Е. В. Андреев1, Е. В. Кравченко1,a, Е. Г. Завьялова1,2, П. С. Еремин3, А. В. Рзянина1, П. А. Марков3, А. Н. Нечаев1
Ключевые слова:
МСК, секретом, кондиционированные среды, бессывороточная культура, выделение экзосом, ультрафильтрация
Категории:
Науки о жизни
, Биология
Аннотация
В исследовании представлен сравнительный анализ различных компонентов кондиционированных сред (КС), полученных с помощью мезенхимальных стволовых клеток (МСК), культивированных с использованием сыворотки и без сыворотки, который выявил существенные различия в их составе и потенциальном клиническом применении. Кондиционированная среда, содержащая сыворотку, демонстрирует значительно более высокие уровени общего белка, невезикулярной РНК, экзосом и наночастиц по сравнению с бессывороточными кондиционированными средами, что отражает вклад как секретома МСК, так и остаточных компонентов фетальной бычьей сыворотки. Фракционирование на основе ультрафильтрации (0,2 мкм-50 кДа) позволяет выделить фракцию, обогащенную экзосомами и белками, сохраняя функционально значимые компоненты секретома МСК. Эта стратегия эффективно захватывает везикулы и белки среднего размера, исключая при этом более крупные или мелкие биомолекулы, что повышает эффективность их использования для целевого анализа. Представленные данные подчеркивают необходимость подбора КС с учетом целей эксперимента и предоставляют информацию для выбора оптимальной стратегии получения секретома МСК, обеспечивающей баланс между конечным результатом, чистотой и нормативными требованиями в области исследований и терапии МСК.
Поддерживающие организации
The authors are grateful to Nikolay Lizunov and Oleg Orelovich for the help with SEMexamination of samples, Alisher Mutali for the help with TEM examination of samples andKirill Tarasov for the data visualization. The research was funded by the Joint Institute for Nuclear Research within the frameworkof projects Nanocomposite and functional track membranes 07-5-1131-2-2024/2028, Highly sen-sitive sensors operating on the principles of molecular recognition for virus detection 07-5-1131-3-2025/2029, TARDISS 05-2-1132-1-2021/2028.
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