| Literature DB >> 25608871 |
Manuel Kleiner1,2, Lora V Hooper3,4, Breck A Duerkop5.
Abstract
BACKGROUND: Viruses are a significant component of the intestinal microbiota in mammals. In recent years, advances in sequencing technologies and data analysis techniques have enabled detailed metagenomic studies investigating intestinal viromes (collections of bacteriophage and eukaryotic viral nucleic acids) and their potential contributions to the ecology of the microbiota. An important component of virome studies is the isolation and purification of virus-like particles (VLPs) from intestinal contents or feces. Several methods have been applied to isolate VLPs from intestinal samples, yet to our knowledge, the efficiency and reproducibility between methods have not been explored. A rigorous evaluation of methods for VLP purification is critical as many studies begin to move from descriptive analyses of virus diversity to studies striving to quantitatively compare viral abundances across many samples. Therefore, reproducible VLP purification methods which allow for high sample throughput are needed. Here we compared and evaluated four methods for VLP purification using artificial intestinal microbiota samples of known bacterial and viral composition.Entities:
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Year: 2015 PMID: 25608871 PMCID: PMC4308010 DOI: 10.1186/s12864-014-1207-4
Source DB: PubMed Journal: BMC Genomics ISSN: 1471-2164 Impact factor: 3.969
Figure 1Schematic diagram of VLP purification methods. An artificial intestinal microbiota sample was generated by the addition of six phages and two bacterial strains to germ-free mouse feces. Upon homogenization of the mixture, the sample was split into 10 equal subsamples. Two subsamples were immediately set aside for total DNA isolation (metagenome). The remaining 8 samples were centrifuged. Upon completion of centrifugation, two samples were treated with 6.5 mM dithiothreitol (DTT). All eight samples were filtered to remove bacteria and particulates and treated with DNase. Two samples were loaded onto a CsCl gradient and phages were banded as described in Methods. The PEG precipitation failed due to the formation of a viscous mass that impaired PEG removal by buffer exchange. After collection of the phages from the CsCl gradients, all 8 samples were extracted for total nucleic acids using phenol/chloroform extraction. G+, Gram-positive; G-, Gram-negative.
Method overview/summary
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| DNA recovered in (ng in sample 1, ng in sample 2) | 42, 44 | 29, 34 | 21, 19 | 636, 459 |
| Sample throughputa | 15-20 | 15-20 | 6-8d | N/A |
| Total duration of protocol (days)b | 1 | 1 | 2 | N/A |
| Hands on time (hours)c | 6 | 6 | 10 | N/A |
| Special equipment needed | No | No | Ultracentrifuge | N/A |
| Intra-method reproducibility | High | High | Medium | N/A |
| Biases against specific phage | Weak | Weak | Strong | N/A |
| Removal efficiency of mouse DNA | High | High | Very high | N/A |
| Removal efficiency of bacterial DNA | Very high | Very high | Very high | N/A |
a:Number of samples that can be processed by one person in parallel; b:Duration of the respective purification protocol from fecal sample to purified VLPs, DNA extraction time not included; c:Hands on time needed for the number of samples that can be processed by one person in parallel (above); d:Sample number limited by rotor size of ultracentrifuge and number of density gradients that can be set up in parallel in a reasonable amount of time.
Figure 2Read abundances from artificial intestinal microbiota samples following VLP purification or whole metagenome processing. (A) Relative read abundances (detailed data in Additional file 1: Tables S1 and S3-S10) (B) Relative read abundances after normalization to genome sizes (Detailed data in Additional file 1: Tables S2-S10). FD, Filtration + DNase – replicates 1&2; DTT, DTT + Filtration + DNAse – replicates 1&2; CsCl, Filtration + DNase + CsCl gradient – replicates 1&2; MG; Total metagenome (no purification procedure) – replicates 1&2. *Denotes organism read abundances with bars too small to be seen in the figure.
Intra- and between method variation based on read abundance ratios*
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| Calculated with % read abundance | |||||||
| M13 | 0.74 | 2.22 | 1.67 | 1.08 | 1.52 | 10.06 | 0.07 |
| P22 | 0.96 | 1.01 | 1.01 | 1.73 | 0.95 | 0.78 | 1.36 |
| ɸVPE25 | 0.94 | 0.92 | 0.75 | 2.33 | 0.99 | 125.23 | 0.01 |
| T3 | 1.01 | 1.01 | 1.14 | 1.69 | 0.93 | 0.94 | 1.15 |
| T7 | 1.03 | 1.00 | 0.71 | 1.88 | 0.94 | 1.57 | 0.68 |
| Calculated with % read abundance normalized to genome size | |||||||
| M13 | 0.75 | 2.24 | 1.63 | 0.73 | 1.60 | 11.20 | 0.06 |
| P22 | 0.98 | 1.02 | 1.01 | 1.19 | 1.00 | 0.91 | 1.10 |
| ɸVPE25 | 0.96 | 0.93 | 0.75 | 1.60 | 1.05 | 146.16 | 0.01 |
| T3 | 1.03 | 1.01 | 1.14 | 1.16 | 0.98 | 1.09 | 0.93 |
| T7 | 1.05 | 1.00 | 0.71 | 1.29 | 0.99 | 1.83 | 0.55 |
*Perfect reproducibility would result in ratios equal to one.
a:Read abundance ratios between methods were calculated using the average read abundance in each method.
Purification method biases for specific phages*
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| Average % read abundance normalized to genome size | ||||
| M13 | 0.010 | 0.007 | 0.001 | 0.027 |
| P22 | 79.605 | 79.695 | 87.830 | 29.338 |
| ɸVPE25 | 5.564 | 5.310 | 0.036 | 9.749 |
| T3 | 6.164 | 6.286 | 5.751 | 2.101 |
| T7 | 4.879 | 4.923 | 2.691 | 2.974 |
| Ratios of genome size normalized % read abundances | ||||
| P22/ɸVPE25 | 14.3 | 15.0 | 2417.5 | 3.0 |
| P22/T3 | 12.9 | 12.7 | 15.3 | 14.0 |
| P22/T7 | 16.3 | 16.2 | 32.6 | 9.9 |
| ɸVPE25/T3 | 0.9 | 0.8 | 0.0 | 4.6 |
| ɸVPE25/T7 | 1.1 | 1.1 | 0.0 | 3.3 |
| T3/T7 | 1.3 | 1.3 | 2.1 | 0.7 |
| T7/M13 | 465 | 748 | 4584 | 108 |
| P22/M13 | 7587 | 12119 | 149630 | 1073 |
| ɸVPE25/M13 | 530 | 807 | 61 | 356 |
| T3/M13 | 587 | 956 | 9797 | 76 |
*In case of absence of purification biases, ratios of size normalized read abundances between phages would be identical in the unpurified control samples (MG) and the purified samples (FD, DTT and CsCl).
Removal efficiency of mouse and bacterial DNA by different purification methods
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| Mouse | 14.26 | 10.49 | 1.20 | 34.63 |
| Phagea | 82.57 | 86.79 | 96.13 | 3.62 |
| Bacteriab | 0.033 | 0.032 | 0.032 | 59.21 |
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| Phage/mouse ratio | 5.79 | 8.27 | 80.31 | 0.10 |
| Factor of ratio change compared to MG method | 55 | 79 | 768 | 1 |
| Estimated % decrease of read generating mouse DNA as compared to MGc | 98.19 | 98.74 | 99.87 | 0.00 |
| Phage/bacteria ratio | 2537.74 | 2674.62 | 2999.83 | 0.06 |
| Factor of ratio change compared to MG method | 41518 | 43757 | 49078 | 1 |
| Estimated % decrease of read generating bacterial DNA as compared to MGc | 99.998 | 99.998 | 99.998 | 0.00 |
a:Sum of read abundances for all added bacteriophage (this excludes the phiX174 used as Illumina internal control); b:Sum of read abundances for the two added bacteria – L. monocytogenes and B. thetaiotaomicron; c:Calculated based on read abundances normalized to phage read abundance.
Assembly statistics
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| P22 No. of contigs | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 |
| P22 largest contig (bp)a | 41660 | 41737 | 41737 | 41737 | 41737 | 41737 | 41659 | 41737 | 41737 |
| P22 coverage (x fold) | N/A | 3651 | 3138 | 3925 | 4027 | 5489 | 4998 | 146 | 107 |
| T7 No. of contigs | 1 | 1 | 2 | 2 | 1 | 1 | 1 | 4 | 1 |
| T7 largest contig (bp) | 39937 | 39855 | 35301 | 35209 | 39344 | 39855 | 39855 | 35472 | 39855 |
| T7 coverage (x fold) | N/A | 256 | 220 | 257 | 273 | 168 | 202 | 16 | 11 |
| T3 No. of contigs | 1 | 1 | 4 | 4 | 2 | 1 | 1 | 2 | 1 |
| T3 largest contig (bp) | 38209 | 37540 | 33483 | 33392 | 37540 | 36121 | 37541 | 33656 | 36120 |
| T3 coverage (x fold) | N/A | 293 | 265 | 305 | 321 | 381 | 310 | 10 | 8 |
| ɸVPE25 No. of contigs | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 1 | 2 |
| ɸVPE25 largest contig (bp) | 86524 | 86520 | 86522 | 86518 | 86542 | 86496 | 86505 | 86534 | 86540 |
| ɸVPE25 coverage (x fold) | N/A | 256 | 225 | 253 | 284 | 1.9 | 2.3 | 55 | 30 |
| M13 No. of contigs | 1 | 7 | 4 | 8 | 4 | 1 | 0 | 1 | 0 |
| M13 largest contig (bp) | 6407 | 1085 | 900 | 814 | 586 | 230 | 0 | 268 | 0 |
| M13 coverage (x fold) | N/A | 0.35 | 0.55 | 0.43 | 0.39 | 0.18 | 0 | 0.14 | 0 |
a:Assemblies of the P22 genome from our datasets are slightly larger than the reference genome, which is likely due to the quasi-circular nature of the P22 genome, which makes it impossible for the assembly algorithm to determine the exact start and end of the genome.