vavilovВавиловский журнал генетики и селекцииVavilov Journal of Genetics and Breeding2500-3259Institute of Cytology and Genetics of Siberian Branch of the RAS10.18699/vjgb-24-97vavilov-4411Research ArticleСИСТЕМНАЯ КОМПЬЮТЕРНАЯ БИОЛОГИЯSYSTEMS COMPUTATIONAL BIOLOGYПрограммный модуль для оценки метаболического потенциала мутантных штаммов бактерии Corynebacterium glutamicumA software module to assess the metabolic potential of mutant strains of the bacterium Corynebacterium glutamicumhttps://orcid.org/0000-0002-5711-7539КазанцевФ. В.KazantsevF. V.

Новосибирск

Novosibirsk

kazfdr@bionet.nsc.ruТрофимоваМ. Ф.TrofimovaM. F.

Новосибирск

Novosibirsk

ХлебодароваТ. М.KhlebodarovaT. M.

Новосибирск

Novosibirsk

https://orcid.org/0000-0001-7754-8611МатушкинЮ. Г.MatushkinYu. G.

Новосибирск

Novosibirsk

https://orcid.org/0000-0003-3138-381XЛашинС. А.LashinS. A.

Новосибирск

Novosibirsk

Курчатовский геномный центр ИЦиГ СО РАН; Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наук; Новосибирский национальный исследовательский государственный университетРоссияKurchatov Genomic Center of ICG SB RAS; Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences; Novosibirsk State UniversityRussian FederationФедеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияInstitute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian FederationКурчатовский геномный центр ИЦиГ СО РАН; Федеральный исследовательский центр Институт цитологии и генетики Сибирского отделения Российской академии наукРоссияKurchatov Genomic Center of ICG SB RAS; Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of SciencesRussian Federation202425012025288897903Copyright © Казанцев Ф.В., Трофимова М.Ф., Хлебодарова Т.М., Матушкин Ю.Г., Лашин С.А., 20252025Казанцев Ф.В., Трофимова М.Ф., Хлебодарова Т.М., Матушкин Ю.Г., Лашин С.А.Kazantsev F.V., Trofimova M.F., Khlebodarova T.M., Matushkin Y.G., Lashin S.A.This work is licensed under a Creative Commons Attribution 4.0 License.https://vavilov.elpub.ru/jour/article/view/4411

Технологии производства различных соединений с применением микроорганизмов приобре­тают все большую популярность в промышленном производстве. Создание современных высокопродуктив­ных штаммов, метаболизм которых ориентирован на синтез конкретного целевого продукта, невозможно без комплексной направленной модификации генома c применением методов математического и компьютерно­го моделирования. Одним из видов бактерий, активно используемых в биотехнологическом производстве, является Corynebacterium glutamicum. Для него существует уже пять полногеномных потоковых моделей, ко­торые можно использовать для задач исследования и оптимизации метаболизма. В работе представлен про­граммный модуль развиваемого в Институте цитологии и генетики СО РАН инструмента FluxMicrobiotech, в рамках которого реализована серия вычислительных протоколов, предназначенных для массового компью­терного анализа потоковых моделей C. glutamicum на высокопроизводительных вычислительных компьюте­рах. Программный модуль реализован на языке Python с применением библиотек Pandas, cobraPy и Escher и настроен на работу по принципу «файл на вход/файл на выход». Модель, условия среды и ограничения моде­ли задаются как отдельные текстовые табличные файлы, что позволяет заготовить серию файлов для каждого из разделов, создавая базы доступных сценариев испытаний для вариаций модели. Или, наоборот, позволяет испытывать одну модель в серии разных условий культивирования. Настроены инструменты постобработки данных моделирования, обеспечивающие визуализацию сводных диаграмм и метаболических карт.

Technologies for the production of a range of compounds using microorganisms are becoming increas­ingly popular in industry. The creation of highly productive strains whose metabolism is aimed to the synthesis of a specific desired product is impossible without complex directed modifications of the genome using mathematical and computer modeling methods. One of the bacterial species actively used in biotechnological production is Co­rynebacterium glutamicum. There are already 5 whole-genome flux balance models for it, which can be used for me­tabolism research and optimization tasks. The paper presents fluxMicrobiotech, a software module developed at the Institute of Cytology and Genetics of the Siberian Branch of the Russian Academy of Sciences, which implements a se­ries of computational protocols designed for high-performance computer analysis of C. glutamicum whole-genome flux balance models. The tool is based on libraries from the opencobra community (https://opencobra.github.io) within the Python programming language (https://www.python.org), using the Pandas (https://pandas.pydata.org) and Escher (https://escher.readthedocs.io) libraries . It is configured to operate on a ‘file-in/file-out’ basis. The model, environmental conditions, and model constraints are specified as separate text table files, which allows one to pre­pare a series of files for each section, creating databases of available test scenarios for variations of the model. Or vice versa, allowing a single model to be tested under a series of different cultivation conditions. Post-processing tools for modeling data are set up, providing visualization of summary charts and metabolic maps.

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