FabT_+or-Tween_S.pyogenesM28_Transcriptomic analysis

Published: 14 May 2024| Version 1 | DOI: 10.17632/68bhhsy2p4.1
Clara Lambert,


We used RNAseq to identify how membrane fatty acid changes might impact and explain the virulence defect during host infection. WT and mFabT expression was compared in THY, and in THY-Tween (as C18:1Δ9 source), which to activates WT FabT repression. RNA isolation and Illumina RNA-seq sequencing: GAS strains were cultured at 37°C in THY or THY-Tween, and cells were harvested during exponential growth (OD600 between 0.4 and 0.5). Independent triplicate cultures were prepared for each condition. For RNA preparation, 2 volumes of RNA protect (Qiagen) was added to cultures prior centrifugation (10 min 12,000 g) and total RNA was extracted after lysing bacteria by a 30 min 15 mg.ml-1 lysozyme, 300 U.ml-1 mutanolysin treatment at 20°C followed by two cycles of Fast-prep (power 6, 30 s) at 4 °C. RNA extraction (Macherey-Nagel RNA extraction kit; Germany) was done according to supplier instructions. RNA integrity was analyzed using an Agilent Bioanalyzer (Agilent Biotechnologies, Ca., USA). 23S and 16S rRNA were depleted from the samples using the MICROBExpress Bacterial mRNA enrichment kit (Invitrogen, France); depletion was controlled on Agilent Bioanalyzer (Agilent Biotechnologies). Libraries were prepared using an Illumina TS kit. Libraries were sequenced generating 10,000,000 to 20,000,000 75-bp-long reads per sample. RNA-Seq data analysis: The MGAS6180 strain sequence (NCBI), which is nearly identical to M28PF1, was used as a reference sequence to map sequencing reads using the STAR software (2.5.2b) BIOCONDA (Anaconda Inc). RNA-seq data were analyzed using the hclust function and a principal component analysis in R 3.5.1 (version 2018-07-02). For differential expression analysis, normalization and statistical analyses were performed using the SARTools package and DESeq2 p-values were calculated and adjusted for multiple testing using the false discovery rate controlling procedure. We used UpsetR to visualize set intersections in a matrix layout comprising the mFabT versus the WT strain grown in THY and in THY-Tween, and growth in THY-Tween versus THY for each strain.



Institut Cochin


Microbiology, Fatty Acid, Gene Regulation, Host-Pathogen Interaction