Ian R. Wheeldon

SIRIUS generates maximally divergent DNA sequences for a given protein, reducing shared subsequences compared to existing methods.

The paper engineers a genetically encoded biosensor, PYRNSAID, to detect profen NSAIDs in wastewater with nanomolar sensitivity and demonstrates its functionality in simulated wastewater matrices.

The paper designs dynamic biosensors for detecting nitazenes and their metabolites using computational methods, achieving low nanomolar detection limits and limited cross-reactivity.

The paper identifies small-molecule sensors using ABA receptors and demonstrates their ability to detect diverse ligands including plant natural products and synthetic chemicals.

The paper designs and engineers minimal protein-based molecular inverters and switches that respond to ligands, demonstrating tunable and modular control of post-translational signaling.

This study examines genomic changes in mating-type loci across Rhodotorula yeast species, revealing structural divergence and inheritance patterns associated with shifts in reproductive strategies.

ALLEGRO designs universal CRISPR sgRNA libraries targeting multiple fungal species, validated experimentally across three fungi and extended to others.

This paper uses Ribo-seq to identify bottlenecks in protein secretion in Komagataella phaffii and improves HSA production through targeted gene knockouts.

The paper uses a PYR1 biosensor-driven CRISPR screen in Kluyveromyces marxianus to identify gene knockouts that enhance geraniol production by up to 2-fold.

The paper designs a high-activity CRISPR sgRNA library for Yarrowia lipolytica and uses it to identify genes involved in acetate and hydrocarbon tolerance.

The paper develops a high-activity CRISPR-Cas9 library for Komagataella phaffii and uses it to identify essential genes related to protein production, secretion, and glycosylation.

acCRISPR improves CRISPR screen accuracy by correcting sgRNA activity, identifying essential genes in yeast under various conditions.

This study uses population genomics to identify genetic targets for improving phenazine biosynthesis in Pseudomonas chlororaphis through genome-wide association analysis and experimental validation.

The paper develops DeepGuide, a deep learning model to predict high activity CRISPR-Cas9 and -Cas12a guides in Yarrowia lipolytica using genome-wide functional screens.

The paper validates genome-wide CRISPR-Cas9 function in Yarrowia lipolytica by quantifying sgRNA efficiency and identifying high-efficiency guides for 94% of genes.