2026-10-14T07:47:14Z https://api.figshare.com/v2/oai

oai:figshare.com:article/34048691 2026-10-01T17:35:59Z category_1 category_8 category_24 category_272 category_39 category_734 category_62 category_132 category_135 portal_5 item_type_3 month_year_10_2026

S1 Table. Linear mixed-effects model results of the effects of Time, Phenotype and their interactions on the natural log of population density estimates (CFU/ml). Rodrigo Zorrilla González (25157813) Michael Travisano (234511) Biophysics Microbiology Evolutionary Biology Environmental Sciences not elsewhere classified Ecology Biological Sciences not elsewhere classified Marine Biology Infectious Diseases Computational Biology kluyveromyces lactis </ generalizable structural constraint div >< p dependent physical interactions based projections revealed alter encounter rates social traits even settling fitness confirmed predicted equilibrium frequency cheating individuals remains manipulated settling density social evolution settling density population density density acts settled fraction settle efficiently results demonstrate multicellular clusters metabolic exchange low densities less enriched interaction frequency high densities findings support evolved enforcement ecological stability direct measurements cluster formation central puzzle S2 Table. ANOVA results of the effects of Time, Phenotype and their interactions on the natural log of population density estimates (CFU/ml). S1 Fig. Snowflake and Co-Unis co-exist over time and Co-Uni persistence is not driven by adaptive changes. A) Change in population density of Co-Uni and Snowflake strains over 15 transfers in coculture, shown as the natural logarithm of colony forming units per ml (ln[CFU/ml]). Lines represent predicted population densities by the linear mixed-effects model. Transfers were conducted every 24 hours under settling selection. B) Change in population density (ln[CFU/ml]) of co-cultures with Co-Uni isolates from the beginning (Day 0) and end (Day 15) of the experiment over 6 transfers. Lines represent predicted population densities by the linear mixed effects model. Transfers were conducted every 24 hours under settling selection. The minimum detection threshold for both strains was approximately 12.5 ln(CFU/ml). S3 Table. Results of linear mixed-effects model analysing the effects of transfer number, phenotype and state (Evolved or ancestral) on population density. S4 Table. Type III ANOVA results for linear-mixed effects model testing the effects of transfer number, phenotype, and state on population density. S5 Table. Two-way ANOVA results for growth rates of Co-Uni and Snowflake isolates, analyzing the effects of phenotype and transfer number. S2 Fig. A) Optical Density measurements (600 nm) for Snowflake and Co-Uni isolates from the beginning (Transfer number 0 in green) and end (Transfer number 15 in purple) of the experiment over time, fitted using a locally estimated scatterplot smoothing (LOESS). B) Intrinsic growth rates for Snowflake and Co-Uni isolates from the beginning (Transfer number 0) and end (Transfer number 15) of the experiment as calculated using the growthcurver package in R. S6 Table. Linear mixed-effects model results for population density influenced by time phenotype, and density. S7 Table. ANOVA results for effects of time, phenotype, and density on population density. S8 Table. Fit parameters and model performance for replicate-level log10(Co-Uni CFU / Snowflake CFU) ratio trajectories across settling densities. S9 Table. Linear regression results testing the relationship between settling density and Co-Uni selection strength (slope). S10 Table. ANOVA results testing the effect of settling density on Co-Uni selection strength (slope). S11 Table. Linear regression on asymptote ratios for Co-Uni and Snowflake frequency dependence. S12 Table. ANOVA for asymptote ratio predicting Co-Uni and Snowflake equilibrium frequency. S13 Table. Parameters from exponential decay fits of Co-Uni CFU at different settling densities. S14 Table. Logistic growth parameters for snowflake CFU across settling densities. S15 Table. Linear regression analysis of Co-Uni CFU at equilibrium against settling density. S16 Table. ANOVA results for Co-Uni CFU predictions at equilibrium across settling densities. S17 Table. Linear regression analysis of Co-Uni CFU decay slope against settling density. S18 Table. ANOVA results for Co-Uni CFU decay slope across settling densities. S3 Fig. Model fits and density-dependent dynamics of Co-Uni CFU trajectories. A) Log10-transformed Co-Uni CFU counts over time for each biological replicate, across different relative settling densities. Lines represent replicate-level linear fits to the log-transformed CFU data; points represent raw measurements. B) Relationship between settling density and decay slope estimated from replicate-level fits. More positive slopes at higher densities indicate slower Co-Uni population decline. C) Predicted equilibrium CFU counts (asymptotic values) extracted from exponential decay models, plotted against relative settling density. S19 Table. Linear regression analysis of Snowflake CFU at equilibrium against settling density. S20 Table. ANOVA results for Snowflake CFU predictions at equilibrium across settling densities. S21 Table. Linear regression analysis of Snowflake CFU decay slope against settling density. S22 Table. ANOVA results for Snowflake CFU decay slope across settling densities. S4 Fig. Model fits and density-dependent dynamics of Snowflake CFU trajectories. A) Log10-transformed Snowflake CFU counts over time for each biological replicate, across different relative settling densities. Lines represent replicate-level linear fits to the log-transformed CFU data; points represent raw measurements. B) Relationship between settling density and growth slope estimated from replicate-level fits. Slopes remain stable across densities, indicating limited density dependence in Snowflake population expansion. C) Predicted equilibrium CFU counts (asymptotic values) extracted from logistic growth models, plotted against relative settling density. No significant trend is observed. S23 Table. Linear regression of relative fitness against settling density. S24 Table. ANOVA results for relative fitness across settling densities. S25 Table. Linear model analysis of relative increase by settling density and phenotype. S26 Table. ANOVA results for relative increase by settling density and phenotype. S27 Table. Comparison of candidate linear models predicting Co-Uni settling fitness as a function of density and Snowflake frequency. (ZIP) 2026-10-01T17:35:57Z Dataset Dataset 10.1371/journal.pone.0359779.s001 https://figshare.com/articles/dataset/_p_S1_Table_Linear_mixed-effects_model_results_of_the_effects_of_Time_Phenotype_and_their_interactions_on_the_natural_log_of_population_density_estimates_CFU_ml_p_/34048691 CC BY 4.0