m+Medelevator.RU
← Поиск публикаций
Environmental science & technology · 2025

Synthetic Microbial Cocultivation for Targeted Production of Odd-Chain Carboxylates and Alcohols from Carbon Monoxide.

СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…

История · было → стало

Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.

Parera Olm Ivette, Benito-Vaquerizo Sara, Dubaere Charles, Martins Dos Santos Vitor A P, Suarez-Diez Maria, Sousa Diana Z

Аннотация

Microbial fermentation of syngas (CO, H2, CO2) using acetogens is a promising route for the revalorisation of one-carbon feedstocks. However, product diversification from syngas using pure cultures of these microorganisms remains a challenge. Here, we present a synthetic microbial community comprising the acetogen Acetobacterium wieringae JM, the propionigenic bacterium Anaerotignum neopropionicum and the chain elongator Clostridium kluyveri, which collectively produce odd- and even-chain carboxylic acids and higher alcohols from CO/CO2. In batch bioreactors, metabolite cross-feeding within the community enabled the production of valerate (0.61 g L-1) and pentanol (0.33 g L-1), which are rare products in CO-fermenting systems. Chemostat experiments showed a metabolic shift induced in the acetogen by the ethanol-consuming species. Furthermore, construction of the genome-scale metabolic model (GEM) of A. wieringae JM and a community model of the triculture allowed us to predict the performance of the culture in continuous (steady-state) process. Simulations using flux balance analysis predicted a feasible triculture with A. wieringae JM dominating the community, and provided insights into the effect of H2 supplementation on the product spectrum. The results of our study underscore the potential of synthetic microbial communities for syngas fermentation, with genome-scale metabolic modeling serving as a powerful tool to identify metabolic shifts and guide experimental design.

Предметные рубрики MeSH

ИП Урсолов Владлен Сергеевич

ИНН 500118482352 · ОГРНИП 314500117700049

Реквизиты и контакты