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An unbiased metagenomic search for infectious agents using monozygotic twins discordantfor chronic fatigue
University of North Carolina.
Karolinska Institutet.
Linköping University, Department of Physics, Chemistry and Biology, Bioinformatics . Linköping University, The Institute of Technology.
Karolinska Institutet.
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2011 (English)In: BMC Microbiology, ISSN 1471-2180, Vol. 11, no 2Article in journal (Refereed) Published
Abstract [en]

Background: Chronic fatigue syndrome is an idiopathic syndrome widely suspected of having an infectious orimmune etiology. We applied an unbiased metagenomic approach to try to identify known or novel infectiousagents in the serum of 45 cases with chronic fatigue syndrome or idiopathic chronic fatigue. Controls were theunaffected monozygotic co-twins of cases, and serum samples were obtained at the same place and time.Results: No novel DNA or RNA viral signatures were confidently identified. Four affected twins and no unaffectedtwins evidenced viremia with GB virus C (8.9% vs. 0%, p = 0.019), and one affected twin had previously undetectedhepatitis C viremia. An excess of GB virus C viremia in cases with chronic fatigue requires confirmation.Conclusions: Current, impairing chronic fatigue was not robustly associated with viremia detectable in serum.

Place, publisher, year, edition, pages
BMC , 2011. Vol. 11, no 2
National Category
Natural Sciences
URN: urn:nbn:se:liu:diva-65704DOI: 10.1186/1471-2180-11-2ISI: 000286331700001OAI: diva2:398441
Original Publication: Patrick F Sullivan, Tobias Allander, Fredrik Lysholm, Shan Goh, Bengt Persson, Andreas Jacks, Birgitta Evengård, Nancy L Pedersen and Björn Andersson, An unbiased metagenomic search for infectious agents using monozygotic twins discordantfor chronic fatigue, 2011, BMC Microbiology, (11), 2. Licensee: BioMed Central Available from: 2011-02-17 Created: 2011-02-17 Last updated: 2012-12-10
In thesis
1. Bioinformatic methods for characterization of viral pathogens in metagenomic samples
Open this publication in new window or tab >>Bioinformatic methods for characterization of viral pathogens in metagenomic samples
2013 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Virus infections impose a huge disease burden on humanity and new viruses are continuously found. As most studies of viral disease are limited to theinvestigation of known viruses, it is important to characterize all circulating viruses. Thus, a broad and unselective exploration of the virus flora would be the most productive development of modern virology. Fueled by the reduction in sequencing costs and the unbiased nature of shotgun sequencing, viral metagenomics has rapidly become the strategy of choice for this exploration.

This thesis mainly focuses on improving key methods used in viral metagenomics as well as the complete viral characterization of two sets of samples using these methods. The major methods developed are an efficient automated analysis pipeline for metagenomics data and two novel, more accurate, alignment algorithms for 454 sequencing data. The automated pipeline facilitates rapid, complete and effortless analysis of metagenomics samples, which in turn enables detection of potential pathogens, for instance in patient samples. The two new alignment algorithms developed cover comparisons both against nucleotide and  protein databases, while retaining the underlying 454 data representation. Furthermore, a simulator for 454 data was developed in order to evaluate these methods. This simulator is currently the fastest and most complete simulator of 454 data, which enables further development of algorithms and methods. Finally, we have successfully used these methods to fully characterize a multitude of samples, including samples collected from children suffering from severe lower respiratory tract infections as well as patients diagnosed with chronic fatigue syndrome, both of which presented in this thesis. In these studies, a complete viral characterization has revealed the presence of both expected and unexpected viral pathogens as well as many potential novel viruses.

Place, publisher, year, edition, pages
Linköping: Linköping University Electronic Press, 2013. 65 p.
Linköping Studies in Science and Technology. Dissertations, ISSN 0345-7524 ; 1489
National Category
Natural Sciences
urn:nbn:se:liu:diva-86194 (URN)978-91-7519-745-6 (ISBN)
Public defence
2013-01-25, Planck, Fysikhuset, Campus Valla, Linköpings universitet, Linköping, 10:15 (English)
Available from: 2012-12-10 Created: 2012-12-10 Last updated: 2012-12-10Bibliographically approved

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