ArticleScientific reports2017
Comparative transcriptional profiling of tildipirosin-resistant and sensitive Haemophilus parasuis.
Article in Scientific reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed.
- Antibacterial effects of cinnamaldehyde and hesperitin on resistant Glaesserella parasuis by suppressing QseBC two-component system.BMC veterinary research · 2025Article
- Transcriptional profile ofFrontiers in veterinary science · 2025Article
- Comparative Transcriptomic Analyses of Haemophilus parasuis Reveal Differently Expressed Genes among Strains with Different Virulence Degrees.Current microbiology · 2021Article
- Inner Mongolian Cashmere Goat Secondary Follicle Development Regulation Research Based on mRNA-miRNA Co-analysis.Scientific reports · 2020Article
- Transcriptional Profiling of Host Cell Responses to VirulentInternational journal of molecular sciences · 2018Article
- The pharmacokinetic-pharmacodynamic modeling and cut-off values of tildipirosin againstOncotarget · 2018Article
- Optimal Regimens and Cutoff Evaluation of Tildipirosin AgainstFrontiers in pharmacology · 2018Article
- Integrative and Conjugative Elements (ICEs) in Pasteurellaceae Species and Their Detection by Multiplex PCR.Frontiers in microbiology · 2018Article
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Authors and funding
9 authors.
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Abstract
Numerous studies have been conducted to examine the molecular mechanism of Haemophilus parasuis resistance to antibiotic, but rarely to tildipirosin. In the current study, transcriptional profiling was applied to analyse the variation in gene expression of JS0135 and tildipirosin-resistant JS32. The growth curves showed that JS32 had a higher growth rate but fewer bacteria than JS0135. The cell membranes of JS32 and a resistant clinical isolate (HB32) were observed to be smoother than those of JS0135. From the comparative gene expression profile 349 up- and 113 downregulated genes were observed, covering 37 GO and 63 KEGG pathways which are involved in biological processes (11), cellular components (17), molecular function (9), cellular processes (1), environmental information processing (4), genetic information processing (9) and metabolism (49) affected in JS32. In addition, the relative overexpression of genes of the metabolism pathway (HAPS_RS09315, HAPS_RS09320), ribosomes (HAPS_RS07815) and ABC transporters (HAPS_RS10945) was detected, particularly the metabolism pathway, and verified with RT-qPCR. Collectively, the gene expression profile in connection with tildipirosin resistance factors revealed unique and highly resistant determinants of H. parasuis to macrolides that warrant further attention due to the significant threat of bacterial resistance.
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