Abigail L. Manson

This study identifies NagU as the primary uridyltransferase in Staphylococcus aureus for UDP-GlcNAc synthesis, which is essential for cell wall synthesis and regulated by its interaction with DacA.

The paper examines the mobilome of multidrug-resistant Enterococcus faecalis from healthy piglets, identifying mobile genetic elements and their roles in antibiotic resistance and adaptation.

The paper identifies efagins, a new class of antibacterial agents that target enterococcal cell wall carbohydrates, and shows they can be engineered for alternative receptor targeting.

This study benchmarks plasmid detection and reconstruction tools on short-read assemblies from diverse bacterial species, finding performance varies with database coverage and assembly quality.

This study shows avibactam resistance emerges rapidly through a large mutational target, with no significant growth rate difference between resistant and susceptible strains.

The paper introduces fai and zol for large-scale comparative analysis of gene clusters and MGEs, enabling comprehensive orthology inference and evolutionary studies across thousands of genomes.

POASTA is an optimal algorithm for partial order alignment that improves speed and memory efficiency, enabling larger alignments in bacterial gene datasets.

This study identifies distinct E. coli transcriptional profiles in the guts of recurrent UTI sufferers using a novel pangenome hybrid selection method.

The paper identifies mutations in the BarA/SirA regulatory pathway in persistent Salmonella infections, showing they reduce virulence and inflammation.

SAP improves bacterial gene function prediction using protein embeddings and conserved synteny, identifying novel toxins in enterococci.

The paper develops a method to trace horizontal gene transfer and persistence of carbapenem resistance genes across bacterial species using genomic data from clinical isolates.

StrainGE identifies low-abundance microbial strains from metagenomic data with higher sensitivity and resolution than existing tools.

QuantTB classifies mixed Mycobacterium tuberculosis infections in whole genome sequencing data, accurately quantifying strains and detecting resistance mutations.