Bacterial metabolic state more accurately predicts antibiotic lethality than growth rate

Abstract

Growth rate and metabolic state of bacteria have been separately shown to affect antibiotic efficacy^1-3. However, the two are interrelated as bacterial growth inherently imposes a metabolic burden⁴; thus, determining individual contributions from each is challenging^5,6. Indeed, faster growth is often correlated with increased antibiotic efficacy^7,8; however, the concurrent role of metabolism in that relationship has not been well characterized. As a result, a clear understanding of the interdependence between growth and metabolism, and their implications for antibiotic efficacy, are lacking⁹. Here, we measured growth and metabolism in parallel across a broad range of coupled and uncoupled conditions to determine their relative contribution to antibiotic lethality. We show that when growth and metabolism are uncoupled, antibiotic lethality uniformly depends on the bacterial metabolic state at the time of treatment, rather than growth rate. We further reveal a critical metabolic threshold below which antibiotic lethality is negligible. These findings were general for a wide range of conditions, including nine representative bactericidal drugs and a diverse range of Gram-positive and Gram-negative species (Escherichia coli, Acinetobacter baumannii and Staphylococcus aureus). This study provides a cohesive metabolic-dependent basis for antibiotic-mediated cell death, with implications for current treatment strategies and future drug development.

Fig. 1 |. Uncoupling growth from metabolism

a, Coupled and uncoupled growth and metabolism. Coupled growth and metabolism is defined as any condition in which both are correlated with increasing nutrient (yellow). Uncoupled refers to scenarios in which growth is correlated with increasing nutrient but metabolism is not (blue). b, Experimental schematic showing illustrative growth curves with increasing levels of nutrient (light to dark grey). The addition of glucose and/or CAA is indicated in green. The red dots indicate the time at which antibiotics are added and metabolism measurements are obtained. The blue tangent lines represent estimates of growth rate that are measured in the absence of antibiotics, through a time window that spans the introduction of the drug. The three-dimensional axes represent the potential environmental conditions introduced at t₋₂. c, Modulating growth and metabolism. Growth rate and metabolic state (ATP/OD) are shown by the left (black) and right (red) y axes, respectively. The x axis shows the percentage of CAA concentration. Coupled (yellow) and uncoupled (blue) growth and metabolism are indicated. The glucose concentration is indicated in the top left and the temperature is indicated in the bottom right. d, NAD⁺/NADH correlates with ATP. Shading (light to dark) indicates increasing concentrations of CAA. Circle, diamond, square and triangle symbols indicate increasing levels of glucose. Data in c and d are the mean of three biological replicates, except at 33 °C, for which the data are the mean of two replicates; error bars that indicate s.d. are included where applicable. Dashed lines were fitted using a single-variable linear regression (Supplementary Table 3). e, OCR correlates with intracellular ATP, measured at 25°C (left) and 37°C (right) for 0% (circles) and 0.4% (triangles) glucose. Shading (light to dark) indicates increasing concentrations of CAA. Data are mean ± s.d. of four biological replicates; the dashed lines are fits obtained using single-variable linear regressions. f, Slopes from c for growth rate (left, black) and ATP/OD (right, red). Shading (dark to light) indicates increasing temperature. Error bars represent 2 s.e. of the slope estimates (Supplementary Table 3).

Fig. 2 |. Metabolic state correlates with antibiotic lethality for both coupled and uncoupled conditions

a, Glucose modulates growth and metabolic coupling. Cells were supplemented with 0%, 0.001%, 0.0025%, 0.01%, 0.025% or 0.1% CAA (dark to light colour) with either 0.004% (left, yellow) or 0.04% (right, blue) glucose at t₋₂ and 37°C for 2 h. Intracellular ATP and growth rate showed coupling with low glucose (yellow) and uncoupling with high glucose (blue). The dotted grey lines indicate single-variable linear regression fit. b, Antibiotic lethality was correlated with levels of intracellular ATP for all conditions. Nine antibiotics (gentamicin, streptomycin, kanamycin, ciprofloxacin, norfloxacin, levofloxacin, ampicillin, carbenicillin and cefsulodin) were added at t₀ at 20× MIC. Survival was quantified as the log-transformed CFU of treated cells minus the log-transformed CFU of untreated cells after 3 h. c, Antibiotic lethality is independent of growth rate when growth and metabolism are uncoupled. Data from b are plotted against growth rate (x axis). In all cases, data are mean ± s.d. of four biological replicates measured on at least two independent days. For b and c, yellow and blue solid lines are the linear regression fits for coupled and uncoupled conditions individually; red dotted line is the regression fit using all blue and yellow data points combined.

Fig. 3 |. Antibiotic lethality depends on cellular metabolism during exponential growth over a wider parameter space

a,b, Survival was measured for all concentrations of glucose and CAA and temperatures using a subset of representative bactericidal drugs (gentamicin (green), ciprofloxacin (yellow) and ampicillin (red)) at 20× MIC, and is plotted against growth rate (a) or ATP/OD (b). Yellow plots indicate coupled glucose concentrations. Blue plots indicate uncoupled glucose concentrations. The glucose concentration is indicated in the bottom left, and the temperature is indicated in the top right. The dashed black lines are the linear regression for each glucose-temperature combination as a function of CAA concentration. All regression statistics can be found in Supplementary Table 5. Data points for survival are the mean of four biological replicates in all cases except for 33 °C, for which there are two replicates; error bars that indicate s.d. are included where applicable.

Fig. 4 |. Metabolic-dependent threshold for lethality and generality

a, Metabolic state correlates better with antibiotic lethality than growth rate for all data. The pooled 96 data points were normalized and sorted by either increasing ATP/OD (top row) or growth rate (bottom row). The effects on growth and metabolism are shown in the grey bar graphs (left two panels) and survival is shown in the coloured bar graphs for 2× (lighter) and 20× (darker) MIC (right three panels). b, Critical metabolic threshold for antibiotic lethality. Survival is measured at CAA concentrations of 0, 0.001, 0.0025, 0.01, 0.025 and 0.1%; shading (dark to light) represents increasing concentrations. ATP/OD is normalized to ATP_crit. Horizontal (100% survival ratio) and vertical (critical threshold) dotted lines are drawn as guides. Survival is normalized to the ATP value immediately preceding the threshold. Data are the mean survival of four biological replicates. c, Corresponding ATP_crit value from b. The y axis shows ATP_crit before normalization, and the x axis shows temperature. Data are the mean survival of four biological replicates. d, Mathematical schematic with simplified assumptions. Survival undergoes a switch-like transition at a normalized metabolic state of m = 1 and decreases linearly at a rate α. M and M₀ are the non-dimensionalized metabolic states of ATP and ATP_crit, respectively. e, Results are general to malic acid at concentrations of 0, 4, 12.6, 40 and 126.5 μg ml⁻¹; shading (dark to light) indicates increasing concentrations. Data are the mean survival of four biological replicates. f, Increasing metabolic sensitivity using ΔatpA. The following CAA concentrations were used: 0%, 0.01% and 0.1%; shading (dark to light) represents increasing concentrations. Data are the mean ± s.d. survival of three biological replicates. g, Decreasing metabolic sensitivity using glutathione. CAA-treated cells (0%, 0.0025%, 0.01% and 0.1%) were supplemented with 10 mM reduced glutathione. Non-normalized data are provided in Supplementary Fig. 11e. Shading (dark to light) represents increasing CAA concentrations. Data are the mean ± s.d. of three biological replicates. In all cases, the error bars indicate s.d. The y axis for e-g shows the survival ratio and the x axis shows ATP_N. 20× MIC was used for all drugs (Supplementary Table 4). In all cases except for d, colours indicate drug (gentamicin (green), ciprofloxacin (yellow), ampicillin (red) and control (grey)). The control (dotted line) for f and g is the linear regression fit of BW25113 data using the corresponding subset of CAA concentrations for each panel.