June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Diagnosing corneal infections in formalin fixed specimens using next generation sequencing
Author Affiliations & Notes
  • Charles Eberhart
    Pathology and Ophthalmology, Wilmer Eye Institute, Timonium, Maryland, United States
  • Zhigang Li
    Ophthalmology, First Affiliated Hospital, Zhengzhou University, Zhengzhou , China
    Pathology and Ophthalmology, Wilmer Eye Institute, Timonium, Maryland, United States
  • Florian P Breitwieser
    Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States
  • Jennifer Lu
    Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States
    Biomedical Engineering, Johns Hopkins, Baltimore, Maryland, United States
  • Albert S Jun
    Wilmer Eye Institute, Baltimore, Maryland, United States
  • Steven L Salzberg
    Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University, Baltimore, Maryland, United States
    Biomedical Engineering, Johns Hopkins, Baltimore, Maryland, United States
  • Footnotes
    Commercial Relationships   Charles Eberhart, None; Zhigang Li, None; Florian P Breitwieser, None; Jennifer Lu, None; Albert Jun, None; Steven Salzberg, None
  • Footnotes
    Support  Research to Prevent Blindness
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 5618. doi:
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    • Get Citation

      Charles Eberhart, Zhigang Li, Florian P Breitwieser, Jennifer Lu, Albert S Jun, Steven L Salzberg; Diagnosing corneal infections in formalin fixed specimens using next generation sequencing. Invest. Ophthalmol. Vis. Sci. 2017;58(8):5618.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Identification of some infectious agents in the cornea can be difficult and time consuming. The dramatically increased speed and reduced cost of next generation sequencing, coupled with new bioinformatics techniques, has made it possible to directly identify and classify non-human DNA and RNA sequences in complex specimens, including formalin fixed tissues. This study tests the ability of next-generation sequencing, combined with computational analysis, to identify a broad range of organisms causing infectious keratitis.

Methods : In this retrospective case study, DNA extracted from 16 cases of infectious keratitis, as well as 4 control corneas with no known infection, was sequenced to detect pathogenic and non-pathogenic microbes. All specimens were formalin fixed, routinely processed and paraffin embedded tissues which had undergone standard microscopic analysis in the ophthalmic pathology laboratory. Infectious cases were also analyzed in the microbiology laboratory using culture, polymerase chain reaction and direct staining to establish a diagnosis. Classified sequence reads were analyzed with two different metagenomics classification engines, Kraken and Centrifuge, and visualized using the Pavian software tool.

Results : Sequencing of the 20 corneal DNA specimens generated 20 million to 45 million reads per sample. The two computational strategies lead to the successful identification of the fungal, bacterial and amoebal pathogens corresponding to those diagnosed clinically in most patients, including all 4 bacterial and mycobacterial cases, 4 of 6 fungal cases, 3 of 3 Acanthamoeba cases, and 1 of 3 herpetic keratitis cases. In several cases, sequences from additional potential pathogens were also identified. The initial DNA sequencing and bioinformatics analysis took approximately three days.

Conclusions : Next generation sequencing combined with computational analysis can be used as a single test to identify a wide range of pathogens in formalin fixed corneal specimens. This technology has potential applications in clinical diagnostics, and in facilitating understanding of how commensal organisms on the ocular surface react to and modulate infections and other diseases.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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