Bacteria have evolved diverse mechanisms to survive environments with antibiotics. Temperature is both a key factor that affects the survival of bacteria in the presence of antibiotics and an environmental trait that is drastically increasing due to climate change. Therefore, it is timely and important to understand links between temperature changes and selection of antibiotic resistance. This review examines these links by synthesizing results from laboratories, hospitals, and environmental studies. First, we describe the transient physiological responses to temperature that alter cellular behavior and lead to antibiotic tolerance and persistence. Second, we focus on the link between thermal stress and the evolution and maintenance of antibiotic resistance mutations. Finally, we explore how local and global changes in temperature are associated with increases in antibiotic resistance and its spread. We suggest that a multidisciplinary, multiscale approach is critical to fully understand how temperature changes are contributing to the antibiotic crisis.

The growth of living organisms varies with temperature. This dependence is described by a temperature response curve that is described by an optimal temperature where growth is maximized and a temperature range (termed breadth) across which the organism can grow.

In bacteria, evolution of resistance to one antibiotic is frequently associated with increased resistance (cross‐resistance) or increased susceptibility (collateral sensitivity) to other antibiotics. Cross‐resistance and collateral sensitivity are typically evaluated at the minimum inhibitory concentration (MIC). However, these susceptibility changes are not well characterized with respect to the mutant prevention concentration (MPC), the antibiotic concentration that prevents a single‐step mutation from occurring. We measured the MIC and the MPC for Staphylococcus epidermidis and 14 single‐drug resistant strains against seven antibiotics. We found that the MIC and the MPC were positively correlated but that this correlation weakened if cross‐resistance did not evolve. If any type of resistance did evolve, the range of concentrations between the MIC and the MPC tended to shift right and widen. Similar patterns of cross‐resistance and collateral sensitivity were observed at the MIC and MPC levels, though more symmetry was observed at the MIC level. Whole‐genome sequencing revealed mutations in both known‐target and nontarget genes. Moving forward, examining both the MIC and the MPC may lead to better predictions of evolutionary trajectories in antibiotic‐resistant bacteria.

Summary The rapid increase of multi-drug resistant bacteria has led to a greater emphasis on multi-drug combination treatments. However, some combinations can be suppressive—that is, bacteria grow faster in some drug combinations than when treated with a single drug. Typically, when studying interactions, the overall effect of the combination is only compared with the single-drug effects. However, doing so could miss “hidden” cases of suppression, which occur when the highest order is suppressive compared with a lower-order combination but not to a single drug. We examined an extensive dataset of 5-drug combinations and all lower-order—single, 2-, 3-, and 4-drug—combinations. We found that a majority of all combinations—54%—contain hidden suppression. Examining hidden interactions is critical to understanding the architecture of higher-order interactions and can substantially affect our understanding and predictions of the evolution of antibiotic resistance under multi-drug treatments.

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Although natural populations are typically subjected to multiple stressors, most past research has focused on single stressors and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 151 ecological three-stressor interactions from 45 published papers. We found that 89% (n=134) of the three-stressor combinations resulted in new or different interactions than previously reported. We also found substantial levels of emergent properties—interactions that are only revealed when all three stressors are present. Antagonism was the most prevalent net interaction whereas synergy was the most prevalent emergent interaction. Understanding multiple stressor interactions is crucial for fundamental questions in ecology and also has implications for conservation biology and population management.

Aims Bacterial response to temperature changes can influence their pathogenicity to plants and humans. Changes in temperature can affect cellular and physiological responses in bacteria that can in turn affect the evolution and prevalence of antibiotic‐resistance genes. Yet, how antibiotic‐resistance genes influence microbial temperature response is poorly understood. Methods and Results We examined growth rates and physiological responses to temperature in two species—E. coli and Staph. epidermidis—after evolved resistance to 13 antibiotics. We found that evolved resistance results in species‐, strain‐ and antibiotic‐specific shifts in optimal temperature. When E. coli evolves resistance to nucleic acid and cell wall inhibitors, their optimal growth temperature decreases, and when Staph. epidermidis and E. coli evolve resistance to protein synthesis and their optimal temperature increases. Intriguingly, when Staph. epidermidis evolves resistance to Teicoplanin, fitness also increases in drug‐free environments, independent of temperature response. Conclusion Our results highlight how the complexity of antibiotic resistance is amplified when considering physiological responses to temperature. Significance Bacteria continuously respond to changing temperatures—whether through increased body temperature during fever, climate change or other factors. It is crucial to understand the interactions between antibiotic resistance and temperature.

Although natural populations are typically subjected to multiple stressors, most past research has focused on single stressors and two-stressor interactions, with little attention paid to higher-order interactions among three or more stressors. However, higher-order interactions increasingly appear to be widespread. Consequently, we used a recently introduced and improved framework to re-analyze higher-order ecological interactions. We conducted a literature review of the last 100 years (1920-2020) and reanalyzed 151 ecological three-stressor interactions from 45 published papers. We found that 89% (n=134) of the three-stressor combinations resulted in new or different interactions than previously reported. We also found substantial levels of emergent properties - interactions that are only revealed when all three stressors are present. Antagonism was the most prevalent net interaction whereas synergy was the most prevalent emergent interaction. Understanding multiple stressor interactions is crucial for fundamental questions in ecology and also has implications for conservation biology and population management.