Biology subjects

Thyer, R.

Publications and source records attributed to Thyer, R..

9 recordsLinked to original sources

bioRxiv2026

A Quantitative Two-Channel Genetic Reporter for Selenocysteine Biosynthesis and Incorporation

Selenocysteine (Sec), the 21st amino acid, is a rare non-canonical amino acid that represents an attractive target for protein engineering due to its desirable chemical properties such as high affinity for metals, strong nucleophilicity, and reversible covalent bond formation. To bypass the natural constraints on Sec placement within proteins, several strategies have been developed to rewire the native translational machinery to enable site-specific incorporation. However, these usually abolish the quality control mechanism that excludes the serine-charged selenocysteinyl-tRNA (Ser-tRNASec), the immediate biosynthetic precursor, from translation resulting in heterogenous protein species. This challenge is confounded by a lack of genetic tools to accurately report the selenylation state of the tRNA pool as most are blind to competing process of Ser incorporation, which can only be observed using analytical methods. To resolve this issue, we have developed a new fluorescent reporter, Selenocysteine Adjusted Ratiometric Chromophore (SeARCh), which exhibits two distinct spectral outputs dependent on the incorporation of either Ser (red) or Sec (green). Using SeARCh, we define several factors which influence the observed Sec:Ser ratio and construct a new hybrid biosynthetic pathway with improved performance, achieving 90% Sec incorporation. Furthermore, SeARCh displays unusually complex mass spectra due to the isotope distribution of selenium and heterogenous nature of the protein in solution and we report specific methods to account for this behaviour and precisely quantify the rare Ser-containing species found at high Sec incorporation efficiencies. Our findings suggest that the equilibrium between selenoprotein and tRNASec expression levels is a key driver of incorporation efficiency and implies a process that is broadly biosynthetically constrained. Collectively these tools represent a significant advance in the metrology of selenocysteine biosynthesis and incorporation and can be used to inform and standardize future engineering efforts.

synthetic biology↗

bioRxiv2025

Mapping the phenotypic landscape of a transcriptional repressor using Deep Mutational Scanning and Growth-based Quantitative Sequencing

CymR is a TetR-family transcriptional repressor that recognizes a well-defined operator sequence in the promoter PcymRC. The native ligand cumate and several structurally related aromatic acids bind at an allosteric site and induce a conformational change in CymR, resulting in release from the DNA operator and de-repression of the promoter. The amino acid residues that contribute to these core functions have not been mapped, nor has the protein been subjected to extensive mutagenesis to modify its function. Here, for the first time, we integrate Deep Mutational Scanning (DMS) with Growth-based Quantitative Sequencing (GROQ-Seq) to evaluate a comprehensive phenotypic landscape of CymR variants, including single amino acid insertions and deletions. We measure this library across a concentration gradient of small molecule inducers to construct an induction curve for all library members. From this analysis, we identify amino acids throughout the protein that are essential for repressor function and discover several mutations that improve the sensitivity of CymR to the ligand perillic acid. In addition, rarely investigated insertion mutants are revealed to be a key driver of novel phenotypes, including several regions of CymR where insertions result in an inverted phenotype and the isolation of variants exhibiting an unusual band-stop phenotype. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=81 SRC="FIGDIR/small/693801v1_ufig1.gif" ALT="Figure 1"> View larger version (30K): org.highwire.dtl.DTLVardef@121b16org.highwire.dtl.DTLVardef@b0478aorg.highwire.dtl.DTLVardef@128f2ecorg.highwire.dtl.DTLVardef@164a426_HPS_FORMAT_FIGEXP M_FIG C_FIG

synthetic biology↗

bioRxiv2025

Engineering a Bright Near-Infrared Fluorescent Protein by Screening a Comprehensive Phenotypic Landscape

Near-infrared fluorescent proteins (niRFPs) are valuable markers for tracking cellular phenomena as they offer greater imaging depth, lower background, and minimal invasiveness relative to other fluorescent probes. The small ultra red fluorescent protein (smURFP) is the brightest niRFP currently reported and has been the subject of several mutagenesis studies to improve its biophysical characteristics. Here, we demonstrate a systematic approach to exploring the mutational landscape of smURFP using a comprehensive deep mutational scanning (DMS) library to identify novel smURFP mutations which confer greater in vivo fluorescence. By observing changes in relative abundance between naive and fluorescence sorted populations, we provide analysis of the enrichment of all possible single-codon substitutions, insertions, and deletions for smURFP. Enriched populations yielded a series of seven single-codon substitutions which confer a three-fold increase in in vivo fluorescence in E. coli when combined. Finally, we assess the potential underlying mechanisms for increased fluorescence by characterizing the biophysical and photophysical properties of the mutant niRFP sequences. We confirm that two of the derived smURFP sequences have a higher molecular brightness than wild type and yield the brightest niRFP reported.

synthetic biology↗

bioRxiv2025

Directed evolution of L-DOPA sensing and production enables efficient incorporation of an expanded genetic code into proteins

3,4-dihydroxyphenylalanine (L-DOPA) is a catechol-containing amino acid derived from L-tyrosine that can be introduced into proteins primarily as a post-translational modification. It can also be introduced in a site-specific manner into proteins via orthogonal tRNA synthetase:tRNA pairs. However, despite the interest in expanded genetic codes containing L-DOPA, efforts to improve metabolism relating to its production have been limited. Here, we report and engineer a LysR-family transcription factor, PP_2251, that can serve as a biosensor for L-DOPA, thereby allowing the optimization of genetic circuits for vastly improved L-DOPA production via compartmentalized partnered replication (CPR), an emulsion PCR-based directed evolution scheme. Using this biosensor, a promiscuous E. coli flavin-dependent monooxygenase (HpaB) was optimized via CPR for enhanced L-DOPA biosynthesis. Engineered HpaB variants could support efficient translational incorporation of L-DOPA into proteins with 80% incorporation efficiency and yields in excess of 250 mg.L-1. Improvements in L-DOPA production are not only of great interest for protein engineering and genetic code expansion but should impact the production of DOPA-derived natural products including catecholamine neurotransmitters and benzylisoquinoline alkaloids (BIAs), molecules of intense pharmaceutical interest.

synthetic biology↗

bioRxiv2024

A modular toolkit for environmental Rhodococcus, Gordonia, and Nocardia enables complex metabolic manipulation.

Soil-dwelling Actinomycetes are a diverse and ubiquitous component of the global microbiome, but largely lack genetic tools comparable to those available in model species such as E. coli or Pseudomonas putida, posing a fundamental barrier to their characterization and utilization as hosts for biotechnology. To address this, we have developed a modular plasmid assembly framework along with a series of genetic control elements for the previously genetically intractable Gram-positive environmental isolate Rhodococcus ruber C208 and demonstrate conserved functionality in diverse environmental isolates of Rhodococcus, Nocardia and Gordonia. This toolkit encompasses Mycobacteriale origins of replication, broad-host range antibiotic resistance markers, transcriptional and translational control elements, fluorescent reporters, a tetracycline-inducible system, and a counter-selectable marker. We use this toolkit to interrogate the carotenoid biosynthesis pathway in Rhodococcus erythropolis N9T-4, a weakly carotenogenic environmental isolate and engineer higher pathway flux towards the keto-carotenoid canthaxanthin. This work establishes several new genetic tools for environmental Mycobacteriales and provides a synthetic biology framework to support the design of complex genetic circuits in these species. IMPORTANCESoil-dwelling Actinomycetes, particularly the Mycobacteriales, include both diverse new hosts for sustainable biomanufacturing and emerging opportunistic pathogens. Rhodococcus, Gordonia and Nocardia are three abundant genera with particularly flexible metabolisms and untapped potential for natural product discovery. Among these, Rhodococcus ruber C208 was shown to degrade polyethylene, Gordonia paraffinivorans can assimilate carbon from solid hydrocarbons, and Nocardia neocaledoniensis (and many other Nocardia) possesses dual isoprenoid biosynthesis pathways. Many species accumulate high levels of carotenoid pigments, indicative of highly active isoprenoid biosynthesis pathways which may be harnessed for fermentation of terpenes and other commodity isoprenoids. Modular genetic toolkits have proven valuable for both fundamental and applied research in model organisms, but such tools are lacking for most Actinomycetes. Our suite of genetic tools and DNA assembly framework were developed for broad functionality and to facilitate rapid prototyping of genetic constructs in these organisms.

microbiology↗

bioRxiv2023

Interrogating the function of bicistronic translational control elements to improve consistency of gene expression

Context independent gene expression is required for genetic circuits to maintain consistent and predicable behavior. Previous efforts to develop context independent translation have leveraged the helicase activity of translating ribosomes via bicistronic design translational control elements (BCDs) located within an efficiently translated leader peptide. We have developed a series of bicistronic translational control elements with strengths that span several orders of magnitude, maintain consistent expression levels across diverse sequence contexts, and are agnostic to common ligation sequences used in modular cloning systems. We have used this series of BCDs to investigate several features of this design, including the spacing of the start and stop codons, the nucleotide identity upstream of the start codon, and factors affecting translation of the leader peptide. To demonstrate the flexibility of this architecture and their value as a generic modular expression control cassette for synthetic biology, we have developed a set of robust BCDs for use in several Rhodococcus species.

synthetic biology↗

bioRxiv2021

Using structurally fungible biosensors to evolve improved alkaloid biosyntheses

A key bottleneck in the microbial production of therapeutic plant metabolites is identifying enzymes that can greatly improve yield. The facile identification of genetically encoded biosensors can overcome this limitation and become part of a general method for engineering scaled production. We have developed a unique combined screening and selection approach that quickly refines the affinities and specificities of generalist transcription factors, and using RamR as a starting point we evolve highly specific (>100-fold preference) and sensitive (EC50 <30 M) biosensors for the alkaloids tetrahydropapaverine, papaverine, glaucine, rotundine, and noscapine. High resolution structures reveal multiple evolutionary avenues for the fungible effector binding site, and the creation of new pockets for different chemical moieties. These sensors further enabled the evolution of a streamlined pathway for tetrahydropapaverine, an immediate precursor to four modern pharmaceuticals, collapsing multiple methylation steps into a single evolved enzyme. Our methods for evolving biosensors now enable the rapid engineering of pathways for therapeutic alkaloids.

synthetic biology↗

bioRxiv2021

DLPacker: Deep Learning for Prediction of Amino Acid Side Chain Conformations in Proteins

AO_SCPLOWBSTRACTC_SCPLOWPrediction of side chain conformations of amino acids in proteins (also termed packing) is an important and challenging part of protein structure prediction with many interesting applications in protein design. A variety of methods for packing have been developed but more accurate ones are still needed. Machine learning (ML) methods have recently become a powerful tool for solving various problems in diverse areas of science, including structural biology. In this work we evaluate the potential of Deep Neural Networks (DNNs) for prediction of amino acid side chain conformations. We formulate the problem as image-to-image transformation and train a U-net style DNN to solve the problem. We show that our method outperforms other physics-based methods by a significant margin: reconstruction RMSDs for most amino acids are about 20% smaller compared to SCWRL4 and Rosetta Packer with RMSDs for bulky hydrophobic amino acids Phe, Tyr and Trp being up to 50% smaller.

biophysics↗

bioRxiv2019

A structure-based deep learning framework for protein engineering

While deep learning methods exist to guide protein optimization, examples of novel proteins generated with these techniques require a priori mutational data. Here we report a 3D convolutional neural network that associates amino acids with neighboring chemical microenvironments at state-of-the-art accuracy. This algorithm enables identification of novel gain-of-function mutations, and subsequent experiments confirm substantive phenotypic improvements in stability-associated phenotypes in vivo across three diverse proteins.

synthetic biology↗