Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method
Abstract
:1. Introduction
2. Materials and Methods
2.1. Samples Processing for 16S rRNA Sequencing
2.2. Shotgun Metagenomic Library Preparation, Sequencing, and Data Quality
2.3. Random Subsampling of Sequences
2.4. Taxonomic and Pathway Annotations
2.5. Statistical Analyses
2.6. Data Availability
3. Results
3.1. Bacterial Richness, but Not Evenness or β-Diversity, Is Affected by Sequencing Depth When Using Marker Gene-Mapping- and Alignment-Based Approaches
3.2. Identification of Certain Bacterial Genera and Species Is Affected by SMS Sequencing Depth When Using a Marker Gene-Mapping-Based Approach, but Not an Alignment-Based Approach
3.3. Assessing the Accuracy of Marker Gene-Mapping- and Alignment-Based Approaches Using Reference Materials
3.4. Sequencing Depth Affects Virus Identification from Metagenomic Samples and Is Subject-Specific
3.5. Pathway Relative Abundances Are Dependent on Sequencing Depth and Are Category-Specific
4. Discussion
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Conflicts of Interest
References
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Sequencing Depth | ||||||||
---|---|---|---|---|---|---|---|---|
Marker Gene Mapping | FDR P | 5 Gb | 3 Gb | 1 Gb | 0.75 Gb | 0.5 Gb | 0.25 Gb | 0.1 Gb |
C. spiroforme | 2.16 × 10−2 | 3.05 × 10−3 | 2.55 × 10−3 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 |
L. lactis | 2.16 × 10−2 | 3.72 × 10−4 | 3.25 × 10−4 | 1.80 × 10−4 | 2.37 × 10−4 | 4.95 × 10−5 | 0.00 × 100 | 0.00 × 100 |
Roseburia inulinivorans | 2.69 × 10−2 | 3.43 × 10−4 | 3.19 × 10−4 | 2.13 × 10−4 | 1.80 × 10−4 | 5.65 × 10−5 | 0.00 × 100 | 0.00 × 100 |
L. bacterium 3 1 46FAA | 2.69 × 10−2 | 6.07 × 10−4 | 5.70 × 10−4 | 4.67 × 10−4 | 4.39 × 10−4 | 4.33 × 10−4 | 2.23 × 10−4 | 0.00 × 100 |
A. colihominis | 3.26 × 10−2 | 2.84 × 10−5 | 1.24 × 10−5 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 |
Eggerthella lenta | 3.55 × 10−2 | 1.34 × 10−4 | 1.35 × 10−4 | 1.35 × 10−4 | 9.57 × 10−5 | 8.66 × 10−5 | 1.76 × 10−5 | 0.00 × 100 |
Clostridium bolteae | 3.55 × 10−2 | 1.11 × 10−3 | 2.22 × 10−4 | 1.13 × 10−4 | 1.37 × 10−4 | 8.32 × 10−5 | 4.48 × 10−5 | 0.00 × 100 |
Streptococcus parasanguinis | 3.55 × 10−2 | 7.19 × 10−4 | 6.53 × 10−4 | 5.14 × 10−4 | 4.78 × 10−4 | 3.33 × 10−4 | 2.02 × 10−4 | 0.00 × 100 |
Lachnospiraceae bacterium 7 1 58FAA | 3.55 × 10−2 | 2.31 × 10−4 | 2.20 × 10−4 | 1.42 × 10−4 | 1.70 × 10−4 | 1.37 × 10−4 | 6.34 × 10−5 | 0.00 × 100 |
Holdemania filiformis | 3.55 × 10−2 | 3.58 × 10−4 | 3.60 × 10−4 | 2.73 × 10−4 | 1.68 × 10−4 | 5.65 × 10−5 | 0.00 × 100 | 0.00 × 100 |
Eubacterium eligens | 3.55 × 10−2 | 1.43 × 10−4 | 1.21 × 10−4 | 6.86 × 10−5 | 4.22 × 10−5 | 0.00 × 100 | 0.00 × 100 | 0.00 × 100 |
Clostridium leptum | 4.25 × 10−2 | 1.56 × 10−3 | 1.51 × 10−3 | 1.29 × 10−3 | 1.38 × 10−3 | 1.04 × 10−3 | 6.93 × 10−4 | 2.28 × 10−4 |
Alignment | FDR P | 5 Gb | 3 Gb | 1 Gb | 0.75 Gb | 0.5 Gb | 0.25 Gb | 0.1 Gb |
C. spiroforme | 1.00 | 2.45 × 10−3 | 2.45 × 10−3 | 2.45 × 10−3 | 2.46 × 10−3 | 2.46 × 10−3 | 2.46 × 10−3 | 2.48 × 10−3 |
L. lactis | 1.00 | 3.79 × 10−4 | 3.79 × 10−4 | 3.78 × 10−4 | 3.78 × 10−4 | 3.78 × 10−4 | 3.62 × 10−4 | 3.84 × 10−4 |
R. inulinivorans | 1.00 | 8.26 × 10−4 | 8.27 × 10−4 | 8.17 × 10−4 | 8.15 × 10−4 | 8.16 × 10−4 | 8.31 × 10−4 | 8.27 × 10−4 |
L. bacterium 3 1 46FAA | 1.00 | 1.71 × 10−4 | 1.70 × 10−4 | 1.71 × 10−4 | 1.70 × 10−4 | 1.72 × 10−4 | 1.72 × 10−4 | 1.69 × 10−4 |
A. colihominis | 1.00 | 5.11 × 10−4 | 5.08 × 10−4 | 5.05 × 10−4 | 5.02 × 10−4 | 5.00 × 10−4 | 5.04 × 10−4 | 4.97 × 10−4 |
E. lenta | 1.00 | 8.92 × 10−4 | 8.93 × 10−4 | 8.95 × 10−4 | 8.95 × 10−4 | 8.90 × 10−4 | 8.96 × 10−4 | 9.18 × 10−4 |
Clostridium bolteae | 1.00 | 1.83 × 10−4 | 1.83 × 10−4 | 1.83 × 10−4 | 1.83 × 10−4 | 1.81 × 10−4 | 1.83 × 10−4 | 1.81 × 10−4 |
S. parasanguinis | 1.00 | 1.90 × 10−4 | 1.90 × 10−4 | 1.91 × 10−4 | 1.91 × 10−4 | 1.95 × 10−4 | 1.80 × 10−4 | 1.79 × 10−4 |
Lachnospiraceae bacterium 7 1 58FAA | 1.00 | 2.77 × 10−4 | 2.78 × 10−4 | 2.79 × 10−4 | 2.80 × 10−4 | 2.84 × 10−4 | 2.84 × 10−4 | 2.78 × 10−4 |
H. filiformis | 1.00 | 3.08 × 10−4 | 3.08 × 10−4 | 3.11 × 10−4 | 3.11 × 10−4 | 3.14 × 10−4 | 3.10 × 10−4 | 3.19 × 10−4 |
E. eligens | 1.00 | 7.07 × 10−4 | 7.04 × 10−4 | 7.08 × 10−4 | 7.12 × 10−4 | 7.19 × 10−4 | 7.19 × 10−4 | 7.28 × 10−4 |
Clostridium leptum | 1.00 | 1.25 × 10−3 | 1.25 × 10−3 | 1.25 × 10−3 | 1.25 × 10−3 | 1.26 × 10−3 | 1.28 × 10−3 | 1.29 × 10−3 |
Bacterial Genera | Marker Gene-Mapping |
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Alignment | |
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16S | |
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Bacterial Species | Marker gene-Mapping |
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Alignment | |
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16S | |
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Pathways | UniProt |
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MetaCyc | |
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Virome |
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Santiago-Rodriguez, T.M.; Garoutte, A.; Adams, E.; Nasser, W.; Ross, M.C.; La Reau, A.; Henseler, Z.; Ward, T.; Knights, D.; Petrosino, J.F.; et al. Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method. Genes 2020, 11, 1380. https://doi.org/10.3390/genes11111380
Santiago-Rodriguez TM, Garoutte A, Adams E, Nasser W, Ross MC, La Reau A, Henseler Z, Ward T, Knights D, Petrosino JF, et al. Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method. Genes. 2020; 11(11):1380. https://doi.org/10.3390/genes11111380
Chicago/Turabian StyleSantiago-Rodriguez, Tasha M., Aaron Garoutte, Emmase Adams, Waleed Nasser, Matthew C. Ross, Alex La Reau, Zachariah Henseler, Tonya Ward, Dan Knights, Joseph F. Petrosino, and et al. 2020. "Metagenomic Information Recovery from Human Stool Samples Is Influenced by Sequencing Depth and Profiling Method" Genes 11, no. 11: 1380. https://doi.org/10.3390/genes11111380