Comprehensive single‐PCR 16S and 18S rRNA community analysis validated with mock communities, and estimation of sequencing bias against 18S

Abstract

Universal primers for SSU rRNA genes allow profiling of natural communities by simultaneously amplifying templates from Bacteria, Archaea, and Eukaryota in a single PCR reaction. Despite the potential to show relative abundance for all rRNA genes, universal primers are rarely used, due to various concerns including amplicon length variation and its effect on bioinformatic pipelines. We thus developed 16S and 18S rRNA mock communities and a bioinformatic pipeline to validate this approach. Using these mocks, we show that universal primers (515Y/926R) outperformed eukaryote-specific V4 primers in observed versus expected abundance correlations (slope = 0.88 vs. 0.67-0.79), and mock community members with single mismatches to the primer were strongly underestimated (threefold to eightfold). Using field samples, both primers yielded similar 18S beta-diversity patterns (Mantel test, p < 0.001) but differences in relative proportions of many rarer taxa. To test for length biases, we mixed mock communities (16S + 18S) before PCR and found a twofold underestimation of 18S sequences due to sequencing bias. Correcting for the twofold underestimation, we estimate that, in Southern California field samples (1.2-80 μm), there were averages of 35% 18S, 28% chloroplast 16S, and 37% prokaryote 16S rRNA genes. These data demonstrate the potential for universal primers to generate comprehensive microbiome profiles.

Evaluating and Improving SSU rRNA PCR Primer Coverage for Bacteria, Archaea, and Eukaryotes Using Metagenomes from Global Ocean Surveys

“…To evaluate the real-world extent of primer biases, we compared PCR primers currently in broad use by the marine microbiology community (Table S2) to SSU rRNA sequences extracted from a geographically diverse set of pelagic ocean metagenomes (Fig 1; Table S1). These analyses were based on the percentage of perfect matches between primers and metagenome sequences as a metric to determine potential PCR performance, since previous studies have shown that even a single mismatch can significantly bias results (3, 13).…”

“…Recent studies have shown that PCR amplicon sequencing of mock microbial communities can recover known relative and absolute abundances extremely well, and thus provides accurate quantification of natural gene copy abundances (3, 13, 14). In turn, this accuracy allows amplicon data to serve as a ground-truth for modeling / ecological studies by quantifying community members and their dynamics.…”

“…While well-designed primers have the potential to recover truly quantitative data, these studies also underscored the critical fact that a single mismatch between the primer and template sequences can have a dramatic effect on the measured community composition in complex natural mixtures. For example, a single internal mismatch in the popular Earth Microbiome Project primer caused a ∼10-fold bias against the most common bacteria in seawater (SAR11 cluster), and terminal 3’ mismatches can completely prevent amplification (2, 3, 6, 13). Since the extent of this bias is not easily predicted, PCR primers should incorporate degenerate bases or specific oligonucleotide variants so that all targeted organisms are perfectly matched without overly diluting the common perfect matches in primer mixtures.…”

“…Previous studies have shown high coverage of natural taxa is possible by designing moderately degenerate primers without sacrificing specificity or PCR efficiency (3, 13). This primer design was accomplished by comparing oligonucleotide sequences to a SSU rRNA database such as SILVA or RDP (11, 12) and then checking for mismatches to organisms known to be abundant in the environment of interest.…”

“…To more fully evaluate the extent to which primers currently in broad use by the marine microbiology community perfectly match naturally occurring sequences, we developed a workflow to conduct in silico primer evaluations with metagenomic SSU rRNA fragments, under the general assumption that metagenomes have fewer methodological biases than PCR. While it is already known that some primers have better coverage for abundant marine organisms versus others (3, 13), a precise quantitative comparison of these primers with others that are in broad use has not yet been conducted.…”