Frank M. Aarestrup

This study uses portable metagenomics to identify diverse pathogens in diarrhoeal samples from Burundi, revealing that many suspected cholera cases are caused by other bacteria like Escherichia coli.

This study shows Rift Valley fever virus lineage C circulates persistently in Rwanda through local transmission, not repeated introductions, based on whole-genome sequencing of livestock samples from 2022-2025.

The paper uses single-cell metagenomics to link plasmid-derived antimicrobial resistance to host bacteria in pigs, identifying resistance-associated features in longitudinal gut microbiome data.

This study examines how ceftiofur antibiotic treatment and E. coli inoculation affect the calf fecal microbiome using shotgun metagenomics and single-cell sequencing.

A ProtT5-embedding, ConvNext-plus-attention ensemble predicts human pathogenic capacity from whole bacterial genomes, outperforming prior predictors on species absent from training and flagging influential proteins.

The paper identifies Acinetobacter sp. as a dominant bacterium in tomato plant microbiota and shows its functional role in nutrient mobilization and stress adaptation, while decoupling its presence from antimicrobial resistance genes.

This study uses sewage metagenomics to distinguish seasonal, human-derived, and environmental microbial communities, offering potential for improved AMR surveillance.

The paper identifies co-occurring antimicrobial resistance genes (ARGs) in metagenomic datasets to highlight potential co-selection in resistomes across different environments.

The paper describes open data sharing, analysis tools, and lessons learned from the European COVID-19 Data Platform's SARS-CoV-2 data collection and analysis efforts.

The paper characterizes plasmids in clinical bacterial isolates from a Tanzanian hospital, finding high plasmid prevalence and co-occurrence of resistance and virulence genes.

The paper curates a large metagenomic dataset to study the global distribution and dynamics of antimicrobial resistance genes.

This paper develops a random forest model to predict plasmid hosts, achieving 0.662 and 0.867 Matthews correlation coefficients at species and order levels, respectively.

The paper introduces a bioinformatics pipeline for rapid phylogenomic analysis of bacterial whole-genome isolates, enabling large-scale surveillance and real-time outbreak detection.

This paper demonstrates that malaria rapid diagnostic tests can be used for large-scale molecular surveillance of antimalarial resistance markers using next-generation sequencing.

The paper describes an informatics platform for structured data storage and pre-publication sharing of pathogen sequencing data with stakeholders.