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Random whole metagenomic sequencing for forensic discrimination of soils.

Khodakova AS, Smith RJ, Burgoyne L, Abarno D, Linacre A - PLoS ONE (2014)

Bottom Line: Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science.Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted.Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, Flinders University, Adelaide, Australia.

ABSTRACT
Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

No MeSH data available.


Related in: MedlinePlus

Comparison of the taxonomic soil profiles generated on full datasets at the phylum (A, B, C) and species (D, E, F) resolution levels.Bray-Curtis distance similarity matrix was calculated from the square-root transformed abundance of DNA fragments matching taxa in the M5NR database (E-value <1×10−5). The Bray-Curtis matrix was used for generating CLUSTER dendrogram, NMDS and CAP ordination plots. CLUSTER analysis (A and D). Red dotted branches on the CLUSTER dendrogram indicate no significant difference between metagenomic profiles (supported by the SIMPROF analysis, p<0.05). NMDS unconstrained ordination (B and E). The NMDS plot displays distances between samples. Data points that are closer to each other represent samples with highly similar metagenomic profiles. CAP constrained ordination (C and F). CAP analysis tests for differences among the groups in multivariate space. The significance of group separation along the canonical axis is indicated by the value of the squared canonical correlation (δ12) and P-value. A contour line on the NMDS and CAP ordinations drawn round each of the cluster defines the superimposition of clusters from CLUSTER dendrogram at the selected level of similarity.
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pone-0104996-g001: Comparison of the taxonomic soil profiles generated on full datasets at the phylum (A, B, C) and species (D, E, F) resolution levels.Bray-Curtis distance similarity matrix was calculated from the square-root transformed abundance of DNA fragments matching taxa in the M5NR database (E-value <1×10−5). The Bray-Curtis matrix was used for generating CLUSTER dendrogram, NMDS and CAP ordination plots. CLUSTER analysis (A and D). Red dotted branches on the CLUSTER dendrogram indicate no significant difference between metagenomic profiles (supported by the SIMPROF analysis, p<0.05). NMDS unconstrained ordination (B and E). The NMDS plot displays distances between samples. Data points that are closer to each other represent samples with highly similar metagenomic profiles. CAP constrained ordination (C and F). CAP analysis tests for differences among the groups in multivariate space. The significance of group separation along the canonical axis is indicated by the value of the squared canonical correlation (δ12) and P-value. A contour line on the NMDS and CAP ordinations drawn round each of the cluster defines the superimposition of clusters from CLUSTER dendrogram at the selected level of similarity.

Mentions: An initial comparison of the taxonomic structures of the metagenomes using lowest (coarsest) resolution profiles derived at the phylum level of taxonomy was performed. CLUSTER analysis with group-average linking based on Bray-Curtis similarity matrices delineated two distinct clusters with similarity of 85% formed by samples from AP-based dataset grouped according to the sites from where the samples were taken (Fig. 1A). These clusters were supported by the SIMPROF analysis that showed statistically significant (p<0.05) evidence of genuine clustering, as indicated by red dotted branches on the dendrogram (Fig. 1A). Two samples from WGA_A group having 94% profiles similarity also formed such a cluster. Other samples form SH- and WGA-based datasets formed mixed clusters. For example, a sample from the WGA_B group formed a united cluster with a sample from the SH_A group and two samples from the SH_B group (similarity 94%), thus indicating that the samples from two different locations were grouped together incorrectly. One more cluster consisted of two samples from SH_A and SH_B groups with 96% of similarity.


Random whole metagenomic sequencing for forensic discrimination of soils.

Khodakova AS, Smith RJ, Burgoyne L, Abarno D, Linacre A - PLoS ONE (2014)

Comparison of the taxonomic soil profiles generated on full datasets at the phylum (A, B, C) and species (D, E, F) resolution levels.Bray-Curtis distance similarity matrix was calculated from the square-root transformed abundance of DNA fragments matching taxa in the M5NR database (E-value <1×10−5). The Bray-Curtis matrix was used for generating CLUSTER dendrogram, NMDS and CAP ordination plots. CLUSTER analysis (A and D). Red dotted branches on the CLUSTER dendrogram indicate no significant difference between metagenomic profiles (supported by the SIMPROF analysis, p<0.05). NMDS unconstrained ordination (B and E). The NMDS plot displays distances between samples. Data points that are closer to each other represent samples with highly similar metagenomic profiles. CAP constrained ordination (C and F). CAP analysis tests for differences among the groups in multivariate space. The significance of group separation along the canonical axis is indicated by the value of the squared canonical correlation (δ12) and P-value. A contour line on the NMDS and CAP ordinations drawn round each of the cluster defines the superimposition of clusters from CLUSTER dendrogram at the selected level of similarity.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4128759&req=5

pone-0104996-g001: Comparison of the taxonomic soil profiles generated on full datasets at the phylum (A, B, C) and species (D, E, F) resolution levels.Bray-Curtis distance similarity matrix was calculated from the square-root transformed abundance of DNA fragments matching taxa in the M5NR database (E-value <1×10−5). The Bray-Curtis matrix was used for generating CLUSTER dendrogram, NMDS and CAP ordination plots. CLUSTER analysis (A and D). Red dotted branches on the CLUSTER dendrogram indicate no significant difference between metagenomic profiles (supported by the SIMPROF analysis, p<0.05). NMDS unconstrained ordination (B and E). The NMDS plot displays distances between samples. Data points that are closer to each other represent samples with highly similar metagenomic profiles. CAP constrained ordination (C and F). CAP analysis tests for differences among the groups in multivariate space. The significance of group separation along the canonical axis is indicated by the value of the squared canonical correlation (δ12) and P-value. A contour line on the NMDS and CAP ordinations drawn round each of the cluster defines the superimposition of clusters from CLUSTER dendrogram at the selected level of similarity.
Mentions: An initial comparison of the taxonomic structures of the metagenomes using lowest (coarsest) resolution profiles derived at the phylum level of taxonomy was performed. CLUSTER analysis with group-average linking based on Bray-Curtis similarity matrices delineated two distinct clusters with similarity of 85% formed by samples from AP-based dataset grouped according to the sites from where the samples were taken (Fig. 1A). These clusters were supported by the SIMPROF analysis that showed statistically significant (p<0.05) evidence of genuine clustering, as indicated by red dotted branches on the dendrogram (Fig. 1A). Two samples from WGA_A group having 94% profiles similarity also formed such a cluster. Other samples form SH- and WGA-based datasets formed mixed clusters. For example, a sample from the WGA_B group formed a united cluster with a sample from the SH_A group and two samples from the SH_B group (similarity 94%), thus indicating that the samples from two different locations were grouped together incorrectly. One more cluster consisted of two samples from SH_A and SH_B groups with 96% of similarity.

Bottom Line: Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science.Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted.Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases.

View Article: PubMed Central - PubMed

Affiliation: School of Biological Sciences, Flinders University, Adelaide, Australia.

ABSTRACT
Here we assess the ability of random whole metagenomic sequencing approaches to discriminate between similar soils from two geographically distinct urban sites for application in forensic science. Repeat samples from two parklands in residential areas separated by approximately 3 km were collected and the DNA was extracted. Shotgun, whole genome amplification (WGA) and single arbitrarily primed DNA amplification (AP-PCR) based sequencing techniques were then used to generate soil metagenomic profiles. Full and subsampled metagenomic datasets were then annotated against M5NR/M5RNA (taxonomic classification) and SEED Subsystems (metabolic classification) databases. Further comparative analyses were performed using a number of statistical tools including: hierarchical agglomerative clustering (CLUSTER); similarity profile analysis (SIMPROF); non-metric multidimensional scaling (NMDS); and canonical analysis of principal coordinates (CAP) at all major levels of taxonomic and metabolic classification. Our data showed that shotgun and WGA-based approaches generated highly similar metagenomic profiles for the soil samples such that the soil samples could not be distinguished accurately. An AP-PCR based approach was shown to be successful at obtaining reproducible site-specific metagenomic DNA profiles, which in turn were employed for successful discrimination of visually similar soil samples collected from two different locations.

No MeSH data available.


Related in: MedlinePlus