# The evaluation of shotgun sequencing and rpoB metabarcoding for taxonomic profiling of bacterial communities

## TL;DR

This study compares shotgun sequencing and rpoB metabarcoding for analyzing bacterial communities, finding that shotgun sequencing offers better taxonomic resolution and more accurate abundance estimates.

## Contribution

The study provides a direct comparison of shotgun sequencing and rpoB metabarcoding for microbial profiling, highlighting the advantages of shotgun sequencing in resolution and quantification.

## Key findings

- Shotgun sequencing using the Assembly-Binning-Method achieved comparable sensitivity and higher precision than rpoB metabarcoding.
- Shotgun sequencing provided better taxonomic resolution by identifying species-level taxa compared to genus-level identification with rpoB.
- Shotgun sequencing outperformed rpoB metabarcoding in quantifying microbial abundance with higher correlation and lower dissimilarity.

## Abstract

The importance of microbial community profiling has been increasingly recognized in biological and environmental research. While metabarcoding has been widely used for such analysis by targeting specific DNA sequences as markers, shotgun sequencing has been proposed as an alternative method because the analysis of whole genomes can potentially reduce biases introduced by targeted approaches. However, it is largely unknown whether shotgun sequencing may provide improved precision for qualitative taxonomic identification and quantitative abundance estimation compared with metabarcoding with housekeeping gene markers, such as the rpoB gene. Furthermore, the comparative performance of various bioinformatics pipelines for shotgun data analysis remains uncertain. In this study, we evaluated the performance of rpoB metabarcoding and shotgun sequencing coupled to various bioinformatic pipelines to describe the bacterial diversity of artificially generated mock bacterial communities, which included eukaryote gDNA intentional contamination or whole-genome amplification. For shotgun sequencing, the Assembly-Binning-Method and k-mer-based approaches were evaluated.

For taxonomic profiling, the Assembly-Binning-Method and rpoB metabarcoding exhibited comparable sensitivity and precision, whereas k-mer approaches produced a notably high number of false negatives. In some cases, the Assembly-Binning-Method improved taxonomic resolution compared with rpoB metabarcoding by identifying taxa at the species level rather than the genus level. Regarding the quantification of microbial composition, the Assembly-Binning-Method consistently showed a higher correlation with expected values ​​and a lower dissimilarity index than rpoB metabarcoding. The use of three sets of reference genomes to calculate depth coverage did not systematically affect the precision of the Assembly-Binning-Method.

These results demonstrate that although shotgun sequencing and rpoB metabarcoding have nearly equivalent accuracy in taxonomic profiling, shotgun sequencing has better taxonomic resolution and outperforms rpoB metabarcoding in quantitative estimation of microbial community abundance using the Assembly-Binning approach.

The online version contains supplementary material available at 10.1186/s12866-025-04149-3.