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Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing
Intracranial infection is one of the most serious complications following neurosurgery. It is well acknowledged that bacteria and fungi are the main pathogens responsible for postoperative intracranial infection. However, the microbial community structure, including composition, abundance and divers...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
D.A. Spandidos
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646973/ https://www.ncbi.nlm.nih.gov/pubmed/29067467 http://dx.doi.org/10.3892/mmr.2017.7082 |
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author | Ruan, Lixin Wu, Daowu Li, Xinchong Huang, Qichuan Lin, Laipeng Lin, Jie Chen, Lie Xu, Peisong Jin, Jie Yang, Ningmin Li, Xianfeng |
author_facet | Ruan, Lixin Wu, Daowu Li, Xinchong Huang, Qichuan Lin, Laipeng Lin, Jie Chen, Lie Xu, Peisong Jin, Jie Yang, Ningmin Li, Xianfeng |
author_sort | Ruan, Lixin |
collection | PubMed |
description | Intracranial infection is one of the most serious complications following neurosurgery. It is well acknowledged that bacteria and fungi are the main pathogens responsible for postoperative intracranial infection. However, the microbial community structure, including composition, abundance and diversity, in postoperative intracranial infection is not fully understood, which greatly compromises our understanding of the necessity and effectiveness of postoperative antibiotic treatment. The present study collected eight cerebrospinal fluid (CSF) samples from patients with intracranial infection following neurosurgical procedures. High-throughput amplicon sequencing for 16S rDNA and internal transcribed spacer (ITS) was performed using the Illumina MiSeq platform to investigate the microbial community composition and diversity between treated and untreated patients. Bioinformatics analysis revealed that the microbial composition and diversity in each patient group (that is, with or without antibiotic treatment) was similar; however, the group receiving antibiotic treatment had a comparatively lower species abundance and diversity compared with untreated patients. At the genus level, Acinetobacter and Staphylococcus were widely distributed in CSF samples from patients with postoperative intracranial infection; in particular, Acinetobacter was detected in all CSF samples. In addition, five ITS fungal libraries were constructed, and Candida was detected in three out of four patients not receiving antibiotic treatment, indicating that the fungal infection should be given more attention. In summary, 16S and ITS high-throughput amplicon sequencing were practical methods to identify pathogens in the different periods of treatment in patients with postoperative intracranial infection. There was a notable difference in microbial composition and diversity between the treated and untreated patients. Alterations in the microbial community structure may provide a signal whether antibiotic treatment worked in postoperative intracranial infection and may assist surgeons to better control the progression of infection. |
format | Online Article Text |
id | pubmed-5646973 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | D.A. Spandidos |
record_format | MEDLINE/PubMed |
spelling | pubmed-56469732017-10-24 Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing Ruan, Lixin Wu, Daowu Li, Xinchong Huang, Qichuan Lin, Laipeng Lin, Jie Chen, Lie Xu, Peisong Jin, Jie Yang, Ningmin Li, Xianfeng Mol Med Rep Articles Intracranial infection is one of the most serious complications following neurosurgery. It is well acknowledged that bacteria and fungi are the main pathogens responsible for postoperative intracranial infection. However, the microbial community structure, including composition, abundance and diversity, in postoperative intracranial infection is not fully understood, which greatly compromises our understanding of the necessity and effectiveness of postoperative antibiotic treatment. The present study collected eight cerebrospinal fluid (CSF) samples from patients with intracranial infection following neurosurgical procedures. High-throughput amplicon sequencing for 16S rDNA and internal transcribed spacer (ITS) was performed using the Illumina MiSeq platform to investigate the microbial community composition and diversity between treated and untreated patients. Bioinformatics analysis revealed that the microbial composition and diversity in each patient group (that is, with or without antibiotic treatment) was similar; however, the group receiving antibiotic treatment had a comparatively lower species abundance and diversity compared with untreated patients. At the genus level, Acinetobacter and Staphylococcus were widely distributed in CSF samples from patients with postoperative intracranial infection; in particular, Acinetobacter was detected in all CSF samples. In addition, five ITS fungal libraries were constructed, and Candida was detected in three out of four patients not receiving antibiotic treatment, indicating that the fungal infection should be given more attention. In summary, 16S and ITS high-throughput amplicon sequencing were practical methods to identify pathogens in the different periods of treatment in patients with postoperative intracranial infection. There was a notable difference in microbial composition and diversity between the treated and untreated patients. Alterations in the microbial community structure may provide a signal whether antibiotic treatment worked in postoperative intracranial infection and may assist surgeons to better control the progression of infection. D.A. Spandidos 2017-10 2017-07-24 /pmc/articles/PMC5646973/ /pubmed/29067467 http://dx.doi.org/10.3892/mmr.2017.7082 Text en Copyright: © Ruan et al. This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License (https://creativecommons.org/licenses/by-nc-nd/4.0/) , which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made. |
spellingShingle | Articles Ruan, Lixin Wu, Daowu Li, Xinchong Huang, Qichuan Lin, Laipeng Lin, Jie Chen, Lie Xu, Peisong Jin, Jie Yang, Ningmin Li, Xianfeng Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title | Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title_full | Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title_fullStr | Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title_full_unstemmed | Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title_short | Analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
title_sort | analysis of microbial community composition and diversity in postoperative intracranial infection using high-throughput sequencing |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5646973/ https://www.ncbi.nlm.nih.gov/pubmed/29067467 http://dx.doi.org/10.3892/mmr.2017.7082 |
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