Exometabolite dynamics over stationary phase reveal strain-specific responses to nutrient limitation

Microbial exponential growth is expected to occur infrequently outside of the laboratory, in the environment. Instead, resource-limited conditions impose non-growth states for microbes. However, non-growth states are uncharacterized for the majority of environmental bacteria, especially in regard to exometabolite production. To investigate exometabolite production in response to nutrient limitation, we compared exometabolites produced over time in stationary phase across three environmental bacteria: Burkholderia thailandensis E264 (ATCC 700388), Chromobacterium violaceum ATCC 31532, and Pseudomonas syringae pathovar tomato DC3000 (ATCC BAA-871). We grew each strain in monoculture and investigated exometabolite dynamics over time from mid-exponential to stationary phase. We focused on exometabolites that were released into the media and accumulated over 45 hours, including approximately 20 hours of stationary phase. In concert, we analyzed transcripts (RNAseq) to inform interpretation of exometabolite output. We found that a majority of exometabolites released under these conditions were strain-specific. A subset of identified exometabolites were involved in both central and secondary metabolism. Transcript analysis supported that exometabolites were released from intact cells, as various transporters were either upregulated or consistently expressed. Interestingly, we found that all strains released succinate, and that each strain re-routed their metabolic pathways involved in succinate production during stationary phase. Overall, these results show that non-growth states can also be metabolically active and dynamic. Furthermore, they show that environmental bacteria have the capability to transform a resource-limited extracellular environment into a rich chemical milieu. This work has implications for understanding microbial community interactions via exometabolites, and within resource-limited environments. Importance Non-growth states are common for bacteria that live in resource-limited environments, and yet these states remain largely uncharacterized in cellular metabolism and metabolite output. Here, we investigated and compared stationary phase exometabolites and RNA transcripts for each of three environmental bacterial strains. We observed that diverse exometabolites were produced and that they collectively exhibited clear and directional dynamics over time. Additionally, each bacteria strain had a characteristic exometabolite profile and dynamic. This work affirms that stationary phase is not at all “stationary” for these bacteria, and sets the stage for understanding how individual metabolisms support interspecies interactions in resource-limited environments.

exometabolites that were released into the media and accumulated over 45 hours, 26 including approximately 20 hours of stationary phase. In concert, we analyzed 27 transcripts (RNAseq) to inform interpretation of exometabolite output. We found that a 28 majority of exometabolites released under these conditions were strain-specific. A 29 subset of identified exometabolites were involved in both central and secondary 30 metabolism. Transcript analysis supported that exometabolites were released from 31 intact cells, as various transporters were either upregulated or consistently expressed. 32 Interestingly, we found that all strains released succinate, and that each strain re-routed 33 their metabolic pathways involved in succinate production during stationary phase. 34 Overall, these results show that non-growth states can also be metabolically active and Non-growth states are common for bacteria that live in resource-limited environments, 42 and yet these states remain largely uncharacterized in cellular metabolism and 43 metabolite output. Here, we investigated and compared stationary phase 44 exometabolites and RNA transcripts for each of three environmental bacterial strains. 45 We observed that diverse exometabolites were produced and that they collectively metabolism. Furthermore, in stationary phase, microbes can re-route metabolic 73 pathways to maintain essential components of the cell and the proton motive force (8). 74 While these adaptations are thought to serve as survival mechanisms, the levels and 75 types of metabolic activities in stationary phase are not well understood for most 76 environmental microbes. 77 It is known, however, that microbes can exhibit appreciable metabolic activity in 78 stationary phase (9). For example, entry into stationary phase resulted in prolonged 79 protein production in Escherichia coli despite that overall protein levels decreased (10). 80 Metabolomic studies of E. coli in stationary phase support that there is continued 81 metabolite production and transformations despite growth arrest (11-13). These studies   We present an investigation of three environmental bacterial strains that are 104 commonly found associated with terrestrial environments (soils or plants) (Table 1).

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These strains were chosen because of reported (19) and observed interactions in the 106 lab. Our previous work established a robust and flexible approach to investigate 107 microbial exometabolite production in either monoculture or co-culture (20). Our 108 approach uses filter plates that allow for the separation of cells from an exometabolite 109 reservoir. Here, we examined the detailed exometabolite and transcript dynamics for 110 each of these three environmental strains over stationary phase, and identified key 111 features of their exometabolomic responses to resource limitation. We found that 112 exometabolite production is dynamic through stationary phase, and that accumulated 113 exometabolites were likely released from intact cells. We also found that a majority of 114 released exometabolites were strain-specific, suggesting that different bacterial strains 115 have individualized responses to resource limitation. Finally, we found that all three 116 strains re-routed metabolic flux in stationary phase.

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Each strain had a distinct exometabolite profile in stationary phase 119 In total, 10,352 features were detected by mass spectral analysis (Table 2,  given the large number of unique features detected for each strain (Table 1). Focusing   Table S2).

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Insights into stationary phase metabolic re-routing 214 We then aimed to interpret strain metabolism in stationary phase by focusing on  Exometabolites could accumulate over stationary phase by two mechanisms.

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Efforts have been put forth to annotate all MS/MS data (38). We used the same 326 approach to computationally predict and classify the chemical ontology of MS/MS data 327 not identified at MSI level 1 or level 2 (Fig. 3). Differences between in silico predictions 328 of MS/MS data (MSI level 3) and MSI levels 1 and 2 was most apparent at the class 329 level (Fig. 3A). This knowledge can be used to direct research efforts and analytical

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Increased studies on growth-limited states will continue to shed light on this 359 predominant microbial physiological state. Even in a simple minimal medium, each 360 strain we studied dynamically altered its environment through the production of a 361 breadth of exometabolites. A limit to our study is the lack of annotated exometabolites.

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Continued advances in mass spectrometry will help to annotate unknown 363 exometabolites to reveal the full extent of exometabolites produced by a microbe. In 364 addition, multi-omic approaches can increase biological insights and inform metabolic 365 models. Combinations of experimental and computational approaches will be useful 366 strategies to manage and predict the response of microorganisms to stress.