Metagenomic Analysis of Cerebrospinal Fluid from Patients with Multiple Sclerosis

  • Karol Perlejewski
  • Iwona Bukowska-Ośko
  • Shota Nakamura
  • Daisuke Motooka
  • Tomasz Stokowy
  • Rafał Płoski
  • Małgorzata Rydzanicz
  • Beata Zakrzewska-Pniewska
  • Aleksandra Podlecka-Piętowska
  • Monika Nojszewska
  • Anna Gogol
  • Kamila Caraballo Cortés
  • Urszula Demkow
  • Adam Stępień
  • Tomasz Laskus
  • Marek Radkowski

Abstract

Multiple sclerosis (MS) is a chronic inflammatory demyelinating disease of central nervous system of unknown etiology. However, some infectious agents have been suggested to play a significant role in its pathogenesis. Next-generation sequencing (NGS) and metagenomics can be employed to characterize microbiome of MS patients and to identify potential causative pathogens. In this study, 12 patients with idiopathic inflammatory demyelinating disorders (IIDD) of the central nervous system were studied: one patient had clinically isolated syndrome, one patient had recurrent optic neuritis, and ten patients had multiple sclerosis (MS). In addition, there was one patient with other non-inflammatory neurological disease. Cerebrospinal fluid (CSF) was sampled from all patients. RNA was extracted from CSF and subjected to a single-primer isothermal amplification followed by NGS and comprehensive data analysis. Altogether 441,608,474 reads were obtained and mapped using blastn. In a CSF sample from the patient with clinically isolated syndrome, 11 varicella-zoster virus reads were found. Other than that similar bacterial, fungal, parasitic, and protozoan reads were identified in all samples, indicating a common presence of contamination in metagenomics. In conclusion, we identified varicella zoster virus sequences in one out of the 12 patients with IIDD, which suggests that this virus could be occasionally related to the MS pathogenesis. A widespread bacterial contamination seems inherent to NGS and complicates the interpretation of results.

Keywords

Cerebrospinal fluid Idiopathic inflammatory demyelinating disorder Metagenomics Multiple sclerosis Next-generation sequencing 

References

  1. Ascherio A, Munger KL (2007) Environmental risk factors for multiple sclerosis. Part II: Noninfectious factors. Ann Neurol 61(6):504–513CrossRefPubMedGoogle Scholar
  2. Benito-Leon J, Pisa D, Alonso R, Calleja P, Diaz-Sanchez M, Carrasco L (2010) Association between multiple sclerosis and Candida species: evidence from a case-control study. Eur J Clin Microbiol Infect Dis 29(9):1139–1145CrossRefPubMedGoogle Scholar
  3. Borkosky SS, Whitley C, Kopp-Schneider A, zur Hausen H, de Villiers EM (2012) Epstein-Barr virus stimulates torque teno virus replication: a possible relationship to multiple sclerosis. PLoS ONE 7(2):e32160. doi:10.1371/journal.pone.0032160 CrossRefPubMedPubMedCentralGoogle Scholar
  4. Brahic M (2010) Multiple sclerosis and viruses. Ann Neurol 68(1):6–8CrossRefPubMedGoogle Scholar
  5. Cantarel BL, Waubant E, Chehoud C, Kuczynski J, DeSantis TZ, Warrington J, Venkatesan A, Fraser CM, Mowry EM (2015) Gut microbiota in multiple sclerosis: possible influence of immunomodulators. J Investig Med 63(5):729–734CrossRefPubMedPubMedCentralGoogle Scholar
  6. Chomczynski P (1993) A reagent for the single-step simultaneous isolation of RNA, DNA and proteins from cell and tissue samples. BioTechniques 15:532–537PubMedGoogle Scholar
  7. FASTX-Toolkit (2016) FASTQ/A short-reads pre-processing tools. http://hannonlab.cshl.edu/fastx_toolkit/index.html. Accessed on 11 April 2016
  8. Goto N, Prins P, Nakao M, Bonnal R, Aerts J, Katayama T (2010) BioRuby: bioinformatics software for the Ruby programming language. Bioinformatics 26(20):2617–2619CrossRefPubMedPubMedCentralGoogle Scholar
  9. Hansen JJ (2015) Immune responses to intestinal microbes in inflammatory bowel diseases. Curr Allergy Asthma Rep 15(10):562. doi:10.1007/s11882-015-0562-9 CrossRefGoogle Scholar
  10. Hughes LE, Bonell S, Natt RS, Wilson C, Tiwana H, Ebringer A, Cunningham P, Chamoun V, Thompson EJ, Croker J, Vowles J (2001) Antibody responses to Acinetobacter spp. and Pseudomonas aeruginosa in multiple sclerosis: prospects for diagnosis using the myelin-acinetobacter-neurofilament antibody index. Clin Diagn Lab Immunol 8(6):1181–1188PubMedPubMedCentralGoogle Scholar
  11. Joscelyn J, Kasper LH (2014) Digesting the emerging role for the gut microbiome in central nervous system demyelination. Mult Scler 20(12):1553–1559CrossRefPubMedGoogle Scholar
  12. Kakalacheva K, Munz C, Lunemann JD (2011) Viral triggers of multiple sclerosis. Biochim Biophys Acta 1812(2):132–140CrossRefPubMedGoogle Scholar
  13. Krametter D, Niederwieser G, Berghold A, Birnbaum G, Strasser-Fuchs S, Hartung HP, Archelos JJ (2001) Chlamydia pneumoniae in multiple sclerosis: humoral immune responses in serum and cerebrospinal fluid and correlation with disease activity marker. Mult Scler 7(1):13–18CrossRefPubMedGoogle Scholar
  14. Laurence M, Hatzis C, Brash DE (2014) Common contaminants in next-generation sequencing that hinder discovery of low-abundance microbes. PLoS ONE 9(5):e97876. doi:10.1371/journal.pone.0097876 CrossRefPubMedPubMedCentralGoogle Scholar
  15. Lunter G, Goodson M (2011) Stampy: a statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res 21(6):936–939CrossRefPubMedPubMedCentralGoogle Scholar
  16. Mancuso R, Delbue S, Borghi E, Pagani E, Calvo MG, Caputo D, Granieri E, Ferrante P (2007) Increased prevalence of varicella zoster virus DNA in cerebrospinal fluid from patients with multiple sclerosis. J Med Virol 79(2):192–199CrossRefPubMedGoogle Scholar
  17. Marrie RA (2004) Environmental risk factors in multiple sclerosis aetiology. Lancet Neurol 3(12):709–718CrossRefPubMedGoogle Scholar
  18. Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. 17(1); doi: 10.14806/ej.17.1.200Google Scholar
  19. Miller RR, Montoya V, Gardy JL, Patrick DM, Tang P (2013) Metagenomics for pathogen detection in public health. Genome Med 5(9):81. doi:10.1186/gm485 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Miyake S, Kim S, Suda W, Oshima K, Nakamura M, Matsuoka T, Chihara N, Tomita A, Sato W, Kim SW, Morita H, Hattori M, Yamamura T (2015) Dysbiosis in the gut microbiota of patients with multiple sclerosis, with a striking depletion of species belonging to Clostridia XIVa and IV clusters. PLoS ONE 10(9):e0137429. doi:10.1371/journal.pone.0137429 CrossRefPubMedPubMedCentralGoogle Scholar
  21. Norrby E, Link H, Olsson JE (1974) Measles virus antibodies in multiple sclerosis. Comparison of antibody titers in cerebrospinal fluid and serum. Arch Neurol 30(4):285–292CrossRefPubMedGoogle Scholar
  22. O’Gorman C, Lucas R, Taylor B (2012) Environmental risk factors for multiple sclerosis: a review with a focus on molecular mechanisms. Int J Mol Sci 13(9):11718–11752CrossRefPubMedPubMedCentralGoogle Scholar
  23. Ordonez G, Pineda B, Garcia-Navarrete R, Sotelo J (2004) Brief presence of varicella-zoster vral DNA in mononuclear cells during relapses of multiple sclerosis. Arch Neurol 61(4):529–532CrossRefPubMedGoogle Scholar
  24. Padmanabhan R, Mishra AK, Raoult D, Fournier PE (2013) Genomics and metagenomics in medical microbiology. J Microbiol Methods 95(3):415–424CrossRefPubMedGoogle Scholar
  25. Pender MP, Burrows SR (2014) Epstein-Barr virus and multiple sclerosis: potential opportunities for immunotherapy. Clin Transl Immunol 3(10):e27. doi:10.1038/cti.2014.25 CrossRefGoogle Scholar
  26. Perlejewski K, Popiel M, Laskus T, Nakamura S, Motooka D, Stokowy T, Lipowski D, Pollak A, Lechowicz U, Caraballo Cortés K, Stępień A, Radkowski M, Bukowska-Osko I (2015) Next-generation sequencing (NGS) in the identification of encephalitis-causing viruses: unexpected detection of human herpesvirus 1 while searching for RNA pathogens. J Virol Methods 226:1–6CrossRefPubMedGoogle Scholar
  27. Polman CH, Reingold SC, Banwell B, Clanet M, Cohen JA, Filippi M, Fujihara K, Havrdova E, Hutchinson M, Kappos L, Lublin FD, Montalban X, O’Connor P, Sandberg-Wollheim M, Thompson AJ, Waubant E, Weinshenker B, Wolinsky JS (2011) Diagnostic criteria for multiple sclerosis: 2010 revisions to the McDonald criteria. Ann Neurol 69(2):292–302CrossRefPubMedPubMedCentralGoogle Scholar
  28. Round JL, Mazmanian SK (2009) The gut microbiota shapes intestinal immune responses during health and disease. Nat Rev Immunol 9(5):313–323CrossRefPubMedPubMedCentralGoogle Scholar
  29. Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, Turner P, Parkhill J, Loman NJ, Walker AW (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87. doi:10.1186/s12915-014-0087-z CrossRefPubMedPubMedCentralGoogle Scholar
  30. Sanders VJ, Waddell AE, Felisan SL, Li X, Conrad AJ, Tourtellotte WW (1996) Herpes simplex virus in postmortem multiple sclerosis brain tissue. Arch Neurol 53(2):125–133CrossRefPubMedGoogle Scholar
  31. Sleator RD, Shortall C, Hill C (2008) Metagenomics. Lett Appl Microbiol 47(5):361–366CrossRefPubMedGoogle Scholar
  32. Sotelo J, Martinez-Palomo A, Ordonez G, Pineda B (2008) Varicella-zoster virus in cerebrospinal fluid at relapses of multiple sclerosis. Ann Neurol 63(3):303–311CrossRefPubMedGoogle Scholar
  33. Sotelo J, Ordonez G, Pineda B, Flores J (2014) The participation of varicella zoster virus in relapses of multiple sclerosis. Clin Neurol Neurosurg 119:44–48CrossRefPubMedGoogle Scholar
  34. Swanborg RH, Whittum-Hudson JA, Hudson AP (2003) Infectious agents and multiple sclerosis–are Chlamydia pneumoniae and human herpes virus 6 involved? J Neuroimmunol 136(1–2):1–8CrossRefPubMedGoogle Scholar
  35. Weiss S, Amir A, Hyde ER, Metcalf JL, Song SJ, Knight R (2014) Tracking down the sources of experimental contamination in microbiome studies. Genome Biol 15(12):564. doi:10.1186/s13059-014-0564-2 CrossRefPubMedPubMedCentralGoogle Scholar
  36. Zawada M (2012) Potential pathogens in multiple sclerosis (MS). Postepy Hig Med Dosw (Online) 66:758–770CrossRefGoogle Scholar
  37. Zivadinov R, Nasuelli D, Tommasi MA, Serafin M, Bratina A, Ukmar M, Pirko I, Johnson AJ, Furlan C, Pozzi-Mucelli RS, Monti-Bragadin L, Grop A, Zambon M, Antonello RM, Cazzato G, Zorzon M (2006) Positivity of cytomegalovirus antibodies predicts a better clinical and radiological outcome in multiple sclerosis patients. Neurol Res 28(3):262–269CrossRefPubMedGoogle Scholar

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Karol Perlejewski
    • 1
  • Iwona Bukowska-Ośko
    • 1
  • Shota Nakamura
    • 2
  • Daisuke Motooka
    • 2
  • Tomasz Stokowy
    • 3
  • Rafał Płoski
    • 4
  • Małgorzata Rydzanicz
    • 4
  • Beata Zakrzewska-Pniewska
    • 5
  • Aleksandra Podlecka-Piętowska
    • 5
  • Monika Nojszewska
    • 5
  • Anna Gogol
    • 5
  • Kamila Caraballo Cortés
    • 1
  • Urszula Demkow
    • 6
  • Adam Stępień
    • 7
  • Tomasz Laskus
    • 1
  • Marek Radkowski
    • 1
  1. 1.Department of Immunopathology of Infectious and Parasitic DiseasesWarsaw Medical UniversityWarsawPoland
  2. 2.Department of Infection Metagenomics, Genome Information Research Center, Research Institute for Microbial DiseasesOsaka UniversityOsakaJapan
  3. 3.Department of Clinical ScienceUniversity of BergenBergenNorway
  4. 4.Department of the Medical GeneticsWarsaw Medical UniversityWarsawPoland
  5. 5.Department of NeurologyWarsaw Medical UniversityWarsawPoland
  6. 6.Department of Laboratory Medicine and Clinical Immunology of Developmental AgeMedical University of WarsawWarsawPoland
  7. 7.Department of NeurologyMilitary Institute of MedicineWarsawPoland

Personalised recommendations