Микробиом кишечника и метаболизм лекарственных соединений
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Аннотация
В курсе физиологии человека кишечник традиционно рассматривают как метаболически активный орган, деятельность которого связывают в первую очередь с продукцией многочисленных пищеварительных ферментов. Развитие технологий молекулярного анализа позволило существенно детализировать эту картину, в первую очередь за счет расшифровки метаболического потенциала кишечной микробиоты. Данные многочисленных метагеномных исследований свидетельствуют, что количество эукариотических и бактериальных клеток в организме человека сопоставимо – около 3.0х1013, при этом количество генов в метагеноме кишечника в сто раз больше, чем в геноме человека. Очевидно, что микробиота кишечника оказывает как прямое, так и опосредованное влияние на метаболизм лекарственных препаратов и ксенобиотиков, что может сказаться на их эффективности и токсичности. Обнаружено, что ксенобиотики, вводимые перорально, могут метаболизироваться кишечными микробными ферментами еще до всасывания из желудочно-кишечного тракта в кровь. Метаболические реакции, выполняемые микробиотой кишечника, значительно отличаются от метаболических реакций печени, обеспечивая модификацию лекарственных препаратов путем ацетилирования, деацетилирования, декарбоксилирования, дегидроксилирования, деметилирования, дегалогенирования и др. Несмотря на то, что метаболизм ксенобиотиков микробными ферментами кишечника до некоторой степени известен, информация о конкретной микрофлоре, опосредующей каждую метаболическую реакцию, всё ещё ограничена, в первую очередь, отсутствием адекватной модели микробного сообщества кишечника, позволяющей накапливать экспериментальные данные для построения вычислительных моделей. Сегодня в исследовании метаболизма лекарственных средств применяют микрофлюидные чипы, на которых функции различных органов и тканей, таких как печень, почки, легкие и кишечник, воспроизводятся в виде in vitro моделей в форме 2D и 3D клеточных культур. Дополнение таких систем микробным сообществом позволит максимально приблизиться к моделированию in vitro сложных биологических процессов в интересах фармакологических исследований и накопления данных для построения вычислительных моделей.
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