SUPPLEMENTARY INFORMATION

Transcription

1 Supplementary Methods A total of 18 denitrifying species were isolated (Suppl. Table S3) and stored in ready to use aliquots at -80 C. In preparation for each experiment (Suppl. Fig. S1), the strains were cultured for 48 h, and sub-cultured for 40 h at 28 C in Trypticase Soy Broth (TSB) to have actively growing microorganisms. Subsequently, species were diluted to 10 7 cells ml -1 as measured by flow cytometry (Cyan LX, Dako, Fort Collins, CO, USA). These dilutions were further used to prepare different mixes of the species, each representing a microbial community with a given degree of initial evenness (as an example see Suppl. Table S1 for 5 of the mixtures used in this work). Suppl. Figure S1: Scheme of the experimental setup. 1

2 Table S1: As an example, the composition of 5 of the mixtures used in this study are given with indication of their respective degrees of initial evenness (as shown by the GINI coefficient value). Numbers in the table refer to the relative abundance for each strain (at a dilution of 10 7 cells ml -1 ) in a given mix. This way, each mix contained the same total volume and thus the same starting concentration (10 7 cells ml -1 ) Mix 1 Mix 2 Mix 3 Mix 4 Mix 5 strain1 % strain2 % strain3 % strain4 % strain5 % strain6 % strain7 % strain8 % strain9 % strain10 % strain11 % strain12 % strain13 % strain14 % strain15 % strain16 % strain17 % strain18 % GINI The mixes were used to assemble microcosms in multiwell plates consisting of a 1/1 dilution in TSB medium supplemented with 6 mm nitrite (final concentrations) using a BioRobot 3000 (Qiagen, Venlo, The Netherlands). Plates were incubated anoxically for 20h at 28 C (control). Low temperature (16 C) and salinity (3% (w/v) NaCl) represented the applied stresses. In the experiment 84 different levels of evenness were used, corresponding to unique G (Gini) and X combinations (with X: concentration of the dominant species). Each G-X combination is referred to as a design point. For X, 13 values were selected, equally spaced between perfect evenness (X = 5.6%) and the maximum possible X value at which the 17 remaining species each have a concentration of 0.67% (X= 89%). For each X, the Gs were spaced 2

3 equally between the minimum and maximum values (Suppl. Figure S2). For a particular design point several Lorenz curves were often possible. When a certain design point was used to construct a microcosm the following procedure was followed: 1. A Lorenz curve was constructed at random with the specified X and G. 2. From this Lorenz curve the 18 different concentrations were derived. 3. These concentrations were attributed at random to the 18 different strains that were mixed together in a microcosm. 4. Each mix was placed in duplo on the multiwell plates. For the first experiments, each of the 84 different regions of initial evenness was used twice. This resulted in 168 different microcosms that were placed in the multiwell plates in duplo. Additionally, another 42 points were chosen from the design points according to an experimental design procedure. This procedure enabled an optimal estimation of the linear and quadratic effects. The 42 points consisted of 4 different design points: perfect evenness, maximal dominance and two regions in the middle of the design space. They were repeated 10, 16, 11 and 5 (total is 42) times in duplo, respectively. Negative controls were positioned in the corners and the centre of each plate to assess potential row, column, and plate effects. Model selection was performed using a series of linear models. Each of the variables and their interactions were entered sequentially and the models were compared based on the Akaike's information criterion (AIC). The parameters of the mean model were estimated by ordinary least squares. The correlation matrix between the explanatory variables is given in Suppl. Table S2. All statistical tests in the paper are two sided tests that are based on the model parameters or linear combination of the model parameters. Tests on the model parameters β are conducted by using t-tests and tests on linear combinations of β are conducted by Chi-square tests by using general linear hypothesis testing. A general linear hypothesis is formulated as Hβ = 0 where H is the r x q hypothesis matrix. Based on the estimate of the variance of ˆ β the hypotheses can for instance be tested by means of a Wald type test statistic, 3

4 ( ) T ( Hˆ Σ β H T ) 1 H ˆ T = H ˆ β ( β ), which is asymptotically χ r 2 distributed under the general linear null hypothesis. For ˆ Σ β the White estimator was used to account for heteroscedasticity (Kutner et al., 2004 cited in the manuscript). 4

5 Suppl. Table S2: Correlation matrix of the explanatory variables; P (experiment effect), S (stress), R (row effect), C (column effect), G (Gini) and X (relative abundance of the most dominant strain) P S R C G X P S R C G X

6 Suppl. Table S3: List of the species a used to create the 1260 mixed microbial communities with different degrees of evenness. Phylum n b ID Collection code a Isolation conditions c Firmicutes 3 Bacillus sp. R ph 7, 37 C, succinate, nitrite α Proteobacteria 18 Paracoccus sp. R ph 7, 20 C, methanol, nitrite 9 Paracoccus sp. R ph 7, 37 C, ethanol, nitrite 10 Paracoccus sp R ph 7, 37 C, glucose, nitrite 16 Brucella sp. R ph 7, 37 C, ethanol nitrite 13 Ochrobactrum sp R ph 7, 37 C, succinate, nitrite 15 Ochrobactrum sp. R ph 8, 37 C, succinate, nitrite β Proteobacteria 7 Acidovorax sp. R ph 6.5, 20 C, pyruvate, nitrite 6 Acidovorax sp. R ph 6.5, 37 C, succinate, nitrite 5 Diaphorobacter sp. R ph 6.5, 37 C, succinate, nitrite 17 Diaphorobacter sp. R ph 8, 20 C, succinate, nitrite 14 Comamonas sp. R ph 6.5, 20 C, pyruvate, nitrite 4 Comamonas sp. R ph 6.5, 20 C, pyruvate, nitrite 11 Comamonas sp. R ph 7, 20 C, acetate, nitrite 2 Comamonas sp; R ph 7.5, 20 C, pyruvate, nitrite γ Proteobacteria 1 Pseudomonas sp. R ph 6.5, 20 C, pyruvate, nitrite 12 Pseudomonas sp. R ph 7, 37 C, succinate, nitrite 8 Pseudomonas sp. R ph 7.5, 20 C, pyruvate, nitrite a Heylen, K. et al. The incidence of nirs and nirk and their genetic heterogeneity in cultivated denitrifiers. Environmental Microbiology 8, (2006). b Code of the species as reported in other sections of this paper (i.e., Supplementary Figure S5) c Conditions used to isolate each species: ph, temperature, carbon source, and nitrogen source. No additional salt has been added for any species. 6

7 Suppl. Figure S2: 84 different levels of initial evenness corresponding to unique G (Gini) and X combinations (with X: concentration of the dominant species). 7

8 Suppl. Figure S3: Demonstration of different Lorenz curves and their corresponding Gini coefficients with green (G=0, perfect evenness), blue (G=0.5), and red (G=1). The Gini coefficient (ranging from 0 to 1) is a single value that describes a specific degree of evenness, measuring the normalized area between a given Lorenz curve and the perfect evenness line. 1 0,9 0,8 0,7 0,6 0,5 0,4 0,3 0,2 0, ,2 0,4 0,6 0,8 1 Cummulative proportion of species 8

9 Suppl. Figure S4: Residual plot of model 8. Left panel: Q-Q plot indicates deviations from normality, but due to the large sample size (n=1260) we can rely on the central limit theorem, which ensures that the parameter estimators are asymptotically normally distributed and that statistical tests on the parameter estimators are valid. Middle panel: observed values with respect to fitted values. Right panel: residuals with respect to Gini. No systematic pattern remains in the residuals, indicating that the effect of the Gini coefficient can be modelled adequately by a quadratic term. 9

10 Suppl. Figure S5: Contribution to the ecosystem function of the species identity of the different species (species number as in Suppl. Table S3) for no stress (white), temperature stress (black), and salt stress (grey). Bars indicate standard errors. Per species, significant (), and very significant () differences with its non-stressed condition are depicted. Contribution Contribution to ecosystem function Species Strain 10