microbeПроблемы особо опасных инфекцийProblems of Particularly Dangerous Infections0370-10692658-719XRussian Research Anti-Plague Institute “Microbe”10.21055/0370-1069-2013-3-55-57microbe-61Research ArticleМИКРОБИОЛОГИЯMICROBIOLOGYСистемная биология Yersinia pestisSystems Biology of Yersinia pestisМотинВ. Л.MotinV. L.vlmotin@utmb.eduУниверситет штата ТехасРоссияUniversity of TexasRussian Federation201320092013035557Copyright © Мотин В.Л., 20132013Мотин В.Л.Motin V.L.Данная работа распространяется под лицензией Creative Commons Attribution 4.0.This work is licensed under a Creative Commons Attribution 4.0 License.https://journal.microbe.ru/jour/article/view/61

Разработанные в последние годы методы -омик (протеомика, геномика, транскриптомика и др.) существенно изменили подход к изучению молекулярной биологии бактериальных патогенов. В настоящее время исследования могут проводиться на уровне полного генома, что дает возможность одновременно оценивать различные компоненты (белки, нуклеиновые кислоты, метаболиты, липиды и т.д.). Эта работа требует постоянного взаимодействия специалистов по многим дисциплинам для интеграции биологии, инструментального анализа и компьютерных наук. Исследования на основе мультиомик были осуществлены при анализе системной биологии Y. pestis . Полученные обобщенные наборы данных позволили внести уточнения в аннотации геномов, выявить новые потенциальные факторы вирулентности, построить регуляторные сети и создать интерактивную компьютерную модель метаболизма.

Omics technologies developed in recent years significantly changed our approach in study molecular biology of bacterial pathogens. The research now can be conducted at a whole-genome level enabling us to simultaneously measure variable components, such as proteins, nucleic acids, metabolites, cell lipid composition, etc . This complex work requires a constant interaction of multi-disciplinary experts to integrate biology, instrumentation and computational science. A multi-omics research (transcriptomics, proteomics, metabolomics) was applied to Y. pestis -centric system biology study. Integrated omics datasets allowed to refine genome annotations, discover novel putative virulence factors, build regulatory networks, and create an interactive computational metabolic model.

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The authors declare that there are no conflicts of interest present.