The unconstrained evolution of fast and efficient antibiotic-resistant bacterial genomes

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1 In the format provided by the authors and unedited. VOLUME: ARTICLE NUMBER: 5 The unconstrained evolution of fast and efficient antibiotic-resistant bacterial genomes Carlos Reding-Roman, Mark Hewlett, Sarah Duxbury, Fabio Gori, Ivana Gudelj & Robert Beardmore r.e.beardmore@exeter.ac.uk NATURE ECOLOGY & EVOLUTION DOI:.8/s

2 Supplementary Figures w/.5mg/ml glucose w/ mg/ml glucose w/.5mg/ml glucose w/ mg/ml glucose w/ mg/ml glucose w/ mg/ml glucose w/ 4mg/mL glucose OD 65nm K =.6 ±. OD (Mean ± SD) r =.9 ±.86 Doublings/h (Mean ± SD) K =.8 ±.4 OD (Mean ± SD) r =.5 ±. Doublings/h (Mean ± SD) K =.84 ±.5 OD (Mean ± SD) r =. ±.4 Doublings/h (Mean ± SD) K =. ±. OD (Mean ± SD) r =. ±.4 Doublings/h (Mean ± SD) K =. ±.8 OD (Mean ± SD) r =.44 ±.4 Doublings/h (Mean ± SD) K =.94 ±.44 OD (Mean ± SD) r =.6 ± 8 Doublings/h (Mean ± SD) K =.45 ±.5 OD (Mean ± SD) r = 5 ±.4 Doublings/h (Mean ± SD) w/ 6mg/mL glucose w/ 8mg/mL glucose w/ mg/ml glucose w/ mg/ml glucose w/ mg/ml glucose w/ 4mg/mL glucose w/ mg/ml glucose OD 65nm K = 6 ±.8 OD (Mean ± SD) r =.4 ±. Doublings/h (Mean ± SD) K =.66 ±.44 OD (Mean ± SD) r =.9 ±.9 Doublings/h (Mean ± SD) K =.8 ±. OD (Mean ± SD) r =.9 ±.8 Doublings/h (Mean ± SD) K =.865 ±. OD (Mean ± SD) r =.4 ±. Doublings/h (Mean ± SD) K =.94 ±. OD (Mean ± SD) r =. ±.6 Doublings/h (Mean ± SD) K =.96 ±. OD (Mean ± SD) r =.6 ±. Doublings/h (Mean ± SD) K =.9 ±.8 OD (Mean ± SD) r = 8 ±. Doublings/h (Mean ± SD) Supplementary Figure S: Representative raw OD data (coloured lines) of the strains of C. glabrata. Each subplot represents the growth of the cultures over a 4h period in SC media supplemented with.5-mg/ml of glucose. We used the logistic model, shown in grey but obscured by data in most cases, to calculate growth rate (r) and carrying capacity (K). S NATURE ECOLOGY & EVOLUTION DOI:.8/s

3 . Escherichia coli MG655 w/ mg/ml glucose Escherichia coli MG655 w/.5mg/ml glucose Escherichia coli MG655 w/.5mg/ml glucose Escherichia coli MG655 w/ mg/ml glucose OD 6nm.. K =. ±. r =. ±. Doublings h K =.4 ±.6 r =.6 ±. Doublings h K =.6 ±.6 r = ±.4 Doublings h K =. ±. r =. ±. Doublings h. Escherichia coli MG655 w/.5mg/ml glucose Escherichia coli MG655 w/ mg/ml glucose Escherichia coli MG655 w/ mg/ml glucose Escherichia coli MG655 w/ mg/ml glucose OD 6nm.. K =.4 ±.8 r = ±. Doublings h K =. ±.5 r =.6 ±. Doublings h K = 5 ±. r =.48 ±.4 Doublings h K =. ±. r =.4 ±. Doublings h a). Escherichia coli w/ mg/ml glucose Escherichia coli w/.5mg/ml glucose Escherichia coli w/.5mg/ml glucose Escherichia coli w/ mg/ml glucose OD 6nm.. K =. ±. r =. ±. Doublings h K =.4 ±. r =.4 ±. Doublings h K =.5 ±.6 r = 8 ±. Doublings h K =.8 ±. r =.64 ±. Doublings h. Escherichia coli w/.5mg/ml glucose Escherichia coli w/ mg/ml glucose Escherichia coli w/ mg/ml glucose Escherichia coli w/ mg/ml glucose OD 6nm.. K = ±.4 r =.6 ±. Doublings h K =.9 ±. r =.6 ±. Doublings h K = 8 ±. r = 5 ±. Doublings h K =.4 ±. r =. ±. Doublings h b). Escherichia coli 4 w/ mg/ml glucose Escherichia coli 4 w/.5mg/ml glucose Escherichia coli 4 w/.5mg/ml glucose Escherichia coli 4 w/ mg/ml glucose OD 6nm.. K =. ±. r =. ±. Doublings h K =. ±. r = ±. Doublings h K =. ±. r =.44 ±. Doublings h K =.6 ±. r =.5 ±.5 Doublings h. Escherichia coli 4 w/.5mg/ml glucose Escherichia coli 4 w/ mg/ml glucose Escherichia coli 4 w/ mg/ml glucose Escherichia coli 4 w/ mg/ml glucose OD 6nm.. K =.66 ±. r =. ±. Doublings h K =.65 ±. r =.66 ±. Doublings h K =. ±.4 r = 6 ±. Doublings h K =. ±. r =.4 ±. Doublings h c) Supplementary Figure S: Representative raw OD data (coloured lines) of E. coli rrn knockouts. Each subplot represents the growth dynamics of a 4h culture in minimal M9 media supplemented with -mg/ml of glucose and casamino acids. The logistic model (grey) is used to calculate growth rate (r) and carrying capacity (K). S NATURE ECOLOGY & EVOLUTION DOI:.8/s

4 yield (c(s) in cells per µ g) x log(c lo ) = r (per h) a) glucose (S in µ g/ml) b) 4 5 yield (cells per µ g) x 6 r (per h) log(c lo ) = r (per h) c) K (cells per ml) c) 5 5 K (cells per ml) x 5 d) r (per h) glucose (S in µ g/ml) d) population density (K(S) in cells per ml) log(c lo ) = glucose (S in µ g/ml) NATURE ECOLOGY & EVOLUTION DOI:.8/s

5 Supplementary Figure S: The relationship between the rate-yield and rk parabolae: one theory that morphs from a tradeup (blue) to a tradeup-tradeo switch (orange). Starting with the expression (5) for yield: c(s) =(c hi + pc lo S)/( + ps), note that this is a withinstrain rate-yield tradeo (RYTO) if and only if c lo <c hi. Panel (a) shows a plot of c(s) for the values of c hi, measured in log cells per µg, as indicated in the panel legend, with log (c lo ) fixed at 5. Typical realisations of equation (), the rate-yield relationship, then have the form shown in (b). Analogous rk relationships from (6) are then shown in (c); the two panels in (c) are identical, except one has linear and one has log-linear x-axes. As growth rate is defined to be r(s) =c(s) V max S/(k m +S) and recalling that K = c(s) S, an algebraic condition for an rk tradeo can be derived on the parameters in this model from the requirement that there is an S dr for which growth is locally maximal: ds (S )=. Models in (c) both do, and do not, meet this condition. For those that do not, r increases with K and we have an rk tradeup, where this condition is met, the rk-curve has a tradeup part that gives way to a tradeo at large enough values of K. Panel (d) shows the two functions r(s) and K(S) =S c(s) in the definition of equation (6) for the same parameter values as panels (a-c). Note how in (d-right) the relationship between population size and the glucose supplied can be nonlinear. NATURE ECOLOGY & EVOLUTION DOI:.8/s

6 Glucose (mg/ml) Candida glabrata (data) Branched Pathway Model Growth rate (h ) a) Glucose (mg/ml) Candida glabrata (data) Branched Pathway Model Growth rate (h ) b) Yield (OD per mg of glucose) Supplementary Figure S4: Robustness of the skewed rk/rate-yield parabolae across C. glabrata stains. (a) Variation in growth rate (r) on the y-axis as a function of carrying capacity (K, x-axis) for data pooled from all cultured strains of C. glabrata. Dots are empirical data measured at di erent glucose concentrations (shown as di erent colours). The prediction from the model in equation (6) in the main text is represented in black. (b) The analogous plot to (a), but for rate-yield data, not rk data. S6 NATURE ECOLOGY & EVOLUTION DOI:.8/s

7 Glucose (mg/ml) C. glabrata 9 (Data) Prediction Glucose (mg/ml) C. glabrata BG (Data) Prediction Growth rate (h ) Growth rate (h ) a) Glucose (mg/ml) C. glabrata BG ssk (Data) Prediction.5 r (h ) Growth rate (h ) Growth rate (h ) Escherichia coli MG655.. K (OD) Candida glabrata Candida glabrata 65 Branched Pathway Model a) Growth rate (h ) C. glabrata (Prediction) C. glabrata 9 (Prediction) C. glabrata 65 (Prediction) C. glabrata BG (Prediction) C. glabrata BG ssk (Prediction) C. glabrata BG ssk (Prediction) b) Supplementary Figure S5: rk parabolae of five C. glabrata strains. a) Relationships between growth rate (r, y-axis) and carrying capacity (K, x-axis) for C. glabrata, data are dots, robust predictions from equation (6) are lines. Bottom-right panel: rk profiles for two clinical isolates of C. glabrata ( and 65) the latter was isolated from a diabetic patient and has higher r, but smaller K (predictions from equation (6) have adjusted R {.98,.88}). (inset) An analogous unimodal rk geometry for E. coli MG655. b) Putting the five predicted rk parabolas of C. glabrata in one S plot highlights strain 65 isolated from a diabetic patient with the greatest low-k, high-r skew. NATURE ECOLOGY & EVOLUTION DOI:.8/s

8 Growth rate (h ) WT ( x rrn) (6 x rrn) (5 x rrn) (4 x rrn) 4 ( x rrn) 5 ( x rrn) Prediction Yield (OD per mg of glucose) WT ( x rrn) (6 x rrn) (5 x rrn) (4 x rrn) 4 ( x rrn) 5 ( x rrn) Prediction.5 Glucose (mg/ml).5.5 Glucose (mg/ml).5 K (OD at stationary phase)..5. WT ( x rrn) (6 x rrn) (5 x rrn). (4 x rrn) 4 ( x rrn).5 5 ( x rrn) Prediction.5 Glucose (mg/ml) Supplementary Figure S6: r, K and yield for E. coli rrn knockout strains cultured at increasing glucose concentrations Growth rate (r, top left), yield (top right) and carrying capacity (K, centre) on the y-axis (dots) at di erent glucose concentrations (x-axis) alongside predictions from equations (5-) (grey). For each concentration of glucose, between-strain di erences in phenotype within each condition (i.e. for each fixed glucose concentration) were tested using a one-way ANOVA. Whether or not (green or red) these di erences are significant (p <.5) is indicated by symbols above the data. If the symbol is a triangle, its orientation (as an up or down arrow) shows if the number of rrn operons is positively (up) or negatively (down) correlated with the phenotype in each plot and a square, not a triangle, is shown when no significant correlation is found either way. As a result, this analysis shows r, K and yield are negatively correlated with operon number in most conditions tested, however not all, and more details associated with these correlations can be found in Supplementary Figures 4 and S8. S8 NATURE ECOLOGY & EVOLUTION DOI:.8/s

9 Yield (OD mg ) Glucose (mg/ml) rrn operons rrn operons Glucose (mg/ml).8 Growth rate (h ).6.4. Glucose (mg/ml) rrn operons Supplementary Figure S: Empirical yield, K and r landscapes (z-axes) showing each of these phenotypes as a function of glucose supply concentration and rrn copy number. Data (dots) are superimposed upon best-fit predictions using theory from the main text. Larger dots denote more rrn operons present in the genome, sizes as Figure 4. S9 NATURE ECOLOGY & EVOLUTION DOI:.8/s

10 .6.5 mg/ml Glucose.5 mg/ml Glucose..5 mg/ml Glucose Yield (OD mg ) Linear trend p.6e 4 Yield (OD mg )..5. Linear trend p.9e 4 Yield (OD mg ).5. Linear trend p 4.48e Number of rrn operons Number of rrn operons Number of rrn operons Yield (OD mg ) mg/ml Glucose Linear trend p 4.4e Yield (OD mg ) mg/ml Glucose Linear trend p.86e 8 Yield (OD mg ) mg/ml Glucose Linear trend p.e Number of rrn operons Number of rrn operons Number of rrn operons Supplementary Figure S8: Increasing copy number of the rrn operon reduces yield in E. coli rrn mutants. The dependence of biomass yield of the rrn knockout strains (y-axis) is shown as a function of rrn operon copy number (x-axis). Linear regressions (solid black line, the outer lines show the prediction ± 95% CI, n = ) determine whether yield and operon copy number are correlated. The correlation is significantly negative in each case: note the x-axis has a negative orientation. To obtain the analogous plot for the K phenotype, multiply y-axes by the amount of glucose in each panel, this does not change the qualitative form of each plot but it does scale the y-axis. S NATURE ECOLOGY & EVOLUTION DOI:.8/s

11 .65.5 mg/ml Glucose.8 mg/ml Glucose..5 mg/ml Glucose.6..6 Growth rate (h ) R =. p val = Yield (OD per mg of glucose) Growth rate (h ).6.4. R = p val = Yield (OD per mg of glucose) Growth rate (h ).4. R =.4 p val = Yield (OD per mg of glucose) Growth rate (h ) mg/ml Glucose R =.6 p val = Yield (OD per mg of glucose) Growth rate (h ) mg/ml Glucose R =.4 p val = Yield (OD per mg of glucose) Growth rate (h ) mg/ml Glucose R =. p val = Yield (OD per mg of glucose) Supplementary Figure S9: Seeking between-strain tradeo s and tradeups in E. coli rrn mutants: correlations between growth rate (r, y-axis) and carrying capacity (K, x-axis) are shown as a function of glucose supply (colour-coded) and rrn operon copy number (dot size). Using linear regressions (black line), we tested whether r and K are correlated. Clearly both negative and positive correlations are observed, depending on the glucose supplied and there is, therefore, no evidence of a rate-yield tradeo between strains consistently across all environmental conditions. To obtain the analogous plot for the K phenotype, multiply x-axes by the amount of glucose in each panel: this produces Supplementary Figure S. S NATURE ECOLOGY & EVOLUTION DOI:.8/s

12 Growth rate (h ) Growth rate (h ) mg/ml Glucose R :., R :. adj adj p.9, p mg/ml Glucose R :., R :.5 adj adj p.95, p Growth rate (h ) Growth rate (h ) mg/ml Glucose. R : 5, R :.4 adj adj p., p mg/ml Glucose R :., R :.6 adj adj p.4, p Growth rate (h ) Growth rate (h ) mg/ml Glucose R adj :.9, R adj :.8 p.9, p mg/ml Glucose R adj :.5, R adj :.8 p.6, p Supplementary Figure S: Between-strain rk data in E. coli rrn mutants: this is a direct analogy of Supplementary Figure S9 but with K plotted on the x-axis instead of yield. A quadratic datafit is a better descriptor of the data than a linear regression in most cases (based on adjusted R values), but note how the form of quadratic is inverted at the highest glucose. The reasons for this are not known. S NATURE ECOLOGY & EVOLUTION DOI:.8/s

13 Lag phase (h) mg/mL Glucose F statistic: 5.6 p.45 Lag phase (h) 4 mg/ml Glucose F statistic:.4 p.558 Lag phase (h) 5 4.5mg/mL Glucose F statistic: 5.65 p.96 a) rrn operons rrn operons rrn operons mg/ml Glucose mg/ml Glucose mg/ml Glucose Lag phase (h) 5 4 F statistic:.5 p.899 Lag phase (h) F statistic: 8.6 p.58 Lag phase (h).5 F statistic: 9 p.686 a) rrn operons rrn operons rrn operons OD 6nm.. WT ( x rrn) 4 ( x rrn) Difference in carrying capacity: 5 ±. OD. ±.6 OD.5 Difference in lag phase:.6 ±.5 h 4. ±. h b) 5 5 Supplementary Figure S: E ect of copy number variation on the lag phase of E. coli rrn mutants. a) Duration of the lag phase (y-axis) as a function of rrn operon copy number (negatively oriented x-axis). Linear regressions (black line) determine whether lag and operon copy number are correlated, evidently the correlation is negative in all cases. b) A comparison of the growth kinetics of the wild-type strain of E. coli K(MG655) and the knockout strain with four rrn deletions ( 4), where the y-axis shows the dynamics of optical density (OD 6nm ) over a 4h period. We note that the removal of rrn operons does not alter the observed growth rate significantly in the case shown when mg/ml of glucose are supplied to the media (two-sided t-test, t =.5, df =4 and p.65). It does increase, however, both the length of the lag phase (t = 5.58, df =4 and p.5) and the carrying capacity (t = 4.9, df =4and p.4). Other glucose concentrations produce analogous observations. S NATURE ECOLOGY & EVOLUTION DOI:.8/s

14 4h (Mean ± SD) 4h (Mean ± SD) OD 6nm.4.. Difference in IC 5 :.6 ±. µg/ml.6 ±. µg/ml Doxycycline (µg/ml) Supplementary Figure S: Doxycycline dose-response profiles for E.coli K(AG), aka Ancestral in the main text. E. coli K(AG) OD 6nm on the y-axis during a growth cycle where measurements have been taken at two time points, one at 4h and one at 4h. The doxycycline concentration supplied is shown on the x-axis. Of note is the qualitatively di erent form of dose-response at the two di erent time points, particularly the large densities in the 4h doseresponse curve. Thus, from these data, doxycycline can be a stimulant of optical density over periods longer than 4h incubation. For example, comparing OD in the zero dox condition against the OD in the.ug/ml dox condition at 4h we obtain t.8, df =4,p.4: no significant di erence. Whereas comparing the OD of the zero dox condition versus that of the.ug/ml dox condition at 48h we obtain a significant di erence: t 9.5, df =4,p 4. OD is therefore maximised in a drug treatment and not in the absence of drug. Importantly, the dose inhibiting cell growth by 5% relative to the no-drug condition (written IC 5 ) varies significantly depending on the incubation time (t 45.88, df =and p.4). Based on the 4h data in this figure, as is standard, we take the minimal inhibitory concentration (MIC) of AG exposed to doxycycline to be.6µg/ml for the purposes of this study. This is also called MIC in the main text; MIC is double this value. NATURE ECOLOGY & EVOLUTION DOI:.8/s

15 .4 Mean ± SE (n=6) t = h t = 4h t = 6h t = 48h OD 6nm....4 t = 6h t = h t = 84h t = 96h OD 6nm....5 Doxycycline (µg/ml).5 Doxycycline (µg/ml).5 Doxycycline (µg/ml).5 Doxycycline (µg/ml) Supplementary Figure S: The course of adaptation of an E. coli K(AG) doseresponse to doxycycline for 6 generations. Empirical dose-response data showing the growth of AG is represented on the y-axis, quoted as the mean optical density at 6nm (OD 6nm ± s.e. (the grey area), n =6) with doxycycline on the x-axis. Treatment lasted four days with a new drug treatment every h, each period of which is termed a season of growth: there are 8 seasons corresponding to each subplot in this figure. Note the non-monotonic overgrowth feature of the later curves whereby some of the drug-treated populations can be as high as the density of the untreated control populations. The drug-treated sample highlighted by a red circle was subjected to wholegenome sequencing, as was the no-doxycycline treatment at the same timepoint. NATURE ECOLOGY & EVOLUTION DOI:.8/s

16 4 Data Media ± 99% CI xmic Dox ± 99% CI xmic Dox ± 99% CI xmic Lag phase (h) no Dox no Dox xmic 8 b) Growth (OD 6nm ) with no Doxycycline.4... Ancestral Media Adapted xmic Adapted no Dox 6 a) Ancestral Media Adapted xmic Adapted 5 5 OD 6nm.4... AG (No Dox) AG (.4µg/mL Dox) Difference in carrying capacity:. ±.44 OD ±. OD Difference in lag phase:. ±. h 4.6 ±. h 4 Supplementary Figure S4: Comparison between the Ancestral, Media Adapted and MIC Adapted strains of E. coli K(AG) described in the main text. a) Di erences in lag phase, shown on the y-axis, for the three strains determined in three di erent environmental conditions: () in M9 media with glucose and casamino acids (called Media or nodox ), () the same media with doxycycline at MIC (called MIC Dox ) and () the same media supplemented with doxycycline at MIC (called MIC Dox ). A two-sided t-test, with p<.5, determined whether di erences in lag were statistically significant (green star) or not (red star) from the Ancestral strain in the same media. Note the absence of lag phase when the Ancestral and Media Adapted strains are grown at x and xmic: they do not growth in these conditions. b) Growth curves of the Ancestral, Media Adapted and xmic Adapted strains cultured in the absence of antibiotic over 4h (left). Note how the growth of the xmic Adapted strain is as fast as the other two and it reaches a greater population size in all three replicates (statistics on next page). (right) Note how the addition of.4µg/ml of doxycycline to media leads to a significant increase in lag phase of Ancestral s (AG) growth (t = 4.9, df =and p.8) and carrying capacity (t = 8.8, df =and p.5), importantly with no significant penalty in growth rate (t =.9, df =and p.5). Thus doxycycline here serves to increase lag phase, not decrease exponential growth rate. NATURE ECOLOGY & EVOLUTION DOI:.8/s

17 Statistics required for Supplementary Figure S4(b): T-test values that Media Adapted has a greater r phenotype than xmic Adapted : t.9, df =6,p.4 5. t-test values that Ancestral has a lower r phenotype than xmic Adapted : t.5, df =6,p.. t-test values that Media Adapted has a smaller K phenotype than xmic Adapted : t., df =6,p 4.. t-test values that Ancestral has a smaller K phenotype than xmic Adapted : t 8., df =6,p.4. NATURE ECOLOGY & EVOLUTION DOI:.8/s

18 mean binned coverage ( bins) 96h Dox replicate f %, p 5.44e f 88%, p 5e 94 96h Dox replicate f 4%, p.68e 8 f 8%, p 4e 6 96h Dox replicate f 5%, p.6e 46 f 84%, p 4e h no Dox replicate 96h no Dox replicate 96h no Dox replicate mean binned coverage ( bins) 4 genome position (Mb) 4 genome position (Mb) 4 genome position (Mb) Supplementary Figure S5: Illumina DNA coverage data for di erent treatments associated with Figures S and. (top) This shows Illumina whole-genome coverage data determined for the three doxycycline-treated replicates highlighted with a red circle in Figure S. It shows the loss of a dlp prophage region (in black) and the amplification of a large genomic region (in blue) containing the acr antibiotic e ux operon. The estimated frequencies of these mutations in each population are shown in each figure legend as an f value. (bottom) This is analogous to the top figure but now for populations taken from Figure S at 96h that have not be exposed to doxycycline. Note the greater uniformity of coverage of Illumina reads across the genome: there is no detected loss of the dlp prophage region nor duplication of the same acr e ux pump in the absence of doxycycline. NATURE ECOLOGY & EVOLUTION DOI:.8/s

19 Supplementary Tables NATURE ECOLOGY & EVOLUTION DOI:.8/s

20 Supplementary Table S: SNPs common to all 96h AG doxycycline-adapted populations (K-AGdox, three replicates) Strain Position Reference Alternate Gene Function Status K-AGdox b.p. G T insh-4 transposase and silent cgg! cgt 5 A G insh-4 trans-activator silent cca! ccg 68 A G insh-4 present on insertion silent cga! cgg 4 T C insh-4 sequence 5 (IS5) silent ttg! Ctg 44 G C insh-4 silent acg! acc 494 C G insh-4 non-silent cac! cag 46 C T insh-4 non-silent gcg! gtg G T Slp Outer membrane lipoprotein non-silent atg! att G A Slp carbon-starvation inducible non-silent gcg! Acg NATURE ECOLOGY & EVOLUTION DOI:.8/s

21 Supplementary Table S: Quality filters for all reported polymorphisms for 96h AG, doxycycline-adapted populations (K-AGdox). Strain Position Reference Alternate Read Depth High quality reads Reference depth Alternate depth Frequency P-value K-AGdox G T % 4 5 A G A G T C G C C T C G A G G T G A NATURE ECOLOGY & EVOLUTION DOI:.8/s

22 Supplementary References 4 Quinlan, A. & Hall, I. Bedtools: A flexible framework for comparing genomic features. Bioinformatics 6 (). NATURE ECOLOGY & EVOLUTION DOI:.8/s