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. 2020 Oct;14(10):2505-2513.
doi: 10.1038/s41396-020-0702-7. Epub 2020 Jun 18.

Dissimilarity-Overlap analysis of replicate enrichment communities

Affiliations

Dissimilarity-Overlap analysis of replicate enrichment communities

Jean C C Vila et al. ISME J. 2020 Oct.

Abstract

The taxonomic composition of microbial communities can vary substantially across habitats and within the same habitat over time. Efforts to build quantitative and predictive models of microbial population dynamics are underway, but fundamental questions remain. How different are population dynamics in different environments? Do communities that share the same taxa also exhibit identical dynamics? In vitro communities can help establish baseline expectations that are critical towards resolving these questions in natural communities. Here, we applied a recently developed tool, Dissimilarity-Overlap Analysis (DOA), to a set of experimental in vitro communities that differed in nutrient composition. The Dissimilarity and Overlap of these communities are negatively correlated in replicate habitats, as one would expect if microbial population dynamics were on average strongly convergent (or "universal") across these replicate habitats. However, the existence of such a negative correlation does not necessarily imply that population dynamics are always universal in all communities. Even in replicate, identical habitats, two different communities may contain the same set of taxa at different abundances in equilibrium. The formation of alternative states in community assembly is strongly associated with the presence of specific taxa in the communities. Our results benchmark DOA, providing support for some of its core assumptions, and suggest that communities sharing the same taxa and external abiotic factors generally (but not necessarily) have a negative correlation between Dissimilarity and Overlap.

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Conflict of interest statement

The authors declare that they have no conflict of interest.

Figures

Fig. 1
Fig. 1. Communities assembled in the same environment show a negative correlation between Dissimilarity and Overlap.
a Schematic description of the experiments in ref. [13]. b DOC of all microbial community pairs that have been assembled in the same environment (n = 276 Samples). Shaded regions indicate the 95% confidence interval (Methods). The vertical dotted red line represents the median Overlap (0.543). The inset shows a linear regression for communities above the median Overlap. We repeat this regression over the same region, subsetting the data to consider (c) each nutrient environment separately; (d) subsets of pairs that have been assembled from the same inoculum (e); subsets of the pairs that have been assembled different inoculum. For each regression, we report m (slope of the linear regression) and a p value calculated as the fraction of bootstrap realization in which this slope is negative (see Methods). f Distributions for community pairs assembled in the same environment (both in glucose, both in citrate, or both in leucine) with high Overlap (O > 0.98). The dotted red line is at half the maximum possible dissimilarity log22. g Histogram showing distributions of Overlaps for community pairs where one has been assembled on glucose and the other on citrate. The dotted lines give the frequency polygon for glucose–glucose community pairs and citrate–citrate community pairs (blue and yellow, respectively). We use the same binwidth (0.04) for both histograms and frequency polygons so the two are comparable. h Glucose–citrate communities with high-Overlap (O > 0.98) have significantly higher mean dissimilarity than glucose–glucose communities or citrate–citrate communities in the same Overlap range (O > 0.98). Displayed p values are computed by bootstrapping (see Methods).
Fig. 2
Fig. 2. A Citrobacter ESV is associated with dynamical dissimilarity in communities assembled in replicate environments.
a Dissimilarity and Overlap of microbial community pairs assembled from the same regional pool on M9 + glucose with above-median Overlap (O > 0.98). b Dissimilarity of the same set of communities. For (a) and (b) we label communities by whether Citrobacter ESV is found in both communities (dark blue), only in one community (light blue) or in neither community (yellow). c DOC of all pairs of microbial communities assembled on glucose that contain Citrobacter ESV (n = 25). d DOC of all pairs of microbial communities assembled on glucose that do not contain Citrobacter (n = 67). e Population dynamics for one pair of glucose communities with high Overlap (O = 0.98) and high Dissimilarity (D = 0.56) (highlighted in (a) with the red circle). Structure of the two communities at the ESVlevel at every transfer. f Phase portraits illustrate the dynamics of the most abundant Enterobacteriaceae and Pseudomonadaceae ESV within those two communities. That black line corresponds to the top community in (e) and the red line corresponds to the bottom community in (e). FC and FP2 represent the fraction of the Citrobacter and Psuedomonas.2 ESVs in the population, whereas FEnt and FPseud represent the fractions of the Enterobacteriaceae and Psuedomonoadacea families. Dynamics are highly convergent until the third transfer, after which the communities diverge to alternative states.

References

    1. Locey KJ, Lennon JT. Scaling laws predict global microbial diversity. Proc Natl Acad Sci USA. 2016;113:5970–5. doi: 10.1073/pnas.1521291113. - DOI - PMC - PubMed
    1. Hunter P. Plant microbiomes and sustainable agriculture: deciphering the plant microbiome and its role in nutrient supply and plant immunity has great potential to reduce the use of fertilizers and biocides in agriculture. EMBO Rep. 2016;17:1696–9. doi: 10.15252/embr.201643476. - DOI - PMC - PubMed
    1. Louca S, Parfrey LW, Doebeli M. Decoupling function and taxonomy in the global ocean microbiome. Science. 2016;353:1272–7. doi: 10.1126/science.aaf4507. - DOI - PubMed
    1. Blaser MJ, Cardon ZG, Cho MK, Dangl JL, Donohue TJ, Green JL, et al. Toward a predictive understanding of Earth’s microbiomes to address 21st century challenges. Mbio 2016;7:e00714–e00716. - PMC - PubMed
    1. Ley RE, Peterson DA, Gordon JI. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell. 2006;124:837–48. doi: 10.1016/j.cell.2006.02.017. - DOI - PubMed