Pipeline for amplifying and analyzing amplicons of the V1–V3 region of the 16S rRNA gene
© The Author(s) 2016
Received: 9 January 2016
Accepted: 19 July 2016
Published: 2 August 2016
Profiling of 16S rRNA gene sequences is an important tool for testing hypotheses in complex microbial communities, and analysis methods must be updated and validated as sequencing technologies advance. In host-associated bacterial communities, the V1–V3 region of the 16S rRNA gene is a valuable region to profile because it provides a useful level of taxonomic resolution; however, use of Illumina MiSeq data for experiments targeting this region needs validation.
Using a MiSeq machine and the version 3 (300 × 2) chemistry, we sequenced the V1–V3 region of the 16S rRNA gene within a mock community. Nineteen bacteria and one archaeon comprised the mock community, and 12 replicate amplifications of the community were performed and sequenced. Sequencing the large fragment (490 bp) that encompasses V1–V3 yielded a higher error rate (3.6 %) than has been reported when using smaller fragment sizes. This higher error rate was due to a large number of sequences that occurred only one or two times among all mock community samples. Removing sequences that occurred one time among all samples (singletons) reduced the error rate to 1.4 %. Diversity estimates of the mock community containing all sequences were inflated, whereas estimates following singleton removal more closely reflected the actual mock community membership. A higher percentage of the sequences could be taxonomically assigned after singleton and doubleton sequences were removed, and the assignments reflected the membership of the input DNA.
Sequencing the V1–V3 region of the 16S rRNA gene on the MiSeq platform may require additional sequence curation in silico, and improved error rates and diversity estimates show that removing low-frequency sequences is reasonable. When datasets have a high number of singletons, these singletons can be removed from the analysis without losing statistical power while reducing error and improving microbiota assessment.
KeywordsV1–V3 16S rRNA gene MiSeq Mock community Microbial ecology
The affordability and scalability of nucleic acid sequencing have enabled researchers to conduct microbial community analyses on an unprecedented scale. One highly used method to query bacterial communities involves sequencing amplicons of the 16S rRNA gene. However, sequence and analysis of these amplicons has numerous technical limitations including chimera formation during the PCR step and errors introduced by sequencing technologies. Previous advances in validating 16S rRNA gene sequence analyses have employed various sequencing platforms, multiple sequencing centers, and both real and mock bacterial communities [1, 2]. In silico methods, such as chimera removal [3, 4], quality filtering , and clustering methods , have been developed and validated to improve analysis of amplicons and are essential to separate true data from noise .
The quality of 16S rRNA gene sequence data is dependent on numerous technical steps that are difficult to control, often resulting in thousands of unique sequences even after implementing quality-control steps. One approach to managing these low-frequency sequences is to implement closed-reference operational taxonomic unit (OTU)-picking, which clusters sequences into OTUs based on their assignment to a reference database . However, many researchers choose not to require phylogenetic assignment prior to clustering because it could eliminate important, undescribed members of the community. An additional approach is to remove low-frequency OTUs after sequence clustering, although it is computationally expensive to retain sequencing artifacts through distance matrix creation and subsequent clustering. Unreferenced removal of sequences prior to OTU-calling improves the speed and feasibility of analyzing large datasets, as we demonstrate here by sequencing and analyzing the 16S rRNA gene, V1–V3 region, of an artificial (mock) microbial community.
The challenge of sequencing 16S rRNA gene amplicons via the MiSeq platform is choosing a variable region that both informs the microbiota of interest and results in an amplicon sufficiently short to overlap both forward and reverse reads of a paired-end reaction. The V4 region has therefore been used for this sequencing method because its short amplicon (~400 bp including primer sequences) is technically amenable to assembly with a low error rate (0.01 %) . However, longer 16S gene regions are sometimes preferred for biological reasons based on the research question despite the potential higher error rates associated with longer amplicon sequences. For example, the V1–V3 region, but not the V3–V5, region can discriminate Staphylococci populations . We have previously used the V1–V3 region to analyze the swine gut microbiota (e.g., ), thus we adapted the MiSeq amplicon method for this region by adding a singleton removal step prior to OTU clustering and validated the method by sequencing 12 technical replicates of a mock community.
Generating the mock community
16S gene composition of the mock community
# 16S genesa
Genome copies per microgramb
Reference or DSMZ catalogue numberc
Campylobacter jejuni 11168
Salmonella enterica serovar Typhimurium SL1344
Escherichia coli mg1655
Megasphaera elsdenii LC-1
Cloacibacillus porcorum CL-84
Haemophilus parasuis 29755
Bordetella bronchiseptica 1289
Staphylococcus aureus USA300
Faecalibacterium prausnitzii A2-165
Lactobacillus delbrueckii subspecies bulgaricus
Oxalobacter formigenes BA-2
Roseburia hominis A2-183
Methanobrevibacter smithii d
Generating and sequencing 16S rRNA gene sequence amplicons
Primers used in this study
The mothur analysis package was used to assemble contigs, align sequences, trim sequences, remove chimeras (UCHIME, ), and remove non-bacterial sequences (mothur versions 1.33.3 and 1.34.0, http://www.mothur.org/wiki/MiSeq_SOP, [2, 12]). Following these quality-control steps, the data were rarified to 6654 sequences/sample and analyzed in three ways: (1) all sequences together, (2) with cross-sample singletons removed, or (3) with cross-sample singletons and doubletons removed. Cross-sample singletons and doubletons were defined as sequences that occurred only once (singletons) or twice (doubletons) among all samples. Taxonomy was assigned by aligning to mothur’s implementation of the SILVA database . OTUs were clustered at 97 % similarity and analyzed in mothur for community metrics. Richness, evenness, and diversity were also conducted in mothur and included the use of the program Catchall . Error analysis was performed in mothur based on the alignment of the experimental mock community to a FASTA file containing the actual 16S rRNA gene sequences from the genome sequences (Additional file 1). A complete list of the commands executed in mothur is available (Additional file 2).
Results and discussion
Sequencing the V1–V3 region yields spurious sequences
Removal of low-frequency sequences improves microbiota assessments
Average diversity estimates of the mock community (n = 12, rarified to 6654 sequences per sample) with and without removing low-frequency sequences
Actual number of OTUsa
Observed number of OTUs
Estimated total number of OTUsb
Chao diversity index
Shannon diversity index
Inverse Simpson index
Error rate (%)
File size (Gb)c
734 ± 56
374,770 ± 214,807
21,676 ± 3273
3.6 ± 0.1
18 ± 0.8
28 ± 0.8
68 ± 13
41 ± 3
2.7 ± 0.02
12 ± 0.3
Single and doubletons removed
22 ± 0.3
22 ± 0.3
23 ± 0.7
2.6 ± 0.02
12 ± 0.3
Removing the large number of clusters with a membership size of one sequence (or one and two sequences) has a distinct advantage for streamlining the clustering of sequences into OTUs by reducing the size of the dataset without detracting from the ability to make valid comparisons. Reducing the number of sequences resulted in a 13-fold decrease in file size and exponentially reduced the time and memory space needed to create the distance matrix since the distance matrix is comprised of pairwise comparisons (Table 3).
Discarding low-frequency sequences can be concerning for those interested in the rare members of a bacterial community. Indeed, defining the rare microbiota in the context of sequencing errors has been explored [18–20]. Other work has supported the value of singleton removal [21, 22]. Our method is beneficial to researchers that use the Illumina MiSeq to sequence longer amplicons, such as the V1-V3 region of the 16S rRNA gene, from hundreds of samples. Removing the singletons and doubletons will suit the vast majority of projects seeking to analyze the abundant (>1 %) community organisms to draw biological conclusions.
HKA analyzed data and drafted the manuscript. DOB, TL, JT, and BB performed experiments or analyses. SMDB, TN, and TAC provided strains. All authors contributed to and finalized the manuscript. All authors read and approved the final manuscript.
The authors thank Stephanie Jones, Lisa Lai, and Sarah Shore for outstanding technical support. Mention of trade names or commercial products in this publication is solely for the purpose of providing specific information and does not imply recommendation or endorsement by the US Department of Agriculture. USDA is an equal opportunity provider and employer.
The authors declare that Diamond V, manufacturer of all-natural, microbial, fermentation-based feed additives, partially funded this work.
Availability of data and materials
The dataset supporting the conclusions of this article is available in GenBank’s Short Read Archive (SRP076629) under Bioproject PRJNA325813. The Cloacibacillus genome is available in GenBank under BioProject PRJNA335387.
Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
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