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  1. Evaluation Summary:

    The authors attempt to derive a threshold of genetic distance, beyond which two microbial strains diverge in their behavior in an ecological community. The question is of broad interest to ecology, especially microbial ecology. To answer this question, the authors followed the population dynamics of individual strains derived from a natural microbial community under constant environmental conditions in the lab. The statistical framework could be improved, and a more rigorous account of how the phylogenetic inference of strains and species was made should be given.

    (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. The reviewers remained anonymous to the authors.)

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  2. Reviewer #1 (Public Review):

    In this manuscript, Goyal et al. address the important question of the taxonomic level that is the most informative ecologically for understanding microbial community dynamics. To do so, they isolate microbial communities from pitcher plants and "domesticate" them for 21 transfers until they reach some steady-state. Then they observe strain and species dynamics in these communities for >300 generations using 16S rRNA (species) and metagenomics (strains). They arrive at the conclusion that strain dynamics can diverge at a genetic distance of ~100 base pairs. I expect this conclusion, and the number value attached to it, to become an important and well-cited figure in microbial ecology. The impact of this study would therefore benefit from a more rigorous account of how the phylogenetic inference of strains and species was made.

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  3. Reviewer #2 (Public Review):

    General sentiment: This paper is, overall, excellent. There are a small number of points which could be clarified, some language which should be amended, and some additional analyses which could potentially strengthen the paper.

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  4. Reviewer #3 (Public Review):

    The authors cultivated natural microbial communities derived from pitcher plants (Sarracenia purpurea) under laboratory conditions over an extended period of time (i.e. > 300 generations). Throughout the experiment, community dynamics were quantified by sequencing metagenomes at different time intervals. By statistically analyzing correlations in the abundances of genotypic variants at different levels of phylogenetic differentiation revealed that (1) strain abundances tended to be more correlated than frequencies of species, (2) strains started to decouple when the genetic distance exceeded 100 SNPs, and (3) the correlation of the abundance trajectories was greater when interspecific strains were compared than between the respective species. The findings were recapitulated with consumer-resource models (with and without phenotypic differences between strains) to exclude the possibility of the observed dynamics being merely the consequence of stochastic effects. Finally, comparing the genomes of coupled versus uncoupled strains suggested SNPs in genes coding for transporters, regulators, and enzymes in central carbon metabolism mainly differentiated strains of both groups. Based on these results, the authors conclude that understanding the long-term evolution of microbial communities requires knowledge of the dynamics on the level of strains rather than species.

    The manuscript is well written and clearly structured. The rather complex data set is presented in a largely comprehensible way.

    However, the main conclusions of the paper rest entirely on the ability to detect ecological interactions between genotypic variants as their correlated changes. For example, strains can show positively or negatively coupled oscillations that may even be time-lagged. Thus, the question is: (i) How sensitive is the statistical approach used to also detecting such patterns? and (ii) How robust is the conclusion if these pattern remain undetected? These points should be clarified in the manuscript.

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