1. Evaluation Summary:

    This study aims to measure interpersonal and interethnic variation in human microbiomes and metabolomes in the San Franciso, CA, area. The strength of the study is in the level of robust analysis of the microbiota. It is interesting that diet is not one of the apparent associations in this study, yet the relationship of microbiota diversity to body habitus is strong in Caucasian subjects. Overall, the key results of this work nicely confirm that there are dissimilarities in gut microbiomes related to differences in ethnicity of subjects.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #3 agreed to share their name with the authors.)

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  2. Reviewer #1 (Public Review):

    The key question that the authors were addressing was how ethnicity differentially affects the microbiota of subjects living in a particular area (in this case East Asians and Caucasians living in San Francisco that have been enrolled in an 'Inflammation, Diabetes, Ethnicity and Obesity cohort - although inflammatory disease was apparently excluded in these subjects).
    The existence of differences between different populations allows potential discrimination of the underlying factors - such as host genetics, diet, lifestyle, physiological parameters, body habitus or other environmental influences. In this case body habitus has been selected as a stratification factor between the two ethnicities. Immigration potentially allows distinction of environmental and host genetical influences.
    The strength of the study is in the level of robust analysis of the microbiotas by a very experienced group of researchers, distinguishing the microbiota differences, especially in lean subject, with analysis of associations that may be driving the differences. It is interesting that diet is not one of the apparent associations in this study, yet the relationship of microbiota diversity to body habitus is strong in Caucasian subjects. These associations cannot easily be extrapolated to causation or mechanism - a fact well recognized in the paper - but remain important observations that rationalize in vivo modeling with experimental animals or in vitro analyses of microbial interactions between different taxa simulating the context of differences in the intestinal milieu. The paper includes work showing that differences of the microbiota can be recapitulated after transfer to germ-free mice, at least over the short term: this is important to provide tools to model the reasons for differences in consortial composition.
    A very large amount of work required to assemble the samples and the clinical phenotypic metadata set making the data an important and definitive contribution for the subjects studied. Of course, this is one sample of extremely variable human conditions and lifestyles that will help build the overall picture of how differences in our genetics and environment shape our intestinal microbiota.

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  3. Reviewer #2 (Public Review):

    The study's primary aims are to test for the differences in the microbiome between self-identified East Asian and White subjects from the San Francisco area in the new IDEO cohort. The study builds on an growing literature which describes variations among ethnic groups. The major conclusion of "emphasize the utility of studying diverse ethnic groups" is not novel to the literature.

    Overall, the strength of the results is that they confirm patterns from different cohorts/studies and demonstrate that ethnic-related differences are common. The results are subject to sample size concerns that may underpin some of the conflicting or lack of significant results. For instance, there is no overlap in highlighted species-level taxonomy differences between 16S and metagenomic analyses, which precludes a clear interpretation of the meaning of those differences and whether taxa should be highlighted in the abstract; there are low AUC values for the random forest modelling; and there is a lack of significance in correlations between BMI and East Asian subjects in F4a where there may be a correlation. While a minor point, it serves to highlight the sample sizes as the range of the variation in East Asian subjects is not as substantial as the White subjects because there are fewer East Asian data points above a 30 BMI (~N=5) relative to those of White subjects (~N=11).

    The microbiome transfers from humans to mice also demonstrate that certain features of interpersonal or ethnic-related differences can be established in mice. This is useful for future studies, but it is not unexpected in and of itself given the robustness of transferring microbiome differences in other human-to-mouse studies. If the phenotype data were more compelling, then the utility of these transfers could be valuable. However, in the current state, I am concerned with the experimental design since the LFPP experiments used N=1 donor per ethnicity for establishing the mice colonies and are resultantly confounded by mice pseudo-replication with recipient mice derived from one donor of each ethnicity. This concern is relevant to interpreting results back to interpersonal or interethnic variation. Are phenotypic differences due to individual differences or ethnic differences? It's not clear. The HFHS experiment also used N=5 donors that somewhat mitigates these concerns, but mixed sexes were used here and there can be sex-specific human microbiome differences. Finally, experimental results are not always consistent and sometimes show opposite trends that may be related to the sampling sizes. For instance, fat and lean mass increased and decreased respectively in LFPP, but there were no statistically-similar differences in HFHS. Moreover, the metabolic fat mass outcomes in mice do not match the expected human donor data. For instance, in LFPP1, White subjects had lower fat mass in humans but recipient mice on average gained more fat. It is difficult to reconcile these differences to a biological or sampling scheme reason.

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  4. Reviewer #3 (Public Review):

    The authors aimed to characterise how gut microbiota changes between different ethnic group for bacterial richness and community structure. They also wanted to address how this is associated with ethnic group within a defined geographical location. They have started to their story by comparing the fecal microbiota of relatively small cohort consisting of 46 lean and obese East Asian and White
    participants living in the San Francisco Bay Area. For that reason they used 16S and shotgun metagenomics. They demonstrated that ethnicity-associated differences in the gut microbiota are stronger in lean individuals and obese did not have a clear difference in the gut microbiota profile between ethnic groups, either suggesting that established obesity or its associated dietary patterns can overwrite long-lasting microbial signatures or alternatively that there is a shared ethnicity-independent microbiome type that predisposes individuals to obesity. The authors did also show the metabolic differences between these ethnic groups and the major differences were in the branched chain amino acid and the short-chain fatty acids. To prove their point, at this stage they have also used different metabolomic methodology. Although some aspects of the work are not very novel, the work does provide additional insights into the effect(s) of ethnicity, current living location and diet on shaping microbiota. Honestly, while reading through the manuscript, I have several questions where I believed that clarification was needed. But somehow, I felt like the authors have been reading my mind every step of the way. At the end of each section whatever I questioned was addressed in the next paragraph There are, however, a few points that I think would like to hear the authors' clarification.

    - The authors pursued the story using 16S data. However, they have shotgun Metagenomics data which gives more power and resolution to microbiota profile. Is there any specific reason why the story was not build with shotgun Metagenomic data? However, if this is the case it will be nice to justify in the text or legend which figure was built with what dataset exactly?
    - Even though the authors mentioned in the discussion that they have not used the same inocula from a donor to different diet, it will be nice if the authors further comments whether they would expect the same results or slightly different results which each different inocula.

    Overall, the study is well executed and claims and conclusions seem relatively well justified by the provided evidence. The findings are interesting for a broad audience of biologists. The findings are interesting for a broad audience of biologists.

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