Report: ZymoBIOMICS^® Shotgun Sequencing Service for Microbiome Analysis

Zymo Research Corporation

1 Results for Group Analysis

Click on the links below to view the results from each group analysis:

01…GroupComparison.illumina.pe

2 Materials and Methods

The samples were processed and analyzed with the ZymoBIOMICS Shotgun Metagenomic Sequencing Service for Microbiome Analysis (Zymo Research, Irvine, CA). Specific details for the project can be found in the final report PDF.

DNA Extraction: One of three different DNA extraction kits was used depending on the sample type and sample volume. In most cases, the ZymoBIOMICS^®-96 MagBead DNA Kit (Zymo Research, Irvine, CA) was used to extract DNA using an automated platform. In some cases, ZymoBIOMICS^® DNA Miniprep Kit (Zymo Research, Irvine, CA) was used. For low biomass samples, such as skin swabs, the ZymoBIOMICS^® DNA Microprep Kit (Zymo Research, Irvine, CA) was used as it permits for a lower elution volume, resulting in more concentrated DNA samples.

Shotgun Metagenomic Library Preparation: Genomic DNA samples were profiled with shotgun metagenomic sequencing. Sequencing libraries were prepared with either the KAPA^™ HyperPlus Library Preparation Kit (Kapa Biosystems, Wilmington, MA) with up to 100 ng DNA input following the manufacturer's protocol using internal single-index 8 bp barcodes with TruSeq^® adapters (Illumina, San Diego, CA) or the Nextera^® DNA Flex Library Prep Kit (Illumina, San Diego, CA) with up to 100 ng DNA input following the manufacturers protocol using internal dual-index 8 bp barcodes with Nextera^® adapters (Illumina, San Diego, CA). All libraries were quantified with TapeStation^® (Agilent Technologies, Santa Clara, CA) and then pooled in equal abundance. The final pool was quantified using qPCR.

Sequencing: The final library was sequenced on either the Illumina HiSeq^® or the Illumina NovaSeq^® M

Bioinformatics Analysis: Raw sequence reads were trimmed to remove low quality fractions and adapters with Trimmomatic-0.33 (Bolger et al., 2014): quality trimming by sliding window with 6 bp window size and a quality cutoff of 20, and reads with size lower than 70 bp were removed. Antimicrobial resistance and virulence factor gene identification was performed with the DIAMOND sequence aligner (Buchfink et al., 2015). Microbial composition was profiled with Centrifuge (Kim et al., 2016) using bacterial, viral, fungal, mouse, and human genome datasets. Strain-level abundance information was extracted from the Centrifuge outputs and further analyzed: (1) to perform alpha- and beta-diversity analyses; (2) to create microbial composition barplots with QIIME (Caporaso et al., 2012); (3) to create taxa abundance heatmaps with hierarchical clustering (based on Bray-Curtis dissimilarity); and (4) for biomarker discovery with LEfSe (Segata et al., 2011) with default settings (p>0.05 and LDA effect size >2).

Statistical Analysis: Statistical calculations were performed using the Python scikit-learn and StatsModels libraries. Differences in alpha diversity (Observed features and Shannon diversity) was analyzed using a ranked one-way ANOVA followed by a Tukey honest significant difference test for multiple post-hoc comparisons. Permutational multivariate analysis of variance (PERMANOVA) used Bray-Curtis and Jaccard distance measures to asses microbial community compositional differences when different categorical groups are provided (999 permutations).

3 References

Bolger, A.M., Lohse, M., and Usadel, B. (2014) Trimmomatic: a flexible trimmer for Illumina sequence data. Bioinformatics 30: 2114-2120.

Buchfink, B., Xie, C., Huson, D.H. (2015) Fast and sensitive protein alignment using DIAMOND. Nature Methods 12:59-60.

Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K. et al. (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7: 335-336.

Kim, D., Song, L., Breitwieser, F.P., Salzberg, S.L. (2016) Centrifuge: rapid and sensitive classification of metagenomic sequences. Genome Res 12:1721-1729.

Segata, N., Izard, J., Waldron, L., Gevers, D., Miropolsky, L., Garrett, W.S., and Huttenhower, C. (2011) Metagenomic biomarker discovery and explanation. Genome Biol 12: R60.