Challenges of the Unknown: Clinical Application of Microbial Metagenomics
Availability of fast, high throughput and low cost whole genome sequencing holds great promise within public health microbiology, with applications ranging from outbreak detection and tracking transmission events to understanding the role played by microbial communities in health and disease. Within...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2015-01-01
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| Series: | International Journal of Genomics |
| Online Access: | http://dx.doi.org/10.1155/2015/292950 |
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| _version_ | 1850228720486318080 |
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| author | Graham Rose David J. Wooldridge Catherine Anscombe Edward T. Mee Raju V. Misra Saheer Gharbia |
| author_facet | Graham Rose David J. Wooldridge Catherine Anscombe Edward T. Mee Raju V. Misra Saheer Gharbia |
| author_sort | Graham Rose |
| collection | DOAJ |
| description | Availability of fast, high throughput and low cost whole genome sequencing holds great promise within public health microbiology, with applications ranging from outbreak detection and tracking transmission events to understanding the role played by microbial communities in health and disease. Within clinical metagenomics, identifying microorganisms from a complex and host enriched background remains a central computational challenge. As proof of principle, we sequenced two metagenomic samples, a known viral mixture of 25 human pathogens and an unknown complex biological model using benchtop technology. The datasets were then analysed using a bioinformatic pipeline developed around recent fast classification methods. A targeted approach was able to detect 20 of the viruses against a background of host contamination from multiple sources and bacterial contamination. An alternative untargeted identification method was highly correlated with these classifications, and over 1,600 species were identified when applied to the complex biological model, including several species captured at over 50% genome coverage. In summary, this study demonstrates the great potential of applying metagenomics within the clinical laboratory setting and that this can be achieved using infrastructure available to nondedicated sequencing centres. |
| format | Article |
| id | doaj-art-2655cc81904043f4bc3909fdc8588147 |
| institution | OA Journals |
| issn | 2314-436X 2314-4378 |
| language | English |
| publishDate | 2015-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | International Journal of Genomics |
| spelling | doaj-art-2655cc81904043f4bc3909fdc85881472025-08-20T02:04:26ZengWileyInternational Journal of Genomics2314-436X2314-43782015-01-01201510.1155/2015/292950292950Challenges of the Unknown: Clinical Application of Microbial MetagenomicsGraham Rose0David J. Wooldridge1Catherine Anscombe2Edward T. Mee3Raju V. Misra4Saheer Gharbia5Genomic Research Unit, Public Health England, Microbiology Services, 61 Colindale Avenue, London NW9 5HT, UKGenomic Research Unit, Public Health England, Microbiology Services, 61 Colindale Avenue, London NW9 5HT, UKGenomic Research Unit, Public Health England, Microbiology Services, 61 Colindale Avenue, London NW9 5HT, UKDivision of Virology, National Institute for Biological Standards and Control, Medicines and Healthcare Products Regulatory Agency, South Mimms, Hertfordshire EN6 3QG, UKGenomic Research Unit, Public Health England, Microbiology Services, 61 Colindale Avenue, London NW9 5HT, UKGenomic Research Unit, Public Health England, Microbiology Services, 61 Colindale Avenue, London NW9 5HT, UKAvailability of fast, high throughput and low cost whole genome sequencing holds great promise within public health microbiology, with applications ranging from outbreak detection and tracking transmission events to understanding the role played by microbial communities in health and disease. Within clinical metagenomics, identifying microorganisms from a complex and host enriched background remains a central computational challenge. As proof of principle, we sequenced two metagenomic samples, a known viral mixture of 25 human pathogens and an unknown complex biological model using benchtop technology. The datasets were then analysed using a bioinformatic pipeline developed around recent fast classification methods. A targeted approach was able to detect 20 of the viruses against a background of host contamination from multiple sources and bacterial contamination. An alternative untargeted identification method was highly correlated with these classifications, and over 1,600 species were identified when applied to the complex biological model, including several species captured at over 50% genome coverage. In summary, this study demonstrates the great potential of applying metagenomics within the clinical laboratory setting and that this can be achieved using infrastructure available to nondedicated sequencing centres.http://dx.doi.org/10.1155/2015/292950 |
| spellingShingle | Graham Rose David J. Wooldridge Catherine Anscombe Edward T. Mee Raju V. Misra Saheer Gharbia Challenges of the Unknown: Clinical Application of Microbial Metagenomics International Journal of Genomics |
| title | Challenges of the Unknown: Clinical Application of Microbial Metagenomics |
| title_full | Challenges of the Unknown: Clinical Application of Microbial Metagenomics |
| title_fullStr | Challenges of the Unknown: Clinical Application of Microbial Metagenomics |
| title_full_unstemmed | Challenges of the Unknown: Clinical Application of Microbial Metagenomics |
| title_short | Challenges of the Unknown: Clinical Application of Microbial Metagenomics |
| title_sort | challenges of the unknown clinical application of microbial metagenomics |
| url | http://dx.doi.org/10.1155/2015/292950 |
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