Документ взят из кэша поисковой машины. Адрес оригинального документа : http://mccmb.belozersky.msu.ru/2013/abstracts/abstracts/218.pdf Дата изменения: Mon Jun 3 21:20:40 2013 Дата индексирования: Thu Feb 27 21:11:59 2014 Кодировка:

Disbalance of gut microbiota during cancer treatment in pediatric patients detected using metagenomic sequencing Tyakht A.V.
Research Institute of Physico-Chemical Medicine, Moscow, Malaya Pirogovskaya 1a, at@niifhm.ru

Alexeev D.G.
Research Institute of Physico-Chemical Medicine, Moscow, Malaya Pirogovskaya 1a, alexeev@niifhm.ru

Kostryukova E.S.
Research Institute of Physico-Chemical Medicine, Moscow, Malaya Pirogovskaya 1a, el-es@yandex.ru

Roumiantsev S.A.
Federal Scientific Clinical Centre of Pediatric Hematology, Oncology and Immunology named after D. Rogachev, Moscow, Samora Mashela 1, s_roumiantsev@mail.ru

Gut microbiota is essential for human host homeostasis. When the host undergoes chemotherapy, structure of his/her microbiota can change drastically. With short-cycle high-throughput sequencer available, metagenomic sequencing allows monitoring of microbiota composition, particularly, quantitative detection of a wide spectrum of bacterial pathogens. Analysis of temporal variation of community structure during and after the treatment will allow to elucidate microbiota recovery mechanism and means for microbiota modulation in order to increase patient survival rate. During the pilot project, 16 stool samples were obtained from 4 children undergoing cancer treatment in Federal Scientific Clinical Centre of Pediatric Hematology, Oncology and Immunology named after D. Rogachev at several time points. DNA was extracted and


shotgun metagenomic sequencing was performed on SOLiD 4. Community structure was assessed by alignment of the reads to catalog of reference microbial genomes and subsequent normalization. The analysis detected significant presence of pathogenic bacteria and fungi in most samples, as well as high fraction of human DNA. Analysis of SNP signatures in reference genomes allowed to assess the hypothesis of single source for some of the pathogen strains. Diverse types of data including temporal evolution of patients microbiota and clinical data were visualized as an interactive network graph, providing a potential exploratory tool for both bioinformaticians and clinical experts. Acknowledgements: sample preparation and DNA sequencing was performed by Larin A.K. and Karpova I.Y. (Research Institute of Physico-Chemical Medicine, Genomic Centre); bioinformatic analysis was performed by the authors in part with Popenko A.S., Kovarsky B.A. and Zelenin A.S. (Research Institute of Physico-Chemical Medicine, Laboratory of Bioinformatics).