Consistent and correctable bias in metagenomic sequencing experiments
- North Carolina State University, United States
- University of Washington, United States
Figures
Figure 1
Bias arises throughout an MGS workflow, creating systematic error between the observed and actual compositions.
Panel A illustrates a hypothetical marker-gene measurement of an even mixture of three taxa. The observed composition differs from the actual composition due to the bias at each step in the …
Figure 2
Consistent multiplicative bias causes systematic error in taxon ratios, but not taxon proportions, that is independent of sample composition.
The even community from Figure 1 and a second community containing the same three taxa in different proportions are measured by a common MGS protocol. Measurements of both samples are subject to the …
Figure 3 with 3 supplements
Our model of bias explains the systematic error observed in the Brooks et al. (2015) cell-mixture experiment.
The top row compares the observed proportions of individual taxa to the actual proportions (Panel A) and to those predicted by our fitted bias model (Panel B). Panel A shows significant error across …
Figure 3—figure supplement 1
The observed error in taxon ratios for all three mixture experiments.
The observed error in taxon ratios (colored dots) against the fitted model prediction (black cross) for the three mixture experiments of Brooks et al. (2015).
Figure 3—figure supplement 2
Observed vs. expected proportions under no bias, copy-number bias only, and the estimated bias.
Comparison of the observed proportions with three types of expected proportions—the actual proportions, the proportions predicted from the estimated 16S copy numbers in Table 3, and the proportions …
Figure 3—figure supplement 3
Comparison between the simple linear model, the linear interactions model of Brooks et al. (2015), and our model.
Comparison of the model fits for the simple linear model, the linear interactions model of Brooks et al. (2015), and our model. The simple linear model has a poor fit, while the Brooks et al. (2015) …
Figure 4 with 1 supplement
Bias of the mock spike-in in the Costea et al. (2017) experiment is consistent across samples with varying background compositions.
Panel A shows the variation in bacterial composition across protocols and specimens (Labels 1 through 8 denote fecal specimens; M denotes the mock-only specimen) and Panel B shows the relative …
Figure 4—figure supplement 1
Estimated bias for the mock taxa for the three protocols.
Estimated bias for the 10 mock taxa for the three protocols in the Costea et al. (2017) experiment. Bias is shown as relative to the average taxon; that is, the efficiency of each taxon is divided …
Figure 5 with 1 supplement
Calibration can remove bias and make MGS measurements from different protocols quantitatively comparable.
For the sub-community defined by the mock spike-in of the Costea et al. (2017) dataset, we estimated bias from three specimens (the estimation set ‘Est’) and used the estimate to calibrate all …
Figure 5—figure supplement 1
Precision in the bias estimate vs. the number of control samples for Protocol H.
Precision in bias estimate decreases with the number of control samples and depends on the noise associated with each taxon. For Protocol H in the Costea et al. (2017) experiment, Panel A shows the …
Figure 6 with 1 supplement
In the Brooks et al. (2015) experiment, bias is primarily driven by DNA extraction and is not substantially reduced by 16S copy-number (CN) correction.
Panel A shows the bias estimate for each step in the experimental workflow (DNA extraction, PCR amplification, and sequencing + (bio)informatics), as well as the bias imposed by performing 16S CN …
Figure 6—figure supplement 1
PCR bias and total bias vs. bias predicted by 16S copy number.
In the Brooks et al. (2015) experiment, variation in 16S copy number is moderately predictive of PCR bias (A) but not of total bias (B). The grey line corresponds to , or perfect agreement between …
Author response image 1
Tables
Table 1
Estimated bias for the three Brooks et al. (2015) mixture experiments.
The first three columns show the bias estimated in each mixture experiment; the second three columns show the bias estimated for individual protocol steps from the mixture estimates. In each case, …
| Mixtures | Steps | |||||
|---|---|---|---|---|---|---|
| Taxon | Cells | DNA | PCR prod. | Extraction | PCR | Seq.+Inf. |
| Lactobacillus iners | 4.7 | 2.3 | 1.2 | 2.0 | 1.9 | 1.2 |
| Sneathia amnii | 4.6 | 2.4 | 1.3 | 1.9 | 1.8 | 1.3 |
| Lactobacillus crispatus | 2.3 | 0.5 | 0.9 | 4.3 | 0.6 | 0.9 |
| Prevotella bivia | 1.8 | 0.4 | 0.9 | 4.6 | 0.4 | 0.9 |
| Atopobium vaginae | 0.3 | 1.1 | 1.0 | 0.3 | 1.0 | 1.0 |
| Streptococcus agalactiae | 0.2 | 2.0 | 0.9 | 0.1 | 2.2 | 0.9 |
| Gardnerella vaginalis | 0.2 | 0.4 | 0.8 | 0.4 | 0.5 | 0.8 |
| Max pairwise bias | 29.3 | 6.1 | 1.6 | 36.6 | 5.2 | 1.6 |
| Avg. pairwise bias | 5.6 | 2.7 | 1.2 | 5.5 | 2.3 | 1.2 |
| Avg. pairwise noise | 1.2 | 1.2 | 1.3 | — | — | — |
Table 2
Estimated bias and differential bias among the spike-in taxa for the three protocols (Protocols H, Q, and W) in the Costea et al. (2017) experiment.
The first three columns show the bias of the given protocol for the 10 mock taxa; the second three columns show the differential bias between protocols for the 10 mock taxa and the contaminant. In …
| Protocol | Protocol/Reference | |||||
|---|---|---|---|---|---|---|
| Taxon | H | Q | W | H/Q | H/W | Q/W |
| Prevotella melaninogenica | 2.81 | 1.55 | 1.37 | 1.82 | 2.05 | 1.12 |
| Clostridium perfringens | 1.18 | 0.49 | 1.14 | 2.41 | 1.04 | 0.43 |
| Salmonella enterica | 1.77 | 2.29 | 0.79 | 0.77 | 2.25 | 2.90 |
| Clostridium difficile | 0.11 | 0.09 | 0.22 | 1.24 | 0.49 | 0.40 |
| Lactobacillus plantarum | 0.02 | 0.77 | 0.35 | 0.02 | 0.05 | 2.18 |
| Vibrio cholerae | 2.10 | 1.16 | 0.89 | 1.81 | 2.37 | 1.31 |
| Clostridium saccharolyticum | 1.21 | 1.44 | 0.59 | 0.84 | 2.05 | 2.45 |
| Yersinia pseudotuberculosis | 1.46 | 1.35 | 0.66 | 1.08 | 2.21 | 2.05 |
| Blautia hansenii | 0.54 | 0.74 | 1.80 | 0.72 | 0.30 | 0.41 |
| Fusobacterium nucleatum | 46.29 | 4.98 | 16.51 | 9.30 | 2.80 | 0.30 |
| Contaminant | — | — | — | 0.89 | 2.13 | 2.38 |
| Max pairwise bias | 2751 | 56 | 74 | 428 | 59 | 10 |
| Avg. pairwise bias | 9.7 | 3.2 | 3.5 | 4.7 | 3.9 | 2.8 |
| Avg. pairwise noise | 1.3 | 1.5 | 1.1 | 1.5 | 1.3 | 1.5 |
Table 3
Estimated genome size and 16S copy number for the seven mock taxa in the Brooks et al. (2015) experiment (Materials and methods).
https://doi.org/10.7554/eLife.46923.016| Taxon | Genome size (Mbp) | Copy number |
|---|---|---|
| Atopobium vaginae | 1.44 | 2* |
| Gardnerella vaginalis | 1.64 | 2 |
| Lactobacillus crispatus | 2.04 | 4 |
| Lactobacillus iners | 1.28 | 5* |
| Prevotella bivia | 2.52 | 4* |
| Sneathia amnii | 1.33 | 3* |
| Streptococcus agalactiae | 2.16 | 7 |
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*Denotes copy numbers that were instead estimated to be 1 by Brooks et al. (2015).
Additional files
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Transparent reporting form
- https://doi.org/10.7554/eLife.46923.017
