Rapid detection of subtype-selective nuclear hormone receptor binding with bacterial genetic selection

Mechanistic discoveries and simulation-guided assay optimization of portable hormone biosensors with cell-free protein synthesis

Nuclear receptors (NRs) influence nearly every system of the body and our lives depend on correct NR signaling. Thus, a key environmental and pharmaceutical quest is to identify and detect chemicals which interact with nuclear hormone receptors, including endocrine disrupting chemicals (EDCs), therapeutic receptor modulators, and natural hormones. Previously reported biosensors of nuclear hormone receptor ligands facilitated rapid detection of NR ligands using cell-free protein synthesis (CFPS). In this work, the advantages of CFPS are further leveraged and combined with kinetic analysis, autoradiography, and western blot to elucidate the molecular mechanism of this biosensor. Additionally, mathematical simulations of enzyme kinetics are used to optimize the biosensor assay, ultimately lengthening its readable window by five-fold and improving sensor signal strength by two-fold. This approach enabled the creation of an on-demand thyroid hormone biosensor with an observable color-change readout. This mathematical and experimental approach provides insight for engineering rapid and field-deployable CFPS biosensors and promises to improve methods for detecting natural hormones, therapeutic receptor modulators, and EDCs.

Analysis of the roles of mutations in thyroid hormone receptor-β by a bacterial biosensor system

Mutations in thyroid hormone receptors (TRs) often lead to metabolic and developmental disorders, but patients with these mutations are difficult to treat with existing thyromimetic drugs. In this study, we analyzed six clinically observed mutations in the ligand-binding domain of the human TRβ using an engineered bacterial hormone biosensor. Six agonist compounds, including triiodothyronine (T3), thyroxine (T4), 3,5,3'-triiodothyroacetic acid (Triac), GC-1, KB-141, and CO-23, and the antagonist NH-3 were examined for their ability to bind to each of the TRβ mutants. The results indicate that some mutations lead to the loss of ability to bind to native ligands, ranging from several fold to several hundred fold, while other mutations completely abolish the ability to bind to any ligand. Notably, the effect of each ligand on each TRβ mutant in this bacterial system is highly dependent on both the mutation and the ligand; some ligands were bound well by a wide variety of mutants, while other ligands lost their affinity for all but the WT receptor. This study demonstrates the ability of our bacterial system to differentiate agonist compounds from antagonist compounds and shows that one of the TRβ mutations leads to an unexpected increase in antagonist ability relative to other mutations. These results indicate that this bacterial sensor can be used to rapidly determine ligand-binding ability and character for clinically relevant TRβ mutants.

Bacterial biosensors for evaluating potential impacts of estrogenic endocrine disrupting compounds in multiple species

To study the effects and possible mechanisms of suspected endocrine disrupting compounds (EDCs), a wide variety of assays have been developed. In this work, we generated engineered Escherichia coli biosensor strains that incorporate the ligand-binding domains (LBDs) of the β-subtype estrogen receptors (ERβ) from Solea solea (sole), and Sus scrofa (pig). These strains indicate the presence of ligands for these receptors by changes in growth phenotype, and can differentiate agonist from antagonist and give a rough indication of binding affinity via dose-response curves. The resulting strains were compared with our previously reported Homo sapiens ERβ biosensor strain. In initial tests, all three of the strains correctly identified estrogenic test compounds with a high degree of certainly (Z' typically greater than 0.5), including the weakly binding test compound bisphenol A (BPA) (Z' ≈ 0.1-0.3). The modular design of the sensing element in this strain allows quick development of new species-based biosensors by simple LBD swapping, suggesting its use in initial comparative analysis of EDC impacts across multiple species. Interestingly, the growth phenotypes of the biosensor strains indicate similar binding for highly estrogenic control compounds, but suggest differences in ligand binding for more weakly binding EDCs.

Bacterial biosensors for screening isoform-selective ligands for human thyroid receptors α-1 and β-1

Subtype-selective thyromimetics have potential as new pharmaceuticals for the prevention or treatment of heart disease, high LDL cholesterol and obesity, but there are only a few methods that can detect agonistic behavior of TR-active compounds. Among these are the rat pituitary GH₃ cell assay and transcriptional activation assays in engineered yeast and mammalian cells. We report the construction and validation of a newly designed TRα-1 bacterial biosensor, which indicates the presence of thyroid active compounds through their impacts on the growth of an engineered Escherichia coli strain in a simple defined medium. This biosensor couples the configuration of a hormone receptor ligand-binding domain to the activity of a thymidylate synthase reporter enzyme through an engineered allosteric fusion protein. The result is a hormone-dependent growth phenotype in the expressing E. coli cells. This sensor can be combined with our previously published TRβ-1 biosensor to detect potentially therapeutic subtype-selective compounds such as GC-1 and KB-141. To demonstrate this capability, we determined the half-maximal effective concentration (EC₅₀) for the compounds T₃, Triac, GC-1 and KB-141 using our biosensors, and determined their relative potency in each biosensor strain. Our results are similar to those reported by mammalian cell reporter gene assays, confirming the utility of our assay in identifying TR subtype-selective therapeutics. This biosensor thus provides a high-throughput, receptor-specific, and economical method (less than US$ 0.10 per well at laboratory scale) for identifying important therapeutics against these targets.

Engineering and optimization of an allosteric biosensor protein for peroxisome proliferator-activated receptor γ ligands

The peroxisome proliferator-activated receptor gamma (PPARγ or PPARG) belongs to the nuclear receptor superfamily, and is a potential drug target for a variety of diseases. In this work, we constructed a series of bacterial biosensors for the identification of functional PPARγ ligands. These sensors entail modified Escherichia coli cells carrying a four-domain fusion protein, comprised of the PPARγ ligand binding domain (LBD), an engineered mini-intein domain, the E. coli maltose binding protein (MBD), and a thymidylate synthase (TS) reporter enzyme. E. coli cells expressing this protein exhibit hormone ligand-dependent growth phenotypes. Unlike our published estrogen (ER) and thyroid receptor (TR) biosensors, the canonical PPARγ biosensor cells displayed pronounced growth in the absence of ligand. They were able to distinguish agonists and antagonists, however, even in the absence of agonist. To improve ligand sensitivity of this sensor, we attempted to engineer and optimize linker peptides flanking the PPARγ LBD insertion point. Truncation of the original linkers led to decreased basal growth and significantly enhanced ligand sensitivity of the PPARγ sensor, while substitution of the native linkers with optimized G(4)S (Gly-Gly-Gly-Gly-Ser) linkers further increased the sensitivity. Our studies demonstrate that the properties of linkers, especially the C-terminal linker, greatly influence the efficiency and fidelity of the allosteric signal induced by ligand binding. Our work also suggests an approach to increase allosteric behavior in this multidomain sensor protein, without modification of the functional LBD.

Protein and RNA engineering to customize microbial molecular reporting

Nature takes advantage of the malleability of protein and RNA sequence and structure to employ these macromolecules as molecular reporters whose conformation and functional roles depend on the presence of a specific ligand (an "effector" molecule). By following nature's example, ligand-responsive proteins and RNA molecules are now routinely engineered and incorporated into customized molecular reporting systems (biosensors). Microbial small-molecule biosensors and endogenous molecular reporters based on these sensing components find a variety of applications that include high-throughput screening of biosynthesis libraries, environmental monitoring, and novel gene regulation in synthetic biology. Here, we review recent advances in engineering small-molecule recognition by proteins and RNA and in coupling in vivo ligand binding to reporter-gene expression or to allosteric activation of a protein conferring a detectable phenotype. Emphasis is placed on microbial screening systems that serve as molecular reporters and facilitate engineering the ligand-binding component to recognize new molecules.

Application of screening methods, shape signatures and engineered biosensors in early drug discovery process

PURPOSE

In this study, two unreported estrogen antagonists were identified using a combination of computational screening and a simple bacterial estrogen sensor.

METHODS

Molecules here presented were initially part of a group obtained from a library of over a half million chemical compounds, using the Shape Signatures method. The structures within this group were then clustered and compared to known antagonists based on their physico-chemical parameters, and possible binding modes of the compounds to the Estrogen Receptor alpha (ER alpha) were analyzed. Finally, thirteen candidate compounds were purchased, and two of them were shown to behave as potential subtype-selective estrogen antagonists using a set of bacterial estrogen biosensors, which included sensors for ER alpha, ER beta, and a negative control thyroid hormone beta biosensor. These activities were then analyzed using an ELISA assay against activated ER alpha in human MCF-7 cell extract.

RESULTS

Two new estrogen receptor antagonists were detected using in silico Shape Signatures method with an engineered subtype-selective bacterial estrogen biosensor and commercially available ELISA assay. Additional thyroid biosensor control experiments confirmed no compounds interacted with human thyroid receptor beta.

CONCLUSIONS

This work demonstrates an effective combination of computational analysis and simple bacterial screens for rapid identification of potential hormone-like therapeutics.

Engineered Chimeric Enzymes as Tools for Drug Discovery: Generating Reliable Bacterial Screens for the Detection, Discovery, and Assessment of Estrogen Receptor Modulators

Engineered protein-based sensors of ligand binding have emerged as attractive tools for the discovery of therapeutic compounds through simple screening systems. We have previously shown that engineered chimeric enzymes, which combine the ligand-binding domains of nuclear hormone receptors with a highly sensitive thymidylate synthase reporter, yield simple sensors that report the presence of hormone-like compounds through changes in bacterial growth. This work describes an optimized estrogen sensor in Escherichia coli with extraordinary reliability in identifying diverse estrogenic compounds and in differentiating between their agonistic/antagonistic pharmacological effects. The ability of this system to assist the discovery of new estrogen-mimicking compounds was validated by screening a small compound library, which led to the identification of two structurally novel estrogen receptor modulators and the accurate prediction of their agonistic/antagonistic biocharacter in human cells. Strong evidence is presented here that the ability of our sensor to detect ligand binding and recognize pharmacologically critical properties arises from allosteric communication between the artificially combined protein domains, where different ligand-induced conformational changes in the receptor are transmitted to the catalytic domain and translated to distinct levels of enzymic efficiency. To the best of our knowledge, this is one of the first examples of an engineered enzyme with the ability to sense multiple receptor conformations and to be either activated or inactivated depending on the nature of the bound effector molecule. Because the proposed mechanism of ligand dependence is not specific to nuclear hormone receptors, we anticipate that our protein engineering strategy will be applicable to the construction of simple sensors for different classes of (therapeutic) binding proteins.