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Herein we describe a detailed protocol for DNA virome analysis of low input human stool samples (Monaco et al., 2016). This protocol is divided into four main steps: 1) stool samples are pulverized to evenly distribute microbial matter; 2) stool is enriched for virus-like particles and DNA is extracted by phenol-chloroform; 3) purified DNA is multiple-strand displacement amplified (MDA) and fragmented; and 4) libraries are constructed and sequenced using Illumina Miseq. Subsequent sequence analysis for viral sequence identification should be sensitive but stringent.
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[Abstract] Herein we describe a detailed protocol for DNA virome analysis of low input human stool samples (Monaco et al., 2016). This protocol is divided into four main steps: 1) stool samples are pulverized to evenly distribute microbial matter; 2) stool is enriched for virus-like particles and DNA is extracted by phenol-chloroform; 3) purified DNA is multiple-strand displacement amplified (MDA) and fragmented; and 4) libraries are constructed and sequenced using Illumina Miseq. Subsequent sequence analysis for viral sequence identification should be sensitive but stringent.
Keywords: Virome, Viral microbiome, Virus-like particles, MDA, Illumina Miseq
[Background] The virome, a dynamic community of eukaryotic viruses, bacteriophages and endogenous retroviruses, represents a minimally characterized component of the human microbiome (Virgin, 2014). In fact, it is estimated that only 1% of the virome has been sequenced and annotated (Mokili et al., 2012). Next generation sequencing (NGS) enables examination of the entire virome, including unculturable viruses. Stool is a readily obtainable specimen type for study of the virome, and alterations in the fecal virome have been associated with a number of disease states (Handley et al., 2012; Norman et al., 2015; Monaco et al., 2016). The fecal virome is largely comprised of bacteriophages, which affect the gastrointestinal tract through alterations in bacterial functions and populations (Duerkop and Hooper, 2013; Reyes et al., 2013; Virgin, 2014). Enteric eukaryotic viruses, while less ubiquitous than bacteriophages, play a more direct role in gastrointestinal tract dysfunction by inducing gastroenteritis, enteritis and colitis. Despite the abundance of bacteriophages in fecal samples, only a few studies thus far have examined the contributions of fecal bacteriophages in human diseases. Inflammatory bowel disease has been associated with increased enteric bacteriophage richness (Norman et al., 2015). In contrast, profound immunosuppression from AIDS in a sub-Saharan cohort resulted in an expanded eukaryotic virome, but had minimal impact on bacteriophage populations (Monaco et al., 2016). More studies are needed to elucidate the role the fecal virome plays in disease states. A key roadblock to studying the stool virome is viral nucleic acid extraction and enrichment from fecal material. Several factors can contribute to difficulty in isolating viral sequences from fecal samples, chief among them the fact that viruses constitute a minority of fecal sample material. Additionally, dilution of feces in collection media (such as RNAlater RNA stabilization reagent) can further hamper the ability to find viral sequences. While many nucleic acid extraction protocols can be used for high input nucleic acid samples to enrich for viral nucleic acid, low input samples, such as those diluted in collection media, represent a challenge with virome studies. After comparison and optimization of several methods, the following protocol was identified as the most universally applicable for isolation of phage and DNA viral sequences from both low (Monaco et al., 2016) and high (Norman et al., 2015) input samples.
Materials and Reagents
Equipment
Procedure
Data analysis
Sequence analysis methods are rapidly evolving due to advances in both hardware speed and software coding. Many sequence processing software tools are open-source (such as BBTools, http://jgi.doe.gov/data-and-tools/bbtools/), as are statistical analysis and graphing packages in R (https://www.r-project.org/). We used VirusSeeker (Zhao et al., 2017), a customized automated bioinformatics pipeline based on VirusHunter (Zhao et al., 2013), to detect sequences sharing nucleotide and amino acid sequence similarity to known viruses (Figure 1 below). We recommend using a stringent protocol for viral sequence identification, such as VirusSeeker, that removes low-quality sequences, repeat sequences, and non-specific viral ‘hits.’ Similarly stringent methods have identified novel viral sequences (Zhao et al., 2013). Basic steps in the analysis protocol are shown in Figure 1. Custom viral databases can be generated after downloading sequences corresponding to all viral genomes from the NCBI database (make note of the date of download as new sequences are frequently added). Deduplication is recommended to minimize amplification bias, and taxon-assigned sequences should be normalized to account for variations in sequencing depth between samples. Novel viral sequences identified or viral sequences of interest should be validated by real-time qPCR using primers specific to the viral sequence. Additionally, sequences can be de novo assembled into longer contigs and compared to the NCBI nr/nt databases to better identify phylogeny of viral sequences of interest (Monaco et al., 2016). Phylogenetic trees comparing sequences of interest to known related viral sequences can be made using free software such as FigTree (http://tree.bio.ed.ac.uk/software/figtree/). Figure 1. Sequence analysis schematic
Notes
Stool pulverization is performed in order to evenly distribute microbial matter in the sample. The use of SM buffer containing gelatin stabilizes bacteriophage populations after freezing for further characterization of bacteriophage of interest, including culturing. Due to risk of contamination, reagents should be used only for fecal microbiome studies. Use the same reagents for all Illumina Miseq runs (i.e., same bottle of sterile water, kits, etc.) as many reagents may be contaminated by microbial DNA, and this ensures even contamination across runs.
Recipes
Acknowledgments
CLM was supported by NIH training grant 5T32AI007172-34, and the work was funded by R24 ODO19793, R01 OD011170, R01 AI111918, and R01 DK101354. DSK is supported by the Burroughs Wellcome Fund. The stool pulverization protocol is adapted from a protocol generously provided by the Jeffrey Gordon laboratory at Washington University in St. Louis. The VLP protocol was adapted from a protocol for phage isolation (Reyes et al., 2013). We would like to thank Brian Keller, M.D., Ph. D for critical review of this manuscript.
References
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