Metagenomic Analysis of Cerebrospinal Fluid from Patients with Multiple Sclerosis
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.
KeywordsCerebrospinal fluid Idiopathic inflammatory demyelinating disorder Metagenomics Multiple sclerosis Next-generation sequencing
This study was supported by grants from the Foundation for Polish Science – 67/UD/SKILLS/2014 and the Polish National Science Center – N/N401/646940.
Conflicts of Interest
The authors declare no conflicts of interest in relation to this article.
- FASTX-Toolkit (2016) FASTQ/A short-reads pre-processing tools. http://hannonlab.cshl.edu/fastx_toolkit/index.html. Accessed on 11 April 2016
- 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
- Martin M (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. 17(1); doi: 10.14806/ej.17.1.200Google Scholar
- 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
- 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
- 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
- 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