Analysis of microbial community composition and diversity in postoperative intracranial infection using high‑throughput sequencing

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.

Figure 1.

Relative abundance and composition of bacteria and fungi in eight CSF samples. The top 20 bacterial (A) phyla and (B) genera, as well as the top 20 fungal (C) phyla and (D) genera in CSF samples obtained from postoperative patients with intracranial infections treated with antibiotics (samples 2, 6, 50 and 54) or untreated (samples 10, 15, 31 and 53). ‘Other’ denotes the relative abundance of bacteria or fungi that were not in the top 20. CSF, cerebrospinal fluid. *P<0.05, untreated vs. antibiotic treatment group.

Figure 2.

Distribution of pathogens in eight CSF samples. (A) Distribution of bacteria at the genus level in eight CSF samples. (B) Distribution of fungi at the genus level in five of the eight CSF samples. CSF, cerebrospinal fluid.

Figure 3.

Bacterial α-diversity in cerebrospinal fluid samples from eight patients with postoperative intracranial infection that have received antibiotic treatment or were untreated. (A) Chao index for bacterial α-diversity. (B) Shannon index for bacterial α-diversity. n=4 per group. **P<0.01 vs. antibiotic treatment group.

Figure 4.

Microbial β-diversity in CSF samples from patients with postoperative intracranial infection with or without antibiotic treatment. The PCoA plots of (A) bacterial and (B) fungal community in the CSF samples. The heatmap of unweighted UniFrac distance for (C) bacterial and (D) fungal community in the CSF samples. Unweighted pair group method with arithmetic mean cluster results for (E) bacterial and (F) fungal community in the CSF samples. n=8 for bacteria; n=5 for fungus. CSF, cerebrospinal fluid; PCoA, Principal co-ordinates analysis.