PCR-based quantification of taxa-specific abundances in microbial communities: Quantifying and avoiding common...

Area of Science:

• Microbial Ecology
• Molecular Biology
• Bioinformatics

Background:

• Quantifying microbial taxa-specific abundances is essential for ecosystem studies.
• Existing quantification methods are prone to errors that can skew results.
• Next-generation sequencing (NGS) and quantitative real-time PCR (qPCR) are common tools.

Purpose of the Study:

• To critically assess error sources in NGS amplicon sequencing and qPCR for microbial abundance quantification.
• To present methods for estimating and minimizing these errors.
• To highlight the impact of errors on data interpretation and future research needs.

Main Methods:

• Review of error sources from DNA extraction to data analysis.
• Consideration of DNA extraction efficiency, PCR bias, and 16S rRNA operon copy number variation.
• Analysis of qPCR and NGS data processing.

Main Results:

• Identified key error sources in microbial abundance quantification.
• Demonstrated that unaddressed errors can lead to results deviating by orders of magnitude from true values.
• Showcased methods to minimize errors and identify large deviations through plausibility checks.

Conclusions:

• NGS amplicon sequencing and qPCR are valuable for determining microbial genome abundances.
• Ignoring identified error sources can lead to significantly inaccurate results.
• Minimizing errors is cost-efficient, and accurate conversion to cell numbers is a key future research area.