Marco Galardini

This study develops a microbial community to study plasmid-mediated AMR spread, showing plasmids protect the community from antibiotics and that HGT dynamics can be controlled.

This study reveals that phage T7 kinase broadly phosphorylates host and phage proteins, disabling bacterial defense systems through widespread phosphorylation.

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 identifies cis non-coding genetic variants associated with gene expression changes in E. coli and P. aeruginosa pangenomes, revealing their role in antimicrobial resistance.

This study identifies nitroxoline's broad antibacterial activity against Gram-negative bacteria, its mode of action involving metal homeostasis and outer membrane disruption, and resistance mechanisms across multiple species.

microGWAS is a pipeline for bacterial GWAS that integrates multiple variant types and analysis tools to identify genetic variants associated with phenotypes like virulence and antimicrobial resistance.

This paper introduces a method to improve the interpretability of bacterial GWAS by linking k-mers to gene clusters, demonstrating its precision and scalability on real datasets.

ChemGAPP is a package for chemical genomics analysis and phenotypic profiling that integrates quality control and provides sub-packages for different screening types.

The paper systematically maps the functional role of phosphorylation by analyzing phospho-deficient mutants in yeast and linking yeast phenotypes to human functional relevance.

The paper assesses how genetic background affects gene deletion phenotypes in yeast, finding significant variation across strains and conditions.

The paper benchmarks variant effect predictors and analyzes SNVs in H. sapiens, S. cerevisiae, and E. coli to predict molecular effects and generate protein complex burden scores.

pyseer is a tool for microbial pangenome-wide association studies that integrates various methods, offers flexible input data handling, and provides new ways to interpret results.

The paper predicts growth defects in Escherichia coli strains using genetic variant impact models and gene function data, achieving reliable predictions for up to 38% of tested conditions.