Laura M. Carroll

The paper identifies rare Bacillus cereus group species in unassembled metagenomic samples, revealing their potential geographic distribution and genomic diversity.

The paper identifies novel insecticidal B. cereus group strains from UK insect-dense regions, revealing Cry toxin genes and uncharacterized biosynthetic gene clusters with potential for biopesticide development.

This study characterizes 20 archived B. paranthracis clinical strains, highlighting phenotypic similarities and differences with B. anthracis and assessing MinION sequencing for antimicrobial resistance detection.

This study identifies NheABC as a pH-dependent cytotoxin in B. cereus that enhances colonization and causes cell death in mammalian cells.

The paper analyzes the biosynthetic potential of the Bacillus cereus group using genomic data, identifying many novel biosynthetic gene clusters.

Sismis is a machine learning tool that accurately detects and classifies secretion systems in bacterial (meta)genomes, identifying many previously unknown systems.

The paper introduces Python libraries for computing average nucleotide identity, matching existing tools' results and integrating with BioPython for workflow use.

This paper introduces Bascet and Zorn, tools for scalable single-cell metagenomic analysis, demonstrating their utility on mock and human saliva samples.

IGUA is a fast and scalable method for delineating gene cluster families in prokaryotic genomes, outperforming existing tools in speed without sacrificing accuracy.

This study develops an exposure assessment model to predict B. cereus group growth in HTST milk under temperature abuse conditions, showing some genotypes can reach 105 CFU/mL by day 35 of storage.

A uniformly processed set of 2,440,377 bacterial and archaeal genomes with search tools and annotations, plus an AI-mined peptide set yielding ATB20, active in a mouse skin infection model.

This study evaluates four bioinformatics tools for detecting crystal protein-encoding genes in Bacillus cereus s.s. biovar Thuringiensis using whole-genome sequencing data, finding IDOPS performs best overall.

The paper develops BTyperDB, a global atlas of Bacillus cereus sensu lato genomes, to improve pathogen surveillance and identify emerging lineages.

A linear conditional random field over ordered protein-domain annotations finds biosynthetic gene clusters de novo more precisely than DeepBGC and runs over three times faster on one CPU.