We would like to refute the suggestion that incorporating secondary structure information improves taxonomy-independent (TI; see Table 1 for list of abbreviations) 16S rRNA binning methods for partial 16S rRNA sequence reads. Although 16S rRNA secondary structure is crucial for its proper function, it is not clear that nucleotide differences at positions important for secondary structure contain unique phylogenetic information that requires different weighting than nucleotide differences at other positions. We support our position, and show the large computational expense required to include secondary structure information, using data from a simulation study. Our findings are important for microbial ecologists, as they confirm that an existing algorithm, ESPRIT-Tree (Cai and Sun, 2011), performs equally or better without consideration of secondary structure. Consequently, microbial ecologists who are already struggling with computational limitations analyzing vast data sets need not suspect that they are missing important improvements in operational taxonomic units (OTU) binning that could be achieved only at much greater computational cost, and can analyze data sets with many millions of sequences with confidence.

Table 1 Abbreviations used in the text
Full size table

Recent advances in high-throughput sequencing technologies have contributed to an explosion in sequence data from studies of the microbial diversity in various environments. The analysis of complex microbial communities frequently includes large-scale sequencing of 16S rRNA, to estimate species composition and diversity in many environments. Although sequencing technologies allow ever deeper interrogation of microbial communities, the availability of efficient bioinformatics tools that handle such vast data sets has become a bottleneck.

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