Consuming polyphenol-rich fruits and vegetables, including blueberries, is associated with beneficial health outcomes. Interest in enhancing polyphenol intakes via dietary supplements has grown, though differences in fruit versus supplement matrix on gut microbiota and ultimate phenolic metabolism to bioactive metabolites are unknown. To evaluate this, 5-month-old, ovariectomized, Sprague-Dawley rats were gavaged for 90 d with a purified extract of blueberry polyphenols (0, 50, 250, or 1000 mg total polyphenols per kg bw per d) or lyophilized blueberries (50 mg total polyphenols per kg bw per d, equivalent to 150 g fresh blueberries per day in humans). Urine, feces, and tissues were assessed for gut microbiota and phenolic metabolism. Significant dose- and food matrix-dependent effects were observed at all endpoints measured. Gut microbial populations showed increased diversity at moderate doses but decreased diversity at high doses. Urinary phenolic metabolites were primarily observed as microbially derived metabolites and underwent extensive host xenobiotic phase II metabolism. Thus, blueberry polyphenols in fruit and supplements induce differences in gut microbial communities and phenolic metabolism, which may alter intended health effects.

Prunes have health benefits, particularly in postmenopausal women. It is likely that the gut microbiome mediates some of these effects, but its exact role remains to be elucidated. This study aims to characterize the effect of prune supplementation on the gut microbiome of postmenopausal women. The fecal microbiome of 143 postmenopausal women ages 55–75 who met the compliance criteria in a randomized controlled trial of a 12-month dietary intervention in one of three treatment groups – no prunes (n = 52), 50 g prunes per day (n = 54), or 100 g prunes per day (n = 37) – was characterized at baseline and at the 12-month endpoint using 16S rRNA gene sequencing and QIIME2. Additional outcomes included assessment of select urinary phenolic metabolites and inflammatory markers. After 12 months, microbiomes of women consuming 50 g prunes had decreased evenness in bacteria taxa (Pielou's Evenness, Kruskal–Wallis p = 0.026). Beta diversity comparisons indicated significant differences in microbiomes among prune treatments (Bray–Curtis PERMANOVA, p = 0.005), and the effect was different at each prune dose (p = 0.057). Prunes enriched some bacterial taxa such as the family Lachnospiraceae (LEfSe LDA = 4.5). Some taxa correlated with urinary phenolic metabolites and inflammatory markers. Blautia negatively correlated with total urinary phenolics (r = −0.25, p = 0.035) and Lachnospiraceae UCG-001 negatively correlated with plasma concentrations of IL-1β (r = −0.29, p = 0.002). Differing gut microbiomes and correlation of some taxa with select phenolic metabolites and inflammatory markers, particularly Lachnospiraceae, after prune consumption suggest a potential mechanism mediating health effects. The microbiome differences at each dose may have implications for the use of prunes as a non-pharmacological whole food intervention for gut health.

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, process rates, and population dynamics, offering valuable insights for a wide range of research questions. Data reuse maximizes the information derived from the labor and resource-intensive SIP approaches. Yet, a review of publicly available SIP sequencing metadata showed that critical information necessary for reproducibility and reuse was often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) framework and include examples of MISIP reporting for common SIP experiments. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires 5 metadata fields—isotope, isotopolog, isotopolog label, labeling approach, and gradient position—and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data (e.g., gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension (e.g., soil). The adoption of the proposed data standard will improve the reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.

The implications of soy consumption on human health have been a subject of debate, largely due to the mixed evidence regarding its benefits and potential risks. The variability in responses to soy has been partly attributed to differences in the metabolism of soy isoflavones, compounds with structural similarities to estrogen. Approximately one-third of humans possess gut bacteria capable of converting soy isoflavone daidzein into equol, a metabolite produced exclusively by gut microbiota with significant estrogenic potency. In contrast, lab-raised rodents are efficient equol producers, except for those raised germ-free. This discrepancy raises concerns about the applicability of traditional rodent models to humans. Herein, we designed a gnotobiotic mouse model to differentiate between equol producers and non-producers by introducing synthetic bacterial communities with and without the equol-producing capacity into female and male germ-free mice. These gnotobiotic mice display equol-producing phenotypes consistent with the capacity of the gut microbiota received. Our findings confirm the model’s efficacy in mimicking human equol production capacity, offering a promising tool for future studies to explore the relationship between endogenous equol production and health outcomes like cardiometabolic health and fertility. This approach aims to refine dietary guidelines by considering individual microbiome differences.

Metagenomic sequencing has revolutionized our ability to capture the vast genetic diversity of microbiomes. The technique provides an especially detailed characterization of intraspecific diversity, and a growing number of studies are using that information to investigate bacterial evolution in nature. Here, we review how these studies operationally define evolution, the sampling approaches and metrics used, and the interpretation of the observed evolutionary signatures. Current studies address three main themes: (1) the mechanisms that generate genetic diversity, (2) the spatiotemporal structure of that diversity, and (3) the evolutionary processes that determine its fate. While metagenomics provides enormous potential to investigate in situ evolution, the approach also introduces new questions, including whether populations defined by read mapping are meaningful proxies for biological units of evolution. Addressing these questions will facilitate investigation of the role of evolution relative to ecological shifts in shaping a microbiome's response to environmental change.

DNA/RNA-stable isotope probing (SIP) is a powerful tool to link in situ microbial activity to sequencing data. Every SIP dataset captures distinct information about microbial community metabolism, kinetics, and population dynamics, offering novel insights according to diverse research questions. Data re-use maximizes the information available from the time and resource intensive SIP experimental approach. Yet, a review of publicly available SIP sequencing metadata reveals that critical information necessary for reproducibility and reuse is often missing. Here, we outline the Minimum Information for any Stable Isotope Probing Sequence (MISIP) according to the Minimum Information for any (x) Sequence (MIxS) data standard framework and include examples of MISIP reporting for common SIP approaches. Our objectives are to expand the capacity of MIxS to accommodate SIP-specific metadata and guide SIP users in metadata collection when planning and reporting an experiment. The MISIP standard requires five metadata fields: isotope, isotopolog, isotopolog label and approach, and gradient position, and recommends several fields that represent best practices in acquiring and reporting SIP sequencing data ( ex. gradient density and nucleic acid amount). The standard is intended to be used in concert with other MIxS checklists to comprehensively describe the origin of sequence data, such as for marker genes (MISIP-MIMARKS) or metagenomes (MISIP-MIMS), in combination with metadata required by an environmental extension ( e.g. , soil). The adoption of the proposed data standard will assure the reproducibility and reuse of any sequence derived from a SIP experiment and, by extension, deepen understanding of in situ biogeochemical processes and microbial ecology.