Gut microbial features and dietary fiber intake predict gut microbiota response to resistant starch supplementation.

Resistant starch (RS) consumption can have beneficial effects on metabolic health, but the response, in terms of effects on the gut microbiota and host physiology, varies between individuals. Factors predicting the response to RS are not yet established and would be useful for developing precision nutrition approaches that maximize the benefits of dietary fiber intake. We sought to identify predictors of gut microbiota response to RS supplementation. We enrolled 76 healthy adults into a 7-week crossover study with 59 individuals completing the study. Participants consumed RS type 2 (RS2), RS type 4 (RS4), and digestible starch, for 10 d each with 5-d washout periods in between. We collected fecal and saliva samples and food records during each treatment period. We performed 16S rRNA gene sequencing and measured fecal short-chain fatty acids (SCFAs), salivary amylase (AMY1) gene copy number, and salivary amylase activity (SAA). Dietary fiber intake was predictive of the relative abundance of several amplicon sequence variants (ASVs) at the end of both RS treatments. AMY1-related metrics were not predictive of response to RS. SAA was only predictive of the relative abundance of one ASV after digestible starch supplementation. Interestingly, SCFA concentrations increased the most during digestible starch supplementation. Treatment order (the order of consumption of RS2 and RS4), alpha diversity, and a subset of ASVs were predictive of SCFA changes after RS supplementation. Based on our findings, dietary fiber intake and gut microbiome composition would be informative if assessed prior to recommending RS supplementation because these data can be used to predict changes in specific ASVs and fecal SCFA concentrations. These findings lay a foundation to support the premise that using a precision nutrition approach to optimize the benefits of dietary fibers such as RS could be an effective strategy to compensate for the low consumption of dietary fiber nationwide.

Processing and storage methods affect oral and gut microbiome composition.

In microbiome studies, fecal and oral samples are stored and processed in different ways, which could affect the observed microbiome composition. In this study, we compared storage and processing methods applied to samples prior to DNA extraction to determine how each affected microbial community diversity as assessed by 16S rRNA gene sequencing. We collected dental swabs, saliva, and fecal samples from 10 individuals, with three technical replicates per condition. We assessed four methods of storing and processing fecal samples prior to DNA extraction. We also compared different fractions of thawed saliva and dental samples to fresh samples. We found that lyophilized fecal samples, fresh whole saliva samples, and the supernatant fraction of thawed dental samples had the highest levels of alpha diversity. The supernatant fraction of thawed saliva samples had the second highest evenness compared to fresh saliva samples. Then, we investigated the differences in observed community composition at the domain and phylum levels and identified the amplicon sequence variants (ASVs) that significantly differed in relative abundance between the conditions. Lyophilized fecal samples had a greater prevalence of Archaea as well as a greater ratio of Firmicutes to Bacteroidetes compared to the other conditions. Our results provide practical considerations not only for the selection of storage and processing methods but also for comparing results across studies. Differences in processing and storage methods could be a confounding factor influencing the presence, absence, or differential abundance of microbes reported in conflicting studies.

Processing and Storage Methods Affect Oral and Gut Microbiome Composition.

Across microbiome studies, fecal and oral samples are stored and processed in different ways, which could affect the observed microbiome composition. Here, we compared treatment methods, which included both storage conditions and processing methods, applied to samples prior to DNA extraction to determine how each affects microbial community diversity as assessed by 16S rRNA gene sequencing. We collected dental swab, saliva, and fecal samples from 10 individuals, with three technical replicates per treatment method. We assessed four methods of processing fecal samples prior to DNA extraction. We also compared different fractions of frozen saliva and dental samples to fresh samples. We found that lyophilized fecal samples, fresh whole saliva samples, and the supernatant fraction of thawed dental samples retained the highest levels of alpha diversity in samples. The supernatant fraction of thawed saliva samples had the second highest alpha diversity compared to fresh. Then we investigated the differences in microbes between different treatments at the domain and phylum levels as well as identified the amplicon sequence variants (ASVs) that were significantly different between the methods producing the highest alpha diversity and the other treatment methods. Lyophilized fecal samples had a greater prevalence of Archaea as well as a greater ratio of Firmicutes to Bacteroidetes compared to the other treatment methods. Our results provide practical considerations, not only for selection of processing method, but also for comparing results across studies that use these methods. Our findings also indicate differences in treatment method could be a confounding factor influencing the presence, absence, or differential abundance of microbes reported in conflicting studies.

Gut microbial features and dietary fiber intake predict gut microbiota response to resistant starch supplementation.

Resistant starch (RS) consumption can have beneficial effects on human health, but the response, in terms of effects on the gut microbiota and host physiology, varies between individuals. Factors predicting the response to RS are not yet established and would be useful for developing precision nutrition approaches that maximize the benefits of dietary fiber intake. We sought to identify predictors of gut microbiota response to RS supplementation. We enrolled 76 healthy adults into a seven-week crossover study. Participants consumed RS type 2 (RS2), RS type 4 (RS4), and a digestible starch, for ten days each with five-day washout periods in between. We collected fecal and saliva samples and food records before and during each treatment period. We performed 16S rRNA gene sequencing and measured fecal short-chain fatty acids (SCFAs), salivary amylase gene copy number, and salivary amylase activity (SAA). Dietary fiber intake was predictive of relative abundance of several amplicon sequence variants (ASVs) at the end of both RS treatments. Treatment order (the order of consumption of RS2 and RS4), alpha diversity, and a subset of ASVs were predictive of SCFA changes after RS supplementation. SAA was only predictive of the relative abundance of ASVs after digestible starch supplementation. Based on our findings, dietary fiber intake and gut microbiome composition would be informative if assessed prior to recommending RS supplementation. Using a precision nutrition approach to optimize the benefits of dietary fibers such as RS could be an effective strategy to compensate for the low consumption of dietary fiber nationwide.