Abstract
Microbial mutualistic cross-feeding interactions are ubiquitous and can drive important community functions. Engaging in cross-feeding undoubtedly affects the physiology and metabolism of individual species involved. However, the nature in which an individual’s physiology is influenced by cross-feeding and the importance of those physiological changes for the mutualism have received little attention. We previously developed a genetically tractable coculture to study bacterial mutualisms. The coculture consists of fermentative Escherichia coli and phototrophic Rhodopseudomonas palustris. In this coculture, E. coli anaerobically ferments sugars into excreted organic acids as a carbon source for R. palustris. In return, a genetically-engineered R. palustris constitutively converts N2 into NH4+, providing E. coli with essential nitrogen. Using RNA-seq and proteomics, we identified transcript and protein levels that differ in each partner when grown in coculture versus monoculture. When in coculture with R. palustris, E. coli gene-expression changes resembled a nitrogen starvation response under the control of the transcriptional regulator NtrC. By genetically disrupting E. coli NtrC, we determined that a nitrogen starvation response is important for a stable coexistence, especially at low R. palustris NH4+ excretion levels. Destabilization of the nitrogen starvation regulatory network resulted in variable growth trends and in some cases, extinction. Our results highlight that alternative physiological states can be important for survival within cooperative cross-feeding relationships.
Importance Mutualistic cross-feeding between microbes within multispecies communities is widespread. Studying how mutualistic interactions influence the physiology of each species involved is important for understanding how mutualisms function and persist in both natural and applied settings. Using a bacterial mutualism consisting of Rhodopseudomonas palustris and Escherichia coli growing cooperatively through bidirectional nutrient exchange, we determined that an E. coli nitrogen starvation response is important for maintaining a stable coexistence. The lack of an E. coli nitrogen starvation response ultimately destabilized the mutualism and, in some cases, led to community collapse after serial transfers. Our findings thus inform on the potential necessity of an alternative physiological state for mutualistic coexistence with another species compared to the physiology of species grown in isolation.
Introduction
Within diverse microbial communities, species engage in nutrient cross-feeding with reciprocating partners as a survival strategy (1). In cases where species are not obligate mutualists, transitioning from a free-living lifestyle to one based on cross-feeding can change the physiological state of the cells involved, the extent to which depends on the nature of the cross-feeding relationship. For example, cross-feeding can promote physiological changes that increase virulence (2, 3) or drastically alter cellular metabolism (4), in some cases allowing for lifestyles that are only possible during mutualistic growth with a partner (4–7). Aside from these examples, relatively little is known about how cell physiology is influenced by mutualistic cross-feeding, despite the prevalence of cross-feeding in microbial communities.
Synthetic communities, or cocultures, are ideally suited for studying the physiological responses to cooperative cross-feeding given their tractability (8, 9). We previously developed a bacterial coculture that consists of fermentative Escherichia coli and the N2-fixing photoheterotroph Rhodopseudomonas palustris (Fig. 1) (10). In this coculture, E. coli anaerobically ferments glucose into organic acids, providing R. palustris with essential carbon. In return, a genetically engineered R. palustris strain (Nx) constitutively fixes N2 gas, resulting in NH4+ excretion that provides E. coli with essential nitrogen. The result is an obligate mutualism that maintains a stable coexistence and reproducible growth trends (10) as long as bidirectional nutrient cross-feeding levels are maintained within a defined range (11, 12).
Here we determined how nutrient cross-feeding between E. coli and R. palustris Nx alters the physiological state of each partner population. Using RNA-seq and proteomic analyses, we identified genes in both species that were differentially expressed in coculture compared to monoculture, with E. coli exhibiting more overall changes in gene expression than R. palustris Nx. Specifically, E. coli gene-expression patterns resembled that of nitrogen-deprived cells, as many upregulated genes were within the nitrogen-starvation response regulon, controlled by the master transcriptional regulator NtrC. Genetic disruption of E. coli ntrC resulted in variable growth trends at low R. palustris NH4+ excretion levels and prevented long-term mutualistic coexistence with R. palustris across serial transfers. Our results highlight the fact that cross-feeding relationships can stimulate alternative physiological states for at least one of the partners involved and that adjusting cell physiology to these alternative states can be critical for maintaining coexistence.
Results
Engaging in an obligate mutualism alters the physiology of cooperating partners
In our coculture, E. coli and R. palustris Nx carry out complementary anaerobic metabolic processes whose products serve as essential nutrients for the respective partner. Specifically, E. coli ferments glucose into acetate, lactate, and succinate, which serve as carbon sources for R. palustris Nx, while other fermentation products such as formate and ethanol accumulate; in return R. palustris Nx fixes N2 and excretes NH4+ as the nitrogen source for E. coli (Fig. 1). We previously demonstrated that our coculture supports a stable coexistence and exhibits reproducible growth and metabolic trends when started from a wide range of starting species ratios, including single colonies (10). However, we hypothesized that coculture conditions would affect the physiology of each species, particularly E. coli, based on the following observations. First, as growth is coupled in our coculture, E. coli is forced to grow 4.6-times slower in coculture with R. palustris Nx than it does in monoculture with abundant NH4+ due to slow NH4+ cross-feeding from R. palustris Nx (10). In contrast, R. palustris Nx grows at a rate in coculture that is comparable to that in monoculture (12), consuming a mixed pool of excreted organic acids from E. coli. Second, coculturing pulls E. coli fermentation forward due to removal of inhibitory end products. For example, we observed higher yields of formate, an E. coli fermentation product that R. palustris does not consume, in cocultures compared to E. coli monocultures (10).
To determine changes in gene-expression patterns imposed by coculturing, we performed RNA-seq and comparative proteomic analyses (13) on exponential phase cocultures and monocultures of E. coli and R. palustris Nx. To make direct comparisons, all cultures were grown in the same basal anaerobic minimal medium, and monocultures were supplemented with the required carbon or nitrogen sources to permit growth for each species. Cocultures and E. coli monocultures were provided glucose as a sole carbon source, whereas a mixture of organic acids and bicarbonate was provided to R. palustris Nx monocultures, as R. palustris does not consume glucose. For a nitrogen source, all cultures were grown under a N2 headspace, and E. coli monocultures were further supplemented with NH4Cl, as E. coli is incapable of using N2. We identified several differentially expressed genes between monoculture and coculture conditions in both species with more differences observed in E. coli compared to R. palustris Nx, in agreement with our initial hypothesis (Fig. 2). For E. coli, out of 4377 ORFs, 55 were upregulated and 68 were downregulated (Table 1) (log2 value cutoff=2). Out of 4836 ORFs in R. palustris Nx, 14 were upregulated and 20 were downregulated (Table 1) (log2 value cutoff=2). We also considered that due to lower E. coli abundance in coculture, the apparently larger E. coli gene response may be partly due to decreased resolution and thus increased error variance. Reassuringly, many of the genes identified as being differentially expressed by RNA-seq were in agreement with the proteomic results (Table 2). Both RNA-seq and proteomic analyses identified the E. coli ammonium transporter AmtB as an important, upregulated gene in coculture, corroborating our previous findings that E. coli AmtB activity is important for stable coexistence with R. palustris (12). Many E. coli genes involved in amino acid and purine biosynthesis were downregulated in coculture (Table 1, Table 2), consistent with the lower observed growth rate. Additionally, many E. coli flagellar and chemotaxis proteins were downregulated in coculture (Table 1, Table 2), perhaps suggesting that motility is not important for coculture growth. Alternatively, lower flagellar and chemotaxis transcript levels could be part of a general stress response (14), perhaps associated with nitrogen limitation in cocultures. Whereas many of the differentially expressed E. coli genes have been characterized in the literature, the R. palustris genes showing the largest differential expression were uncharacterized genes encoding upregulated putative alcohol/aldehyde dehydrogenases and a downregulated putative TonB-dependent receptor/siderophore (Table 1, Table 2). Together, these datasets provide insight on how engaging in obligate cross-feeding changes the lifestyle of each partner.
An E. coli nitrogen starvation response is important for mutualistic growth with R. palustris
We chose to further examine differential gene expression patterns in E. coli as its growth rate and fermentation profile are drastically affected by coculturing, whereas the R. palustris Nx growth rate is similar to that in monoculture. We identified several E. coli genes and proteins that were upregulated in coculture with R. palustris Nx compared to monoculture growth (Table 1, Table 2). We hypothesized that the deletion of highly upregulated E. coli genes would negatively affect its growth in coculture. We made deletions in E. coli genes that were identified in both RNA-seq and proteome datasets as well as the highest upregulated E. coli transcript (rutA). We did not examine the effect of deleting amtB in this case as we previously determined it to be important for coculture growth (12). These selected E. coli genes were all involved in metabolism of alternative nitrogen sources such as D-ala-D-ala dipeptides (ddpX, ddpA) (15), pyrimidines (rutA) (16), amino acids (argT) (17), and polyamines (patA, potF) (18). In monocultures with 15mM NH4C1, there were negligible differences in growth or fermentation profiles between WT E. coli and any of the single deletion mutants (Fig. S1). These results are consistent with findings by others, as these genes are only important when scavenging alternative nitrogen sources that are not present in our defined medium. We next tested these E. coli mutants in coculture with R. palustris Nx to determine if these genes were important when NH4+ is slowly cross-fed from R. palustris Nx. All cocultures using the E. coli mutants paired with R. palustris Nx exhibited similar growth and population trends to cocultures with WT E. coli (Fig. 3). Additionally, there were no significant differences in the growth rates, growth yields, or product yields from cocultures containing the E. coli mutants (Fig. S2). These data suggest that none of these highly expressed E. coli genes are solely important for coculture growth. While it is possible that synergistic expression of these genes is important for E. coli’s lifestyle in coculture, the actual nitrogen sources accessed by expression of these genes are absent in the defined medium. Thus, unless E. coli gains access to alternative nitrogen sources that we are unaware of in coculture with R. palustris Nx, synergistic expression of these genes likely provides little to no benefit.
Even though individual deletions of the E. coli genes showing high expression in coculture had no effect on coculture trends, we noted that they were all involved in nitrogen scavenging and fell within the regulon of the transcription factor, NtrC, which controls the nitrogen starvation response (19). During nitrogen limitation, the sensor kinase NtrB phosphorylates the response regulator NtrC (19). Phosphorylated NtrC then binds to DNA and activates expression of ∼45 genes (20), including those we tested genetically above and amtB, which we previously determined to be important for coculture growth (12). To examine the importance of the E. coli nitrogen starvation response in coculture, we deleted ntrC. We first checked for any general defects of the resulting ΔNtrC mutant in monoculture with 15 mM NH4Cl and found that it exhibited similar growth and metabolic trends to WT E. coli (Fig. S3). We then paired E. coli ΔNtrC with R. palustris Nx in coculture. Compared to cocultures using WT E. coli, cocultures with E. coli ΔNtrC exhibited slower growth rates, longer lag periods (Fig. 4A), and lower final E. coli cell densities (Fig. 4D). The long lag phase was less prominent in cocultures inoculated from single colonies (Fig. S4A) compared to cocultures inoculated with a 1% dilution of stationary cocultures (Fig. 4A). This result suggests that starting E. coli ΔNtrC cocultures from single colonies stimulated early growth, perhaps by increasing the E. coli frequency to be similar to that of R. palustris when started with colonies of similar sizes rather than a dilution of stationary cocultures wherein the E. coli frequency was low (∼0.1%; Fig. 4D). A higher initial E. coli frequency might help E. coli acquire excreted NH4+ before it is taken back up by R. palustris cells and thereby promote reciprocal cross-feeding, similar to what we observed previously in cocultures with E. coli ΔAmtB mutants that were defective for NH4+ uptake (12).
The overall coculture metabolism was also altered when E. coli ΔNtrC was paired with R. palustris Nx. In cocultures pairing WT E. coli with R. palustris Nx, glucose is typically fully consumed within 5 days coinciding with the accumulation of formate and ethanol (10). Cocultures pairing E. coli ΔNtrC with R. palustris Nx differed in this regard, leaving ∼40% of the glucose unconsumed after 10 days and exhibiting little to no formate and ethanol accumulation (Fig. S4B). Even despite the lower glucose consumption, the final R. palustris cell density of cocultures pairing R. palustris Nx with E. coli ΔNtrC was similar to those with WT E. coli. This unexpectedly high cell density could be explained by consumption of formate and ethanol by R. palustris Nx, though we have never observed consumption of formate by R. palustris Nx in monoculture. Alternatively, a lack of formate and/or ethanol production by E. coli could explain the high cell density if the fermentation profile were shifted towards organic acids that R. palustris normally consumes, namely acetate, lactate and succinate. Together, these data indicate that misregulation of the nitrogen starvation response affected coculture growth and metabolism.
As noted above, the low E. coli ΔNtrC population and decreased coculture growth rate when paired with R. palustris Nx resembled trends from cocultures that contained E. coli ΔAmtB mutants (12). We previously found that the E. coli NH4+ transporter, AmtB, was required for coexistence with R. palustris Nx across serial transfers as the transporter gives E. coli a competitive advantage in acquiring the transiently available NH4+ before it can be reclaimed by the R. palustris population (12). To determine if E. coli ΔNtrC was capable of maintaining a stable coexistence in coculture, we inoculated cocultures of E. coli ΔNtrC paired with R. palustris Nx at equivalent CFUs and performed serial transfers every 10 days. While average final E. coli frequencies were consistently between 0.6 – 2.8 % (Fig. 5A), the values became variable over serial transfers, as did coculture growth rates, lag periods, and net changes in both E. coli and R. palustris cell densities (Fig. 5). This variability was due to 2 of the 4 lineages exhibiting improved coculture growth over successive transfers Fig. 5B, C), perhaps due to the emergence of compensatory mutations, while the other two lineages showed declining growth trends (Fig. 5D, E). Indeed, by transfers 5 and 6 there was little to no coculture growth in the slower-growing lineages (Fig 4D, E). The heterogeneity in growth trends through serial transfers of cocultures with E. coli ΔNtrC is in stark contrast to the stability of cocultures with WT E. coli, which we have serially transferred over 100 times with no extinction events (McKinlay, unpublished data). The nitrogen starvation response thus appears to be important for long-term survival of the mutualism.
Increased NH4+ cross-feeding levels can compensate for the absence of a nitrogen starvation response
The NtrC regulon is critical during periods of nitrogen starvation, activating a wide variety of genes that are important for scavenging diverse nitrogen sources (20). We hypothesized that higher R. palustris NH4+ cross-feeding levels could mitigate the poor growth of E. coli ΔNtrC in coculture by making the nitrogen starvation response less important for survival. Previously, we engineered an R. palustris Nx strain that excretes 3-times more NH4+ by deleting R. palustris NH4+ transporters encoded by amtBl and amtB2 (NxΔAmtB) (10). N2-fixing bacteria use AmtB to reacquire NH4+ that leaks outside the cell, and ΔAmtB mutants thus accumulate NH4+ into the supernatant (10, 12, 21). In agreement with our hypothesis, cocultures with R. palustris NxΔAmtB exhibited similar growth trends regardless of the E. coli strain used (Fig. 4B, D). As R. palustris NxΔAmtB excretes more NH4+ than R. palustris Nx, it was previously shown to result in faster WT E. coli growth and subsequent fermentation rates in coculture, ultimately leading to the accumulation of consumable organic acids (Fig. S4B) and acidification of the medium, inhibiting R. palustris growth (10). Cocultures pairing R. palustris NxΔAmtB and E. coli ΔNtrC similarly exhibited growth (Fig. 4B,D), and fermentation profile trends (Fig. S4B) that were indistinguishable from cocultures pairing R. palustris NxΔAmtB with WT E. coli. These similar trends indicate that high R. palustris NH4+ excretion can eliminate the trends observed when the E. coli nitrogen starvation response is compromised due to a ΔNtrC mutation.
One possibility for why high NH4+ cross-feeding levels eliminate the need for E. coli ntrC is that the free NH4+ levels might be sufficiently high enough to prevent activation of the E. coli NtrC regulon. However, comparative RNA-seq and proteomic analyses revealed that the same E. coli genes within the NtrC regulon that were highly upregulated in cocultures pairing WT E. coli with R. palustris Nx were also upregulated in cocultures with R. palustris NxΔAmtB (Table 1, Table 2). Thus, even though the E. coli nitrogen-starvation response is activated when cocultured with R. palustris NxΔAmtB, this response is likely dispensable if there is sufficiently high NH4+ cross-feeding.
E. coli NtrC is required for adequate AmtB expression to access cross-fed NH4+ in coculture
While a high level of R. palustris NH4+ excretion can compensate for an improper E. coli nitrogen-starvation response, less NH4+ excretion could potentially exaggerate problems emerging from the absence of NtrC. We previously constructed an R. palustris ΔAmtB strain that excreted 1/3rd of the NH4+ than R. palustris Nx in monoculture and which could not coexist in coculture with E. coli ΔAmtB (12). The reason for this lack of coexistence was due to R. palustris ΔAmtB outcompeting E. coli ΔAmtB for the lower level of transiently available NH4+, thus limiting E. coli growth and thereby the reciprocal supply of fermentation products to R. palustris (12). Expression of E. coli amtB is thus important in coculture in order to maintain coexistence. Indeed, RNA-seq and proteomic analyses revealed that E. coli AmtB transcript and protein levels were upregulated in all cocultures pairing WT E. coli with any of the three R. palustris strains (Nx, NxΔAmtB, ΔAmtB) (Table 1, Table 2). We thus wondered whether E. coli ΔNtrC would coexist with the low NH4+-excreting strain R. palustris ΔAmtB in coculture, as E. coli amtB expression is transcriptionally activated by NtrC. Consistent with our previous findings, R. palustris ΔAmtB supported a high relative WT E. coli population in coculture (Fig. 4D) (12). When cocultured with WT E. coli, R. palustris ΔAmtB responds to NH4+ loss to E. coli by upregulating nitrogenase activity since it has a wildtype copy of NifA (12). As a result, R. palustris ΔAmtB cross-feeds enough NH4+ to stimulate a high WT E. coli frequency and subsequent accumulation of consumable organic acids, similar to cocultures with R. palustris NxΔAmtB (Fig 3D, Fig. S4B) (12). In contrast, when we paired E. coli ΔNtrC with R. palustris ΔAmtB, little to no coculture growth was observed (Fig. 4C), similar to previous observations in cocultures pairing E. coli ΔAmtB with R. palustris ΔAmtB (12). Cocultures inoculated with single colonies of each species in this pairing grew to low cell densities Fig. S4A), and cocultures inoculated from these cocultures resulted in little to no growth, even after prolonged incubation (Fig. 4C).
As AmtB is under the control of NtrC (20), we hypothesized that cocultures pairing E. coli ΔNtrC with R. palustris ΔAmtB resulted in insufficient E. coli amtB expression, leading to a decreased ability to capture NH4+, which R. palustris will reaquire if given the chance (12). We thus predicted that increased expression of amtB in E. coli ΔNtrC would result in increased net growth of both species, as E. coli ΔNtrC would be more competitive for essential NH4+ and be able to grow and produce more organic acids for R. palustris ΔAmtB. To test this prediction, we obtained a plasmid harboring an IPTG-inducible copy of amtB (pamtB) for use in E. coli ΔNtrC. AmtB is typically tightly regulated and only expressed when NH4+ concentrations are below 20 µM, as cells acquire sufficient NH4+ through passive diffusion of NH3 across the membrane at higher concentrations (22). Additionally, excessive NH4+ uptake through AmtB transporters that exceeds the rate of assimilation can result in a futile cycle, as excess NH3 inevitably diffuses outside the cell (19). We first tested the effect of pamtB in WT E. coli monocultures with 15 mM NH4CL Induction with 1 mM IPTG prevented growth whereas 0.1 mM IPTG permitted growth albeit at a decreased growth rate (Fig. S5). We thus decided to use 0.1 mM IPTG to induce amtB expression in all cocultures described below. In cocultures pairing E. coli ΔNtrC pamtB with R. palustris ΔAmtB, more growth was observed than in cocultures with E. coli ΔNtrC harboring an empty vector (pEV) (Fig. 6A). In cocultures with E. coli ΔNtrC pEV, the R. palustris ΔAmtB cell density increased whereas the E. coli cell density did not (Fig. 6B). The R. palustris growth was likely due to growth-independent cross-feeding of fermentation products from E. coli maintenance metabolism, a phenomenon we described previously (11). In contrast, cell densities of both species increased in cocultures pairing R. palustris ΔAmtB with E. coli ΔNtrC pamtB (Fig. 6C), in agreement with our hypothesis that poor E. coli amtB expression contributed to the lack of growth in this coculture pairing. While E. coli amtB expression in this coculture pairing was sufficient to restore growth of both species, there are likely other genes within the NtrC regulon that contribute to E. coli growth in coculture. For example, the E. coli NtrC-regulated serine/threonine kinase yeaG has been shown to play a role in survival during nitrogen starvation by promoting metabolic heterogeneity (23). Indeed, E. coli yeaG and its associated protein of unknown function yeaH are both highly upregulated in coculture (Table 1). Thus, while we cannot rule out that other genes within the E. coli ntrC regulon are not important for coculture growth, the necessity of NtrC to upregulate amtB is clearly important.
Discussion
In this study, we found that reciprocal nutrient cross-feeding between E. coli and R. palustris resulted in significant changes in gene expression in both species compared to monocultures. Based on the RNA-seq and proteomic analyses, we determined that E. coli alters its physiology to adopt a nitrogen-starved state in response to low NH4+ cross-feeding levels from R. palustris. We subsequently determined that this nitrogen-starved state is important for coexistence as genetic elimination of the master transcriptional regulator, NtrC, resulted in variable population outcomes. Mutualistic nutrient cross-feeding has also been shown to change the lifestyle of interacting partners in other systems. In natural communities, nutrient cross-feeding can alter gene-expression patterns to adapt each species to a syntrophic lifestyle (24–27). In some cases, the lifestyles exhibited within a mutualism might not even be possible during growth in isolation. For example, in synthetic communities that pair the sulfate-reducer Desulfovibiro vulgaris with the methanogen Methanococcus maripaludis, the methanogen consumes H2, which maintains low partial pressures that permit the sulfate reducer to adopt a fermentative lifestyle that would otherwise be thermodynamically infeasible (5). Similarly, in an experimental Geobacter coculture, direct electron transfer from Geobacter metallireducens to Geobacter sulfurreducens makes ethanol fermentation by G. metallireducens thermodynamically possible (7).
Similar to our mutualistic system, the mutualism between D. vulgaris and M. maripaludis represents a facultative mutualism, at least in the short term prior to evolutionary erosion of independent lifestyles (28). For mutualistic relationships to persist between partners that are conditionally capable of a free-living lifestyle, the relationship must exhibit resilience, or the ability to recover its function after a disturbance (29). One important resilience factor is the activation of regulatory networks that allow for microbes to quickly respond to environmental perturbations. Whereas flexible gene expression is useful for an individual microbe’s survival, excessive flexibility can sometimes lead to community collapse between mutualists in a fluctuating environment (30, 31). In the coculture of D. vulgaris and M. maripaludis, alternating between coculture and monoculture conditions, which require different metabolic lifestyles, resulted in community collapse (30, 31). Surprisingly, community collapse could be avoided by mutations that disrupted the D. vulgaris regulatory response needed to adapt cells for optimal growth rates in monoculture (30). Disruption of this regulatory response resulted in a heterogeneous D. vulgaris population, ensuring that a subpopulation would be primed for immediate mutualistic growth upon transition between growth conditions (31). In our system, the E. coli nitrogen starvation regulatory network was specifically activated by coculturing with R. palustris and was important for coculture stability. It is currently unclear if transitioning E. coli between monoculture and coculture conditions would result in similar community collapse or whether the NtrC-regulated network would adjust rapidly enough to meet the demands of each condition.
Nutrient starvation and other stress responses are widely conserved in diverse microbes and are primarily regarded as necessary for an individual’s survival in nutrient-limited environments (32–35). Many microbial communities are composed of primarily slow-growing or even non-growing subpopulations (36–38). However, lack of microbial growth in these communities does not imply cessation of cross-feeding, as bacteria often carry out growth-independent maintenance processes at slow rates (39), and such activities can be coupled to cross-feeding (11). Our findings suggest that nutrient starvation and perhaps other stress responses can help stabilize microbial cross-feeding interactions, especially at low nutrient cross-feeding levels. The extent to which specific starvation or stress responses are active in diverse mutualistic relationships remains unclear, yet likely depends on the environmental context. Together our results highlight the important role that alternate physiological states, including stress responses, can play in establishing and maintaining mutualistic cross-feeding relationships.
Materials and Methods
Strains and growth conditions
Strains, plasmids, and primers are listed in Table S1. All R. palustris strains contained ΔuppE and ΔhupS mutations to facilitate accurate colony forming unit (CFU) measurements by preventing cell aggregation (40) and to prevent H2 uptake, respectively. E. coli was cultivated on Luria-Burtani (LB) agar and R. palustris on defined mineral (PM) (41) agar with 10 mM succinate. (NH4)2SO4 was omitted from PM agar for determining R. palustris CFUs. Monocultures and cocultures were grown in 10 mL of defined M9-derived coculture medium (MDC) (10) in 27-mL anaerobic test tubes under 100% N2 as described (10). For harvesting RNA and protein, 100-mL cultures were grown in 260-mL serum vials. In both cases, MDC was supplemented with cation solution (1 % v/v; 100 mM MgSO4 and 10 mM CaCl2) and glucose (25 mM), unless indicated otherwise. R. palustris monocultures were further supplemented with 15 mM sodium bicarbonate, 7.8 mM sodium acetate, 8.7 mM disodium succinate, 1.5 mM sodium lactate, 0.3 mM sodium formate, and 6.7mM ethanol. E. coli monoculturas were further supplemented with 2.5 mM NH4CL Kanamycin was added to a final concentration of 30 µg/ml for E. coli where appropriate. Chloramphenicol was added to a final concentration of 5 µg/ml for both R. palustris and E. coli where appropriate. All cultures were grown at 30°C laying horizontally under a 60 W incandescent bulb with shaking at 150 rpm. Starter cocultures were inoculated with 200 µL MDC containing a suspension of a single colony of each species. Test cocultures and serial transfers were inoculated using a 1% dilution from starter cocultures. For experiments requiring a starting species ratio of 1:1, E. coli and R. palustris starter monocultures were grown to equivalent cell densities, and inoculated at equal volumes.
Generation of E. coli mutants
P1 transduction (42) was used to introduce deletions from Keio collection strains into MG1655. The genotype of kanamycin-resistant colonies was confirmed by PCR and sequencing.
Analytical procedures
Cell density was assayed by optical density at 660 nm (OD660) using a Genesys 20 visible spectrophotometer (Thermo-Fisher, Waltham, MA, USA). Growth curve readings were taken in culture tubes without sampling (i.e., tube OD660). Specific growth rates were determined using readings between 0.1-1.0 OD660 where there is linear correlation between cell density and OD660. Final OD660 measurements were taken in cuvettes and samples were diluted into the linear range as necessary. Glucose, organic acids, formate and ethanol were quantified using a Shimadzu high-performance liquid chromatograph (HPLC) as described (43).
Sample collection for transcriptomics and proteomics
Monocultures and cocultures were grown in 100-mL volumes to late exponential phase and chilled in an ice-water bath. A 1-mL sample was collected for protein quantification using a Pierce BCA Protein Assay Kit as per the manufacturer’s protocol. A 5- ml sample was removed for RNA extraction and 90 ml was used for proteomic analysis. All samples were centrifuged at 4°C, supernatants discarded, and cell pellets frozen in liquid N2 and stored at −80°C.
RNA-seq
Total RNA was isolated from cell pellets using the RNeasy kit (Qiagen, Valencia, CA, USA) as per the manufacturer’s protocol. In order to calculate baseline expression levels, RNA sequencing reads resulting from monoculture were mapped to their corresponding reference genome (E. coli str. K-12 substr. MG1655 (44), NCBI RefSeq: NC_000913.3; R. palustris CGA0009 (45), NCBI RefSeq: NC_005296.1) using the Tuxedo protocol for RNA expression analysis (46) (Workflow deposited at https://github.com/behrimg/Task3/RNASeq). Specifically, split-reads were aligned to the reference genome with Tophat2 (v.2.1.0) (47) and Bowtie2 (v.2.1.0) (48). Following mapping, transcripts were assembled with cufflinks (v.2.2.0) (49), and differential expression was identified with the cufflinks tool, cuffdiff (v.2.2.0). To assure that crossmapping of homologous sequencing reads would not complicate expression analysis from the co-culture experiments, monoculture reads were additionally mapped as described to the opposing genome. As all potential crossmapping was confined to residual rRNA reads, these regions were excluded from the analysis and the co-culture RNA-seq reads where analyzed by mapping the sequenced reads to both reference genomes with no further correction.
Preparation of protein samples for MS
Cell pellets were resuspended in 1 mL total protein buffer (TPB; 20mM HEPES-NaOH pH7.4, 150mM NaCl, 2mM EDTA, 0.2mM DTT, 1:100 PMSF, 1:100 protease inhibitors cocktail IV) and sonicated at 20% intensity (7 seconds on, 7 seconds off) for 5 min in an ice bath. Then 1/10 volume of 20% SDS was added. Samples were vortexed, boiled for 5 min, and immediately placed on ice. Debris was cleared by centrifuging for 30 s at 10,000 × g at 4°C and the supernatant was collected. Protein content of different lysates was analyzed by Coomassie staining following SDS-PAGE and sample aliquots containing 200 µg protein were subjected to chloroform:methanol protein extraction as described (50).
Analysis by LC-MS/MS
Mass spectrometry was performed at the Mass Spectrometry and Proteomics Research Laboratory (MSPRL), FAS Division of Science, at Harvard University. Samples were individually labeled with tandem mass tag (TMT) 10-plex reagents according to the manufacturer’s protocol (ThermoFisher Scientific) and mixed. The mixed sample was dried in a speedvac and re-diluted with Buffer A (0.1 % formic acid in water) for injection for HPLC runs. The sample was submitted for a single liquid chromatography coupled to tandem mass spectrometry (LC-MS/MS) experiment which was performed on a LTQ Orbitrap Elite (ThermoFisher Scientific) equipped with Waters (Milford, MA) NanoAcquity HPLC pump Peptides were separated onto a 100 µm inner diameter microcapillary trapping column packed first with approximately 5 cm of C18 Reprosil resin (5 µm, 100 Å, Dr. Maisch GmbH, Germany) followed by analytical column ∼20 cm of Reprosil resin (1.8 µm, 200 Å, Dr. Maisch GmbH, Germany). Separation was achieved through applying a gradient from 5—27% ACN in 0.1% formic acid over 90 min at 200 nl min-1. Electrospray ionization was enabled through applying a voltage of 1.8 kV using a home-made electrode junction at the end of the microcapillary column and sprayed from fused silica pico tips (New Objective, MA). The LTQ Orbitrap Elite was operated in data-dependent mode for the mass spectrometry methods. The mass spectrometry survey scan was performed in the Orbitrap in the range of 395 —1,800 m/z at a resolution of 6 × 104, followed by the selection of the twenty most intense ions (TOP20) for CID-MS2 fragmentation in the ion trap using a precursor isolation width window of 2 m/z, AGC setting of 10,000, and a maximum ion accumulation of 200 ms. Singly charged ion species were not subjected to CID fragmentation. Normalized collision energy was set to 35 V and an activation time of 10 ms. Ions in a 10 ppm m/z window around ions selected for MS2 were excluded from further selection for fragmentation for 60 s. The same TOP20 ions were subjected to HCD MS2 event in Orbitrap part of the instrument. The fragment ion isolation width was set to 0.7 m/z, AGC was set to 50,000, the maximum ion time was 200 ms, normalized collision energy was set to 27V and an activation time of 1 ms for each HCD MS2 scan.
Mass spectrometry data analysis
Raw data were submitted for analysis in MaxQuant 1.5.6.5 (13). Assignment of MS/MS spectra was performed by searching the data against a protein sequence database including all entries from the E. coli MG1655 proteome (51), the R. palustris CGA009 proteome (45), and other known contaminants such as human keratins and common lab contaminants. MaxQuant searches were performed using a 20 ppm precursor ion tolerance with a requirement that each peptide had N termini consistent with trypsin protease cleavage, allowing up to two missed cleavage sites. 10-plex TMT tags on peptide amino termini and lysine residues were set as static modifications while methionine oxidation and deamidation of asparagine and glutamine residues were set as variable modifications. MS2 spectra were assigned with a false discovery rate (FDR) of 1% at the protein level by target-decoy database search. Per-peptide reporter ion intensities were exported from MaxQuant (evidence.txt). Only peptides with a parent ion fraction greater than or equal to 0.5 were used for subsequent analysis (6063 of 9987 peptides). Intensities were calculated as the sum of peptide intensities. Ratios between conditions were computed at the peptide level, and the protein ratio was computed as the mean of peptide ratios. All ratios were normalized by dividing by the median value for proteins from the same species. Ratio significance for coculture conditions at an FDR of 1% was computed by determining the ratio r at which 99% of genes have ratio less than r when comparing biological replicate monocultures.
Expression of E. coli amtB in coculture
The ASKA collection (52) plasmid harboring an IPTG- inducible copy of amtB (pCA24N amtB) was purified from strain JW0441-AM and introduced by electroporation into WT E. coli and E. coli ΔNtrC. Cocultures were inoculated with either single colonies of each species or at a 1:1 starting species ratio, as indicated in the figure legends. IPTG and 5 µg/ml chloramphenicol were supplemented to cocultures to induce E. coli amtB expression in cocultures and maintain the plasmid, respectively.
Acknowledgments
We thank B. A. Budnik and R. A. Robins (Harvard MSPRL) for assistance with mass spectrometry.
We thank P. L. Foster for providing the Keio and ASKA E. coli collections. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Biological and Environmental Research under Award Number DE-SC0008131 to JBM, by the U.S. Army Research Office, grant W911NF-14-1-0411 to ML, DAD, and JBM, by a National Institutes of Health National Service Award F32GM123703 to MGB, and by the Indiana University College of Arts and Sciences.
Footnotes
Conflict of interest. The authors declare no conflict of interest