Charles Langelier

The paper tracks antibiotic resistance gene (ARG) dynamics in mice during long-term antibiotic treatment, finding that commensal bacteria reduce ARG burden by outcompeting resistant taxa.

The paper identifies immune signatures in SLE cutaneous subtypes using transcriptomics, revealing subtype-specific pathways and potential therapeutic targets.

This study uses proteomics to analyze immune responses in tracheal aspirate and plasma from critically ill children with viral lower respiratory tract infections, identifying diagnostic biomarkers and correlations with viral load and coinfections.

This study identifies immune subtypes in hospitalized COVID-19 patients linked to clinical outcomes and long COVID risk through longitudinal multi-omics analysis.

This study investigates viral reactivation in COVID-19 patients, finding associations between reactivation of specific virus families and clinical outcomes, including mortality and PASC symptoms.

This study identifies immune programs linked to COVID-19 severity and mortality through longitudinal multi-omics analysis of 1,152 hospitalized patients.

The paper develops an open-source, cloud-based tool for detecting pathogens and antimicrobial resistance genes in metagenomic and whole-genome sequencing data, demonstrating its application across clinical and environmental studies.

The paper identifies cell-specific transposable element (TE) gene expression associations with SLE phenotypes, finding 731 differentially expressed TEs linked to antiviral pathways and IFN signaling.

This study uses metagenomic sequencing to identify pathogens in pediatric meningitis cases in Bangladesh, revealing a Chikungunya virus outbreak and other previously undetected causes.

This paper develops a metagenomic sequencing approach to diagnose lower respiratory tract infections by integrating pathogen detection, microbiome analysis, and host transcriptome data.

The paper investigates a pediatric brainstem encephalitis outbreak using metagenomic next-generation sequencing, finding that mNGS significantly improves EV-A71 detection in CSF and confirms the outbreak strain's relation to a neuroinvasive isolate.

This study uses metagenomic sequencing and the IDseq platform to identify microbial pathogens in Ugandan children with fever, revealing common pathogens and novel viruses.

This study uses metagenomic sequencing to detect respiratory pathogens in hematopoietic transplant patients, finding it more sensitive than conventional methods and identifying new pathogens.