Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples

Prakhar Vijayvargiya, Patricio R. Jeraldo, Matthew J. Thoendel, Kerryl E. Greenwood-Quaintance, Zerelda Esquer Garrigos, M. Rizwan Sohail, Nicholas Chia, Bobbi S. Pritt, Robin Patel

Research output: Contribution to journalArticle

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Abstract

Background Vector-borne pathogens are a significant public health concern worldwide. Infections with these pathogens, some of which are emerging, are likely under-recognized due to the lack of widely-available laboratory tests. There is an urgent need for further advancement in diagnostic modalities to detect new and known vector-borne pathogens. We evaluated the utility of metagenomic shotgun sequencing (MGS) as a pathogen agnostic approach for detecting vector-borne pathogens from human blood samples. Methods Residual whole blood samples from patients with known infection with Babesia microti, Borrelia hermsii, Plasmodium falciparum, Mansonella perstans, Anaplasma phagocytophilum or Ehrlichia chaffeensis were studied. Samples underwent DNA extraction, removal of human DNA, whole genome amplification, and paired-end library preparation, followed by sequencing on Illumina HiSeq 2500. Bioinformatic analysis was performed using the Livermore Metagenomics Analysis Toolkit (LMAT), Metagenomic Phylogenetic Analysis (MetaPhlAn2), Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) and Kraken 2. Results Eight samples were included in the study (2 samples each for P. falciparum and A. phagocytophilum). An average of 27.5 million read pairs was generated per sample (range, 18.3–38.8 million) prior to removal of human reads. At least one of the analytic tools was able to detect four of six organisms at the genus level, and the organism present in five of eight specimens at the species level. Mansonella and Ehrlichia species were not detected by any of the tools; however, mitochondrial cytochrome c oxidase subunit I amino acid sequence analysis suggested the presence of M. perstans genetic material. Conclusions MGS is a promising tool with the potential to evolve as a non-hypothesis driven diagnostic test to detect vector-borne pathogens, including protozoa and helminths.

Original languageEnglish (US)
Article numbere0222915
JournalPloS one
Volume14
Issue number10
DOIs
StatePublished - Jan 1 2019

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Metagenomics
Mansonella
Firearms
Pathogens
Blood
sequence analysis
Anaplasma phagocytophilum
pathogens
blood
Plasmodium falciparum
Ehrlichia chaffeensis
Babesia microti
Ehrlichia
Blood-Borne Pathogens
Borrelia
sampling
Borrelia hermsii
Helminths
DNA
Protein Sequence Analysis

ASJC Scopus subject areas

  • Biochemistry, Genetics and Molecular Biology(all)
  • Agricultural and Biological Sciences(all)
  • General

Cite this

Vijayvargiya, P., Jeraldo, P. R., Thoendel, M. J., Greenwood-Quaintance, K. E., Garrigos, Z. E., Rizwan Sohail, M., ... Patel, R. (2019). Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples. PloS one, 14(10), [e0222915]. https://doi.org/10.1371/journal.pone.0222915

Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples. / Vijayvargiya, Prakhar; Jeraldo, Patricio R.; Thoendel, Matthew J.; Greenwood-Quaintance, Kerryl E.; Garrigos, Zerelda Esquer; Rizwan Sohail, M.; Chia, Nicholas; Pritt, Bobbi S.; Patel, Robin.

In: PloS one, Vol. 14, No. 10, e0222915, 01.01.2019.

Research output: Contribution to journalArticle

Vijayvargiya, P, Jeraldo, PR, Thoendel, MJ, Greenwood-Quaintance, KE, Garrigos, ZE, Rizwan Sohail, M, Chia, N, Pritt, BS & Patel, R 2019, 'Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples', PloS one, vol. 14, no. 10, e0222915. https://doi.org/10.1371/journal.pone.0222915
Vijayvargiya P, Jeraldo PR, Thoendel MJ, Greenwood-Quaintance KE, Garrigos ZE, Rizwan Sohail M et al. Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples. PloS one. 2019 Jan 1;14(10). e0222915. https://doi.org/10.1371/journal.pone.0222915
Vijayvargiya, Prakhar ; Jeraldo, Patricio R. ; Thoendel, Matthew J. ; Greenwood-Quaintance, Kerryl E. ; Garrigos, Zerelda Esquer ; Rizwan Sohail, M. ; Chia, Nicholas ; Pritt, Bobbi S. ; Patel, Robin. / Application of metagenomic shotgun sequencing to detect vector-borne pathogens in clinical blood samples. In: PloS one. 2019 ; Vol. 14, No. 10.
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AU - Greenwood-Quaintance, Kerryl E.

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N2 - Background Vector-borne pathogens are a significant public health concern worldwide. Infections with these pathogens, some of which are emerging, are likely under-recognized due to the lack of widely-available laboratory tests. There is an urgent need for further advancement in diagnostic modalities to detect new and known vector-borne pathogens. We evaluated the utility of metagenomic shotgun sequencing (MGS) as a pathogen agnostic approach for detecting vector-borne pathogens from human blood samples. Methods Residual whole blood samples from patients with known infection with Babesia microti, Borrelia hermsii, Plasmodium falciparum, Mansonella perstans, Anaplasma phagocytophilum or Ehrlichia chaffeensis were studied. Samples underwent DNA extraction, removal of human DNA, whole genome amplification, and paired-end library preparation, followed by sequencing on Illumina HiSeq 2500. Bioinformatic analysis was performed using the Livermore Metagenomics Analysis Toolkit (LMAT), Metagenomic Phylogenetic Analysis (MetaPhlAn2), Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) and Kraken 2. Results Eight samples were included in the study (2 samples each for P. falciparum and A. phagocytophilum). An average of 27.5 million read pairs was generated per sample (range, 18.3–38.8 million) prior to removal of human reads. At least one of the analytic tools was able to detect four of six organisms at the genus level, and the organism present in five of eight specimens at the species level. Mansonella and Ehrlichia species were not detected by any of the tools; however, mitochondrial cytochrome c oxidase subunit I amino acid sequence analysis suggested the presence of M. perstans genetic material. Conclusions MGS is a promising tool with the potential to evolve as a non-hypothesis driven diagnostic test to detect vector-borne pathogens, including protozoa and helminths.

AB - Background Vector-borne pathogens are a significant public health concern worldwide. Infections with these pathogens, some of which are emerging, are likely under-recognized due to the lack of widely-available laboratory tests. There is an urgent need for further advancement in diagnostic modalities to detect new and known vector-borne pathogens. We evaluated the utility of metagenomic shotgun sequencing (MGS) as a pathogen agnostic approach for detecting vector-borne pathogens from human blood samples. Methods Residual whole blood samples from patients with known infection with Babesia microti, Borrelia hermsii, Plasmodium falciparum, Mansonella perstans, Anaplasma phagocytophilum or Ehrlichia chaffeensis were studied. Samples underwent DNA extraction, removal of human DNA, whole genome amplification, and paired-end library preparation, followed by sequencing on Illumina HiSeq 2500. Bioinformatic analysis was performed using the Livermore Metagenomics Analysis Toolkit (LMAT), Metagenomic Phylogenetic Analysis (MetaPhlAn2), Genomic Origin Through Taxonomic CHAllenge (GOTTCHA) and Kraken 2. Results Eight samples were included in the study (2 samples each for P. falciparum and A. phagocytophilum). An average of 27.5 million read pairs was generated per sample (range, 18.3–38.8 million) prior to removal of human reads. At least one of the analytic tools was able to detect four of six organisms at the genus level, and the organism present in five of eight specimens at the species level. Mansonella and Ehrlichia species were not detected by any of the tools; however, mitochondrial cytochrome c oxidase subunit I amino acid sequence analysis suggested the presence of M. perstans genetic material. Conclusions MGS is a promising tool with the potential to evolve as a non-hypothesis driven diagnostic test to detect vector-borne pathogens, including protozoa and helminths.

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