An improved dual-indexing approach for multiplexed 16S rRNA gene sequencing on the Illumina MiSeq platform

Abstract

Background: To take advantage of affordable high-throughput next-generation sequencing technologies to characterize microbial community composition often requires the development of improved methods to overcome technical limitations inherent to the sequencing platforms. Sequencing low sequence diversity libraries such as 16S rRNA amplicons has been problematic on the Illumina MiSeq platform and often generates sequences of suboptimal quality.

Results: Here we present an improved dual-indexing amplification and sequencing approach to assess the composition of microbial communities from clinical samples using the V3-V4 region of the 16S rRNA gene on the Illumina MiSeq platform. We introduced a 0 to 7 bp "heterogeneity spacer" to the index sequence that allows an equal proportion of samples to be sequenced out of phase.

Conclusions: Our approach yields high quality sequence data from 16S rRNA gene amplicons using both 250 bp and 300 bp paired-end MiSeq protocols and provides a flexible and cost-effective sequencing option.

Figures

Figure 1

Dual-indexed 16S rRNA gene PCR amplification strategy with heterogeneity spacer primers for sequencing on the MiSeq platform. (A) Dual-indexed PCR amplification primers targeting the V3-V4 hypervariable regions of the 16S rRNA gene contain a heterogeneity spacer region and linker sequence optimized for sequencing on the Illumina MiSeq platform. Using this approach enables sequencing using the standard Illumina HP10 and HP11 sequencing primers allowing for additional sequencing flexibility. (B) Schematic showing the first thirty sequencing cycles of eight mock amplicons prepared using the dual-indexed approach. This diagram illustrates how the index sequence and heterogeneity spacer (colored letters, white background) helps to alleviate the “low sequence diversity” issue associated with the MiSeq platform by creating a more even base composition at each cycle of the run.

Figure 2

Flow diagram outlining the sequence data analysis process. Pre-processing for sequences generated with the 250 bp paired-end read (250PE; left panel) and 300 bp paired-end read (300PE; right panel) MiSeq protocols. R1 and R2 refers to read 1 and read 2.

Figure 3

Taxonomic assignments of clinical samples. (A) Ten anal samples sequenced using 250 bp paired-end read (250PE) MiSeq protocol (pool 199–205). Ten vaginal samples sequenced using (B) 250PE and (C) 300 bp paired-end read (300PE) MiSeq protocols (pool 235–240) and analyzed using QIIME (version 1.6.0).