Effects of antibiotics on bacterial cell morphology and their physiological origins

Abstract

Characterizing the physiological response of bacterial cells to antibiotic treatment is crucial for the design of antibacterial therapies and for understanding the mechanisms of antibiotic resistance. While the effects of antibiotics are commonly characterized by their minimum inhibitory concentrations or the minimum bactericidal concentrations, the effects of antibiotics on cell morphology and physiology are less well characterized. Recent technological advances in single-cell studies of bacterial physiology have revealed how different antibiotic drugs affect the physiological state of the cell, including growth rate, cell size and shape, and macromolecular composition. Here, we review recent quantitative studies on bacterial physiology that characterize the effects of antibiotics on bacterial cell morphology and physiological parameters. In particular, we present quantitative data on how different antibiotic targets modulate cellular shape metrics including surface area, volume, surface-to-volume ratio, and the aspect ratio. Using recently developed quantitative models, we relate cell shape changes to alterations in the physiological state of the cell, characterized by changes in the rates of cell growth, protein synthesis and proteome composition. Our analysis suggests that antibiotics induce distinct morphological changes depending on their cellular targets, which may have important implications for the regulation of cellular fitness under stress.

Keywords: antibiotic resistance; antibiotics; bacteria; cell shape; growth physiology; size control.

Figure 1.. Effects of antibiotics on bacterial cell morphology, classified by their action.

(A) A schematic of a rodlike bacterial cell that illustrates four different cellular targets of antibiotic action: membrane, ribosomes, cell wall, DNA. We assume a spherocylindrical geometry for all cells addressed in this figure, with the exception of (F), where we consider an ellipsoidal shape. (B) Changes in E. coli cell volume after antibiotic application, normalized by the initial volume. Data presented are taken from refs [4, 5, 12] and additional data can be found in references [15, 17, 18, 32]. We indicate concentrations above MIC [12] with hashes on the bars and an asterisk next to the antibiotic name. The remaining data accounts for concentrations below MIC [5]. Here we group rifampicin with ribosome-targeting drugs since its action on RNA polymerase directly inhibits global protein synthesis (same for D and E). (C) Effects of antibiotics on Gram-negative E. coli cell shape, characterized by cell length (x-axis) and surface-to-volume ratio (y-axis). We normalize cell lengths and surface-to-volume ratios for each antibiotic by their initial values and provide simple cell shape schematics in each quadrant of the morpho-space in comparison to the shape of the untreated cell (black solid circle). Panel (B) is to be used as a legend to match markers to antibiotic names. (D-F) Effects of antibiotics on different organisms (D: Gram-negative A. baumannii [17], E: Gram-positive B. subtilis [15, 18, 33], and F: Gram-positive S. aureus [34, 35]). (G-I) Dependence of different cell morphology metrics (G: volume, H: surface-to-volume ratio, I: aspect ratio) on the concentration of the ribosome-targeting antibiotic chloramphenicol. We normalize antibiotic concentration by the half-maximal inhibitory concentration IC₅₀, as defined in Eq. (1), along with volume, surface-to-volume ratio, and aspect ratio by their initial values. We include two representative trajectories each for fast, medium, and slow growing E. coli cells in different nutrient environments.

Figure 2.. Antibiotics control cell morphology by modulating physiological parameters for cell growth, surface synthesis and protein production.

(A) A coarse-grained model of bacterial cell physiology describing exponential volume growth (at rate $k$), surface area synthesis (at rate $k_s$) and division protein synthesis (at rate $k_d$). (B) Effect of antibiotics on the physiological rate constants $k,k_s$ and $k_d$ that regulate cell shape and growth. The plot shows the dependence of $k/k_s$ (∝ surface-to-volume ratio) on $k/k_d$ (∝ cell volume) with or without antibiotic treatment. In the absence of antibiotics, the rate constants are related by the equation of state: $k_s\approx 2\pi k^{2/3}{k}_d^{1/3}$ (solid line). Antibiotics modulate one or more of these rate constants depending on its cellular target (colored arrows), resulting in cell shape changes and deviations from the equation of state. The yellow arrow pointing downward represents antibiotics that cause cell rounding, e.g., fosfomycin, while the one pointing toward bottom right represents antibiotics that cause both cell rounding and filamentation, e.g., ampillicin (also see Table I). (C) Cellular resource partitioning under antibiotic stress. The schematic shows the proteome mass of a bacterial divided into four coarse-grained sectors based on proteomics abundance data [47] partitioning by functional groups [48]: 1) Sector V containing proteins that regulate $k$ (21%–41% of the total proteome mass), 2) Sector S containing proteins that control $k_s$ (12%–14%), 3) Sector D containing division proteins that regulate $k_d$ (<0.5%), and 4) Sector ‘Others’ containing all other proteins. Note that proteins in the sectors V, S and D have little overlap with each other. Thicker solid lines connecting drug targets and sectors represent stronger inhibitory effect, and thinner solid lines represent weaker inhibitory effect.