Microbes in natural environments often encounter diverse mixtures of organic compounds, yet how mixed substrate environments and their molecular composition shape microbial phenotypes remains understudied. Here, we examined how a defined fungal exudate mimic (FEM) mixture influences growth and metabolism in Pseudomonas putida KT2440 compared to individual substrates matched for total carbon and nitrogen. Growth on FEM initiated 2 h earlier than growth on glucose alone and exhibited both the lowest lag and shortest time to maximum biomass compared to individual substrates. Fructose was the only individual substrate that supported significantly higher maximum biomass than FEM, but exhibited a nearly 15-fold longer lag phase. Gas chromatography mass spectrometry analysis revealed dynamic temporal patterns of substrate utilization within the FEM mixture, with early preferential utilization of malate, followed by overlapping utilization of multiple substrates between 3 and 8 h. By integrating growth and substrate uptake kinetics with genome-scale metabolic modeling and validating model-predicted pathway activity using temporal proteomics, we show that experimentally constrained model predictions accurately captured substrate utilization dynamics across multiple FEM concentrations, and predicted temporal shifts in the dominant substrates supporting growth. Through this integrative experimental-modeling approach, we demonstrate that the mixed substrate FEM environment elicits an emergent growth phenotype characterized by the lowest lag, shortest time to maximum biomass, and relatively high maximum biomass in Pseudomonas putida, a combination of traits not simultaneously reproduced by any individual substrate. IMPORTANCE:How mixed-nutrient substrate environments influence bacterial growth and metabolism is not well understood and is challenging to predictively model. Using Pseudomonas putida KT2440, we show that growth on a defined mixture of substrates inspired by mycorrhizal fungal hyphal exudates produces a distinct and emergent growth phenotype characterized by a lower lag, shorter time to maximum biomass, and relatively high biomass accumulation when compared to individual substrates alone. This combination of growth traits is not simultaneously reproduced by any individual substrate, even when total carbon and nitrogen are matched. By integrating growth measurements and temporal substrate uptake data with dynamic flux balance analysis and proteomics, we demonstrate that metabolic responses to mixed substrates can be quantitatively interpreted. These findings highlight the importance of studying microbes under chemically realistic conditions and suggest that learning from naturally occurring molecular environments may provide new strategies for engineering microbial growth conditions and improving bioprocess performance.
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