High-Throughput Transcriptomic Profiling Reveals the Inhibitory Effect of Hydroquinine on Virulence Factors in Pseudomonas aeruginosa

There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

Abstract

Hydroquinine is an organic alkaloid compound that exhibits antimicrobial activity against several bacterial strains including strains of both drug-sensitive and multidrug-resistant P. aeruginosa. Despite this, the effects of hydroquinine on virulence factors in P. aeruginosa have not yet been characterized. We therefore aimed to uncover the mechanism of P. aeruginosa hydroquinine-sensitivity using high-throughput transcriptomic analysis. We further confirmed whether hydroquinine inhibits specific virulence factors using RT-qPCR and phenotypic analysis. At half the minimum inhibitory concentration (MIC) of hydroquinine (1.250 mg/mL), 254 genes were differentially expressed (97 downregulated and 157 upregulated). We found that flagellar-related genes were downregulated by between −2.93 and −2.18 Log2-fold change. These genes were consistent with the analysis of gene ontology and KEGG pathway. Further validation by RT-qPCR showed that hydroquinine significantly suppressed expression of the flagellar-related genes. By analyzing cellular phenotypes, P. aeruginosa treated with ½MIC of hydroquinine exhibited inhibition of motility (30–54% reduction) and pyocyanin production (~25–27% reduction) and impaired biofilm formation (~57–87% reduction). These findings suggest that hydroquinine possesses anti-virulence factors, through diminishing flagellar, pyocyanin and biofilm formation.

Related collections

Most cited references 52

Record: found
Abstract: found
Article: not found

Fast gapped-read alignment with Bowtie 2.

Ben Langmead, Steven L Salzberg (2022)

As the rate of sequencing increases, greater throughput is demanded from read aligners. The full-text minute index is often used to make alignment very fast and memory-efficient, but the approach is ill-suited to finding longer, gapped alignments. Bowtie 2 combines the strengths of the full-text minute index with the flexibility and speed of hardware-accelerated dynamic programming algorithms to achieve a combination of high speed, sensitivity and accuracy.

0 comments Cited 13279 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

featureCounts: an efficient general purpose program for assigning sequence reads to genomic features.

Y. Liao, G K Smyth, W Shi (2014)

Next-generation sequencing technologies generate millions of short sequence reads, which are usually aligned to a reference genome. In many applications, the key information required for downstream analysis is the number of reads mapping to each genomic feature, for example to each exon or each gene. The process of counting reads is called read summarization. Read summarization is required for a great variety of genomic analyses but has so far received relatively little attention in the literature. We present featureCounts, a read summarization program suitable for counting reads generated from either RNA or genomic DNA sequencing experiments. featureCounts implements highly efficient chromosome hashing and feature blocking techniques. It is considerably faster than existing methods (by an order of magnitude for gene-level summarization) and requires far less computer memory. It works with either single or paired-end reads and provides a wide range of options appropriate for different sequencing applications. featureCounts is available under GNU General Public License as part of the Subread (http://subread.sourceforge.net) or Rsubread (http://www.bioconductor.org) software packages.

0 comments Cited 7152 times – based on 0 reviews      Review now

Bookmark

Record: found
Abstract: found
Article: not found

Pseudomonas aeruginosa: all roads lead to resistance.

Elena Breidenstein, César de la Fuente-Núñez, Robert E. W. Hancock (2011)

Pseudomonas aeruginosa is often resistant to multiple antibiotics and consequently has joined the ranks of 'superbugs' due to its enormous capacity to engender resistance. It demonstrates decreased susceptibility to most antibiotics due to low outer membrane permeability coupled to adaptive mechanisms and can readily achieve clinical resistance. Newer research, using mutant library screens, microarray technologies and mutation frequency analysis, has identified very large collections of genes (the resistome) that when mutated lead to resistance as well as new forms of adaptive resistance that can be triggered by antibiotics themselves, in in vivo growth conditions or complex adaptations such as biofilm growth or swarming motility. Copyright © 2011 Elsevier Ltd. All rights reserved.