Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection
<p>Abstract</p> <p>Background</p> <p>Enriching environmental samples to increase the probability of detection has been standard practice throughout the history of microbiology. However, by its very nature, the process of enrichment creates a biased sample that may have...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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BMC
2012-07-01
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| Series: | BMC Research Notes |
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| Online Access: | http://www.biomedcentral.com/1756-0500/5/378 |
| _version_ | 1819037878937714688 |
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| author | Pettengill James B McAvoy Eugene White James R Allard Marc Brown Eric Ottesen Andrea |
| author_facet | Pettengill James B McAvoy Eugene White James R Allard Marc Brown Eric Ottesen Andrea |
| author_sort | Pettengill James B |
| collection | DOAJ |
| description | <p>Abstract</p> <p>Background</p> <p>Enriching environmental samples to increase the probability of detection has been standard practice throughout the history of microbiology. However, by its very nature, the process of enrichment creates a biased sample that may have unintended consequences for surveillance or resolving a pathogenic outbreak. With the advent of next-generation sequencing and metagenomic approaches, the possibility now exists to quantify enrichment bias at an unprecedented taxonomic breadth.</p> <p>Findings</p> <p>We investigated differences in taxonomic profiles of three enriched and unenriched tomato phyllosphere samples taken from three different tomato fields (n = 18). 16S rRNA gene meteganomes were created for each of the 18 samples using 454/Roche’s pyrosequencing platform, resulting in a total of 165,259 sequences. Significantly different taxonomic profiles and abundances at a number of taxonomic levels were observed between the two treatments. Although as many as 28 putative <it>Salmonella</it> sequences were detected in enriched samples, there was no significant difference in the abundance of <it>Salmonella</it> between enriched and unenriched treatments.</p> <p>Conclusions</p> <p>Our results illustrate that the process of enriching greatly alters the taxonomic profile of an environmental sample beyond that of the target organism. We also found evidence suggesting that enrichment may not increase the probability of detecting a target. In conclusion, our results further emphasize the need to develop metagenomics as a validated culture independent method for pathogen detection.</p> |
| first_indexed | 2024-12-21T08:28:25Z |
| format | Article |
| id | doaj.art-4c5f64374cd14eac80f05c792d591fa8 |
| institution | Directory Open Access Journal |
| issn | 1756-0500 |
| language | English |
| last_indexed | 2024-12-21T08:28:25Z |
| publishDate | 2012-07-01 |
| publisher | BMC |
| record_format | Article |
| series | BMC Research Notes |
| spelling | doaj.art-4c5f64374cd14eac80f05c792d591fa82022-12-21T19:10:16ZengBMCBMC Research Notes1756-05002012-07-015137810.1186/1756-0500-5-378Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detectionPettengill James BMcAvoy EugeneWhite James RAllard MarcBrown EricOttesen Andrea<p>Abstract</p> <p>Background</p> <p>Enriching environmental samples to increase the probability of detection has been standard practice throughout the history of microbiology. However, by its very nature, the process of enrichment creates a biased sample that may have unintended consequences for surveillance or resolving a pathogenic outbreak. With the advent of next-generation sequencing and metagenomic approaches, the possibility now exists to quantify enrichment bias at an unprecedented taxonomic breadth.</p> <p>Findings</p> <p>We investigated differences in taxonomic profiles of three enriched and unenriched tomato phyllosphere samples taken from three different tomato fields (n = 18). 16S rRNA gene meteganomes were created for each of the 18 samples using 454/Roche’s pyrosequencing platform, resulting in a total of 165,259 sequences. Significantly different taxonomic profiles and abundances at a number of taxonomic levels were observed between the two treatments. Although as many as 28 putative <it>Salmonella</it> sequences were detected in enriched samples, there was no significant difference in the abundance of <it>Salmonella</it> between enriched and unenriched treatments.</p> <p>Conclusions</p> <p>Our results illustrate that the process of enriching greatly alters the taxonomic profile of an environmental sample beyond that of the target organism. We also found evidence suggesting that enrichment may not increase the probability of detecting a target. In conclusion, our results further emphasize the need to develop metagenomics as a validated culture independent method for pathogen detection.</p>http://www.biomedcentral.com/1756-0500/5/378Enrichment biasMetagenomicsPathogenTaxonomy |
| spellingShingle | Pettengill James B McAvoy Eugene White James R Allard Marc Brown Eric Ottesen Andrea Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection BMC Research Notes Enrichment bias Metagenomics Pathogen Taxonomy |
| title | Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| title_full | Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| title_fullStr | Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| title_full_unstemmed | Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| title_short | Using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| title_sort | using metagenomic analyses to estimate the consequences of enrichment bias for pathogen detection |
| topic | Enrichment bias Metagenomics Pathogen Taxonomy |
| url | http://www.biomedcentral.com/1756-0500/5/378 |
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