Laboratory evolution reveals a two-dimensional rate-yield tradeoff in microbial metabolism

Repeated glucose oscillations in high cell-density cultures influence stress-related functions of Escherichia coli

Engineering microbial cells for the commercial production of biomolecules and biochemicals requires understanding how cells respond to dynamically changing substrate (feast-famine) conditions in industrial-scale bioreactors. Scale-down methods that oscillate substrate are commonly applied to predict the industrial-scale behavior of microbes. We followed a compartment modeling approach to design a scale-down method based on the simulation of an industrial-scale bioreactor. This study uses high cell-density scale-down experiments to investigate Escherichia coli knockout strains of five major glucose-sensitive transcription factors (Cra, Crp, FliA, PrpR, and RpoS) to study their regulatory role during glucose oscillations. RNA-sequencing analysis revealed that the glucose oscillations caused the down-regulation of several stress-related functions in E. coli. An in-depth analysis of strain physiology and transcriptome revealed a distinct phenotype of the strains tested under glucose oscillations. Specifically, the knockout strains of Cra, Crp, and RpoS resulted in a more sensitive transcriptional response than the control strain, while the knockouts of FliA and PrpR responded less severely. These findings imply that the regulation orchestrated by Cra, Crp, and RpoS may be essential for robust E. coli production strains. In contrast, the regulation by FliA and PrpR may be undesirable for temporal oscillations in glucose availability.

Active microbial population dynamics and life strategies drive the enhanced carbon use efficiency in high-organic matter soils

Microbial carbon use efficiency (CUE) is a critical parameter that controls carbon storage in soil, but many uncertainties remain concerning adaptations of microbial communities to long-term fertilization that impact CUE. Based on H218O quantitative stable isotope probing coupled with metagenomic sequencing, we disentangled the roles of active microbial population dynamics and life strategies for CUE in soils after a long-term (35 years) mineral or organic fertilization. We found that the soils rich in organic matter supported high microbial CUE, indicating a more efficient microbial biomass formation and a greater carbon sequestration potential. Organic fertilizers supported active microbial communities characterized by high diversity and a relative increase in net growth rate, as well as an anabolic-biased carbon cycling, which likely explains the observed enhanced CUE. Overall, these results highlight the role of population dynamics and life strategies in understanding and predicting microbial CUE and sequestration in soil.IMPORTANCEMicrobial CUE is a major determinant of global soil organic carbon storage. Understanding the microbial processes underlying CUE can help to maintain soil sustainable productivity and mitigate climate change. Our findings indicated that active microbial communities, adapted to long-term organic fertilization, exhibited a relative increase in net growth rate and a preference for anabolic carbon cycling when compared to those subjected to chemical fertilization. These shifts in population dynamics and life strategies led the active microbes to allocate more carbon to biomass production rather than cellular respiration. Consequently, the more fertile soils may harbor a greater microbially mediated carbon sequestration potential. This finding is of great importance for manipulating microorganisms to increase soil C sequestration.

A coarse-grained resource allocation model of carbon and nitrogen metabolism in unicellular microbes

Coarse-grained resource allocation models (C-GRAMs) are simple mathematical models of cell physiology, where large components of the macromolecular composition are abstracted into single entities. The dynamics and steady-state behaviour of such models provides insights on optimal allocation of cellular resources and have explained experimentally observed cellular growth laws, but current models do not account for the uptake of compound sources of carbon and nitrogen. Here, we formulate a C-GRAM with nitrogen and carbon pathways converging on biomass production, with parametrizations accounting for respirofermentative and purely respiratory growth. The model describes the effects of the uptake of sugars, ammonium and/or compound nutrients such as amino acids on the translational resource allocation towards proteome sectors that maximized the growth rate. It robustly recovers cellular growth laws including the Monod law and the ribosomal growth law. Furthermore, we show how the growth-maximizing balance between carbon uptake, recycling, and excretion depends on the nutrient environment. Lastly, we find a robust linear correlation between the ribosome fraction and the abundance of amino acid equivalents in the optimal cell, which supports the view that simple regulation of translational gene expression can enable cells to achieve an approximately optimal growth state.

Functional decomposition of metabolism allows a system-level quantification of fluxes and protein allocation towards specific metabolic functions

Quantifying the contribution of individual molecular components to complex cellular processes is a grand challenge in systems biology. Here we establish a general theoretical framework (Functional Decomposition of Metabolism, FDM) to quantify the contribution of every metabolic reaction to metabolic functions, e.g. the synthesis of biomass building blocks. FDM allowed for a detailed quantification of the energy and biosynthesis budget for growing Escherichia coli cells. Surprisingly, the ATP generated during the biosynthesis of building blocks from glucose almost balances the demand from protein synthesis, the largest energy expenditure known for growing cells. This leaves the bulk of the energy generated by fermentation and respiration unaccounted for, thus challenging the common notion that energy is a key growth-limiting resource. Moreover, FDM together with proteomics enables the quantification of enzymes contributing towards each metabolic function, allowing for a first-principle formulation of a coarse-grained model of global protein allocation based on the structure of the metabolic network.

Mutualism-enhancing mutations dominate early adaptation in a two-species microbial community

Species interactions drive evolution while evolution shapes these interactions. The resulting eco-evolutionary dynamics and their repeatability depend on how adaptive mutations available to community members affect fitness and ecologically relevant traits. However, the diversity of adaptive mutations is not well characterized, and we do not know how this diversity is affected by the ecological milieu. Here we use barcode lineage tracking to address this question in a community of yeast Saccharomyces cerevisiae and alga Chlamydomonas reinhardtii that have a net commensal relationship that results from a balance between competitive and mutualistic interactions. We find that yeast has access to many adaptive mutations with diverse ecological consequences, in particular those that increase and reduce the yields of both species. The presence of the alga does not change which mutations are adaptive in yeast (that is, there is no fitness trade-off for yeast between growing alone or with alga), but rather shifts selection to favour yeast mutants that increase the yields of both species and make the mutualism stronger. Thus, in the presence of the alga, adaptative mutations contending for fixation in yeast are more likely to enhance the mutualism, even though cooperativity is not directly favoured by natural selection in our system. Our results demonstrate that ecological interactions not only alter the trajectory of evolution but also dictate its repeatability; in particular, weak mutualisms can repeatably evolve to become stronger.

Density-dependent effects are the main determinants of variation in growth dynamics between closely related bacterial strains

Although closely related, bacterial strains from the same species show significant diversity in their growth and death dynamics. Yet, our understanding of the relationship between the kinetic parameters that dictate these dynamics is still lacking. Here, we measured the growth and death dynamics of 11 strains of Escherichia coli originating from different hosts and show that the growth patterns are clustered into three major classes with typical growth rates, maximal fold change, and death rates. To infer the underlying phenotypic parameters that govern the dynamics, we developed a phenomenological mathematical model that accounts not only for growth rate and its dependence on resource availability, but also for death rates and density-dependent growth inhibition. We show that density-dependent growth is essential for capturing the variability in growth dynamics between the strains. Indeed, the main parameter determining the dynamics is the typical density at which they slow down their growth, rather than the maximal growth rate or death rate. Moreover, we show that the phenotypic landscape resides within a two-dimensional plane spanned by resource utilization efficiency, death rate, and density-dependent growth inhibition. In this phenotypic plane, we identify three clusters that correspond to the growth pattern classes. Overall, our results reveal the tradeoffs between growth parameters that constrain bacterial adaptation.

Trade-offs predicted by metabolic network structure give rise to evolutionary specialization and phenotypic diversification

Mitigating trade-offs between different resource-utilization functions is key to an organism's ecological and evolutionary success. These trade-offs often reflect metabolic constraints with a complex molecular underpinning; therefore, their consequences for evolutionary processes have remained elusive. Here, we investigate how metabolic architecture induces resource utilization constraints and how these constraints, in turn, elicit evolutionary specialization and diversification. Guided by the metabolic network structure of the bacterium Lactococcus cremoris, we selected two carbon sources (fructose and galactose) with predicted co-utilization constraints. By evolving L. cremoris on either fructose, galactose or a mix of both sugars, we imposed selection favoring divergent metabolic specializations or co-utilization of both resources, respectively. Phenotypic characterization revealed the evolution of either fructose or galactose specialists in the single-sugar treatments. In the mixed sugar regime, we observed adaptive diversification: both specialists coexisted, and no generalist evolved. Divergence from the ancestral phenotype occurred at key pathway junctions in the central carbon metabolism. Fructose specialists evolved mutations in the fbp and pfk genes that appear to balance anabolic and catabolic carbon fluxes. Galactose specialists evolved increased expression of pgmA (the primary metabolic bottleneck of galactose metabolism) and silencing of ptnABCD (the main glucose transporter) and ldh (regulator/enzyme of downstream carbon metabolism). Overall, our study shows how metabolic network architecture and historical contingency serve to predict targets of selection and inform the functional interpretation of evolved mutations. The elucidation of the relationship between molecular constraints and phenotypic trade-offs contributes to an integrative understanding of evolutionary specialization and diversification.

Global pleiotropic effects in adaptively evolved Escherichia coli lacking CRP reveal molecular mechanisms that define the growth physiology

Evolution facilitates emergence of fitter phenotypes by efficient allocation of cellular resources in conjunction with beneficial mutations. However, system-wide pleiotropic effects that redress the perturbations to the apex node of the transcriptional regulatory networks remain unclear. Here, we elucidate that absence of global transcriptional regulator CRP in Escherichia coli results in alterations in key metabolic pathways under glucose respiratory conditions, favouring stress- or hedging-related functions over growth-enhancing functions. Further, we disentangle the growth-mediated effects from the CRP regulation-specific effects on these metabolic pathways. We quantitatively illustrate that the loss of CRP perturbs proteome efficiency, as evident from metabolic as well as ribosomal proteome fractions, that corroborated with intracellular metabolite profiles. To address how E. coli copes with such systemic defect, we evolved Δcrp mutant in the presence of glucose. Besides acquiring mutations in the promoter of glucose transporter ptsG, the evolved populations recovered the metabolic pathways to their pre-perturbed state coupled with metabolite re-adjustments, which altogether enabled increased growth. By contrast to Δcrp mutant, the evolved strains remodelled their proteome efficiency towards biomass synthesis, albeit at the expense of carbon efficiency. Overall, we comprehensively illustrate the genetic and metabolic basis of pleiotropic effects, fundamental for understanding the growth physiology.

Vitreoscilla Haemoglobin: A Tool to Reduce Overflow Metabolism

Overflow metabolism is a phenomenon extended in nature, ranging from microbial to cancer cells. Accumulation of overflow metabolites pose a challenge for large-scale bioprocesses. Yet, the causes of overflow metabolism are not fully clarified. In this work, the underlying mechanisms, reasons and consequences of overflow metabolism in different organisms have been summarized. The reported effect of aerobic expression of Vitreoscilla haemoglobin (VHb) in different organisms are revised. The use of VHb to reduce overflow metabolism is proposed and studied through flux balance analysis in E. coli at a fixed maximum substrate and oxygen uptake rates. Simulations showed that the presence of VHb increases the growth rate, while decreasing acetate production, in line with the experimental measurements. Therefore, aerobic VHb expression is considered a potential tool to reduce overflow metabolism in cells.

Identification of flux trade-offs in metabolic networks

Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C₃ plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.

Energetic scaling in microbial growth

Microbial growth is a clear example of organization and structure arising in nonequilibrium conditions. Due to the complexity of the microbial metabolic network, elucidating the fundamental principles governing microbial growth remains a challenge. Here, we present a systematic analysis of microbial growth thermodynamics, leveraging an extensive dataset on energy-limited monoculture growth. A consistent thermodynamic framework based on reaction stoichiometry allows us to quantify how much of the available energy microbes can efficiently convert into new biomass while dissipating the remaining energy into the environment and producing entropy. We show that dissipation mechanisms can be linked to the electron donor uptake rate, a fact leading to the central result that the thermodynamic efficiency is related to the electron donor uptake rate by the scaling law [Formula: see text] and to the growth yield by [Formula: see text] These findings allow us to rederive the Pirt equation from a thermodynamic perspective, providing a means to compute its coefficients, as well as a deeper understanding of the relationship between growth rate and yield. Our results provide rather general insights into the relation between mass and energy conversion in microbial growth with potentially wide application, especially in ecology and biotechnology.

Understanding and mathematical modelling of cellular resource allocation in microorganisms: a comparative synthesis

BACKGROUND

The rising consensus that the cell can dynamically allocate its resources provides an interesting angle for discovering the governing principles of cell growth and metabolism. Extensive efforts have been made in the past decade to elucidate the relationship between resource allocation and phenotypic patterns of microorganisms. Despite these exciting developments, there is still a lack of explicit comparison between potentially competing propositions and a lack of synthesis of inter-related proposals and findings.

RESULTS

In this work, we have reviewed resource allocation-derived principles, hypotheses and mathematical models to recapitulate important achievements in this area. In particular, the emergence of resource allocation phenomena is deciphered by the putative tug of war between the cellular objectives, demands and the supply capability. Competing hypotheses for explaining the most-studied phenomenon arising from resource allocation, i.e. the overflow metabolism, have been re-examined towards uncovering the potential physiological root cause. The possible link between proteome fractions and the partition of the ribosomal machinery has been analysed through mathematical derivations. Finally, open questions are highlighted and an outlook on the practical applications is provided. It is the authors' intention that this review contributes to a clearer understanding of the role of resource allocation in resolving bacterial growth strategies, one of the central questions in microbiology.

CONCLUSIONS

We have shown the importance of resource allocation in understanding various aspects of cellular systems. Several important questions such as the physiological root cause of overflow metabolism and the correct interpretation of 'protein costs' are shown to remain open. As the understanding of the mechanisms and utility of resource application in cellular systems further develops, we anticipate that mathematical modelling tools incorporating resource allocation will facilitate the circuit-host design in synthetic biology.

Exploiting unconventional prokaryotic hosts for industrial biotechnology

Developing cost-efficient biotechnological processes is a major challenge in replacing fossil-based industrial production processes. The remarkable progress in genetic engineering ensures efficient and fast tailoring of microbial metabolism for a wide range of bioconversions. However, improving intrinsic properties such as tolerance, handling, growth, and substrate consumption rates is still challenging. At the same time, synthetic biology tools are becoming easier applicable and transferable to nonmodel organisms. These trends have resulted in the exploitation of new and unconventional microbial systems with sophisticated properties, which render them promising hosts for the bio-based industry. Here, we highlight the metabolic and cellular capabilities of representative prokaryotic newcomers and discuss the potential and drawbacks of these hosts for industrial application.

Production of Indole Auxins by Enterobacter sp. Strain P-36 under Submerged Conditions

Bioactive compounds produced by plant growth-promoting bacteria through a fermentation process can be valuable for developing innovative second-generation plant biostimulants. The purpose of this study is to investigate the biotechnological potential of Enterobacter on the production of auxin—a hormone with multiple roles in plant growth and development. The experiments were carried in Erlenmeyer flasks and a 2-L fermenter under batch operating mode. The auxin production by Enterobacter sp. strain P-36 can be doubled by replacing casein with vegetable peptone in the culture medium. Cultivation of strain P36 in the benchtop fermenter indicates that by increasing the inoculum size 2-fold, it is possible to reduce the fermentation time from 72 (shake flask cultivation) to 24 h (bioreactor cultivation) and increase the auxin volumetric productivity from 6.4 to 17.2 mg [IAAequ]/L/h. Finally, an efficient storage procedure to preserve the bacterial auxin was developed. It is noteworthy that by sterilizing the clarified fermentation broth by filtration and storing the filtrated samples at +4 °C, the level of auxin remains unchanged for at least three months.

Functional Analysis of Deoxyhexose Sugar Utilization in Escherichia coli Reveals Fermentative Metabolism under Aerobic Conditions

l-Rhamnose and l-fucose are the two main 6-deoxyhexoses Escherichia coli can use as carbon and energy sources. Deoxyhexose metabolism leads to the formation of lactaldehyde, whose fate depends on oxygen availability. Under anaerobic conditions, lactaldehyde is reduced to 1,2-propanediol, whereas under aerobic conditions, it should be oxidized into lactate and then channeled into the central metabolism. However, although this all-or-nothing view is accepted in the literature, it seems overly simplistic since propanediol is also reported to be present in the culture medium during aerobic growth on l-fucose. To clarify the functioning of 6-deoxyhexose sugar metabolism, a quantitative metabolic analysis was performed to determine extra- and intracellular fluxes in E. coli K-12 MG1655 (a laboratory strain) and in E. coli Nissle 1917 (a human commensal strain) during anaerobic and aerobic growth on l-rhamnose and l-fucose. As expected, lactaldehyde is fully reduced to 1,2-propanediol under anoxic conditions, allowing complete reoxidation of the NADH produced by glyceraldehyde-3-phosphate-dehydrogenase. We also found that net ATP synthesis is ensured by acetate production. More surprisingly, lactaldehyde is also primarily reduced into 1,2-propanediol under aerobic conditions. For growth on l-fucose, ¹³C-metabolic flux analysis revealed a large excess of available energy, highlighting the need to better characterize ATP utilization processes. The probiotic E. coli Nissle 1917 strain exhibits similar metabolic traits, indicating that they are not the result of the K-12 strain's prolonged laboratory use. IMPORTANCE E. coli's ability to survive in, grow in, and colonize the gastrointestinal tract stems from its use of partially digested food and hydrolyzed glycosylated proteins (mucins) from the intestinal mucus layer as substrates. These include l-fucose and l-rhamnose, two 6-deoxyhexose sugars, whose catabolic pathways have been established by genetic and biochemical studies. However, the functioning of these pathways has only partially been elucidated. Our quantitative metabolic analysis provides a comprehensive picture of 6-deoxyhexose sugar metabolism in E. coli under anaerobic and aerobic conditions. We found that 1,2-propanediol is a major by-product under both conditions, revealing the key role of fermentative pathways in 6-deoxyhexose sugar metabolism. This metabolic trait is shared by both E. coli strains studied here, a laboratory strain and a probiotic strain. Our findings add to our understanding of E. coli's metabolism and of its functioning in the bacterium's natural environment.

Evolution of Pseudomonas aeruginosa toward higher fitness under standard laboratory conditions

Identifying genetic factors that contribute to the evolution of adaptive phenotypes in pathogenic bacteria is key to understanding the establishment of infectious diseases. In this study, we performed mutation accumulation experiments to record the frequency of mutations and their effect on fitness in hypermutator strains of the environmental bacterium Pseudomonas aeruginosa in comparison to the host-niche-adapted Salmonella enterica. We demonstrate that P. aeruginosa, but not S. enterica, hypermutators evolve toward higher fitness under planktonic conditions. Adaptation to increased growth performance was accompanied by a reversible perturbing of the local genetic context of membrane and cell wall biosynthesis genes. Furthermore, we observed a fine-tuning of complex regulatory circuits involving multiple di-guanylate modulating enzymes that regulate the transition between fast growing planktonic and sessile biofilm-associated lifestyles. The redundancy and local specificity of the di-guanylate signaling pathways seem to allow a convergent shift toward increased growth performance across niche-adapted clonal P. aeruginosa lineages, which is accompanied by a pronounced heterogeneity of their motility, virulence, and biofilm phenotypes.

Microbial inefficient substrate use through the perspective of resource allocation models

Microorganisms extract energy from substrates following strategies that may seem suboptimal at first glance. Beyond the so-called yield-rate trade-off, resource allocation models, which focus on assigning different functional roles to the limited number of enzymes that a cell can support, offer a framework to interpret the inefficient substrate use by microorganisms. We review here relevant examples of substrate conversions where a significant part of the available energy is not utilised and how resource allocation models offer a mechanistic interpretation thereof, notably for open mixed cultures. Future developments are identified, in particular, the challenge of considering metabolic flexibility towards uncertain environmental changes instead of strict fixed optimality objectives, with the final goal of increasing the prediction capabilities of resource allocation models. Finally, we highlight the relevance of resource allocation to understand and enable a promising biorefinery platform revolving around lactate, which would increase the flexibility of waste-to-chemical biorefinery schemes.

Bacterial fitness landscapes stratify based on proteome allocation associated with discrete aero-types

The fitness landscape is a concept commonly used to describe evolution towards optimal phenotypes. It can be reduced to mechanistic detail using genome-scale models (GEMs) from systems biology. We use recently developed GEMs of Metabolism and protein Expression (ME-models) to study the distribution of Escherichia coli phenotypes on the rate-yield plane. We found that the measured phenotypes distribute non-uniformly to form a highly stratified fitness landscape. Systems analysis of the ME-model simulations suggest that this stratification results from discrete ATP generation strategies. Accordingly, we define "aero-types", a phenotypic trait that characterizes how a balanced proteome can achieve a given growth rate by modulating 1) the relative utilization of oxidative phosphorylation, glycolysis, and fermentation pathways; and 2) the differential employment of electron-transport-chain enzymes. This global, quantitative, and mechanistic systems biology interpretation of fitness landscape formed upon proteome allocation offers a fundamental understanding of bacterial physiology and evolution dynamics.

Enhanced nutrient uptake is sufficient to drive emergent cross-feeding between bacteria in a synthetic community

Interactive microbial communities are ubiquitous, influencing biogeochemical cycles and host health. One widespread interaction is nutrient exchange, or cross-feeding, wherein metabolites are transferred between microbes. Some cross-fed metabolites, such as vitamins, amino acids, and ammonium (NH₄⁺), are communally valuable and impose a cost on the producer. The mechanisms that enforce cross-feeding of communally valuable metabolites are not fully understood. Previously we engineered a cross-feeding coculture between N₂-fixing Rhodopseudomonas palustris and fermentative Escherichia coli. Engineered R. palustris excretes essential nitrogen as NH₄⁺ to E. coli, while E. coli excretes essential carbon as fermentation products to R. palustris. Here, we sought to determine whether a reciprocal cross-feeding relationship would evolve spontaneously in cocultures with wild-type R. palustris, which is not known to excrete NH₄⁺. Indeed, we observed the emergence of NH₄⁺ cross-feeding, but driven by adaptation of E. coli alone. A missense mutation in E. coli NtrC, a regulator of nitrogen scavenging, resulted in constitutive activation of an NH₄⁺ transporter. This activity likely allowed E. coli to subsist on the small amount of leaked NH₄⁺ and better reciprocate through elevated excretion of fermentation products from a larger E. coli population. Our results indicate that enhanced nutrient uptake by recipients, rather than increased excretion by producers, is an underappreciated yet possibly prevalent mechanism by which cross-feeding can emerge.

Carbon Use Efficiency and Its Temperature Sensitivity Covary in Soil Bacteria

The strategy that microbial decomposers take with respect to using substrate for growth versus maintenance is one essential biological determinant of the propensity of carbon to remain in soil. To quantify the environmental sensitivity of this key physiological trade-off, we characterized the carbon use efficiency (CUE) of 23 soil bacterial isolates across seven phyla at three temperatures and with up to four substrates. Temperature altered CUE in both an isolate-specific manner and a substrate-specific manner. We searched for genes correlated with the temperature sensitivity of CUE on glucose and deemed those functional genes which were similarly correlated with CUE on other substrates to be validated as markers of CUE. Ultimately, we did not identify any such robust functional gene markers of CUE or its temperature sensitivity. However, we found a positive correlation between rRNA operon copy number and CUE, opposite what was expected. We also found that inefficient taxa increased their CUE with temperature, while those with high CUE showed a decrease in CUE with temperature. Together, our results indicate that CUE is a flexible parameter within bacterial taxa and that the temperature sensitivity of CUE is better explained by observed physiology than by genomic composition across diverse taxa. We conclude that the bacterial CUE response to temperature and substrate is more variable than previously thought.IMPORTANCE Soil microbes respond to environmental change by altering how they allocate carbon to growth versus respiration-or carbon use efficiency (CUE). Ecosystem and Earth System models, used to project how global soil C stocks will continue to respond to the climate crisis, often assume that microbes respond homogeneously to changes in the environment. In this study, we quantified how CUE varies with changes in temperature and substrate quality in soil bacteria and evaluated why CUE characteristics may differ between bacterial isolates and in response to altered growth conditions. We found that bacterial taxa capable of rapid growth were more efficient than those limited to slow growth and that taxa with high CUE were more likely to become less efficient at higher temperatures than those that were less efficient to begin with. Together, our results support the idea that the CUE temperature response is constrained by both growth rate and CUE and that this partly explains how bacteria acclimate to a warming world.