Antibiotics inhibit key targets that are critical for growth. It makes intuitive sense, therefore, that growth plays an important role in antibiotic lethality. In fact, the correlation between growth rate and antibiotic efficacy has been demonstrated for decades. More recently, however, there is growing appreciation for the role of metabolism in lethality. On the one hand, mounting evidence demonstrates that downstream from the initial antibiotic-target binding event, a secondary cascade of energetically demanding metabolic processes actively contributes to cell death; on the other hand, metabolically dormant cells are protected from antibiotic treatment, a phenotypic state known as tolerance (Figure 1).
Figure 1. Metabolism plays an active role in antibiotic lethality
This appreciation and understanding of metabolism is certainly novel, but it is also firmly rooted in what we have known for decades: metabolism and growth are tightly coupled processes, yet metabolism accounts for a greater number of biological processes in the cell beyond biomass generation. Indeed, because of these additional non-growth maintenance functions that depend on metabolism, such as swimming or responding to stress, growth and metabolism can become readily uncoupled. This led us to ask a seemingly obvious question: is growth an (admittedly excellent) proxy for metabolism? If we push the environmental conditions, would we see that metabolism in fact provides a more fundamental explanation for the observed relationship between growth and lethality? To put that another way, does the cellular metabolic state better predict survival than the growth rate? As the title of our paper might hint, our answer to all of these questions is yes.
We first sought to establish conditions whereby growth and metabolism could be readily coupled or uncoupled from one another. That way, we could measure survival as a function of each individually, and tease out their relative contribution. We achieved this by capitalizing on non-linear carbon and nitrogen utilization efficiencies. Specifically, we used a rich amino acid nutrient source to tune the growth rate, and this growth rate was either coupled or not to the metabolic state of the cell (quantified primarily with ATP) depending on the corresponding concentration of glucose.
What we saw was surprising: when growth and metabolism were coupled, both growth rate and metabolic state were equally predictive of survival. However, when growth and metabolism were uncoupled, only the metabolic state remained correlated with survival, while growth rate was independent of survival. This suggests that the metabolic state better predicts survival than the growth rate. Naturally, we wanted to see the extent to which this finding was true. So, we performed these experiments using nine bactericidal antibiotics that cover the major mechanisms, along with a significantly larger parameter set covering ~100 data points of diverse growth rates and metabolic states. Indeed, doing so revealed that even across all of these conditions, and drugs, the metabolic state remained inversely correlated with survival at high ATP. And, survival was entirely independent of the growth rate across all of these conditions. So, we had our conclusion: the metabolic state in fact predicts survival better than the growth rate.
What does this all mean? To expand our understanding, we built a simple model to account for these dynamics. That model shows that even when growth is absent, killing can be nonzero; this is incredibly important not just because it supports our conclusion, but because currently, the antibiotics discovery pipeline focuses almost entirely on growth inhibition. To put our findings another way, this suggests that – in theory – we should be able to target and kill bacterial cells without necessarily inhibiting their growth, which could elucidate an entirely novel pathway towards developing new antibiotics and adjuvants.
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