Nutrient dominance governs the assembly of microbial communities in mixed nutrient environments
- Department of Ecology & Evolutionary Biology and Microbial Sciences Institute, Yale University, United States
- Department of Microbial Biotechnology, Centro Nacional de Biotecnología, CSIC, Cantoblanco, Spain
Figures
Figure 1
Predicting community composition in mixed nutrient environments.
(A) Community composition in a single nutrient (nutrient 1 or nutrient 2) vs a mixture of nutrients (nutrient 1 + nutrient 2). Assuming that nutrients act independently, the null model predicts that …
Figure 2 with 5 supplements
Systematic deviations from the null prediction reveals that some nutrients interact to shape community assembly.
(A) Schematic of experimental design. Two different soil samples were inoculated in minimal M9 medium supplemented with either a single carbon source (CS1 or CS2) or a mixture of two carbon sources …
Figure 2—figure supplement 1
Community assembly in a single carbon source.
Two soil samples were inoculated in minimal M9 medium supplemented with a single carbon source (three or four replicates each) and propagated into fresh media every 48 hr for 10 transfers (Materials …
Figure 2—figure supplement 2
Community assembly in a mixture of two carbon sources.
Two soil samples were inoculated in minimal M9 medium supplemented with two carbon sources (glucose or succinate + another carbon source), and propagated into fresh media every 48 hr for 10 …
Figure 2—figure supplement 3
Systematic deviations from the null (additive) prediction reveal interactions between nutrients.
Figure 2—figure supplement 4
Comparison of the observed relative abundance and abundance predicted by the null model.
Shown is the observed vs predicted abundance for different taxonomic levels and focal carbon source (CS) (mean ± SE). Table shows the Pearson’s R and RMSE for each family-focal carbon source …
Figure 2—figure supplement 5
Community yield in each single carbon source.
Total community biomass (OD620) at the end of the 48 hr incubation period at Transfer 10. There are four biological replicates per carbon source per inoculum, except for glycine with three replicates.
Figure 3 with 4 supplements
Sugars generally dominate over organic acids.
(A) Detecting interactions and hierarchies of dominance between nutrients on microbial community composition. Drawing the single and pairwise abundance landscapes for each species allows us to …
Figure 3—figure supplement 1
Dominance is the most common type of nutrient interaction, especially in the sugar–acid mixtures.
(A) Interaction type for each pair of carbon source and family. An interaction between nutrients occurs when the abundance in the mixture is significantly greater or lower than predicted by the null …
Figure 3—figure supplement 2
Family-level dominance for mixtures of acid–acid and sugar–sugar.
For each carbon source pair, the filled circles show the mean ± SD of N = 8 unique replicates (two inocula × four replicates each), and the open symbols show all eight replicates individually …
Figure 3—figure supplement 3
Patterns of nutrient interaction at the genus level.
(A) Multiple types of nutrient interactions are possible, including dominance, synergy, and antagonism (Figure 3A). An interaction occurs when ε is significantly greater or lower than 0 (one-sided …
Figure 3—figure supplement 4
The systematic dominance of sugars observed at the family level does not apply to the genus level.
To determine the genus-level dominance, the two inocula are considered separately (different shapes) as the genera that are sampled in one inocula may not be sampled in the other inocula. Purple …
Figure 4 with 5 supplements
Family-level asymmetry in nutrient benefits can lead to dominance.
(A) Schematic illustrating different scenarios of nutrient preference. There are two families (FS and FA) and two resource classes (RS and RA). Without resource specialization, FS and FA have equal …
Figure 4—figure supplement 1
Enterobacteriaceae generally have a strong growth advantage in sugars.
Twenty-two strains belonging to the four dominant families, namely Enterobacteriaceae (7), Pseudomonadaceae (5), Moraxellaceae (6), and Rhizobiaceae (4) were isolated from the self-assembled …
Figure 4—figure supplement 2
Stochastic colonization has no qualitative effect on the pattern of additivity found using a Microbial Consumer Resource Model.
Relative abundance of each species (A) or species grouped by family (B) in simulated communities grown in a mixture of nutrients plotted against the predicted relative abundance from simulated …
Figure 4—figure supplement 3
The predictive accuracy of the null model decreases with lower levels of resource specialization.
In Figure 4B (right-hand panel), we performed consumer-resource model simulations and plotted the observed and predicted relative abundance of each family in 300 communities grown on a different …
Figure 4—figure supplement 4
Consumption matrices for different patterns of nutrient preference between families used in the consumer-resource model simulations.
(A) The schematics illustrate different scenarios of nutrient preference for two families (FS and FA) and two resource classes (RS and RA). Without resource specialization, FS and FA have equal …
Figure 4—figure supplement 5
Oxygen demands are similar across the different carbon sources.
We carried out flux-balance analysis using a genome-scale metabolic model of E. coli to determine if different carbon sources are likely to exhibit large differences in oxygen demand (Materials and …
Author response image 1
Tables
Key resources table
| Reagent type (species) or resource | Designation | Source or reference | Identifiers | Additional information |
|---|---|---|---|---|
| Chemical compound, drug | D-Glucose | VWR | 0188–500 | |
| Chemical compound, drug | D-Cellobiose | Sigma | 22150–10G | |
| Chemical compound, drug | D-Fructose | Acros Organics | 161355000 | |
| Chemical compound, drug | D-Ribose | Acros Organics | AC132361000 | |
| Chemical compound, drug | Glycerol (80%, w/v) | Teknova | G8797 | |
| Chemical compound, drug | Sodium Succinate hexahydrate | Alfa Aesar | 419A3 | |
| Chemical compound, drug | Sodium hydrogen fumarate | Alfa Aesar | B24683 | |
| Chemical compound, drug | Sodium benzoate | Alfa Aesar | A15946 | |
| Chemical compound, drug | L-Glutamine 200 mM (29.23 mg/mL) | Sigma | G7513-100ML | |
| Chemical compound, drug | Glycine | Sigma | G7126-100G | |
| Software, algorithm | R | R Development Core Team, 2017. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. https://www.r-project.org/ | RRID:SCR_001905 | R version 3.4.3 |
| Software, algorithm | DADA2 | Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: High-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13: 581–583. | Version 1.6.0 | |
| Software, algorithm | Community simulator | Marsland R, Cui W, Goldford J, Mehta P. The Community Simulator: A Python package for microbial ecology. PLoS One. 2020;15: e0230430. | Version 1.0 | |
| Software, algorithm | COBRApy | Ebrahim A, Lerman JA, Palsson BO, Hyduke DR. COBRApy: COnstraints-Based Reconstruction and Analysis for Python. BMC Syst Biol. 2013;7: 74. | RRID:SCR_012096 | Version 0.17.0 |
Additional files
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Supplementary file 1
Supplementary tables.
(a) Carbon sources used in this study. (b) Taxonomy of strains used in the growth rate assay and community they were isolated from.
- https://cdn.elifesciences.org/articles/65948/elife-65948-supp1-v1.docx
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Transparent reporting form
- https://cdn.elifesciences.org/articles/65948/elife-65948-transrepform-v1.docx
