Metabolite exchange among co-growing cells is frequent by nature, however, is not necessarily occurring at growth-relevant quantities indicative of non-cell-autonomous metabolic function. Complementary auxotrophs of Saccharomyces cerevisiae amino acid and nucleotide metabolism regularly fail to compensate for each other's deficiencies upon co-culturing, a situation which implied the absence of growth-relevant metabolite exchange interactions. Contrastingly, we find that yeast colonies maintain a rich exometabolome and that cells prefer the uptake of extracellular metabolites over self-synthesis, indicators of ongoing metabolite exchange. We conceived a system that circumvents co-culturing and begins with a self-supporting cell that grows autonomously into a heterogeneous community, only able to survive by exchanging histidine, leucine, uracil, and methionine. Compensating for the progressive loss of prototrophy, self-establishing communities successfully obtained an auxotrophic composition in a nutrition-dependent manner, maintaining a wild-type like exometabolome, growth parameters, and cell viability. Yeast, as a eukaryotic model, thus possesses extensive capacity for growth-relevant metabolite exchange and readily cooperates in metabolism within progressively establishing communities.https://doi.org/10.7554/eLife.09943.001
Life is sustained by an array of chemical reactions that is collectively referred to as metabolism. Some of these reactions break down complex substances to release energy and vital compounds, while others make new molecules from smaller building blocks.
Bacterial communities are regularly composed of heterogeneous species, several of which have lost one or more essential metabolic pathways. Nevertheless, these cells can still survive by making use of metabolic products released by their neighbouring cells.
Yeast are single-celled fungi that also form colonies and, as eukaryotes, they possess cells that are more similar to our own. However, in the laboratory, complementary metabolically deficient yeast cells do not survive when mixed together. It was presumed this is because yeast cells make only enough of each essential metabolite for themself, and so can’t replace those that are missing from their neighbouring cells. Campbell et al. now challenge this view by finding that yeast cells release a variety of metabolites, they use these released metabolites in preference to making their own, and possess the capacity to grow on the basis of a non-cell-autonomous metabolism.
This discovery came with the design of a new experimental test to study metabolite exchange interactions. This method uses yeast cells that have one or more of their own metabolic genes disabled, and instead have a copy of these genes on small circular DNA 'mini-chromosomes' (called plasmids). The gene on the plasmid can compensate for the yeast having its own gene missing, and allows the cell to still make the metabolic product it needs to survive. However, as a single cell divides to form a colony, cells randomly lose these plasmids, leaving some of the cells deficient for a particular metabolite. These cells can only survive if the other cells in the colony export the missing metabolite in the quantity needed for growth. Using this test, Campbell et al. found that yeast cells can export missing metabolites at levels needed to sustain these emerging metabolic mutants. Additionally, these yeast communities could grow at levels comparable to other yeast without metabolic deficiencies. The resulting colonies also feature one of several different genetic and metabolic profiles, which change in response to the metabolite that is missing.
These findings demonstrate that yeast cells can exchange high amounts of metabolites, sufficient to form cooperative colonies, and as metabolite concentrations are not altered compared to normal cells, it is likely that exchange of metabolites is ongoing between neighbours in yeast communities. The additional discovery that yeast stop making metabolites when they can obtain them from neighbouring cells has implications for research. This is because many yeast genetic studies use metabolically deficient strains that are supplemented in culture with metabolites. Future work could address whether such supplementation has kept certain functions of metabolism hidden.https://doi.org/10.7554/eLife.09943.002
All living cells possess a system for biochemical reactions, the metabolic network, which supplies cells with their necessary molecular constituents. The reactions participating in this network are highly conserved, so much so that all life is made up of a markedly similar set of metabolites (Braakman and Smith, 2013; Caetano-Anolles et al., 2009). The functionality of the metabolic system is bound to a series of transport reactions that facilitate the uptake of metabolites from the environment, as well as metabolite export. Metabolite export primarily occurs for the purpose of maintaining balance of the metabolic system ('overflow metabolism') and to maintain chemical and physical integrity of the metabolic network. This includes indiscriminate metabolite export through non-specific multi-drug transporters required in removal of toxic metabolites for cells (Paczia et al., 2012; Piedrafita et al., 2015). Co-growing cells can uptake the released metabolites and exploit their presence. Indeed, to a lower extent, metabolite export of metabolites can specifically occur for the purpose of establishing inter-cellular metabolic interactions in biosynthetic metabolism (Nigam, 2015; Paczia et al., 2012; Yazaki, 2005) and can lead to mutualistic situations in which cells profit from coexistence (Foster and Bell, 2012; Oliveira et al., 2014). In between species, mutually positive interactions can readily establish when exchange concerns an overflow metabolite, exemplified by yeast–algae interactions that can form on the basis of a CO2 and sugar exchange (Hom and Murray, 2014), or between different cells of the same species or tissue, exemplified in tumours, when lactate produced in excess by one cell type is metabolised by another (Bonuccelli et al., 2010), or between neurons and glial cells that exchange sugar metabolites (Bélanger et al., 2011; Volkenhoff et al., 2015).
It is more difficult to assess whether metabolite exchange is indicative of non-cell-autonomous metabolism, when exchange concerns metabolites that are needed by both exchange partners, amino acids, and nucleobases for instance. Exchange of costly intermediates is associated with a significant risk, as exported metabolites can be lost through diffusion, chemical damage, or cheating (Dobay et al., 2014; Oliveira et al., 2014; Wintermute and Silver, 2010). Despite these constraints, exchange of intermediates is frequently observed within bacterial microbial communities. Many bacterial species lose essential biosynthetic pathways, disabling them from living autonomously, which may explain why more than 90% of bacteria cannot be cultivated in the absence of a community environment (Costerton et al., 1994; Johnson et al., 2012). The energetic benefit and selective advantage associated with non-autonomous cellular metabolism is often not clear but might involve, for example, the ability to reduce genome size which would in turn facilitate faster proliferation. This may explain why bacteria frequently appear to cooperate in the biosynthesis of more costly and biosynthetically complex metabolites, such as aromatics (Mee et al., 2014).
While metagenomics has boosted the knowledge of metabolite exchange strategies in bacteria (Blaser et al., 2013; Manor et al., 2014; Zelezniak et al., 2015), relatively little is known about eukaryotic species. This includes yeast, a popular single cellular eukaryotic model organism, whose metabolic capacities are regularly exploited in biotechnology. Yeast cells are known to participate in multi-species communities (e.g. on human skin (Findley et al., 2013)), but as wild yeast isolates usually maintain similar prototrophic genomes (Jeffares et al., 2015; Liti et al., 2009), metagenomic data are not conclusive about yeast's metabolite exchange strategies. In laboratory experiments, yeast cultures were, however, not effective in supporting co-growth of auxotrophs that have complementary defects in amino acid and nucleotide metabolism, unless they were genetically modified to increase metabolite export (Müller et al., 2014; Shou et al., 2007). This contrasts with analogous studies in bacterial species, in which such growth experiments regularly show that co-cultured cells can overcome complementary metabolic deficiencies (Foster and Bell, 2012; Oliveira et al., 2014; Pande et al., 2014; Vetsigian et al., 2011). In the absence of quantitative metabolite data, this observation has triggered the conclusion that co-growing prototrophic yeast cells produce amino acid and nucleotide metabolites predominantly for themselves and export them at insufficient quantities to support growth of co-growing cells (Momeni et al., 2013; Shou et al., 2007).
Conflicting with this interpretation, we here report that yeast colonies maintain a rich exometabolome and that cells exploit this metabolic pool preferentially over their own biosynthetic capacities, which implies that metabolite exchange establishes as a natural property of yeast growth. To test whether yeast indeed possesses the capacity for metabolite exchange at growth relevant quantities, we established an alternative method to co-culture experiments. We exploited the stochastic segregation of episomes to randomly and progressively introduce metabolic auxotrophies into a yeast population which self-establishes from an initially prototrophic cell. This strategy enabled co-growing auxotrophs to enter an efficient state of metabolic cooperation, named self-establishing metabolically cooperating communities (SeMeCos). Despite an auxotrophic cell composition of up to 97%, SeMeCos achieve metabolic efficiency, growth parameters, and cell viability similar to that of genetically prototrophic cells, revealing a natural capacity of yeast to exchange metabolites at growth relevant quantities. In a SeMeCo that possesses auxotrophies in histidine, leucine, uracil and methionine metabolism, we distinguish up to eight cell types, each of which is unable to survive on its own, or in co-culture studies, however, could adapt effectively and cooperatively to overcoming metabolic deficiencies, once self-established in a community structure. Communities have a stable population composition as well as distinct spatial heterogeneity, which was, however, not essential for metabolite exchange, as SeMeCos maintain growth in liquid suspension. Self-establishing, complex communities thus demonstrate that yeast is not only exchanging metabolites, but is also able to do so at growth relevant quantities, to facilitate growth on the basis of a non-cell-autonomous metabolism.
Histidine, leucine, uracil, and methionine biosynthetic pathways were chosen for our study as (i) they can be interrupted by deletion of a single, non-redundant gene, which has been reported not to cause compensatory mutations and (ii) because cells possess efficient uptake mechanisms for these nutrients (Mülleder et al., 2012; Pronk, 2002; Teng et al., 2013). Paired combinations of histidine (his3Δ), leucine (leu2Δ), uracil (ura3Δ), or methionine (met15Δ) auxotrophs were unable to sustain growth in the absence of supplementation required for both individual cell types (Figure 1A). A similar result was obtained by co-culturing flocculating yeast cells (Figure 1—figure supplement 1), which are able to maintain biofilm-like physical contact (Smukalla et al., 2008), and in Schizosaccharomyces pombe (Figure 1B), indicating evolutionary conservation of this observation in yeast species.
In two previous studies, leucine/tryptophan and adenine/lysine auxotrophic cell pairs, respectively (Müller et al., 2014; Shou et al., 2007), could co-grow upon removing metabolic feedback control. Feedback resistance renders cells metabolite over-exporters, leading to the conclusion that wild-type yeast cells produce intermediates primarily for themselves, at quantities that are not sufficient for growth relevant metabolite exchange (Momeni et al., 2013; Shou et al., 2007). In a detailed analysis of the intra-colony exometabolome, using an ultra-sensitive mass spectrometry method, the intra-colony fluid showed however to contain a plethora of metabolites, with the amino acids glutamine, glutamate, and alanine being the most highly concentrated (Figure 1C). Furthermore, histidine, leucine, methionine, and uracil all showed to be part of this exometabolome (Figure 1C).These measurements were obtained from cells in exponential growth phase, where apoptosis and necrosis are negligible. Comparing extracellular metabolite concentrations to intracellular levels (the endometabolome) we observed a general trend of correlation between the highest and lowest concentrated metabolites (r2 = 0.517; Figure 1Di), but overall extracellular metabolite concentrations do not replicate the corresponding endometabolome. Tryptophan, phenylalanine, proline, and valine, for instance, were over-proportionally more concentrated inside the cell, whereas uracil, serine, tyrosine, and glycine were relatively over-represented in the extracellular fluid (Figure 1Di). Instead, highly similar exometabolome concentration values (r2 = 0.971) were observed in the related yeast strain BY4741 upon complementing its auxotrophies with the centromere-containing single-copy vector (a minichromosome), 'pHLUM', which contains all four marker genes (Mülleder et al., 2012) (Figure 1Dii). Metabolite concentrations in the exometabolome between these two related yeast strains are hence substantially more similar than the endo- versus exometabolome in the same strain, implying that the intra-colony exometabolome is a distinct metabolite pool.
A second requirement to establish metabolite exchange is that cells need to be able to sense extracellular metabolites and to exploit them as a nutrient source. Yeast is known to uptake amino acids when they are available extracellularly (Stahl and James, 2014). We tested how extensive this uptake was by comparing the uptake rates between auxotrophs and prototrophs. Remarkably, prototrophic cells consumed histidine, leucine, methionine, and uracil at a comparable rate to the genetic auxotrophs, who depend 100% on external metabolite pools (Figure 1E). This demonstrated that yeast cells completely shift from de novo synthesis to uptake in the presence of each of the four metabolites. Studying the URA3 genotype in greater detail confirmed the preference of uptake over self-synthesis. Enzymes involved in uracil biosynthesis remained expressed in both the URA3 and the ura3Δ strains under fully supplemented conditions (Figure 1—figure supplement 2), but uracil biosynthesis-related intermediates shifted to similar concentrations both in the wild-type strain and in the ura3Δ strain once uracil was supplemented (Figure 1F). The only exception was the direct substrate of the URA3 enzyme (orotidine-5'-phosphate decarboxylase), orotidine-5'-phosphate (OMP), which accumulated upon uracil supplementation once its metabolising enzyme (URA3) was deleted (Figure 1Fi). In summary, yeast cells do not compensate for metabolic deficiencies in co-culture experiments consistently as others reported previously (Müller et al., 2014; Shou et al., 2007), but they (i) export the relevant metabolites even when grown on minimal media and (ii) take up histidine, leucine, uracil, and methionine at similar rates to auxotrophs if supplementation is available. At least for uracil, (iii) the biosynthetic enzymes and majority of biosynthetic intermediates in the supplemented wild-type cell resemble those of the corresponding auxotroph.
In light of these results, we speculated that the inability to cooperate could be found in the nature of the co-culturing experiment. To establish an alternative method, we made use of a, in other circumstances disadvantageous, property of yeast plasmids, their occasional, stochastic loss from cells (segregation). Segregation is observed for both popular replication types, centromeric 'cen' and 2µ, at a rate of 2–4% expressed per cell division (Christianson et al., 1992). This property allowed us to randomly and progressively introduce auxotrophies into a developing yeast community starting from a single, initially prototrophic, cell: when a plasmid carries a gene that complements for an auxotrophy, a newly budded cell re-gains the metabolic deficiency according to the segregation of its plasmid. We transformed plasmids from the classic pRS and p400 series which express HIS3, LEU2, MET15, or URA3 genes under the respective S. cerevisiae promoters (Christianson et al., 1992; Mumberg et al., 1995; Sikorski and Hieter, 1989) into the standard laboratory strain BY4741, deficient in these markers (Brachmann et al., 1998) (Figure 2Ai). As expected, the transformed cells grew competently in the absence of histidine, leucine, uracil, and methionine supplementations. We then quantified plasmid segregation and confirmed earlier literature values (Figure 2Aii and Figure 2—source data 1) (Christianson et al., 1992; Ghosh et al., 2007).
Cells having lost prototrophy can only continue growth if they obtain the relevant nutrient from the environment (Figure 2B). Transferred to minimal media, the lack of nutrient supplementation leads to three possible outcomes (Figure 2C): First, if the cooperative potential would not suffice to overcome the increasing content of metabolically deficient cells, colony growth would only be explained by cells maintaining all four plasmids (Figure 2C left). Alternatively, if the segregation is faster than the growth rate of cells carrying four plasmids, the colonies would not be able to grow (Figure 2C centre). Finally, the third outcome is that colony growth continues, despite an increasing auxotrophic composition, facilitated by cells exchanging histidine, leucine, uracil, and methionine at growth relevant quantities (Figure 2C right). First, we observed that upon approximately 33 biomass doublings, segregation for HIS3 and URA3 had continued until less than 50% of cells were prototrophs (Figure 2D), even though a 1:1 co-culture of the same auxotrophs was not able to co-grow (Figure 1A). Then, we assayed for the formation of a heterogeneous yeast community, starting from the four-plasmid (4P) strain, that can give rise to the emergence of 16 complementary auxotrophic genotypes (Figure 2B). In the 4P strain, individual plasmid segregation rates were similar but not identical to yeast carrying one plasmid at a time and were in linear correlation, indicating that no specific interaction between the plasmids occurred (Figure 2Aii). With a total segregation rate of 11%, 4P cells regain auxotrophy rapidly so that only 21 cell divisions (doublings) would result in >90% of cells losing prototrophy (Figure 2E). The continuous loss of prototrophy from the 4P strain was experimentally confirmed on rich (YPD) media; In the presence of rich supplementation, only 45 biomass doublings resulted in 96% of cells losing prototrophy (Figure 2F).
Testing whether cells can maintain growth by cooperating in the biosynthesis of histidine, leucine, uracil, and methionine, colonies were grown over 7 days on minimal media agar through dilution and re-spotting once giant colonies had formed (every 48 hr), so that the continuous gain in biomass necessitates constant de novo synthesis of intermediate metabolites. The experiment yielded viable colonies and from the obtained biomass, we calculated that 57 doublings had occurred. Fifty-seven doublings would have been sufficient for >99% of cells to segregate (Figure 2E). Replica plating revealed a predominantly auxotrophic composition of the obtained colonies. These were composed of 73.3 ± 3.7% auxotrophic cells (Figure 2G left), of which 39.9% had lost one plasmid, 20.6% two, 6.6% three, and 6.1% had lost all four markers (Figure 2G centre). No auxotrophies were in a 1:1 ratio with each other (36.9% for uracil, 27.7% leucine, 23.7% histidine, and 11.7% methionine (Figure 2G right), despite the segregation rates predicting a relatively equal distribution, implying that selection pressure for certain metabotypes affected colony composition (Figure 2G right and Figure 2—figure supplement 1).
We also confirmed that S. pombe is capable of forming similar communities, indicating conservation in these evolutionary distant yeast species (Figure 2—figure supplement 2). As additional controls, we (i) re-isolated the auxotrophs from the established colonies, and repeated the co-culture experiment, after having grown the cells for 48 hr in supplemented media, as with the original strains (Figure 1A). Even when isolated from a functional cooperating colony, complementary auxotrophic cells did not complement each other's deficiencies upon co-culturing (Figure 2—figure supplement 3), ruling out the possibility that new mutations altering metabolite exchange capacities could explain the formation of the cooperating community. We also mixed all four auxotrophs together, both in a 1:1 mixture, as well as in the ratio observed from the community and performed co-culturing both with and without co-cultivation before spotting; These attempts did not result in successful co-growth either (Figure 2–figure supplement 4). Hence, by exploiting plasmid segregation to overcome culturing and allowing the community to self-establish, heterogeneous yeast colonies were formed, which could sustain exponential growth under nutrient limitation, despite the majority of cells being auxotrophic for at least one metabolite. These co-growing cells could therefore overcome metabolic deficiencies through cooperative metabolism, demonstrating that yeast possesses metabolite exchange capacities at a growth relevant quantity.
The obtained colonies were viable on minimal media and showed no apparent growth defects, despite containing a content of 73% auxotrophs, each of which were non-viable in co-culture studies (Figure 1A,B, Figure 1—figure supplement 1, Figure 2—figure supplement 3,4). To characterise the properties of this community, we started with LC-MS/MS to compare its exometabolome against prototrophic yeast strains (YSBN5, BY4741-pHLUM), and the unpassaged strain carrying the four plasmids (4P); (Figure 3A,B and Figure 3—source data 1). SeMeCo colonies possessed similar extracellular metabolite concentrations to prototrophic controls (Figure 3Bi). Of particular note are the extracellular concentrations of H, L, U, and M. Aside from a statistically non-significant trend towards a lower leucine concentration, only uracil (U) was significantly affected. To our surprise, however, the concentration of this metabolite was increased, indicating that SeMeCo had adapted by maintaining a higher level of uracil in its exometabolome (Figure 3Bii).
SeMeCo also maintained wild-type like growth efficiency and biomass-forming capacities under nutrient limitation (Figure 3C). Comparing SeMeCo against prototrophic yeast strains (Figure 3A), dry biomass formation did not vary significantly (Figure 3C centre; p-values = 0.27, 0.70, and 0.09 for FourP, pHLUM, and YSBN5, respectively). In liquid media, lag phase was prolonged, and the maximum specific growth rate (µmax) was slightly reduced compared to the genetically prototrophic YSBN5 or pHLUM cells (0.17 OD595/hr vs 0.20 and 0.21 OD595/hr, respectively) (Figure 3C right). However, this difference appeared more as a cost of plasmid segregation, as both lag phase and µmax did not vary significantly between SeMeCo and the FourP strain (0.17 and 0.16 OD595/hr, respectively) (Figure 3C right). Finally, we tested to what extent cell death occurs in the cooperating community. Both a wild-type (YSBN5) and a SeMeCo culture were grown to exponential phase and cells were counted. Then, the cultures were plated on SC media and the number of colony-forming units (CFUs) determined. The CFU count was nearly equal between SeMeCo and YSBN5, and similar to a 1:1 relationship to the cell count measured prior to spotting (Figure 3D). This indicates that cells in SeMeCo have a comparable colony-forming capacity to that of exponentially growing wild-type cells, and in both populations, virtually every cell can form a new colony.
To establish if cells cooperating in SeMeCo are distributed in a random or organised manner, we analysed colony spatial structure using confocal fluorescence microscopy (Figure 4A). For this, the community was re-established with alternative plasmids that express the fluorescent protein markers CFP (cyan fluorescent protein), Venus (yellow fluorescent protein), Sapphire (a UV-excitable green fluorescent protein [Sheff and Thorn, 2004]), and mCherry (red fluorescent protein) coupled to the auxotrophic markers HIS3, URA3, LEU2, and MET15, respectively (Bilsland et al., 2013). Segregation of the labelled plasmids were within the same range, although not identical to the original pRS and p400 plasmids (Figure 4—figure supplement 1). Images were acquired with a SP5 on a DMI6000 inverted microscope (Leica, Wetzlar, Germany) and show the underside of a live two day micro-colony which had, prior to imaging, been growing on minimal media (SM). In our hands, the Sapphire-LEU2 fluorescence was also visible under the imaging conditions used to visualise Venus-URA3. For this reason, the Venus-URA3 channel was removed from the colony image. The spatial heterogeneity of fluorescent markers in the micro-colony revealed that cells in SeMeCo unequally distribute over the macroscopic structure, and form regions where the biosynthesis of a particular metabolite dominates (Figure 4A). A prediction in truly cooperating communities is, however, whether complementary cells maintain physical proximity to each other, to oppose diffusion of exchanged metabolites (Müller et al., 2014). Using computational image analyses of colony micrographs, we find that even when the most stringent cut-off was applied, complementary metabotypes across the community maintained an average distance (6.86 μm) of less than two cell diameters (Figure 4B). Cells are hence most likely to exchange the majority of metabolites with those maintaining close proximity. Despite these results, SeMeCo could, however, continue growth after disruption of this spatial structure in liquid media (Figure 3C). To verify this assumption, SeMeCo was replicated for 7 days in liquid minimal media, as previously, with re-dilution every 2 days. Indeed, the liquid culture maintained a similar content of auxotrophs as obtained with colony grown SeMeCos (Figure 4—figure supplement 2). The capacity of SeMeCos to overcome metabolic deficiencies through metabolic cooperation is hence not in essence bound to colonial growth.
To determine not only the spatial but also the population structure, we switched back to the non-fluorescent SeMeCo to avoid confounding effects of fluorescent protein expression, and quantified by replica plating the colony contribution of all 16 possible metabotypes, resulting from all possible combinations of the four auxotrophies (Figure 2B). These experiments revealed that within SeMeCo, 95.6% of cells belonged only to 8 of the 16 possible metabolic combinations (Figure 5A). We questioned whether this composition was the result of a stochastic event, however, the dominance of the same metabotypes establish three times independently. Moreover, the eight successful metabotypes contributed to SeMeCo at comparable percentages (Figure 5A inset). Using our segregation rate model as well as growth rate data, we could rule out this colony composition being a result of (i) varying plasmid segregation rate, (ii) the number or type of auxotrophy, or (iii) differences in growth rates. First, a community composition calculated on the basis of the experimentally determined plasmid segregation values (Figure 2E, Figure 2—figure supplement 1) showed zero correlation with the actual population composition (r² = 0.051) (Figure 5B). Second, all histidine, leucine, uracil, or methionine auxotrophies, as well as all plasmid numbers (1 to 4) were found amongst both the frequent and rare metabotypes. For instance, while single uracil (HIS3, LEU2, MET15, ura3∆; 19.7%) or leucine (HIS3, URA3, MET15, leu2∆; 11.1%) auxotrophs were amongst the most frequent cells, their methionine-deficient counterparts (HIS3, URA3, LEU2, met15∆; 0.4%) were among the most rare (Figure 5A). Also, the high frequency of the dual auxotrophs LEU2, MET15, his3∆, ura3∆ (8.1%) and HIS3, MET15, leu2∆, ura3∆ (10.1%), contrasts with the rareness of the other dual auxotrophs (HIS3, URA3, leu2∆, met15∆ (1.1%), MET15, URA3, leu2∆, his3∆ (0.2%), URA3, LEU2, his3∆, met15∆ (0.5%), and LEU2, HIS3, ura3∆, met15∆ (0.6%)). Thus, the number of plasmids or type of auxotrophy a cell had did not indicate whether a cell-type would be rare or frequent (Figure 5A). Finally, the growth rate of 16 strains, carrying the same marker and supplement combination that replicates the 16 metabotypes (Mülleder et al., 2012) did not distinguish the depleted from the selected metabotypes either (Figure 5C).
As growth potential and segregation parameters did not explain the population architecture of SeMeCo, we conclude that this community was selected for on its ability to cooperate effectively. If this interpretation is correct, it would imply that a different pressure to cooperate would result in a different SeMeCo composition. To test this hypothesis, we focussed on uracil, as mass spectrometry had detected an increase in uracil concentration in the SeMeCo colony exometabolome, indicating that uracil is the most limiting metabolite (Figures 2G right and 3Bii). SeMeCos established on uracil adapted a different composition, resulting from a dramatic decline in cells needed to produce uracil. Importantly, this included the prototroph with its total content in the community decreasing from 26.7% in the original SeMeCo to solely 3.0%, so that 97.0% of cells were cooperating auxotrophs (Figure 5D). Hence, SeMeCo colonies establish a population that is dynamic to changes in the external metabolite pool, and can persist in a state with virtually all cells being genetically auxotrophic for at least one essential metabolite.
Metabolic exchange interactions occur frequently among cells that grow in proximity to one another, as metabolites are constantly released from cells for different reasons, such as overflow metabolism, metabolite repair, as well as export to facilitate metabolite exchange. In bacteria, a subset of such metabolite exchanges are of a cooperative nature in the sense that all exchange partners profit from this situation (Oliveira et al., 2014), whereas for the majority of eukaryotic organisms, metabolite exchange strategies remain unclear. Despite yeast auxotrophs being viable in supplemented and rich media (Mülleder et al., 2012), in the absence of amino acid supplementation, they fail to complement metabolic deficiencies in several pairs or higher order co-culture experiments (Figure 1A,B, [Müller et al., 2014; Shou et al., 2007]), a clear difference to bacterial studies, where similar experiments were effective (Foster and Bell, 2012; Freilich et al., 2011; Harcombe, 2010; Pande et al., 2014; Ramsey et al., 2011; Vetsigian et al., 2011). This led to speculations that yeast might, in contrast to many bacterial species, lack the required export capacities to enable growth relevant exchange of intermediary metabolites such as amino acids and nucleobases (Shou et al., 2007). Analysing the intra-colony exometabolome we could, however, detect the required metabolites; in fact, we found that cells within a colony are surrounded by a rich exometabolome. We also found that yeast would efficiently exploit the nutrients when available, to the extent that they solely rely on these extracellular metabolites. This result implied that metabolite exchange among co-growing yeast cells is frequent by nature; the lack of complementation in the co-culture experiments could thus reflect a limit of the experiment itself, and not represent the metabolite exchange capacities of yeast cells.
To circumvent combining two or more cultures, we chose an approach of synthetic biology and exploited the stochastic loss of plasmids to progressively introduce the metabolic deficiencies in random combination from an initially single cell. The progressive loss of prototrophy allowed cells to maintain cell growth on the basis of metabolite exchange, resulting in a community with 73% auxotrophy, which increased to 97% upon supplementation with the most limiting metabolite, uracil. Despite its dominant auxotrophic composition, the SeMeCo community could maintain a wild-type like exometabolome, metabolic efficiency, as well as cell viability, implying that this type of cooperation is a robust physiological property. Hence yeast's natural metabolite export and import capacities are wholly sufficient to support co-growth on the basis of metabolite exchange.
The establishment of SeMeCos was not facilitated by mixing the auxotrophs in a higher order combination either. This is consistent with the notion that losing more metabolic genes reduces biochemical capabilities and does not add new ones. The key of the SeMeCo system is instead to allow the progressive self-establishment of the community starting from the single cell (Figure 2). Metabolic feedback regulatory systems therefore do not inhibit metabolite export in general but prevent cooperative co-growth when already pre-established co-cultures are mixed (Müller et al., 2014; Shou et al., 2007). A possible role of these mechanisms could perhaps prevent the spread of foreign, potentially cheating, cells that derive from a competing yeast colony. We could replicate behaviour which is in favour of such an assumption; By spiking into SeMeCo a cell culture possessing the same genotype as a frequent (HIS3 LEU2 ura3Δ MET15) and rare (his3Δ leu2Δ URA3 MET15) genotype (Figure 5A), we observed that both genotypes were rapidly depleted from the pre-established SeMeCo, irrespective of the frequency of the respective genotype in SeMeCo (Figure 5—figure supplement 1).
Studying the genotypic composition of SeMeCo implied that there are a defined set of interactions underlying the properties of the cooperating community, which maintained a similar population composition involving eight reproducibly concentrated metabotypes when established independently. This indicates that this quantitatively defined community composition was most effective in metabolic cooperation. This finding may close an important gap in the understanding of the evolution of multicellularity; If a defined composition is most effective in cooperative growth, a selection advantage could be provided by any sort of physical bonding which can maintain cooperation partners in the defined equilibria, and would in addition, provide additional protection against the invasion of cheating cell types. Indeed, the exometabolome data implies that the number of metabolite exchange interactions among co-growing cells could be significant. The colony exometabolome contained a vast array of biomolecules, including the majority of amino acids (Figure 1C) (Castrillo et al., 2007; Paczia et al., 2012; Silva and Northen, 2015). The finding that yeast cells prefer uptake over synthesis of amino acids and uracil, even when they are genetically prototrophic, shows that exchange interactions will readily establish once the cellular environment has acquired a critical concentration of metabolites. This has implications for the interpretation of metagenomic studies and cheating/benefactor experiments, as for this reason, it cannot be concluded from the genetic presence or absence of a single metabolic pathway, or from following the synthesis of a single metabolite, how many other metabolites are being exchanged as well.
Even without selective pressure, both wild-type yeasts and SeMeCo established an amino-acid-rich exometabolome on minimal media (Figure 1C) and engaged in metabolite uptake when nutrients were available (Figure 1E). This implies that these features are a natural property of yeast and raises the question of why natural yeast communities are not composed of co-growing, genetic, auxotrophs. To answer this question, one needs to keep in mind that possessing metabolic genes in the genome is not equal to the pathway being constantly active; Indeed, prototrophs can flexibly switch from self-synthesis to amino acid uptake (Figure 1). Being genetically prototrophic hence gives a higher level of metabolic flexibility, as prototrophic cells can re-activate a synthetic pathway when required. Unlike in SeMeCo, the genotype of a cell in a natural community is not in essence reflecting its metabotype or its metabolic role in the community. Additionally, the natural life cycle of yeast involves the formation of endospores, which are important for enduring starvation, and to spread between habitats. Without a prototrophic genotype, a single spore can no longer establish a colony on its own as genetic auxotrophy would interrupt the yeast life cycle. Second, only a fraction of the natural yeast life cycle occurs under exponential growth that requires abundant carbohydrate and nitrogen supply. The maintenance of a prototrophic genotype both in S. pombe and in S. cerevisiae wild isolates (Jeffares et al., 2015; Liti et al., 2009) is hence fully compatible with the presence of elaborate amino acid and nucleotide exchange mechanisms.
The finding that these cells fully shift from self-synthesis to uptake for histidine, leucine, methionine, and uracil, once these metabolites are provided, has direct implications on research using yeast, a primary eukaryotic model organism in genome-scale studies. A majority of yeast genetic experiments are conducted in auxotrophic strains, requiring amino-acid supplemented or rich media compositions. Important parts of biosynthetic metabolism (amino acid biosynthesis can account for up to 50% of metabolic flux towards biomass) may have thus stayed silent in a significant amount of functional genomics experiments. The effects of metabolic–genetic interactions on cellular physiology could thus substantially exceed our current knowledge and could be discovered upon switching to minimal nutrient supplementations. In this context, SeMeCos are simple to handle, establish rapidly and are easy to analyse, and therefore represent an effective and broadly applicable eukaryotic model system to study both cooperativity and effects of metabolism in the laboratory.
In summary, using histidine, leucine, methionine, and uracil as model metabolic pathways for exchangeable metabolites, we found that S. cerevisiae cells prefer these nutrients' uptake over their self-synthesis and maintain an amino-acid-rich exometabolome in the extracellular colony space, indicators of ongoing inter-cellular metabolite exchange. Although yeast is known to fail in compensating for auxotrophy in pairwise and higher order co-culture experiments, the cells did successfully enter a state of metabolic cooperative growth upon exploiting stochastic plasmid segregation so that a single cell could progressively develop into a complex heterogeneous community. Composed of auxotrophic cell types that are non-viable on their own, SeMCo communities were able to overcome metabolic deficiencies and maintain metabolite concentrations and robustness similar to wild-type cells. Additionally, cooperation had imposed different metabolic roles on contributing cells. Progressive community formation thus reveals that yeast possesses full capacity to exchange anabolic metabolites at growth relevant quantities and readily establishes a non-cell-autonomous metabolism within complex but defined community structures.
Yeast cells were grown under standard conditions on synthetic minimal (SM or EMM), SC and rich (YPD or YES) media. Plasmid segregation was calculated according to Christianson et al. (1992), by monitoring plasmid retention after cells are shifted from non-selective to selective media, and by expressing the number of cells that have lost the marker as a function of generation time. Metabolites were quantified after quenching using an online UPLC-coupled 6460 (Agilent Technologies, Waldbronn, Germany) triple quadrupole mass spectrometer. Confocal fluorescence microscopy was conducted with a SP5 confocal on a DMI6000 inverted microscope (Leica) using a 10x/0.3 HC PL Fluotar Air objective.
All experiments involved, unless otherwise indicated, used BY4741 yeast strain (his3Δ1, leu2Δ0, ura3Δ0, met15Δ0)(Brachmann et al., 1998) with prototrophy restored by complementation either with vectors p423 (HIS3), pRS425 (LEU2), p426 (URA3), and pRS411 (MET15) (Christianson et al., 1992; Mumberg et al., 1995; Sikorski and Hieter, 1989), with the centromeric vector (minichromosome) pHLUM (Mülleder et al., 2012); Addgene number: 40276), or with the fluorescent protein vectors yEpCFP_HIS (HIS3), yEpSapphire_LEU (LEU2), yEpVenus_URA (URA3) (Bilsland et al., 2013), and pRS411-GPDpr-mCherry (MET15) (Table 1). Cloning was conducted according to standard procedures; oligonucleotides are listed in Table 2.
All experiments involving wild-type yeast strains were carried out using as indicated, and using YSBN5, a prototrophic haploid variant of S. cerevisiae S288c (Canelas et al., 2010). For microscopy analyses of colony spatial organisation, BY4741 had prototrophy restored by complementation with the above fluorescent protein vectors (Table 1). For fluorescence-activated cell sorting (FACS), BY4741 was used with mCherry labelled derivatives of pHLUM, pHLM-GPDpr-mCherry, and pUM-GPDpr-mCherry (Table 1). For S. pombe experiments, ED666 yeast strain (ade6-M210 ura4-D18 leu1-32) was used that had uracil and leucine prototrophy restored by complementation with vectors pFS118 (ura4+) and pREP41-MCS+ (LEU2) (Table 1).
Yeast was cultivated if not otherwise indicated at 30ºC, in rich (YPD; 1% yeast extract [Bacto], 2% peptone [Bacto] or YES; [Formedium; 35.25 g/L]), complete supplemented synthetic media (SC; CSM complete supplement mixture [MP Biomedicals; 0.56 g/L], YNB, yeast nitrogen base [Sigma; 6.8 g/L]), or minimal supplemented synthetic media (SM; YNB [Sigma; 6.8 g/L] or EMM; [Formedium; 32.3 g/L]), with 2% glucose (Sigma) as the carbon source. Media recipes and amino acid compositions for S. cerevisiae were used as previously published (Mülleder et al., 2012).
For S. cerevisiae, auxotrophic derivatives of prototrophic BY4741 (Mülleder et al., 2012) were cultured alone or mixed in combination with other auxotrophs, and 1.1e05 cells of individual or mixed auxotrophs were spotted on respective selective media. Growth was then documented after 2 days incubation at 30°C. For the flocculation experiments, a FLO+ derivative of BY4741 was obtained by back-crossing and tetrad dissection of a tpo1Δ (YLL028W) strain obtained from Euroscarf (Frankfurt, Germany). For S. pombe, 1.9e04 cells of auxotrophic derivatives of ED666 h+, prototrophic for leucine and uracil, were spotted alone or mixed together on corresponding selective media. Growth was then documented after 2 days incubation at 30°C.
All proteogenic amino acids (except for cysteine) and uracil, citrulline, and ornithine were analysed by selective reaction monitoring (SRM) using an online coupled UPLC (1290 Infinity, (Agilent))/ triple quadrupole mass spectrometer ( 6460, (Agilent)) system. The compounds were separated by hydrophilic interaction chromatography on an ACQUITY UPLC BEH amide column (2.1 mm × 100 mm, 1.7 µm) by gradient elution. Solvent A consisted of 95:5:5 acetonitrile:methanol:water, 10 mM ammonium formate, 0.176% formic acid, and solvent B of 50:50 acetonitrile:water, 10 mM ammonium formate, 0.176% formic acid. The gradient conditions were 0–07 min 85% B, 0.7–27–2.55 min 85–585–5% B, 2.55–255–2.75 5% B, 2.75–275–2.8 min 5–855–85% B and 2.8–38–3.25 min 85% B at a constant flow rate of 0.9 mL/min and 25°C column temperature. SRM (Q1/3 settings) are given in Table 3. Metabolite signals were automatically integrated using Masshunter (Agilent) corrected after manual inspection and quantified by external calibration.
Cells were spotted on SM solid media and incubated at 30°C in FLUOstar OPTIMA plate reader (BMG LABTECH, Aylesbury, United Kingdom) to establish giant colony. Cells were collected at 26 hr (exponential phase) and re-suspended in H2O. Cells were then gently centrifuged, and pellet (intracellular) and supernatant (extracellular) fractions were separated. Metabolites were extracted from both fractions using 75% boiling ethanol containing l-taurine as an internal standard. Here, samples were left to incubate with extraction solvent in water bath (80°C) for 2 min then mixed vigorously. Incubation and vigorous mixing step was then repeated. Solvent was evaporated using a Concentrator plus Speed Vac (Eppendorf, Hamburg, Germany) and samples were reconstituted in 50 µL 80% ethanol with intracellular fraction diluted 1:5 with 80% ethanol. All samples were submitted to LC-MS/MS and metabolite identification, and quantification was then performed as in 'LC-MS/MS based quantification of amino acids and uracil'. Data was illustrated following correction to the internal standard of amino acid abundances from both intra- and extracellular fractions.
S. cerevisiae strains were transferred from cryo-preserved cultures to SC solid media, grown for 2 days and selected on SM solid media, supplemented only with required amino acids/ nucleobases for 1 day. Pre-cultures were inoculated in 1.5 mL SM containing the minimal supplementation and cultured O/N at 30°C. Main cultures were started at an OD595 of 0.15 in 1.5 mL of SC media in deep well 96-well plates and cultured in a Titramax (Heidolph, Schwabach, Germany)for 30 hr (950 rpm, 30°C, 4 mm stirring bead/ well). Samples of 50 µL were harvested every 3 hr, where cells were removed by centrifugation (3000 g, 5 min) and the supernatant diluted 1:20 in absolute ethanol. Then, 1 µL of supernatant was used for quantification of extracellular metabolites by LC-MS/MS. ‘gcFitModel’ function from ‘grofit’ R package (Kahm et al, 2010) was used to estimate the uptake rate of histidine, leucine, uracil, and methionine in different auxotrophic strains.
After O/N pre-culture S288c MATa yeast without auxotrophies and ura3Δ yeast (S288c, MATa) (Mülleder et al., 2012) were grown in 30 mL SM in shake flasks at 30°C, 300 rpm. The media contained either (i) no additives, (ii) uracil (20 mg/L) (iii) or uracil (20 mg/L), leucine (60 mg/L), methionine (20 mg/L) and histidine (20 mg/L). During mid-exponential growth (OD595 between 0.7 and 1.2), 1 mL samples of the cultures were quenched in 4 mL -40°C 60% methanol, 10 mM NH4-acetate. After centrifugation (-9°C, 4500 g), the cell pellet was stored at -80°C until extraction.
Prior to extraction, 13C-yeast internal standard was spiked into the cell pellets, which were subsequently extracted with 1 mL 80°C 75% ethanol, 10 mM NH4-acetate for 3 min. During extraction, the suspension was vortexed on a 0.5–15–1 min time interval. After extraction, the suspension was centrifuged (-9°C, 4500 g) and the supernatant, hence the extract, was dried in a vacuum centrifuge before being stored at -80°C until measurement. For LC-MS measurements, the dried extracts were dissolved in 50–10050–100 µL H2O.
The metabolites were separated with reversed phase ion-pairing chromatography on a Acquity UPLC (Waters, Cheshire, United Kingdom) with a Waters Acquity T3-endcapped column (150 mm, 2.1 mm, 18 µm) as described in (Buescher et al., 2010). Subsequently, the metabolites were analysed with a TSQ quantum ultra triple quadrupole mass spectrometer (Thermo Fisher Scientific, Waltham, MA) (Buescher et al., 2010). Specifically, the metabolites were ionised with an electro spray (ESI) and the mass spectrometer was run in negative mode with SRM. The SRM transitions used are described in (Buescher et al., 2010) and for orotidine-monophosphate, where no standard was available, we used the phosphate fragment (m/z 367 → 79) trajectory (Horai et al., 2010). The obtained data was integrated with an in-house software and normalised to 13C-internal standard and OD595, hence biomass. The median value of different replicates were then scaled and used to illustrate data.
Plasmid stability (segregation) of vectors p423 (HIS3), pRS425 (LEU2), p426 (URA3), and pRS411 (MET15) was determined according to Christianson et al. (1992). BY4741 (his3Δ1, leu2Δ0, ura3Δ0, met15Δ0) either transformed with one or all four plasmids, respectively, for either the four non-fluorescent or fluorescent vectors, were cultured in 25 mL of YPD media for 48 hr then plated at 1:100,000 dilution on YPD solid media. Plasmid retention was then calculated by replica plating CFUs from YPD solid media onto selective solid media. Number of doublings (g) and segregation rate (m) were calculated as in (Christianson et al., 1992).
Segregation rates of p423 (HIS3), pRS425 (LEU2), p426 (URA3), and pRS411 (MET15) were simulated over generation time in R by iterative cycling (looping). The script is given in Supplementary file 1. Plasmid abundances were binned by plasmid number (0 to 4) and illustrated with R package 'ggplot2' in terms of auxotrophy.
Unless otherwise indicated, cells were first spotted and grown for 2 nights on SM solid media to establish a giant colony. The colony was then re-suspended in H2O and diluted to 3.4e03 cells in 200 μL SM, and their optical density (OD595) was recorded in a FLUOstar OPTIMA plate reader (BMG LABTECH) every 20 min for 40 hr at 30ºC. Both maximum specific growth rate (μmax) and lag phase were determined from growth curves using a model-richards fit from the R ‘grofit’ package (Kahm et al, 2010). For determining dry biomass, colony was re-suspended in H2O and normalised to 1.1e07 cells in 100 mL SM, then incubated for 72 hr at 30°C and pelleted. Pellets were dried for 5 days at 50°C and then weighed to obtain dry biomass. μmax for individual metabotypes was determined in batch SM culture (50 mL) and supplemented accordingly for the different auxotrophic requirements.
Cells from giant colonies of SeMeCo and YSBN5 were grown to exponential growth phase in SC media, and cell number was then measured with a CASY Model TTC (Roche Innovatis, Switzerland) cell counter. Cells were then diluted and plated on solid SC media to establish individual CFUs and the number of CFUs with initial cell number were compared.
A micro-colony of BY4741 with prototrophy restored by complementation with the fluorescent protein vectors yEpCFP_HIS (HIS3), yEpSapphire_LEU (LEU2), yEpVenus_URA (URA3) (Bilsland et al., 2013), and pRS411-GPDpr-mCherry (MET15) (Table 1) was grown for 2 nights on SM. Prior to imaging, colony was embedded in 2% agarose (Type I-B; Sigma) and gently transferred to a μ-slide glass bottom (ibidi). Cells were imaged with a DMI6000 inverted Leica SP5 confocal microscope, using a 10×/0.3 HC PL Fluotar Air objective, running LAS AF software (version 22.214.171.12423). Fluorescence for each marker was separated by excitation (CFP: 458 nm, Sapphire: 405 nm, Venus: 514 nm and mCherry: 561 nm). In our hands, the Sapphire-LEU2 was also visible under the imaging conditions used to visualise the Venus-URA3. For this reason, we removed Venus-URA3 channel from the colony image. A look-up table was applied to each channel post-acquisition to allow visualisation of the different channels together using ImageJ software.
For the microscopy image showing fluorescent-labelled cells in a colony, prototrophs and auxotrophs were identified as being present or absent using several cut-offs for fluorescent signal intensity. Based on these different cut-off values (0.1, 0.2, 0.3, and 0.4), the monochrome fluorescence microscopy images of each individual marker (HIS3, LEU2 and MET15) were recognised as metabolite producing (prototrophic) or requiring (auxotrophic) pixels. The auxotrophic pixels were marked black, prototrophic pixels white, and the background was illustrated grey to separate it from the colony pixels. For each auxotrophic pixel, the distance to the next prototrophic pixel was calculated and distance values for the minimum, mean, overall maximum, and maximum for 90% of cells were taken for each marker.
Genotypes depicting SeMeCo frequent (HIS3, LEU2, MET15, ura3Δ) and rare (his3Δ, leu2Δ, URA3, MET15) metabotypes were reconstructed by transforming mCherry labelled derivatives of pHLUM (pHLM-GPDpr-mCherry and pUM-GPDpr-mCherry, respectively) into BY4741. Strains were spiked into established SeMeCo in 1:10 (frequent or rare metabotype: SeMeCo) ratio taken from their established giant colonies on selective media (where plasmid segregation is ongoing). Abundance of fluorescent cells was monitored immediately after mixing and approximately 48 hr after re-establishment of giant colony on minimal solid media with a BD LSRFortessa cell analyser. Data analysis was performed with FlowJo.
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Mohan BalasubramanianReviewing Editor; University of Warwick, United Kingdom
eLife posts the editorial decision letter and author response on a selection of the published articles (subject to the approval of the authors). An edited version of the letter sent to the authors after peer review is shown, indicating the substantive concerns or comments; minor concerns are not usually shown. Reviewers have the opportunity to discuss the decision before the letter is sent (see review process). Similarly, the author response typically shows only responses to the major concerns raised by the reviewers.
Thank you for submitting your work entitled "Cell-cell heterogeneity emerges as a consequence of metabolism in a cooperating eukaryotic cell community" for peer review at eLife. Your submission has been favorably evaluated by Diethard Tautz (Senior Editor) and four reviewers, one of whom, Mohan Balasubramanian, is a member of our Board of Reviewing Editors.
The reviewers have consulted with one another to come to some understanding of what revisions should be required to produce a revised manuscript suitable for publication in eLife. The reviewers raise a general concern about using your approach to delve into aspects of yeast cell biology and physiology and we are concerned that this could require more than the two months we normally allow for return of a revised manuscript.
The referees points are provided verbatim, however, please pay attention to and be sure to address the key points in this letter.
The referees liked the new approach using plasmid loss to generate a synthetic yeast community exchanging nutrients, but questioned how the work may provide information on yeast physiology. This could be achieved, for example, using the Sigma1278b strain strategy mentioned by Reviewer #2.
There were also concerns about the lack of cell biological analyses and I would encourage you to address these satisfactorily with experiments and discussion.
Please pay close attention to the point raised by Reviewer #3 on the exo versus endometabolome differences in the context of the colony and address it satisfactorily with experiments and discussion.
This is in interesting manuscript from Ralser and colleagues using a new approach to generating complex yeast community that exchange metabolites, and such exchange is essential for colony viability. The authors show that they can generate synthetic colonies that contain auxotrophs for 4 different amino acids/nucleobases. At one level this is exciting, but at another level, I am unclear what we have learned about yeast physiology from this work.
1) The plasmid loss based approach to generating the SeMeCo colony is a clever trick, but how does it generate the SeMeCo. Delving into the mechanism of how gradual loss of plasmids in a mixed population (as opposed to mixing various auxotrophs) leads to SeMeCo will be a great strength.
2) The paper lacks a cell biological analysis of the phenomenon. For example, Muller, Murray use a fluorescence based assay to look at the position of the two genotypes in the colony. Admittedly, the situation here is more complex with a larger number of genotypes, but is still not insurmountable and some cell biological insight into colony organization will help.
3) It is also not strictly correct to say that exchange of metabolites/cooperation does not happen in yeast, since the papers by Shou and Murray labs (cited in this paper as well) do generate a synthetic cross-feeding colony, except that these authors had to down-regulate feedback mechanisms involved in amino acid metabolism. What the current paper has done is to increase the complexity and this has been achieved using a different clever approach. This needs to be better articulated.
Campbell and coworkers report the establishment of a community of yeast cells with different auxotrophies that manages to grow through exchanges of metabolites. Specifically, they started from an auxotrophic mutant that was restored to prototrophy through transformation with plasmids that complemented the missing biosynthetic genes. As this prototroph divides, some of the plasmids are lost in some of the progeny, resulting in a complex but reproducible community of prototrophs and several auxotrophs; demonstrating that the cells must be exchanging nutrients that support growth of the different auxotrophs.
The main conclusion from this elegant work is that (eukaryotic) yeast cells are able to exchange metabolites. I am quite excited about this result, because it is getting at an underexplored, yet very interesting and possibly important aspect of cooperation, community formation and multicellularity in eukaryotes. As such, I support publication of this paper in eLife. However, I also have several important questions and remarks.
1) I think that the main story of the paper is a bit underdeveloped still, and that the second part of the paper (where the authors measure stress resistance, etc.) is perhaps less essential and a bit unconnected from the main story. To me, the most important question is how important and realistic the findings are for natural conditions. This particular experiment and the establishment of SeMeCos represents a scenario that is not very realistic in nature, where all the genes are maintained more or less stably in the genome instead of residing on unstable plasmids. The authors find that auxotrophic mutants that are mixed together do not seem able to develop some sort of mutualistic community. Moreover, in natural conditions, exchange of metabolites between yeast cells may not be very relevant, since if it were, one would expect that feral yeast colonies or communities would contain a very high rate of (different) auxotrophs? This also makes me wonder whether SeMeCo's develop mostly because of the cost of maintaining the plasmids, rather than a benefit of losing specific metabolic pathways to specialize in others? Last but not least, I also wonder whether the lab yeast strain BY4741, a derivative of S288C, which is known to be impaired in several mechanisms related to community formation (biofilms, pseudohyphal growth, mats…), is a wise choice for these experiments.
Some additional experiments may tell us much more about the real-life importance of metabolite exchange in yeasts. Firstly, I would argue to repeat the key experiments in a strain that is capable of forming communities, like for example Sigma1278b. At first sight, this might seem like a prohibitive amount of work, but it is not since it simply entails using some of the available auxotrophs (or generating a few new ones through transformation) to see if they can support each other in liquid suspension, colonies or biofilms/mats. If so, this would mute a lot of doubts (including whether the cost of maintaining a plasmid is a player). Second, I would also suggest transforming Sigma with (at least two of) the plasmids to investigate if and how this strain realizes SeMeCo's similar to S288c. If the authors decide to follow this suggestion, I would also argue for the inclusion of constitutively expressed fluorescent markers, so that they can easily count the different lineages through cytometry and also follow their spatial distributions in colonies/biofilms (see second remark below).
Last but not least, I think that the authors need to state more clearly what they think is the relevance of their findings in natural conditions – they seem to avoid this question a bit instead of being very explicit about it and discussing it in great detail. One very interesting bit of information would be if and how many auxotrophs are recovered from nature? Is there any data available? Or can the authors explore this themselves?
2) One of the most intriguing questions is whether the different auxotropic mutants arrange into some kind of spatial pattern in the colonies, so that complimentary strains (that can compensate each other's auxotrophies) would be in close proximity. This should be relatively easy to study by integrating a fluorescent marker in each of the plasmids (e.g. three dyes with a very different spectrum, like CFP, YFP and RFP).
3) It is unclear to me whether it is sufficient to keep cells in exponential phase to exclude the influence of dying cells (which could contribute nutrients, rather than through exchange between living cells). The fact that the "exometabolome" differs in composition from that inside of living cells may not be the ultimate proof, as it seems possible that dead cells do not only contribute metabolites that were free molecules when the cell was still alive, but also through (active or passive) breakdown of biomolecules after the cells disintegrate. Perhaps one way to tackle this is to let cultures grow well into stationary phase and/or add a certain number of dead cells and monitor if and how this changes the dynamics. Another way would be to investigate colonies, as it is known that cells in the center of colonies experience starvation and cell death (see for example work by Palkova and colleagues).
4) The SeMeCo's seem to show convergence towards a stable state (with a defined and complex ratio of different auxotrophic mutants). Are we sure that this is indeed a stable state? And why do not all prototrophs disappear? Would it be worth letting some communities grow much longer to see what happens in the long term?
Cells within community may cooperate by exchanging metabolites, easing the metabolic burden on individuals. Budding yeast "wild type" auxotrophs do not complement metabolic deficiencies when grown in co-cultures, leading to speculations that yeast may be deficient in some aspect of metabolite export. The manuscript under review describes budding yeast communities capable of metabolic exchange and cooperation. The key trick is to allow those communities to self-establish from a single cell initially auxotrophic for synthesis of three amino acids and uracil in which auxotrophy is covered by complementing plasmids. Each of these plasmids can be lost stochastically during cell division, leading to a mixture of possible phenotypes. The authors show that such stochastic plasmid loss leads to the emergence of heterogeneous colonies where auxotrophic neighbors grow and exchange metabolites between each other. It is a clever approach leading to a neat observation and the manuscript describes a lot of experimental work. My biggest problem with this story is that there is no attempt to get at the underlying mechanism and to understand just how SeMeCos differ from cells in co-culture.
Are individual SeMeCo cells sensitive to end-product feedback? Could they have accumulated mutations inactivating the feedback inhibition? Other mutations/genome rearrangements? Do cells maintain ploidy?
Somewhat related, is it possible to reproduce mutualistic growth from scratch, in co-cultures, using mixed populations of cells with metabotype composition similar to SeMeCos? Perhaps in conditioned SeMeCo media, since the authors suggest that "exchange interactions will readily establish once the cellular environment has acquired a critical concentration of metabolites".
I do not quite understand why SeMeCos transferred to the liquid minimal medium – and at very low dilutions (Figure 3C) – do not show longer lag phase as compared to their parent strain and grow normally. Do they overproduce and/or over-secrete metabolites under these conditions? Would it be expected that metabolite concentration is initially very low? Or are those initially proliferating cells prototrophs that may later start losing plasmids, re-establishing the community?
I do not get the logic behind experiments shown in Figure 1C–D. The authors first show that many metabolites are found in extracellular space within yeast colonies. They then argue that these metabolites must be exported rather than released from lysing cells because endo- and exometabolomes of exponentially growing cells are different. I appreciate that growing cells may well export metabolites but why is this detour to exponentially growing cultures where cell lysis is negligible? How is it related to colonies where growth is restricted to a small outward layer and cell viability within a colony center is likely decreased?
Similarly, what is the reason for including an experiment shown in 2Av? The fact that cells lose plasmids in the absence of selection is not particularly surprising.
What is the degree of cell death during community establishment? Somewhat related, what is the efficiency of SeMeCo establishment? Do all cells eventually give rise to a mutualistic community?
This is an interesting paper describing how it is possible to evolve yeast communities where certain members produce specific amino acids/nucleotides and other members consume these metabolites. The authors demonstrate that this community behaves similar to wild type prototrophic strains, both in terms of specific growth rate and in response to stress. The authors present an impressive number of controls and perform a detailed analysis of the established community. So overall this is a sound paper and I do not really have any specific comments to the Results and Discussion. However, I am a little puzzled about the rationale of this work. It is not clear what we are learning in terms of new biology from the study. It is an interesting observation that both phototrophs and auxotrophs take up metabolites at the same rate, but I think this has been observed before. The authors can probably easily revise their paper to take this point into account, as I am certain that they in fact could argue for the rationale of this study.
[Editors' note: further revisions were requested prior to acceptance, as described below.]
Thank you for resubmitting your work entitled "Self-establishing communities enable metabolic cooperation in a eukaryote" for further consideration at eLife. Your revised article has been favorably evaluated by Diethard Tautz (Senior Editor), Mohan Balasubramanian (Reviewing editor), and three reviewers. The manuscript has been improved but there are some remaining issues that need to be addressed before acceptance, as outlined below:
As you will see, the referees have asked you to consider and rewrite some points mentioned below and also discuss some caveats that they have noted.
Overall, I think that this paper has matured significantly and should be published. I feel that the new experiments make the study much stronger, and I specifically appreciate the authors' efforts to re-write the Discussion section to better highlight the biological relevance of their findings, as well as the remaining questions.
That said, as I was re-reading the paper, I again started wondering why auxotrophic mutants, even when mixed at the same ratios as found in SeMeCos, fail to establish a growing population; whereas prototrophic cells that contain unstable plasmids are able to form a community with some fractions of the population showing plasmid loss that results in auxotrophy. I understand the authors' argument that feral yeasts often do not show auxotrophies because they may only rarely grow exponentially and because they may go through sexual cycles where they need to be able to survive and divide as single haploid cells. But why would mixing auxotrophs in rich medium not yield the same result as a population where the haploids are gradually formed through plasmid loss as the population grows?
One important potential artefact would be that after plasmid loss, the proteins encoded by the lost plasmids remain present and active in the cells for a few generations. It is well known that protein carry-over can persist for more than 5 doublings, so in principle, it could be possible that the population contains "zombies" – cells that are able to survive and even divide for a few rounds, but whose lineage is eventually bound to disappear when the limiting proteins become too diluted because of divisions and protein turnover… This could also explain why at least a fraction of the population remains prototrophic.
I am sure that the authors have also thought about this possibility and will be able to provide arguments against my speculation. It might be useful to also include these in the paper. One possibility would be to closely examine the fluorescence profiles in the SeMeCos – are there any signs of auxotrophs still showing (reduced) fluorescence, or is there a clear bimodal distribution?
Reviewer #3 [abridged]:
I am fine with the revision – it is a considerably improved and focused version of the manuscript. There are several instances where the text will benefit from further edits. I will point out a few:
The authors mention that they "re-isolated individual prototrophs from the established colonies…". I am somewhat confused – is this a typo and it should be "individual auxotrophs", since the authors attempt and fail to co-culture them later? Or do the authors mean that culturing prototrophs for 48 hour in supplemented medium (liquid? solid?) may induces plasmid loss? Either way, it could be worth clarifying this point.
In the subheading “SeMeCos reveal composition dynamics in response to nutritional changes”, the authors state that: "These findings are hence consistent with the notion that metabolic cooperation prevents population intermixing, so that cooperation partners within the colony retain close proximity to prevent diffusion of the exchanged metabolite". Yet, the authors also show that metabolite exchange is not constrained by colonial growth and does continue in liquid cultures. I wonder if the authors could add a sentence or two to discuss this point.
I have no further comments to this paper. I think the revised version provides a better rationale for the work, and I also think the authors have addressed all the other reviewers’ comments satisfactorily.https://doi.org/10.7554/eLife.09943.025
- Markus Ralser
- Markus Ralser
- Markus Ralser
- Markus A Keller
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
We thank Uwe Sauer (ETH Zurich) for support in metabolite measurements and scientific discussion and Elizabeth Bilsland for kindly donating the fluorescent protein plasmids to help determine colony spatial organisation.
- Mohan Balasubramanian, Reviewing Editor, University of Warwick, United Kingdom
© 2015, Campbell et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.