Pseudomonas aeruginosa uses quorum sensing (QS) to modulate the expression of several virulence factors that enable it to establish severe infections. The QS system in P. aeruginosa is complex, intricate and is dominated by two main N-acyl-homoserine lactone circuits, LasRI and RhlRI. These two QS systems work in a hierarchical fashion with LasRI at the top, directly regulating RhlRI. Together these QS circuits regulate several virulence associated genes, metabolites, and enzymes in P. aeruginosa. Paradoxically, LasR mutants are frequently isolated from chronic P. aeruginosa infections, typically among cystic fibrosis (CF) patients. This suggests P. aeruginosa can undergo significant evolutionary pathoadaptation to persist in long term chronic infections. In contrast, mutations in the RhlRI system are less common. Here, we have isolated a clinical strain of P. aeruginosa from a CF patient that has deleted the transcriptional regulator RhlR entirely. Whole genome sequencing shows the rhlR locus is deleted in PA80 alongside a few non-synonymous mutations in virulence factors including protease lasA and rhamnolipid rhlA, rhlB, rhlC. Importantly we did not observe any mutations in the LasRI QS system. PA80 does not appear to have an accumulation of mutations typically associated with several hallmark pathoadaptive genes (i.e., mexT, mucA, algR, rpoN, exsS, ampR). Whole genome comparisons show that P. aeruginosa strain PA80 is closely related to the hypervirulent Liverpool epidemic strain (LES) LESB58. PA80 also contains several genomic islands (GI’s) encoding virulence and/or resistance determinants homologous to LESB58. To further understand the effect of these mutations in PA80 QS regulatory and virulence associated genes, we compared transcriptional expression of genes and phenotypic effects with isogenic mutants in the genetic reference strain PAO1. In PAO1, we show that deletion of rhlR has a much more significant impact on the expression of a wide range of virulence associated factors rather than deletion of lasR. In PA80, no QS regulatory genes were expressed, which we attribute to the inactivation of the RhlRI QS system by deletion of rhlR and mutation of rhlI. This study demonstrates that inactivation of the LasRI system does not impact RhlRI regulated virulence factors. PA80 has bypassed the common pathoadaptive mutations observed in LasR by targeting the RhlRI system. This suggests that RhlRI is a significant target for the long-term persistence of P. aeruginosa in chronic CF patients. This raises important questions in targeting QS systems for therapeutic interventions.
Bibliographical noteFunding Information:
Genome assembly and comparative genomics. The PA80 whole genome sequence was provided by MicrobesNG (http://www.microbesng.uk) which is supported by the BBSRC (grant number BB/L024209/1). The PA80 gene sequence has been submitted to GenBank (PRJNA675745) and is now publicly available. The PA80 genomic DNA library was prepared using Nextera XT Library Prep Kit (Illumina, San Diego, USA) with slight modifications. Hamilton Microlab STAR automated liquid handling system was used for DNA quantification and library preparation. The pooled libraries were quantified using the Kapa Biosystems Library Quantification Kit for Illumina on a Roche light cycler 96 qPCR machine and sequenced on the Illumina HiSeq using a 250 bp paired end protocol. Reads were adapter trimmed using Trimmomatic 0.3v software and for de novo assembly SPAdes v3.7 was used. The total number of contigs in the PA80 genome assembly was 97. The number of contigs of length ≥ 0 bp and length ≥ 1000 bp were 145 and 90 respectively. The assembled contigs were then annotated and aligned with the reference PAO1 genome (GCF_000006765.1) using BWA-MEM80 and variant calling was performed using VarScan and annotated using Prokka 1.11. Only for MexT and MexS, the PA14 (GCF_006974045.1) genome was used for reference as previously recommended67. From the genome sequences, using NCBI local blast (BLAST v2.10) the specific gene sequences were extracted, and alignments were compared. Using the BAM alignment file generated by BWA-MEM algorithm, variants like SNP, insertion and deletions were identified using Mega-X software.
This work was supported by Ulster University, Northern Ireland through a Vice Chancellor’s Research Scholarship studentship to S.A.K.S Ahmed. The authors would also like to thank the Centre for Cognitive and Skill Enhancement at IUB for computational support to the bioinformatic analysis.
This work was supported by the Northern Ireland Research & Development Office, HPSS(NI) Grant RRG9.3. Professor Banat and group would like to acknowledge support of the European Union Framework Programme for Research and Innovation, Horizon 2020 under Grant agreement No. 635340 MARISURF.
© 2021, The Author(s).
- Bacterial Proteins/genetics
- Cystic Fibrosis/microbiology
- Gene Expression Regulation, Bacterial
- Genetic Variation
- Pseudomonas aeruginosa/genetics
- Quorum Sensing
- Virulence Factors/genetics