Evaluating Bioinformatic Pipeline Performance for Forensic Microbiome Analysis^*,†,‡.

Area of Science:

• Forensic Science
• Microbiology
• Bioinformatics

Background:

• Microbial communities offer potential evidence in forensic investigations.
• Current bioinformatic analysis methods for high-throughput sequencing data lack standardization across laboratories.
• Variations in analysis can influence microbial community composition and subsequent findings.

Purpose of the Study:

• To highlight the necessity of standardized bioinformatic methodologies in forensic microbiology.
• To compare the outcomes of different bioinformatic pipelines and parameter settings using postmortem microbiome data.

Main Methods:

• Analysis of identical postmortem microbiome sequencing data using three distinct open-source bioinformatic pipelines: MG-RAST, mothur, and QIIME2.
• Comparison of results based on variations in minimum library size, minimum sequences per sample, and overall sample size.

Main Results:

• Significant differences observed in relative abundance, alpha-diversity, and beta-diversity across the analyzed pipelines, even with identical input data.
• Increasing minimum library size and sample size led to the detection of more low-abundant and infrequent microbial taxa.
• Bioinformatic pipeline selection and parameter configuration demonstrably influence analytical outcomes.

Conclusions:

• The choice of bioinformatic pipeline and specific parameters critically affects microbial community analysis in forensic contexts.
• Standardization of computational methods is essential for the accurate and reproducible application of forensic microbiology in the criminal justice system.
• Further research into standardized bioinformatic approaches is vital for advancing forensic microbiology applications.