The East Asian gut microbiome is distinct from colocalized White subjects and connected to metabolic health

Essential revisions:

1) In Table 1 the significance of differences between the East Asian and white ethnicities is given as adjusted P values. This potentially obscures a significant difference between the groups in single metrics that are then used to stratify later analysis. For example it appears that BMI and weight may be significantly different in the obese East Asian and white subjects, and that the obese East Asians are taking less exercise.

We have modified our manuscript as suggested: Table S1 now displays unadjusted p-values, while also referring to our multiple testing correction in the footnote. As expected, switching to unadjusted (nominal) p-values revealed more variables that are significantly different between groups; however, these differences were mainly restricted to obese EA and W individuals. This observation fits with the prior literature wherein differences in body composition and health related BMI outcomes are well-established and provided the rationale for our study (discussed in our Introduction).

In contrast, we only identified a single variable (triglyceride levels) that was significantly different between lean EA and W individuals. Thus, the central finding of our manuscript revealing variations in the gut microbiotas of lean EA and W subjects is only confounded by a single difference in triglyceride levels. Furthermore, the p-value was borderline (p=0.02) and did not survive multiple hypothesis testing.

We have modified our main text to reflect this new information:

“While several factors linked to body composition were different between obese EA and W subjects using a nominal p-value, only triglyceride levels were significantly different between lean EA and W subjects and this trend did not survive multiple testing correction (Table S1).”

2) Could you please provide more information on the setting of recruitment and justify the limitations of bias in the dataset? It also sounds as if there is a far more detailed clinical metadataset available for these subjects (smoking, medications, parameters summarized in Figure S4). It would help other investigators to have this data available on an (anonymized) per subject basis. The conclusions include (correct) statements about the importance of the IDEO cohort, but the metadata is important for cross-comparison between studies.

As requested, we have expanded our methods section to provide a more detailed discussion of recruitment and justify limitations of bias in our dataset (copied below). We have also provided more comprehensive metadata linked to the participants we recruited into this study from IDEO (IDEO_Extended_Data.csv). This includes data on smoking, medications, and all of the parameters summarized in Figure S4 as the reviewers requested. A subset of this data was included in Table S2 in our original submission. We have preserved all of the data in Table S2 in its original form and supplemented all of the additional requested data, including 404 non-redundant metadata variables, in the IDEO_Extended_Data.csv file, which is posted to our laboratory’s github repository for this manuscript.

“Human subjects

The IDEO cohort was established to explore the pathogenesis of obesity and metabolic diseases in highly vulnerable segments of the population. […] Samples were aliquoted and stored at -80°C.”

3) In Figure 1, you showed that richness and diversity are higher in W than EA. However, all the major phyla are higher in EA population. Even though you showed the statistical differences between tested group, please add the taxa bar plot to show the overall picture of the groups, preferably at phylum and genus level.

We have updated Figure 1C. We opted to present the phylum data as box plots to be consistent with the CLR-transformed values of taxonomic abundances that we used throughout the figures. CLR values (which are on a log2 scale) cannot be stacked in the same way as percent relative abundances. In our opinion, stacked bar graphs are also difficult to interpret due to the small size of each bar, the high abundance of the top 2 phyla relative to the others, and the lack of any indication of variance within a group.

We think that the expanded Figure 1C makes the overall picture at the phylum level quite clear. In our previous submission, we highlighted 6 bacterial phyla that are significantly different between ethnicity, of which only one, Verrucomicrobiota, was significantly enriched in W subjects. In this updated figure, we show the other bacterial phyla, including Desulfobacterota and Cyanobacteria, which trends to be higher in W subjects though not individually significant. The abundances of the non-significant phyla, collectively, are higher in W compared to EA subjects (p = 0.012, Wilcoxon rank-sum test). We discuss these results in the main text as follows:

“Phylogenetic analyses of all ASVs revealed marked variations in the direction of change across different phyla between EA and W subjects (Figure S1A), indicating that the phylum level trends (Figure 1C) resulted from the integration of subtle shifts across multiple component members (Figure 1D-F).”

As requested, we have also included an additional panel, Figure 1D, showing stacked bar plots of average relative abundances at the genus level. Consistent with the observation that W subjects have higher microbial diversity and lower relative abundances of the major phyla compared to EA subjects, the bar plots show that W subjects have higher relative abundances of the lower abundance taxa (merged into a single category as “Remainder” in the bar plots).

4) It is difficult to appreciate the timing of the output of the transfer experiments in 7A and E. Depending on the direction of the trajectory in 7A (do the samples generally separate or converge?), what happens if you down-sample to remove the samples in the bottom left of the ordination plot?

We apologize for the confusion. The samples shown in Figure 7A represent gnotobiotic mice that are connected by the same donor, not longitudinal samples from the same mice. Samples were collected at the end of each experiment (6 weeks in the case of LFPP1, 3 weeks in the case of LFPP2, and 4 weeks in the case of the HFHS experiment as described in the methods section of our manuscript – only one time point per experiment). Because these samples do not represent different time points from the same experiment, all of them are required for comparisons between ethnicities.

Figure 7A combines results from two independent experiments where microbial communities of the recipient mice largely cluster by sample donor and donor ethnicity. In a prior version of this manuscript, we had separated these two LFPP experiments; however, we were encouraged by our previous reviewers to focus on trends that are consistent across the two replicate experiments, providing the rationale for the current figure.

For your information, we have re-separated these two experiments into two separate LFPP experiments (see Author response image 1) . The samples described in the reviewer question are represented by the EA recipients in the new LFPP1 plot in (Author response image 1) (the blue dots). We hope this clarifies our experimental design. Given that these are not multiple timepoints and because comparisons between all recipient mice between both ethnicities is appropriate and was recommended during our initial round of review, we have opted to include all samples and experiments in the main text.

Author response image 1

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5) The interpretation in the last sentence of the discussion that the transfer experiments support the redundancy of host genetics in maintaining the differences depends on the absence of stochastic effects during the transfer (i.e. that replicate controls from the same subject map together by comparison). It is suggested that the interpretation could be offered with this caveat.

We think that this comment refers to the final sentence in the first paragraph of our original discussion, which read:

“Our experiments using inbred germ-free mice support the stability of ethnicity-associated differences in the gut microbiota on both the LFPP and HFHS diets, while also demonstrating that variations in host genetics are not necessary to maintain these signatures, at least over short timescales.”

We considered potential stochastic effects during our experimental design and data analysis. Although we conducted three different experiments with varied conditions and detected the impact of ethnicity on gut microbial community composition, we cannot fully exclude that stochastic effects linked to gnotobiotic transplantation impacted our results. We have modified the last sentence of the first paragraph of the discussion to include this caveat and related points:

“Our experiments using inbred germ-free mice support the stability of ethnicity-associated differences in the gut microbiota on both the LFPP and HFHS diets, while also demonstrating that variations in host genetics are not necessary to maintain these signatures, at least over short timescales. Even though we conducted multiple experiments and recipient mice from the same donor generally mapped together, differences between the human donor and recipient mouse microbiotas inherent to gnotobiotic transplantation warrant further investigation…”

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