Biology subjects

Wheeldon, I.

Publications and source records attributed to Wheeldon, I..

16 recordsLinked to original sources

bioRxiv2026

Maximally Divergent Synonymous Gene Design with SIRIUS

The design of maximally divergent DNA sequences translating into the same protein is a critical problem in synthetic biology. Current design tools that rely on heuristics or machine learning often fail to effectively minimize the length of shared subsequences between the gene copies, compromising strain stability. Here, we introduce SIRIUS, a combinatorial optimization algorithm designed to generate maximally divergent coding sequences for a given protein of interest. Leveraging integer linear programming enforcing host-specific codon usage thresholds, SIRIUS stabilizes synthetic constructs and broadens the accessible design space for robust and scalable synethtic biology. Experimental results show that SIRIUS produces diverse sequences with fewer shared subsequences than existing methods. SIRIUS is freely available on GitHub at https://github.com/ucrbioinfo/sirius.

synthetic biology↗

bioRxiv2026

Protein engineering of a genetically encoded biosensor for wastewater detection of profen NSAIDs

Non-steroidal anti-inflammatory drugs (NSAIDs) are pervasive environmental contaminants due to their frequent and widespread use, multiple paths of release into surface and ground water supply, diversity of the chemical class, and toxicity to aquatic and other non-target species. In particular, the 2-arylpropionic acid ("profen") class of NSAIDs poses significant risks to aquatic ecosystems due to incomplete removal during wastewater treatment. Current monitoring precludes high frequency testing at point sources. Here we present the engineering and application of a genetically encodable, protein-based biosensor for the detection of the NSAIDs ketoprofen and pranoprofen in wastewater effluent. We repurposed the plant hormone receptor PYR1 to bind selectively to profens using computational protein design, deep mutational scanning, and yeast 2 hybrid and yeast surface display screening. The resulting sensor, PYRNSAID, has a nanomolar limit of detection for ketoprofen and panoprofen, and {micro}M sensitivity to the NSAIDs ibuprofen, fenoprofen, tolmetin and diclofenac. We also demonstrated dose responsive-activity of our sensor in simulated wastewater matrices containing the common wastewater contaminants sulfamethoxazole, caffeine, acetaminophen, and 2,4, dichlorophenol using a split Nanoluc luminescence assay. PYRNSAID is the first step towards a scalable, cost-effective alternative for real-time monitoring of pharmaceutical pollution.

bioengineering↗

bioRxiv2025

Design of post-translational, ligand-controlled inverters and switches

Rational control over diverse, ligand-responsive output networks is a foundational challenge in synthetic biology, particularly for systems based on post-translational signaling. Here, we present the design and engineering of minimal, modular protein architectures for chemically responsive molecular inverters and digital switches. Our inverter design modifies the plant-derived PYR1-HAB1 chemically inducible dimerization module by incorporating a constitutive activator, which is then competitively displaced by the ligand-bound PYR1 receptor, converting the native dimerization-on mechanism into a signal-off inverter. We establish key design features and demonstrate predictable tuning of the inverters transfer function, including its maximum output, half-maximal inhibitory concentration, and minimum output, solely by adjusting protein stoichiometry. The architecture is modular, enabling plug-and-play response to diverse, user-defined drug-like small molecules. We show that an inverter biosensor for an environmental contaminant functions in engineered living cells with a low nanomolar sensitivity. Additionally, we convert the PYR1-HAB1 sensor into a digital switch by adding an engineered molecular titrant to the system. Overall, this work provides a generalizable, minimal, and tunable protein scaffold for programming complex, post-translational signaling logic, significantly expanding the toolkit for sophisticated biological circuit design.

synthetic biology↗

bioRxiv2025

Genomic rearrangements at the MAT locus suggest reproductive shifts in Rhodotorula yeasts

Transitions from canonical outcrossing to rare, cryptic, or noncanonical reproduction are widespread in fungi, but how mating-type (MAT) systems are reorganized at the genomic and population levels during these shifts remains unclear. The coexistence of sexually reproducing species and putatively asexual lineages makes Rhodotorula a natural comparative system for addressing this question. We analyzed 249 globally sampled strains using a combination of long-read and short-read sequencing. Phylogenomics resolved three major clades and several closely related species complexes. Chromosome-scale assemblies confirmed physical separation of the pheromone/receptor (P/R) and homeodomain (HD) loci, whereas non-random P/R-HD associations revealed constrained tetrapolar inheritance. The P/R locus showed conserved synteny within mating types but extensive structural divergence between A1 and A2 alleles, whereas the HD locus remained compact and conserved. Mating-type distributions varied across clades, with both A1 and A2 present in Clade C, lineage-structured partitioning in Clade B, and pronounced A2 dominance in Clade A. Genome-wide linkage disequilibrium (LD) decay in putatively asexual R. mucilaginosa, although slower than in sexual R. diobovata, was consistent with historical recombination in a species without an observed sexual cycle. Clade A further exhibited deep trans-specific polymorphism of STE3.A2 and relaxed purifying selection, mosaic A2 P/R configurations retaining RHA.A1, A1/A2 and A2/A2 hybrid genomes, and A2-associated gene content beyond MAT loci. In conclusion, our findings underscore the dynamic nature of MAT-locus remodeling in Rhodotorula and establish this genus as a valuable model for investigating transitions from heterothallism toward reproductive strategies less dependent on opposite-type partners.

evolutionary biology↗

bioRxiv2025

Computational design of dynamic biosensors for emerging synthetic opioids

Nitazenes are an emergent class of synthetic opioids that rival or exceed fentanyl in their potency. These compounds have been detected internationally in illicit drugs and are the cause of increasing numbers of hospitalizations and overdoses. New analogs are consistently released, making detection challenging - new ways of testing a wide range of nitazenes and their metabolic products are urgently needed. Here, we developed a computational protocol to redesign the plant abscisic acid receptor PYR1 to bind diverse nitazenes and maintain its dynamic transduction mechanism. The best design has a low nanomolar limit of detection in vitro against nitazene and menitazene. Deep mutational scanning yielded sensors able to recognize a range of clinically relevant nitazenes and the common metabolic byproduct in complex biological matrices with limited cross-specificity against unrelated opioids. Application of protein design tools on privileged receptors like PYR1 may yield general sensors for a wide range of applications in vitro and in vivo.

biochemistry↗

bioRxiv2025

Unusually Broad-spectrum small-molecule sensing using a single protein scaffold

Small-molecule sensing in plants is dominated by chemical-induced dimerization modules. In the abscisic acid (ABA) system, allosteric receptors recruit phosphatase effectors and achieve nM in vivo responses from {micro}M receptor-ligand interactions. This sensitivity amplification could enable ABA receptors to serve as generic scaffolds for designing small-molecule sensors. To test this, we screened collections of mutant ABA-receptors against 2,726 drugs and other ligands and identified 569 sensors for 6.7% of these ligands. The mutational patterns indicate strong selection for ligand-specific binding pockets. We used these data to develop a sensor design pipeline and isolated sensors for multiple plant natural products, 2,4,6-trinitrotoluene (TNT), and "forever" per- and polyfluoroalkyl substances (PFAS). Thus, the ABA sensor system enables design and isolation of small-molecule sensors with broad chemical scope and antibody-like simplicity.

synthetic biology↗

bioRxiv2025

Kingdom-Wide CRISPR Guide Design with ALLEGRO

Designing CRISPR single guide RNA (sgRNA) libraries targeting entire kingdoms of life will significantly advance genetic research in diverse and underexplored taxa. Current sgRNA design tools are often species-specific and fail to scale to large, phylogenetically diverse datasets, limiting their applicability to comparative genomics, evolutionary studies, and biotechnology. Here, we present ALLEGRO, a combinatorial optimization algorithm able to design minimal, yet highly effective sgRNA libraries targeting thousands of species. Leveraging integer linear programming, ALLEGRO identified compact sgRNA sets simultaneously targeting several genes of interest for over 2,000 species across the fungal kingdom. We experimentally validated the sgRNAs designed by ALLEGRO in Kluyveromyces marxianus, Komagataella phaffii, and Yarrowia lipolytica. In addition, we adopted a generalized Cas9-Ribonucleoprotein delivery system coupled with protoplast transformation to extend ALLEGROs sgRNA libraries to other untested fungal genomes, such as Rhodotorula araucariae. Our experimental results, along with cross-validation, show that ALLEGRO enables efficient CRISPR genome editing, supporting the development of universal sgRNA libraries applicable to entire taxonomic groups.

bioinformatics↗

bioRxiv2025

Ribo-seq guided design of enhanced protein secretion in Komagataella phaffii

The production of recombinant proteins requires the precise coordination of various biological processes, including protein synthesis, folding, trafficking, and secretion. The overproduction of a heterologous protein can impose various bottlenecks on these networks. Identifying and alleviating these bottlenecks can guide strain engineering efforts to enhance protein production. The methylotrophic yeast Komagataella phaffii is used for its high capacity to produce recombinant proteins. Here, we use ribosome profiling to identify bottlenecks in protein secretion during heterologous expression of human serum albumin (HSA). Validation of this analysis showed that the knockout of non-essential genes whose gene products target the ER, through co- and post-translational mechanisms, and have high ribosome utilization can increase production of a heterologous protein, HSA. A triple knockout in co-translationally translocated carbohydrate and acetate transporter Gal2p, cell wall maintenance protein Ydr134cp, and the post-translationally translocated cell wall protein Aoa65896.1 increased HSA production by 35%. This data-driven strain engineering approach uses cell-level information to identify gene targets for phenotype improvement. This specific case identifies hits and creates strains with improved HSA production, with Ribo-seq and bioinformatic analysis to identify non-essential ER targeted proteins that are high ribosome utilizers.

systems biology↗

bioRxiv2024

PYR1 biosensor-driven genome-wide CRISPR screens for improved monoterpenoid production in Kluyveromyces marxianus

Monoterpenoids are valued for their roles as flavors, fragrances, insecticides, and energy-dense fuels. Microbial biosynthesis offers sustainable biosynthesis routes for these important molecules, but production levels remain limited. Here, we introduce a biosensor-driven microbial engineering strategy to enhance monoterpenoid production, specifically targeting geraniol. Using mutagenized libraries of the PYR1 receptor--a versatile biosensor from plant ABA signaling pathways with a malleable binding pocket--we screened 24 monoterpenoids and identified PYR1 variants responsive to eight, including geraniol. A low background, highly selective geraniol-sensitive PYR1 variant was expressed in the thermotolerant yeast Kluyveromyces marxianus as a growth-based biosensor circuit, allowing for rapid strain engineering. By coupling the geraniol-sensitive PYR1 sensor with a genome-wide CRISPR-Cas9 mutagenesis approach, we identified six gene knockouts that enhance geraniol production, achieving up to a 2-fold increase in titer. This study demonstrates the power of the PYR1 biosensor platform to enable rapid strain engineering and the identification of mutants that improve titer of a desired metabolite.

synthetic biology↗

bioRxiv2024

Optimized genome-wide CRISPR screening enables rapid engineering of growth-based phenotypes in Yarrowia lipolytica

CRISPR-Cas9 functional genomic screens uncover gene targets linked to various phenotypes for metabolic engineering with remarkable efficiency. However, these genome-wide screens face a number of design challenges, including variable guide RNA activity, ensuring sufficient genome coverage, and maintaining high transformation efficiencies to ensure full library representation. These challenges are prevalent in non-conventional yeast, many of which exhibit traits that are well suited to metabolic engineering and bioprocessing. To address these hurdles in the oleaginous yeast Yarrowia lipolytica, we designed a compact, high-activity genome-wide sgRNA library. The library was designed using DeepGuide, a sgRNA activity prediction algorithm, and a large dataset of [~]50,000 sgRNAs with known activity. Three guides per gene enables redundant targeting of 98.8% of genes in the genome in a library of 23,900 sgRNAs. We deployed the optimized library to uncover genes essential to the tolerance of acetate, a promising alternative carbon source, and various hydrocarbons present in many waste streams. Our screens yielded several gene knockouts that improve acetate tolerance on their own and as double knockouts in media containing acetate as the sole carbon source. Analysis of the hydrocarbon screens revealed genes related to fatty acid and alkane metabolism in Y. lipolytica. The optimized CRISPR gRNA library and its successful use in Y. lipolytica led to the discovery of alternative carbon source-related genes and provides a workflow for creating high-activity, compact genome-wide libraries for strain engineering. HighlightsO_LIDesigned a compact, high activity CRISPR sgRNA knockout library for Yarrowia lipolytica. C_LIO_LIDeveloped an efficient pipeline for discovering genes involved in alternative carbon-source utilization. C_LIO_LIIdentified single and double gene knockouts that improve growth on acetate. C_LIO_LIIdentified genes with improved fitness and essentiality for hydrocarbon growth. C_LI

synthetic biology↗

bioRxiv2024

Functional genomic screening in Komagataella phaffii enabled by high-activity CRISPR-Cas9 library

CRISPR-based high-throughput genome-wide loss-of-function screens are a valuable approach to functional genetics and strain engineering. The yeast Komagataella phaffii is a host of particular interest in the biopharmaceutical industry and as a metabolic engineering host for proteins and metabolites. Here, we design and validate a highly active 6-fold coverage genome-wide sgRNA library for this biotechnologically important yeast containing 30,848 active sgRNAs targeting over 99% of its coding sequences. Conducting fitness screens in the absence of functional non-homologous end joining (NHEJ), the dominant DNA repair mechanism in K. phaffii, provides a quantitative means to assess the activity of each sgRNA in the library. This approach allows for the experimental validation of each guides targeting activity, leading to more precise screening outcomes. We used this approach to conduct growth screens with glucose as the sole carbon source and identify essential genes. Comparative analysis of the called gene sets identified a core set of K. phaffii essential genes, many of which relate to protein production, secretion, and glycosylation. The high activity, genome-wide CRISPR library developed here enables functional genomic screening in K. phaffii, applied here to gene essentiality classification, and promises to enable other genetic screens. HighlightsO_LIDesigned and validated a high activity genome-wide CRISPR-Cas9 library for K. phaffii C_LIO_LIDisabling NHEJ DNA repair enables the generation of genome-wide guide activity profiles C_LIO_LIActivity-corrected fitness screens identify a high confidence set of essential genes in K. phaffii C_LIO_LIProtein production, secretion, and glycosylation pathways are essential in K. phaffii but not in other yeasts C_LI

systems biology↗

bioRxiv2024

GMMA can stabilize proteins across different functional constraints

Stabilizing proteins without otherwise hampering their function is a central task in protein engineering and design. PYR1 is a plant hormone receptor that has been engineered to bind diverse small molecule ligands. We sought a set of generalized mutations that would provide stability without affecting functionality for PYR1 variants with diverse ligand-binding capabilities. To do this we used a global multi-mutant analysis (GMMA) approach, which can identify substitutions that have stabilizing effects and do not lower function. GMMA has the added benefit of finding substitutions that are stabilizing in different sequence contexts and we hypothesized that applying GMMA to PYR1 with different functionalities would identify this set of generalized mutations. Indeed, conducting FACS and deep sequencing of libraries for PYR1 variants with two different functionalities and applying a GMMA analysis identified 5 substitutions that, when inserted into four PYR1 variants that each bind a unique ligand, provided 2-6{degrees}C in increased thermal stability and no decrease in functionality.

biochemistry↗

bioRxiv2023

Population genomics-guided engineering of phenazine biosynthesis in Pseudomonas chlororaphis

The emergence of next-generation sequencing (NGS) technologies has made it possible to not only sequence entire genomes, but also identify metabolic engineering targets across the pangenome of a microbial population. This study leverages NGS data as well as existing molecular biology and bioinformatics tools to identify and validate genomic signatures for improving phenazine biosynthesis in Pseudomonas chlororaphis. We sequenced a diverse collection of 34 Pseudomonas isolates using short- and long-read sequencing techniques and assembled whole genomes using the NGS reads. In addition, we assayed three industrially relevant phenotypes (phenazine production, biofilm formation, and growth temperature) for these isolates in two different media conditions. We then provided the whole genomes and phenazine production data to a unitig-based microbial genome-wide association study (mGWAS) tool to identify novel genomic signatures responsible for phenazine production in P. chlororaphis. Post-processing of the mGWAS analysis results yielded 330 significant hits influencing the biosynthesis of one or more phenazine compounds. Based on a quantitative metric (called the phenotype score), we elucidated the most influential hits for phenazine production and experimentally validated them in vivo in the most optimal phenazine producing strain. Two genes significantly increased phenazine-1-carboxamide (PCN) production: a histidine transporter (ProY_1), and a putative carboxypeptidase (PS__04251). A putative MarR-family transcriptional regulator decreased PCN titer when overexpressed in a high PCN producing isolate. Overall, this work seeks to demonstrate the utility of a population genomics approach as an effective strategy in enabling identification of targets for metabolic engineering of bioproduction hosts.

systems biology↗

bioRxiv2022

acCRISPR: An activity-correction method for improving the accuracy of CRISPR screens

High throughput CRISPR screens are revolutionizing the way scientists unravel the genetic underpinnings of novel and evolved phenotypes. One of the critical challenges in accurately assessing screening outcomes is accounting for the variability in sgRNA cutting efficiency. Poorly active guides targeting genes essential to screening conditions obscure the growth defects that are expected from disrupting them. Here, we develop acCRISPR, an end-to-end pipeline that identifies essential genes in pooled CRISPR screens using sgRNA read counts obtained from next-generation sequencing. acCRISPR uses experimentally determined cutting efficiencies for each guide in the library to provide an activity correction to the screening outcomes, thus determining the fitness effect of disrupted genes. This is accomplished by calculating an optimization metric that quantifies the tradeoff between guide activity and library coverage, which is maximized to accurately classify genes essential to screening conditions. CRISPR-Cas9 and -Cas12a screens were carried out in the non-conventional oleaginous yeast Yarrowia lipolytica to determine a high-confidence set of essential genes for growth under glucose, a common carbon source used for the industrial production of oleochemicals. acCRISPR was also used in gain-and loss-of-function screens under high salt and low pH conditions to identify known and novel genes that were related to stress tolerance. Collectively, this work presents an experimental-computational framework for CRISPR-based functional genomics studies that may be expanded to other non-conventional organisms of interest.

synthetic biology↗

bioRxiv2021

Genome-wide functional screens enable the prediction of high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica

Genome-wide functional genetic screens have been successful in discovering genotype-phenotype relationships and in engineering new phenotypes. While broadly applied in mammalian cell lines and in E. coli, use in non-conventional microorganisms has been limited, in part, due to the inability to accurately design high activity CRISPR guides in such species. Here, we develop an experimental-computational approach to sgRNA design that is specific to an organism of choice, in this case the oleaginous yeast Yarrowia lipolytica. A negative selection screen in the absence of non-homologous end-joining, the dominant DNA repair mechanism, was used to generate single guide RNA (sgRNA) activity profiles for both SpCas9 and LbCas12a. This genome-wide data served as input to a deep learning algorithm, DeepGuide, that is able to accurately predict guide activity. DeepGuide uses unsupervised learning to obtain a compressed representation of the genome, followed by supervised learning to map sgRNA sequence, genomic context, and epigenetic features with guide activity. Experimental validation, both genome-wide and with a subset of selected genes, confirms DeepGuides ability to accurately predict high activity sgRNAs. DeepGuide provides an organism specific predictor of CRISPR guide activity that could be broadly applied to fungal species, prokaryotes, and other non-conventional organisms.

synthetic biology↗

bioRxiv2018

Validating genome-wide CRISPR-Cas9 function in the non-conventional yeast Yarrowia lipolytica

Genome-wide mutational screens are central to understanding the genetic underpinnings of evolved and engineered phenotypes. The widespread adoption of CRISPR-Cas9 genome editing has enabled such screens in many organisms, but identifying functional sgRNAs still remains a challenge. To address this limitation, we developed a methodology to quantify the cutting efficiency of each sgRNA in a genome-scale library in the biotechnologically important yeast Yarrowia lipolytica. Screening in the presence and absence of native DNA repair enabled high-throughput quantification of sgRNA function leading to the identification of high efficiency sgRNAs that cover 94% of genes. Library validation enhanced the classification of essential genes by identifying inactive guides that create false negatives and mask the effects of successful disruptions. Quantification of guide effectiveness also creates a dataset from which functional determinants of CRISPR-Cas9 can be identified. Finally, application of the library identified mutations that led to high lipid accumulation and eliminated pseudohyphal morphology.

synthetic biology↗