Characterizing Kiwifruit Carbohydrate Utilization in vitro and its Consequences for Human Faecal Microbiota
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- 作者：Douglas I. Rosendale ; Paul A. Blatchford ; Ian M. Sims ; Shanthi G. Parkar ; Susan M. Carnachan ; Duncan Hedderley ; Juliet Ansell
- 刊名：Journal of Proteome Research
- 出版年：2012
- 出版时间：December 7, 2012
- 年：2012
- 卷：11
- 期：12
- 页码：5863-5875
- 全文大小：442K
- 年卷期：v.11,no.12(December 7, 2012)
- ISSN：1535-3907
文摘
It is well accepted that our gut bacteria have coevolved with us in relation to our genetics, diet and lifestyle and are integrated metabolically with us to affect our gut health adversely or beneficially. 鈥淲ho is there鈥?may vary quite widely between individuals, as might 鈥渉ow they do it鈥? but 鈥渨hat they make鈥?may be less variable. Many different individual species of bacteria can perform the same saccharolytic functions and so the availability of substrate (host or diet-derived) along with the degradative enzymes they possess may be key drivers of gut ecology. In this case study, we discuss detailed microbial ecology and metabolism analysis for three individuals following 48 h of in vitro faecal fermentation, using green kiwifruit as the substrate. In parallel, we have analyzed the chemical changes to the kiwifruit carbohydrates present in the fermenta to close the circle on substrate usage/degradative enzymes possessed/microbes present/microbial byproducts produced. In the absence of host carbohydrate, we see that kiwifruit carbohydrates were differentially utilized to drive microbial diversity, yet resulted in similar byproduct production. The starting ecology of each individual influenced the quantitative and qualitative microbial changes; but not necessarily the metabolic byproduct production. Thus, we propose that it is the consistent functional changes that are relevant for assessment of gut health benefits of any food. We recommend that in this era of large scale genotype/鈥搊mics studies that hypothesis-driven, bottom-up research is best placed to interpret metagenomic data in parallel with functional, phenotypic data.