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.

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.