extremely selective for progesterone but not its biosynthetic precursor, pregnenolone. Collaborators have used this sensor to identify mutations in 3-beta-hydroxysteroid dehydrogenase that improve progesterone bioproduction in yeast. We are currently applying these methods to develop sensors for new small molecules.
While the biosynthetic pathway required to produce digoxigenin is not known, other steroids such as progesterone have been successfully produced by yeast. An additional round of mutagenesis and screening allowed us to create a sensor that is extremely selective for progesterone but not its biosynthetic precursor, pregnenolone. Collaborators have used this sensor to identify mutations in 3-beta-hydroxysteroid dehydrogenase that improve progesterone bioproduction in yeast. We are currently applying these methods to develop sensors for new small molecules.
Engineering ligand-gated dimers to control cellular functions
Ben Jester (former lab member)
Protein-protein interactions drive the overwhelming majority of cellular processes, such as signaling, differentiation, and proliferation. Interacting protein domains coordinate these critical functions by ensuring that functional domains act on the appropriate target. Native interacting domains can often be replaced with an alternative pair of interacting proteins that result in near wild-type function. For example, the protein pair of FKBP and FRB is a popular substitute for interacting domains because interaction between these two proteins is dependent upon the small molecule rapamycin. When fused to functional domains requiring co-localization for activity, they provide the researcher with temporal control over a cellular process. Currently, the toolkit for small molecule-gated protein-protein interactions is exceptionally small. As the field of synthetic biology continues to grow, so will the need for tools that provide temporal control over multiple cellular processes.
To approach this problem, we have taken an unstable, homodimeric ligand-binding domain (LBD) and converted it into a ligand-dependent dimer. The LBD used here, DIG10.3, is a small protein that is degraded by the cell until it binds to the small molecule digoxigenin. To measure LBD dimerization, we made two fusion proteins: a single monomer of the LBD fused to a DNA-binding domain (DBD), and a single monomer of the LBD fused to a transcriptional activation domain (TAD). In an assay conceptually similar to the yeast two-hybrid system, dimerization between these two fusion proteins should induce the expression of a reporter protein. Previous work with this protein has shown that mutations to the dimer interface of DIG10.3 can lead to destabilization of the protein. By testing pairs of proteins that contained mutations at the dimer interface or in the ligand-binding pocket, we were able to identify dimers that respond to either digoxigenin or progesterone, or that required both ligands to activate reporter expression.
To approach this problem, we have taken an unstable, homodimeric ligand-binding domain (LBD) and converted it into a ligand-dependent dimer. The LBD used here, DIG10.3, is a small protein that is degraded by the cell until it binds to the small molecule digoxigenin. To measure LBD dimerization, we made two fusion proteins: a single monomer of the LBD fused to a DNA-binding domain (DBD), and a single monomer of the LBD fused to a transcriptional activation domain (TAD). In an assay conceptually similar to the yeast two-hybrid system, dimerization between these two fusion proteins should induce the expression of a reporter protein. Previous work with this protein has shown that mutations to the dimer interface of DIG10.3 can lead to destabilization of the protein. By testing pairs of proteins that contained mutations at the dimer interface or in the ligand-binding pocket, we were able to identify dimers that respond to either digoxigenin or progesterone, or that required both ligands to activate reporter expression.
The use of dimeric proteins fused to two different components (i.e. a DNA-binding domain and a transcriptional activation domain) is limited by the possibility of non-functional dimers that can form between identical components. Using a crystal structure model of the DIG10.3 homodimer, we made several rational mutations to the dimer interface that were predicted to favor heterodimerization of the two proteins. Two redesigns based on either a “charge-swap” (1a and 1b) or “knob-in-hole” (2a and 2b) model generated a pair of orthogonal interfaces and improved inducible reporter activation by more than 10-fold. On-going work is focused on exploring how directed evolution and deep sequencing may allow us to identify additional unique interfaces and deploying multiple pairs of ligand-dependent dimers in the same cell.
