| Literature DB >> 23077578 |
Yibao Ma1, Yuanxi Xu, Bryan D Yestrepsky, Roderick J Sorenson, Meng Chen, Scott D Larsen, Hongmin Sun.
Abstract
Staphylococcus aureus is a major human pathogen and one of the more prominent pathogens causing biofilm related infections in clinic. Antibiotic resistance in S. aureus such as methicillin resistance is approaching an epidemic level. Antibiotic resistance is widespread among major human pathogens and poses a serious problem for public health. Conventional antibiotics are either bacteriostatic or bacteriocidal, leading to strong selection for antibiotic resistant pathogens. An alternative approach of inhibiting pathogen virulence without inhibiting bacterial growth may minimize the selection pressure for resistance. In previous studies, we identified a chemical series of low molecular weight compounds capable of inhibiting group A streptococcus virulence following this alternative anti-microbial approach. In the current study, we demonstrated that two analogs of this class of novel anti-virulence compounds also inhibited virulence gene expression of S. aureus and exhibited an inhibitory effect on S. aureus biofilm formation. This class of anti-virulence compounds could be a starting point for development of novel anti-microbial agents against S. aureus.Entities:
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Year: 2012 PMID: 23077578 PMCID: PMC3471953 DOI: 10.1371/journal.pone.0047255
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Figure 1Compound structures and effects on SK expression.
A) Structure of CCG-203592 B) Structure of CCG-205363 C) Effects of CCG-203592 on the production of SK activity. Normalized SK activity of GAS treated with CCG-203592 at concentrations from 0.5 to 50 µM (SK activity of culture media divided by OD600 nm of bacteria culture, then normalized to the value for DMSO treated GAS which was defined as 100%). The data is presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). D) Effect of CCG-205363 on the production of SK activity. The value was presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate).
Figure 2The effect of CCG-203592 and CCG-205363 on S. aureus biofilm formation.
A) Dose-response curve of CCG-203592 inhibition on RN6390 biofilm formation. The data is presented as % inhibition mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). Percent inhibition is relative to DMSO control. B) Dose-response curve of CCG-205363 inhibition on RN6390 biofilm formation. The value was presented as % inhibition mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate).
Figure 3The effect of 50 µM CCG-203592 on S. aureus RN1, NRS234 and NRS235 biofilm formation.
Biofilm formation was determined by OD595 nm reading of crystal violet stain solubilized by ethanol with DMSO treatment as controls. The data is presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). ** p<0.01.
Figure 4The effect of CCG-203592 on S. aureus biofilm formation on silicone wafer.
A) RN6390 biofilm formation on medical grade silicone wafer at different concentrations as determined by OD595 nm reading of crystal violet stain solubilized by ethanol. The data is presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). * p<0.05, ** p<0.01. B) Scan electron microscopy representative images of RN6390 biofilm formation on silicone wafer treated with different concentrations of CCG-203592 from triplicate.
Figure 5The effect of CCG-203592 on S. aureus and mammalian cell viability.
A) Growth curves for RN6390 in the presence of CCG-203592 (50 µM) (grey curve) or DMSO alone (dark curve) as determined by OD600 nm. The data is presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). B) HeLa cell viability (as determined by mitochondrial reduction of MTT substrate) in the presence of CCG-203592 at different concentrations normalized to the value for DMSO treated samples which was defined as 100%. The data is presented as mean±standard error of means for a total of 12 samples (pooled from 3 independent experiments in quadruplicate).
Virulence factor genes tested by Real time RT-PCR.
| Gene | Function | Primers | Reference |
| 16S rRNA | Internal standard gene | F: CTGGTAGTCCACGCCGTAAAC R: |
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| icaA | Polysaccharide intercellular adhesion/polymeric N-acetyglucosamine production | F: AACAGAGGTAAAGCCAACGCACTC R: |
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| dltD | Esterification of teichoic acids with D-alanine | F: GTGCTGCTGGTGCAGATGTTCAAT R: |
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| atlA | Autolysin | F: TGTCGAAGTATTTGCCGACTTCGC R: |
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| Psmα operon | Phenol soluble modulins α | F: ACCCATGTGAAAGACCTCCTTTGT R: |
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| SPA | Surface and secreted protein for bacterial aggregation | F: GCGCAACACGATGAAGCTCAACAA R: |
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| lrgA | Cell death and lysis | F: CTGGTGCTGTTAAGTTAGGCGAAG R: |
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| sdrD | SD-repeat-containing protein | F : AGTACACAGTGGGAACAGCATC R : |
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| sspB | Cysteine protease | F: CCAGCAAATTGTTGTTGTGCTAG R: |
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| SigB | Gene expression regulator | F: TCAGCGGTTAGTTCATCGCTCACT R: |
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| AgrA | Gene expression regulator | F: AAGCATGACCCAGTTGGTAACA R:ATCCATCGCTGCAACTTTGTAGA |
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| RNAIII | Gene expression regulator | F: GCACTGAGTCCAAGGAAACTAACTCT R: |
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| CodY | Gene expression regulator | F: AAAGAAGCGCGCGATAAAGCTG R: |
|
| ebpS | Surface protein | F: TTTCCGGTGAACCTGAACCGTAGT R: |
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| cidA | Cell death and lysis | F: AGCGTAATTTCGGAAGCAACATCC R: |
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| Hla | Alpha-Toxin | F: CTGAAGGCCAGGCTAAACCACTTT R: |
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Figure 6The effect of CCG-203592 on expression of selected S. aureus genes.
Real time RT-PCRs were performed at mid-logarithmic growth phase (ML), late logarithmic growth phase (LL) and stationary (S) phase. The values are presented as the fold of change of gene transcriptional level of samples treated with 50 µM CCG-203592 versus that of samples treated with DMSO as calculated by 2(−ΔΔ Ct) method. The data is presented as mean±standard error of means for a total of 9 samples (pooled from 3 independent experiments in triplicate). * p<0.05, ** p<0.01.