Zhigang Li1,2, Florian P Breitwieser3, Jennifer Lu3,4, Albert S Jun5, Laura Asnaghi2, Steven L Salzberg3,4,6, Charles G Eberhart2,5. 1. Department of Ophthalmology, First Affiliated Hospital, Zhengzhou University, Zhengzhou, China. 2. Department of Pathology, Johns Hopkins University, Baltimore, Maryland, United States. 3. Center for Computational Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States. 4. Department of Biomedical Engineering, Johns Hopkins University, Baltimore, Maryland, United States. 5. Department of Ophthalmology, Johns Hopkins University, Baltimore, Maryland, United States. 6. Departments of Computer Science and Biostatistics, Johns Hopkins University, Baltimore, Maryland, United States.
Abstract
Purpose: We test the ability of next-generation sequencing, combined with computational analysis, to identify a range of organisms causing infectious keratitis. Methods: This retrospective study evaluated 16 cases of infectious keratitis and four control corneas in formalin-fixed tissues from the pathology laboratory. Infectious cases also were analyzed in the microbiology laboratory using culture, polymerase chain reaction, and direct staining. Classified sequence reads were analyzed with two different metagenomics classification engines, Kraken and Centrifuge, and visualized using the Pavian software tool. Results: Sequencing generated 20 to 46 million reads per sample. On average, 96% of the reads were classified as human, 0.3% corresponded to known vectors or contaminant sequences, 1.7% represented microbial sequences, and 2.4% could not be classified. The two computational strategies successfully identified the fungal, bacterial, and amoebal pathogens in most patients, including all four bacterial and mycobacterial cases, five of six fungal cases, three of three Acanthamoeba cases, and one of three herpetic keratitis cases. In several cases, additional potential pathogens also were identified. In one case with cytomegalovirus identified by Kraken and Centrifuge, the virus was confirmed by direct testing, while two where Staphylococcus aureus or cytomegalovirus were identified by Centrifuge but not Kraken could not be confirmed. Confirmation was not attempted for an additional three potential pathogens identified by Kraken and 11 identified by Centrifuge. Conclusions: Next generation sequencing combined with computational analysis can identify a wide range of pathogens in formalin-fixed corneal specimens, with potential applications in clinical diagnostics and research.
Purpose: We test the ability of next-generation sequencing, combined with computational analysis, to identify a range of organisms causing infectious keratitis. Methods: This retrospective study evaluated 16 cases of infectious keratitis and four control corneas in formalin-fixed tissues from the pathology laboratory. Infectious cases also were analyzed in the microbiology laboratory using culture, polymerase chain reaction, and direct staining. Classified sequence reads were analyzed with two different metagenomics classification engines, Kraken and Centrifuge, and visualized using the Pavian software tool. Results: Sequencing generated 20 to 46 million reads per sample. On average, 96% of the reads were classified as human, 0.3% corresponded to known vectors or contaminant sequences, 1.7% represented microbial sequences, and 2.4% could not be classified. The two computational strategies successfully identified the fungal, bacterial, and amoebal pathogens in most patients, including all four bacterial and mycobacterial cases, five of six fungal cases, three of three Acanthamoeba cases, and one of three herpetic keratitis cases. In several cases, additional potential pathogens also were identified. In one case with cytomegalovirus identified by Kraken and Centrifuge, the virus was confirmed by direct testing, while two where Staphylococcus aureus or cytomegalovirus were identified by Centrifuge but not Kraken could not be confirmed. Confirmation was not attempted for an additional three potential pathogens identified by Kraken and 11 identified by Centrifuge. Conclusions: Next generation sequencing combined with computational analysis can identify a wide range of pathogens in formalin-fixed corneal specimens, with potential applications in clinical diagnostics and research.
Authors: Albert J Eid; Elie F Berbari; Irene G Sia; Nancy L Wengenack; Douglas R Osmon; Raymund R Razonable Journal: Clin Infect Dis Date: 2007-08-13 Impact factor: 9.079
Authors: Cristina Aurrecoechea; Ana Barreto; John Brestelli; Brian P Brunk; Shon Cade; Ryan Doherty; Steve Fischer; Bindu Gajria; Xin Gao; Alan Gingle; Greg Grant; Omar S Harb; Mark Heiges; Sufen Hu; John Iodice; Jessica C Kissinger; Eileen T Kraemer; Wei Li; Deborah F Pinney; Brian Pitts; David S Roos; Ganesh Srinivasamoorthy; Christian J Stoeckert; Haiming Wang; Susanne Warrenfeltz Journal: Nucleic Acids Res Date: 2012-11-21 Impact factor: 16.971
Authors: Thuy Doan; Michael R Wilson; Emily D Crawford; Eric D Chow; Lillian M Khan; Kristeene A Knopp; Brian D O'Donovan; Dongxiang Xia; Jill K Hacker; Jay M Stewart; John A Gonzales; Nisha R Acharya; Joseph L DeRisi Journal: Genome Med Date: 2016-08-25 Impact factor: 11.117
Authors: Paul A Kitts; Deanna M Church; Françoise Thibaud-Nissen; Jinna Choi; Vichet Hem; Victor Sapojnikov; Robert G Smith; Tatiana Tatusova; Charlie Xiang; Andrey Zherikov; Michael DiCuccio; Terence D Murphy; Kim D Pruitt; Avi Kimchi Journal: Nucleic Acids Res Date: 2015-11-17 Impact factor: 16.971
Authors: Lawson Ung; Paulo J M Bispo; Swapna S Shanbhag; Michael S Gilmore; James Chodosh Journal: Surv Ophthalmol Date: 2018-12-24 Impact factor: 6.048
Authors: Darren S J Ting; Bhavesh P Gopal; Rashmi Deshmukh; Gerami D Seitzman; Dalia G Said; Harminder S Dua Journal: Ocul Surf Date: 2021-11-13 Impact factor: 5.033
Authors: Mihail Zemba; Otilia-Maria Dumitrescu; Andreea-Elena Dimirache; Daniel Constantin Branisteanu; Florian Balta; Marian Burcea; Andreea Dana Moraru; Sinziana Gradinaru Journal: Exp Ther Med Date: 2021-12-13 Impact factor: 2.447