- 作者: Cheng-Shyuan Rau, Shao-Chun Wu, Johnson Chia-Shen Yang, Tsu-Hsiang Lu, Yi-Chan Wu, Yi-Chun Chen, Siou-Ling Tzeng, Chia-Jung Wu and Ching-Hua Hsieh
- 作者服務機構: Department of Neurosurgery, Kaohsiung Chang Gung Memorial Hospital and Chang Gung University College of Medicine, Kaohsiung City , Taiwan R.O.C
- 中文摘要: --
- 英文摘要:
Background:
We profiled the expression of circulating microRNAs (miRNAs) in mice using Illumina small RNA deep sequencing in order to identify the miRNAs that may potentially be used as biomarkers to distinguish between gram-negative and gram-positive bacterial infections.
Results:
Recombinant-specific gram-negative pathogen Escherichia coli (Xen14) and gram-positive pathogen Staphylococcus aureus (Xen29) were used to induce bacterial infection in mice at a concentration of 1 × 108
bacteria/100 μL of phosphate buffered saline (PBS). Small RNA libraries generated from the serum of mice after exposure to PBS, Xen14, Xen29, and Xen14 + Xen29 via the routes of subcutaneous injection (I), cut wound (C), or under grafted skin (S) were analyzed using an Illumina HiSeq2000 Sequencer. Following exposure to gram-negative bacteria alone, no differentially expressed miRNA was found in the injection, cut, or skin graft models. Exposure to mixed bacteria induced a similar expression pattern of the circulating miRNAs to that induced by gram-positive
bacterial infection. Upon gram-positive bacterial infection, 9 miRNAs (mir-193b-3p, mir-133a-1-3p, mir-133a-2-3p, mir-133a-1-5p, mir-133b-3p, mir-434-3p, mir-127-3p, mir-676-3p, mir-215-5p) showed upregulation greater than
4-fold with a p-value < 0.01. Among them, mir-193b-3p, mir-133a-1-3p, and mir-133a-2-3p presented the most common miRNA targets expressed in the mice exposed to gram-positive bacterial infection.
Conclusions:
This study identified mir-193b-3p, mir-133a-1-3p, and mir-133a-2-3p as potential circulating miRNAs for gram-positive bacterial infections. - 中文關鍵字: --
- 英文關鍵字: microRNAs (miRNAs), Circulating microRNAs, Gram-positive bacteria, Gram-negative bacteria, Small RNA deep sequencing