Additional file 1 of Four ways of implementing robustness quantification in strain characterisation
Creators: name: Torello Pianale, Luca
name: Caputo, Fabio
name: Olsson, Lisbeth
Publisher: name: figshare
Year: 2024
Subjects: subject: Biochemistry
subject: Space Science
subject: Medicine
subject: Microbiology
subject: FOS: Biological sciences
subject: Cell Biology
subject: Genetics
subject: Molecular Biology
subject: Physiology
subject: Ecology
subject: Biological Sciences not elsewhere classified
subject: Mathematical Sciences not elsewhere classified
subject: Developmental Biology
subject: Computational Biology

description: Additional file 1: Table S1. Trace metals and vitamin solutions. Composition of (A) trace metal and (B) vitamin solutions used in Delft medium. Figure S1. Growth curves and robustness across conditions in oxygen-limited flask cultivations. Overview of selected S. cerevisiae strains in flask screening under oxygen-limited conditions using different lignocellulosic hydrolysates. (a) Growth curves. (b) Correlation between performance and robustness across conditions, R(c), for five functions (lag phase, specific growth rate, ethanol/glycerol/cell mass yields) based on non-woody (WSH50, SBH50, CSH50, and OHH50) or woody (SLRH50, HGSH50, and BiH50) biomass. Figure S2. Maximum specific growth rates and lag phases. Maximum specific growth rates (a) and lag phases (b) of parental and biosensor strains in all tested media. Statistical differences between the biosensor and parental strains are represented above the bar plots; those between the control (Delft) and all other conditions are shown below the bar plots. As no differences in functions were observed between the parental and biosensor strains, all strains (three replicates each) have been used for a more reliable statistical analysis. *p ≤ 0.05; **p ≤ 0.01, ***p ≤ 0.001, and ****p ≤ 0.0001. Figure S3. Growth curves and robustness across conditions in BioLector screening. Overview of selected S. cerevisiae strains in flask screening under oxygen-limited conditions using lignocellulosic hydrolysates. (a) Growth curves. (b) Correlation between performance and robustness across conditions for two functions (lag phase and specific growth rate) dividing non-woody (WSH60, SBH60, CSH60, and OHH60) or woody (SLRH60, HGSH60, and BiH60) lignocellulosic hydrolysates. Figure S4. Line plots for intracellular parameters examined via BioLector I screening. Overview of all line plots for the biosensors used in BioLector screening. Cell mass is represented as the natural logarithm of scattered light, while intracellular parameters are denoted as fluorescence ratios (a.u.). Figure S5. Overview of biosensor outputs categorised by growth phase and medium. Overview of biosensor output for eight intracellular parameters computed either for the lag phase (left) or exponential phase (right) taking into consideration all tested media (“ALL”), only woody hydrolysates or only non-woody hydrolysates. Red dots identify the mean fluorescent output across all media in that group. Note that for glycolytic flux, the higher the biosensor output the lower the flux. Figure S6. Robustness over time of intracellular parameters categorised by growth phase and medium. Robustness over time (i.e., the stability of a function over time) for eight intracellular parameters computed either for the lag phase (left) or exponential phase (right). Robustness was computed taking into consideration all tested media (“ALL”), only woody hydrolysates or only non-woody hydrolysates. Red dots identify the mean R(t) across all media in that group. Figure S7. Line plots for GlyOx fluorescence outputs. Output from the GlyOx biosensor for glycolytic flux (a) and oxidative stress response (b). Violin plots represent the distribution of the intracellular parameter within the cell population at each timepoint. Red dots represent the mean across all cells. At least 25 cells were analysed for each timepoint. Figure S8. Line plots for RibUPR fluorescence outputs. Output from the RibUPR biosensor for ribosome abundance (a) and unfolded protein response (b). Violin plots represent the distribution of the intracellular parameter within the cell population at each timepoint. Red dots represent the mean across all cells. At least 25 cells were analysed for each timepoint. Figure S9. Scatter plots for GlyOx fluorescence outputs. Scatter plots summarising the correlation between glycolytic flux and oxidative stress response for each cell at each timepoint (0, 4, 8, 12, 16, 20, and 24 h) for CEN.PK113-7D (a), EthanolRed (b), and PE2 (c). Each dot represents a cell. At least 25 cells were analysed for each timepoint. Figure S10. Scatter plots for RibUPR fluorescence outputs. Scatter plots summarising the correlation between ribosome abundance and unfolded protein response for each cell at each timepoint (0, 4, 8, 12, 16, 20, and 24 h) for CEN.PK113-7D (a), EthanolRed (b), and PE2 (c). Each dot represents a cell. At least 25 cells were analysed for each timepoint. Figure S11. Robustness across populations for intracellular parameters categorised by medium. Robustness across populations (i.e., how homogeneous a function is within a cell population) for four intracellular parameters (top to bottom): glycolytic flux, ribosome abundance, oxidative stress response, and unfolded protein response. Red dots identify the mean R(p) across all timepoints for each strain in each medium.