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Updated: Feb 20, 2026

Microbiota Analysis Using Two-step PCR and Next-generation 16S rRNA Gene Sequencing
Published on: October 15, 2019
Analysis of microbial community composition and diversity in postoperative intracranial infection using
Lixin Ruan1, Daowu Wu1, Xinchong Li1
1Department of Neurosurgery, The People's Hospital of Pingyang, Wenzhou, Zhejiang 325400, P.R. China.
Abstract:
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.
Insights
Postoperative intracranial infections reveal similar microbial composition between treated and untreated patients. Antibiotic treatment, however, reduced microbial diversity and abundance, highlighting its impact on infection dynamics.
Area of Science:
- Neuroscience
- Microbiology
- Infectious Diseases
Background:
- Postoperative intracranial infection is a severe neurosurgical complication.
- Bacteria and fungi are primary pathogens, but their community structure in infections is poorly understood.
- This knowledge gap impacts the effectiveness of antibiotic treatments.
Purpose of the Study:
- To investigate microbial community structure (composition, abundance, diversity) in postoperative intracranial infections.
- To compare microbial profiles between antibiotic-treated and untreated patients.
- To assess the utility of high-throughput sequencing for pathogen identification.
Main Methods:
- Collected eight cerebrospinal fluid (CSF) samples from patients with intracranial infection.
- Utilized high-throughput amplicon sequencing (16S rDNA and ITS) on the Illumina MiSeq platform.
- Performed bioinformatics analysis to compare microbial communities.
Main Results:
- Microbial composition and diversity were similar between treated and untreated groups.
- Antibiotic treatment led to lower species abundance and diversity compared to untreated patients.
- Acinetobacter and Staphylococcus were prevalent genera; Acinetobacter was found in all samples.
- Candida was detected in untreated patients, suggesting fungal importance.
Conclusions:
- 16S and ITS sequencing are effective for identifying pathogens in intracranial infections.
- Significant differences in microbial structure exist between treated and untreated patients.
- Microbial community alterations may indicate treatment efficacy and aid infection control.
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