Lars Barquist

The paper confirms high levels of antisense transcription in Orientia tsutsugamushi across multiple strains and suggests it may be a regulated mechanism in its lifecycle.

This study identifies resistance determinants to antisense antibiotics by analyzing mutations in gram-negative pathogens exposed to CPP-PNA conjugates, revealing adaptation strategies and resistance mechanisms.

This study uses TraDIS to identify conditionally essential genes in Salmonella Typhimurium during porcine infection, revealing niche-specific and conserved fitness requirements.

The paper compares dual RNA-seq data from eight Orientia tsutsugamushi strains in endothelial cells, finding no clear gene expression patterns correlating with virulence but identifying strain-specific interferon responses and conserved bacterial pathways.

The paper shows that the pcnB gene in Shigella flexneri promotes virulence by sustaining optimal levels of the virulence plasmid pINV, enhancing colonization and infection.

This study identifies Fe-S cluster damage as a trigger of the stringent response in Gram-negative pathogens, linking metabolic stress to virulence and transcriptional control.

The paper investigates antisense PNA conjugates against Fusobacterium nucleatum and discovers a non-targeting control PNA, FUS79, with bactericidal activity independent of antisense effects.

This study shows that biased sampling in bacterial genome data leads to poor performance in machine learning models predicting antimicrobial resistance.

This study identifies RbpB as a key RNA-binding protein regulating polysaccharide utilization in gut Bacteroides through post-transcriptional control of PULs.

IMPRINT uses cell-free transcription-translation to methylate DNA, bypassing bacterial restriction and improving transformation efficiency in diverse bacteria.

The paper identifies a small RNA, MasB, that increases Bacteroides thetaiotaomicron tolerance to tetracyclines by modulating gene expression under antibiotic stress.

The paper introduces a method to correct chromosomal location bias in functional genomics data from antibiotic-treated bacteria, improving accuracy in mutant drug sensitivity predictions.

This study investigates how network depth affects gene set inference from bacterial transcriptomes using denoising autoencoders and identifies genes uniquely induced during human colonization.

The paper introduces MASON, a webserver for designing antisense oligomers targeting bacterial mRNAs, and demonstrates its off-target prediction capabilities using experimental data.

The paper develops a mixed-effect random forest model to predict CRISPRi guide efficiency using data from depletion screens and gene-specific features, outperforming existing methods.

The paper shows that CRISPR-Cas13 systems require target transcript expression above a threshold to induce dormancy, distinguishing pathogenic from benign invaders and preventing autoimmunity.

The paper uses TraDIS to identify genes involved in twitching motility-mediated biofilm expansion in Pseudomonas aeruginosa, revealing both known and novel components.

The paper uses machine learning to identify genetic signatures of host adaptation in Salmonella enterica strains associated with extraintestinal disease.