|
1
|
Kilianski A, Carcel P, Yao S, Roth P, Schulte J, Donarum GB, Fochler ET, Hill JM, Liem AT, Wiley MR, Ladner JT, Pfeffer BP, Elliot O, Petrosov A, Jima DD, Vallard TG, Melendrez MC, Skowronski E, Quan PL, Lipkin WI, Gibbons HS, Hirschberg DL, Palacios GF, Rosenzweig CN. Pathosphere.org: pathogen detection and characterization through a web-based, open source informatics platform. BMC Bioinformatics 2015; 16:416. [PMID: 26714571 PMCID: PMC4696252 DOI: 10.1186/s12859-015-0840-5] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2015] [Accepted: 12/08/2015] [Indexed: 01/15/2023] Open
Abstract
BACKGROUND The detection of pathogens in complex sample backgrounds has been revolutionized by wide access to next-generation sequencing (NGS) platforms. However, analytical methods to support NGS platforms are not as uniformly available. Pathosphere (found at Pathosphere.org) is a cloud - based open - sourced community tool that allows for communication, collaboration and sharing of NGS analytical tools and data amongst scientists working in academia, industry and government. The architecture allows for users to upload data and run available bioinformatics pipelines without the need for onsite processing hardware or technical support. RESULTS The pathogen detection capabilities hosted on Pathosphere were tested by analyzing pathogen-containing samples sequenced by NGS with both spiked human samples as well as human and zoonotic host backgrounds. Pathosphere analytical pipelines developed by Edgewood Chemical Biological Center (ECBC) identified spiked pathogens within a common sample analyzed by 454, Ion Torrent, and Illumina sequencing platforms. ECBC pipelines also correctly identified pathogens in human samples containing arenavirus in addition to animal samples containing flavivirus and coronavirus. These analytical methods were limited in the detection of sequences with limited homology to previous annotations within NCBI databases, such as parvovirus. Utilizing the pipeline-hosting adaptability of Pathosphere, the analytical suite was supplemented by analytical pipelines designed by the United States Army Medical Research Insititute of Infectious Diseases and Walter Reed Army Institute of Research (USAMRIID-WRAIR). These pipelines were implemented and detected parvovirus sequence in the sample that the ECBC iterative analysis previously failed to identify. CONCLUSIONS By accurately detecting pathogens in a variety of samples, this work demonstrates the utility of Pathosphere and provides a platform for utilizing, modifying and creating pipelines for a variety of NGS technologies developed to detect pathogens in complex sample backgrounds. These results serve as an exhibition for the existing pipelines and web-based interface of Pathosphere as well as the plug-in adaptability that allows for integration of newer NGS analytical software as it becomes available.
Collapse
Affiliation(s)
- Andy Kilianski
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA.
| | | | - Shijie Yao
- OptiMetrics, Inc, Abingdon, MD, USA. .,Joint Genome Institute, Department of Energy, LBNL, Berkley, CA, USA.
| | - Pierce Roth
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA. .,OptiMetrics, Inc, Abingdon, MD, USA.
| | | | | | | | - Jessica M Hill
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA. .,OptiMetrics, Inc, Abingdon, MD, USA.
| | - Alvin T Liem
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA. .,OptiMetrics, Inc, Abingdon, MD, USA.
| | - Michael R Wiley
- Center for Genome Sciences, United States Medical Research Institute of Infectious Diseases, Ft. Detrick, Frederick, MD, USA.
| | - Jason T Ladner
- Center for Genome Sciences, United States Medical Research Institute of Infectious Diseases, Ft. Detrick, Frederick, MD, USA.
| | - Bradley P Pfeffer
- Center for Genome Sciences, United States Medical Research Institute of Infectious Diseases, Ft. Detrick, Frederick, MD, USA.
| | - Oliver Elliot
- Department of Biomedical Informatics, Columbia University, New York, NY, USA.
| | - Alexandra Petrosov
- The Center for Infection and Immunity, Columbia University, New York, NY, USA.
| | - Dereje D Jima
- Walter Reed Army Institute of Research, Viral Diseases Branch, Silver Spring, MD, USA.
| | - Tyghe G Vallard
- Walter Reed Army Institute of Research, Viral Diseases Branch, Silver Spring, MD, USA.
| | - Melanie C Melendrez
- Walter Reed Army Institute of Research, Viral Diseases Branch, Silver Spring, MD, USA.
| | | | - Phenix-Lan Quan
- The Center for Infection and Immunity, Columbia University, New York, NY, USA.
| | - W Ian Lipkin
- The Center for Infection and Immunity, Columbia University, New York, NY, USA.
| | - Henry S Gibbons
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA.
| | - David L Hirschberg
- The Center for Infection and Immunity, Columbia University, New York, NY, USA. .,Department of Interdisciplinary Arts and Sciences, University of Washington Tacoma, Tacoma, WA, USA.
| | - Gustavo F Palacios
- Center for Genome Sciences, United States Medical Research Institute of Infectious Diseases, Ft. Detrick, Frederick, MD, USA.
| | - C Nicole Rosenzweig
- Biosciences Division, Edgewood Chemical and Biological Center, 5183 Blackhawk Rd, Aberdeen Proving Ground, Edgewood, MD, 21010, USA.
| |
Collapse
|
|
2
|
Inouye M, Dashnow H, Raven LA, Schultz MB, Pope BJ, Tomita T, Zobel J, Holt KE. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med 2014. [PMID: 25422674 DOI: 10.1186/s13073–014–0090–6] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022] Open
Abstract
Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data. Source code is available from http://katholt.github.io/srst2/.
Collapse
Affiliation(s)
- Michael Inouye
- Medical Systems Biology, Department of Pathology, The University of Melbourne, Parkville, Victoria Australia ; Department of Microbiology and Immunology, The University of Melbourne, Parkville, Victoria Australia
| | - Harriet Dashnow
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia ; Victorian Life Sciences Computation Initiative, The University of Melbourne, 187 Grattan Street Carlton, Melbourne, Victoria Australia
| | - Lesley-Ann Raven
- Medical Systems Biology, Department of Pathology, The University of Melbourne, Parkville, Victoria Australia
| | - Mark B Schultz
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia
| | - Bernard J Pope
- Victorian Life Sciences Computation Initiative, The University of Melbourne, 187 Grattan Street Carlton, Melbourne, Victoria Australia ; Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria Australia
| | - Takehiro Tomita
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, Victoria Australia ; Microbiological Diagnostic Unit, The University of Melbourne, Parkville, Victoria Australia
| | - Justin Zobel
- Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria Australia
| | - Kathryn E Holt
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia
| |
Collapse
|
|
3
|
Inouye M, Dashnow H, Raven LA, Schultz MB, Pope BJ, Tomita T, Zobel J, Holt KE. SRST2: Rapid genomic surveillance for public health and hospital microbiology labs. Genome Med 2014; 6:90. [PMID: 25422674 PMCID: PMC4237778 DOI: 10.1186/s13073-014-0090-6] [Citation(s) in RCA: 719] [Impact Index Per Article: 71.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2014] [Accepted: 10/16/2014] [Indexed: 01/06/2023] Open
Abstract
Rapid molecular typing of bacterial pathogens is critical for public health epidemiology, surveillance and infection control, yet routine use of whole genome sequencing (WGS) for these purposes poses significant challenges. Here we present SRST2, a read mapping-based tool for fast and accurate detection of genes, alleles and multi-locus sequence types (MLST) from WGS data. Using >900 genomes from common pathogens, we show SRST2 is highly accurate and outperforms assembly-based methods in terms of both gene detection and allele assignment. We include validation of SRST2 within a public health laboratory, and demonstrate its use for microbial genome surveillance in the hospital setting. In the face of rising threats of antimicrobial resistance and emerging virulence among bacterial pathogens, SRST2 represents a powerful tool for rapidly extracting clinically useful information from raw WGS data. Source code is available from http://katholt.github.io/srst2/.
Collapse
Affiliation(s)
- Michael Inouye
- Medical Systems Biology, Department of Pathology, The University of Melbourne, Parkville, Victoria Australia ; Department of Microbiology and Immunology, The University of Melbourne, Parkville, Victoria Australia
| | - Harriet Dashnow
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia ; Victorian Life Sciences Computation Initiative, The University of Melbourne, 187 Grattan Street Carlton, Melbourne, Victoria Australia
| | - Lesley-Ann Raven
- Medical Systems Biology, Department of Pathology, The University of Melbourne, Parkville, Victoria Australia
| | - Mark B Schultz
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia
| | - Bernard J Pope
- Victorian Life Sciences Computation Initiative, The University of Melbourne, 187 Grattan Street Carlton, Melbourne, Victoria Australia ; Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria Australia
| | - Takehiro Tomita
- Department of Microbiology and Immunology, The University of Melbourne, Parkville, Victoria Australia ; Microbiological Diagnostic Unit, The University of Melbourne, Parkville, Victoria Australia
| | - Justin Zobel
- Department of Computing and Information Systems, The University of Melbourne, Parkville, Victoria Australia
| | - Kathryn E Holt
- Department of Biochemistry and Molecular Biology, Bio21 Molecular Science and Biotechnology Institute, University of Melbourne, Parkville, Victoria 3010 Australia
| |
Collapse
|