Towards optimized viral metagenomes for double-stranded and single-stranded DNA viruses from challenging soils

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Microbiology

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Introduction

Methods

Field site and sampling

Experiment 1: optimizing DNA extraction

Experiment 2: optimizing particle lysis and purification

Bioinformatics and statistics

Data availability

Results and Discussion

Experiment 1: different DNA extraction methods display variable efficiencies and recover distinct vOTUs

Experiment 2: heat-based lysis of non-CsCl-purified virus particles provides the most comprehensive viromes

ssDNA viruses are recovered in all 3 habitats

Conclusions

Supplemental Information

ssDNA vOTUs from both Experiments

Thedetected ssDNA virus sequences (see methods) were clustered at 95% average nucleotide identify (ANI) across 85% of their contig length, resulting in 13 vOTUs from the 18 viromes. The ssDNA viruses from each experiment are listed along with their corresponding marker gene and habitat of origin.

DOI: 10.7717/peerj.7265/supp-1

Experiment 1 Bioanalyzer results

Extracted DNA was run on a Bioanalyzer High Sensitivity DNA Assay for all samples and successful libraries (see methods) are shown. Each sample had 15 PCR cycles. Upper marker designated with purple and lower marker with green.

DOI: 10.7717/peerj.7265/supp-2

Experiment 1 DNA extract purity via A260/A230

Bog samples are shown on the left of each panel, fen samples on the right. DNA extraction methods are color-coded: purple for CTAB, blue for Wizard, and green for PowerSoil. * denotes significant difference via one-way ANOVA, α 0.05, and Tukey’s test with p-value < 0.05.† denotes significant difference for t test, p-value < 0.05;†† = p-value < 0.01;††† = p-value < 0.001. DNA extract purity via A260/A230 is shown.

DOI: 10.7717/peerj.7265/supp-3

Relative abundance of vOTUs across 2 bog and 4 fen viromes with variable genome coverage cutoffs (Experiment 1)

Four heatmaps are shown comparing the relative abundances of the 516 vOTUs with different thresholds on the minimum percentage of genome covered (10%, 20%, 30%, and 75%). The relative abundance was normalized per Gbp of metagenome and log10-transformed. All mapping used a minimum nucleotide identify of 90%.

DOI: 10.7717/peerj.7265/supp-4

Relative abundance of vOTUs across 12 palsa viromes with variable genome coverage cutoffs (Experiment 2)

Six heatmaps are shown comparing the relative abundances of the 66 vOTUs with different thresholds on the minimum percentage of genome covered, increasing in increments of 10 (0–60%). The relative abundance was normalized per Gbp of metagenome and log10-transformed. All mapping used a minimum nucleotide identify of 90%.

DOI: 10.7717/peerj.7265/supp-5

Diversity metrics of vOTUs

(A)Richness (R),Pielou’s evenness index (J), and Shannon’s Diversity index (H) were calculated for each virome and the viromes are plotted by habitat. Within each habitat the viromes are denoted by a circle, but displayed differently per treatment. For Experiment 1 (bog and fen), viromes are colored green for PowerSoil and blue for Wizard DNA extractions methods. Experiment 2 (palsa) viromes are outlined in red for heat treated samples or blue for bead-beating samples. The marker is filled in for samples that were CsCl purified. (B) A principal coordinate analysis of the viromes by normalized relative abundance of the 66 vOTUs from Experiment 2 based on their Bray-Curtis dissimilarity. Viromes distinguished by soil core, purification (+CsCl outlined in red), and lysis method.

DOI: 10.7717/peerj.7265/supp-6

Raw Data

Raw data is provided for the qPCR data and the total DNA extracted for Experiment 1.

DOI: 10.7717/peerj.7265/supp-7

Additional Information and Declarations

Competing Interests

The authors declare there are no competing interests.

Author Contributions

Gareth Trubl, Yueh-Fen Li conceived and designed the experiments, performed the experiments, analyzed the data, prepared figures and/or tables, authored or reviewed drafts of the paper, approved the final draft.

Simon Roux, Benjamin Bolduc and Josué Rodríguez-Ramos analyzed the data, authored or reviewed drafts of the paper, approved the final draft.

Natalie Solonenko conceived and designed the experiments, performed the experiments, authored or reviewed drafts of the paper, approved the final draft.

Emiley A. Eloe-Fadrosh contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

Virginia I. Rich and Matthew B. Sullivan conceived and designed the experiments, contributed reagents/materials/analysis tools, authored or reviewed drafts of the paper, approved the final draft.

Data Availability

The following information was supplied regarding data availability:

Raw data is available in the IsoGenieDB, in the Viral Sequencing Data section at https://isogenie-db.asc.ohio-state.edu/datasources#viral_sequencing. All datasets named Trubl Soil Viromes were used in this study.

Funding

This study was funded by the Genomic Science Program of the United States Department of Energy Office of Biological and Environmental Research (grants DE-SC0010580 and DE-SC0016440), The Office of Science, Office of Workforce Development for Teachers and Scientists, Office of Science Graduate Student Research (SCGSR) program, and by the Gordon and Betty Moore Foundation Investigator Award (GBMF#3790 to Matt Sullivan). The SCGSR program is administered by the Oak Ridge Institute for Science and Education (ORISE) for the DOE. ORISE is managed by ORAU under contract number DE-SC0014664. The work conducted by the US Department of Energy Joint Genome Institute, a DOE Office of Science User Facility, is supported by the Office of Science of the US Department of Energy under contract no. DE-AC02-05CH11231. Bioinformatics were supported by The Ohio Supercomputer Center and by the National Science Foundation under Award Numbers DBI-0735191 and DBI-1265383; URL: www.cyverse.org. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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