Myxobacteria are known for complex social behaviors including outer membrane exchange (OME), in which cells exchange large amounts of outer membrane lipids and proteins upon contact. The TraA cell surface receptor selects OME partners based on a variable domain. However, traA polymorphism alone is not sufficient to precisely discriminate kin. Here, we report a novel family of OME-delivered toxins that promote kin discrimination of OME partners. These SitA lipoprotein toxins are polymorphic and widespread in myxobacteria. Each sitA is associated with a cognate sitI immunity gene, and in some cases a sitB accessory gene. Remarkably, we show that SitA is transferred serially between target cells, allowing the toxins to move cell-to-cell like an infectious agent. Consequently, SitA toxins define strong identity barriers between strains and likely contribute to population structure, maintenance of cooperation, and strain diversification. Moreover, these results highlight the diversity of systems evolved to deliver toxins between bacteria.https://doi.org/10.7554/eLife.29397.001
Most people do not think of bacteria as having a social life. However, some groups, such as myxobacteria, are highly cooperative. Although these microbes exist as individual cells, they can also move and hunt in coordinated packs and when nutrients are low, about a million cells come together to build spore-filled structures. To do so, myxobacteria need to recognize their sibling cells among the vast number of different species of microbes found in soil.
One way that the bacteria recognise their kin is by displaying a variable cell surface protein, called TraA, that identifies other individuals that display the same protein on their surface. Upon recognition, cells exchange resources by briefly fusing their outer membranes. This allows bacteria to help to rejuvenate damaged sibling cells by delivering healthy cell components to them. Now, using a genetic approach, Vassallo et al. present evidence that bacteria can also exchange toxins.
The newly identified toxin-exchange system works alongside the TraA kin recognition system to allow myxobacteria to recognize and verify their true sibling cells in diverse environments. The cells involved in the exchange must contain matching immunity proteins to survive the interaction – thus the exchange does not harm sibling cells. Strikingly, once the toxic proteins are delivered, they can be passed on to other cells by a series of transfers, much like an infection spreads throughout a population.
The study performed by Vassallo et al. provides a new framework for understanding how microbes recognize their kin to build a community. These insights will help investigators to explore other microbial ecosystems, including those found inside the human body. Additionally, the results also suggest ways in which cells can be engineered to specifically recognize other cells to transfer materials between them. This system could be adapted to program different cell types so that they interact with specific partners and perform complex tasks.https://doi.org/10.7554/eLife.29397.002
Cooperative, social organisms benefit by resource sharing and division of labor between individuals in a population. These behaviors entail directing beneficial action toward kin, often at a fitness cost to the actor. Relatedness between individuals must be high for such cooperative action to remain evolutionarily viable (Hamilton, 1964a, 1964b). This requires that social organisms recognize their kin, and direct preferential action toward them (kin discrimination). The mechanisms by which social microbes recognize and direct benefits toward kin cells are not well understood. However, insights in this area will help us to understand the organization of microbes into social groups and the behaviors that maintain cooperation despite seemingly opposing evolutionary pressures to be selfish.
The soil bacterium Myxococcus xanthus is a model organism for the study of social behavior and cooperation (Cao et al., 2015). Myxobacterial populations divide labor and share resources during coordinated behaviors such as swarming, predation, and starvation-induced fruiting body development. Their social lifestyle, which includes multicellular development by an aggregation strategy, requires that they direct cooperative behavior towards their clonemates or close kin. One such cooperative behavior is outer membrane exchange (OME). During OME, swarming cells in a population simultaneously donate and receive prodigious amounts of outer membrane (OM) material between one another during cell contact. Exchanged material includes membrane lipids, lipoproteins and lipopolysaccharide (Nudleman et al., 2005; Wei et al., 2011; Vassallo et al., 2015; Pathak et al., 2012). The mechanism for exchange is thought to involve transient OM fusion catalyzed by the OM receptor TraA and an associated protein, TraB (Cao et al., 2015; Pathak et al., 2012). Our model predicts that transient OM fusion between two cells enables the lateral diffusion of OM lipids and proteins between OMs until cells move apart and the membranes are again separated (Cao et al., 2015). This process occurs constitutively on surfaces and facilitates efficient OM homogenization of populations with heterogeneous OMs (Wei et al., 2011). Exchange of fluorescent OM lipoprotein reporters, as well as endogenous OM lipoproteins, demonstrates that nearly all recipient cells receive substantial amounts of cargo protein within two hours of co-culture (Nudleman et al., 2005; Wei et al., 2011). Furthermore, cells with lethal defects in lipopolysaccharide biosynthesis can be sustained in a population by OME with wild-type (WT) donors (Vassallo et al., 2015). Based on this observation, OME is hypothesized to help physiologically heterogeneous populations move toward homeostasis and buffer cell damage to support synchronized and cohesive group behaviors (Vassallo et al., 2015; Vassallo and Wall, 2016). This robust system for sharing cellular goods must be discriminately targeted to closely related cells – that is, clonemates. Otherwise, this organism risks donating private goods to competing, non-kin genotypes. In this regard, we previously showed that TraA has a variable domain that specifies recognition between cells through homotypic interactions (Pathak et al., 2013; Cao and Wall, 2017). Thus, myxobacteria with divergent, incompatible TraA receptors do not engage in OME. traA is therefore a greenbeard gene in that it allows myxobacteria to identify cells with identical alleles and to direct beneficial treatment toward those cells (Dawkins, 1976). Greenbeard alleles do not exclusively recognize kin genotypes, but instead recognize any genotype that possesses the same allele (kind discrimination) (Queller, 2011; Strassmann et al., 2011). Indeed, although TraA sequence diversity in the variable domain is high, some non-kin genotypes share compatible traA alleles (Pathak et al., 2013). In fact, some Myxococcus isolates that antagonize one another in co-culture possess the same traA alleles (Pathak et al., 2013). Based on this observation, we hypothesized that there are additional genetic determinants that more precisely discriminate kin during social interactions.
Bacterial kin discrimination is often mediated by antagonism toward non-kin. One mechanism that bacteria use to this end is the delivery of polymorphic toxins between cells in close contact (Zhang et al., 2012; Ruhe et al., 2013; Cardarelli et al., 2015; Wenren et al., 2013). These toxins usually share homology in species-specific amino-terminal domains required for presentation and/or delivery, but vary in their carboxy-terminal toxin domains (Zhang et al., 2012). Each toxin is associated with a cognate immunity protein, typically encoded together in an operon, which specifically neutralizes toxicity in the producing cell and in clonemates or close kin that share the locus. The presence of a polymorphic toxin/immunity pair in one strain leads to antagonism toward related strains that do not possess immunity (Riley and Wertz, 2002). Examples include contact-dependent growth inhibition (CDI; a type Vb secretion system) (Aoki et al., 2005, Aoki et al., 2010); modular type IV secretion system (T4SS) (Souza et al., 2015), type VI secretion system (T6SS) (Russell et al., 2011; MacIntyre et al., 2010; Schwarz et al., 2010; Hood et al., 2010), and type VII secretion system (T7SS) (Cao et al., 2016) effectors; as well as the MafB toxins of Neisseria (Jamet and Nassif, 2015a). The competitive advantages offered by these toxins likely drives positive selection for novel toxin/immunity pairs, which in turn helps to define kin groups through inter-strain antagonism. Mining of prokaryotic genomes revealed that polymorphic toxins are indeed quite prevalent and diverse (Zhang et al., 2012). Additionally, many homologous C-terminal toxin domains are shared between distantly related toxin-delivery systems from diverse organisms, suggesting that these toxins have evolved from a common pool of domains (Zhang et al., 2012). Currently there is a knowledge gap between the number of toxin domains discovered through bioinformatic analysis and the experimental characterization of their delivery mechanisms (Jamet and Nassif, 2015b; Benz and Meinhart, 2014). It seems likely that additional, uncharacterized modes of polymorphic toxin delivery remain to be discovered, with each mechanism adapted to the host’s particular lifestyle. As mechanisms that promote inter-strain and inter-species conflict, polymorphic toxins appear to play a strong role in the evolution of microbes. For instance, kin discrimination by polymorphic toxins may help maintain cooperation in social organisms such as myxobacteria by promoting local relatedness (Hamilton, 1964a; Vos and Velicer, 2009). In addition, they likely play an important role in symbiosis (Hillman and Goodrich-Blair, 2016) and in population structure within ecological niches such as the soil (Varivarn et al., 2013), rhizosphere (Ma et al., 2014), and human gut (Zheng et al., 2015; Russell et al., 2014).
We previously showed that the widely used DK1622 reference strain of M. xanthus is killed by ancestral strains when co-cultured on surfaces (Dey et al., 2016). A traA mutation in either strain abolishes this behavior, indicating that OME is required for antagonism. Further, this antagonism requires a hyper-variable region of the chromosome called Mx-alpha, which is composed of roughly 100 kb of prophage and mobile genetic elements and can be found in multiple copies of imperfect repeats in M. xanthus genomes (Dey et al., 2016). In ancestral strains that antagonize DK1622, there are three homologous Mx-alpha units apparently arranged in tandem. However, two of these units (~200 kb) were lost by spontaneous deletion during the construction of DK1622 (Dey et al., 2016). From these observations, we hypothesized that OME-delivered toxins encoded within the Mx-alpha repeat elements are responsible for antagonism.
Here, we identify the genetic determinant of this antagonism as one of several related, polymorphic, OM lipoprotein toxins that are encoded on Mx-alpha and transferred to target cells by OME. OME between strains that contain different toxins leads to mutual cell death, which establishes territorial barriers between populations. These toxins belong to a large and diverse family found in myxobacteria and display features that make them unique among polymorphic toxin systems. Strikingly, we show that these toxins are serially transferred from cell-to-cell by OME, which results in a potent killing system. Finally, we provide evidence that OME-mediated antagonism contributes to the ecology and evolution of these social microbes.
M. xanthus inter-strain antagonism related to the presence of Mx-alpha was originally observed as ‘swarm inhibition’, during which a nonmotile ancestor strain (Mx-alpha+) inhibited the outward swarming of a motile strain (missing two of three Mx-alpha units) during co-culture on agar. This phenomenon is traA-dependent and therefore is likely an outcome of OME (Pathak et al., 2013) (see Figure 1). Swarm inhibition was further demonstrated to be caused by cell death of the motile strain (Dey et al., 2016). We first sought to identify the specific genetic determinant on Mx-alpha that was required for antagonism and cell death of the susceptible motile strain. Sequence analysis of the two Mx-alpha units retained in the ancestral DK101 strain (a.k.a. DZF1) (Müller et al., 2013) but lost in DK1622 revealed a candidate toxin gene (MXF1DRAFT_07513), which we have designated sitA1 for swarm inhibition toxin. This gene encodes a predicted lipoprotein that contains a C-terminal nuclease domain with a WHH motif (Zhang et al., 2011) (Figure 1A). The absence of lysine at the +2 position or alanine at the +7 position relative to the +1 cysteine in the N-terminal lipobox suggests that this protein is localized to the OM (Bhat et al., 2011) (see Supplementary file 1). Given that OME efficiently transfers OM lipoproteins between cells (Wei et al., 2011), this open reading frame (ORF) represents a promising candidate for the antagonistic determinant. Immediately downstream of sitA1 is a gene (sitI1) that shows homology to the SUKH-family of immunity proteins commonly found in polymorphic toxin systems (Zhang et al., 2011) (Figure 1A). Upstream of sitA1 is a hypothetical gene (sitB1) of unknown function. The sitB1 ORF overlaps with sitA1 by 11 base pairs, suggesting that the genes form an operon and function together (Figure 1A).
To test if sitA1 is the swarm inhibition toxin, we used the swarm inhibition assay as a readout for the contribution of sitA or sitI toward cell death of the susceptible motile strain during co-culture with the antagonistic, nonmotile ancestral strain. In this assay, cell death of the susceptible strain results in no cells visibly escaping the mixed culture spot. In contrast, abrogation of cell death results in the appearance of the motile strain moving outward from the colony co-culture. As shown previously (Pathak et al., 2013; Dey et al., 2016; Dey and Wall, 2014), nonmotile ancestral cells inhibited the motility of DK1622, but not the DK1622 ∆traA strain (Figure 1B, rows 1–4). Importantly, nonmotile ancestors carrying a sitA1 mutation did not inhibit DK1622 (Figure 1B, row 5). Further, expression of sitI1 in motile DK1622 cells also prevented antagonism (Figure 1B, row 6), consistent with the prediction that sitI encodes an immunity protein that neutralizes SitA1. To test whether sitBAI1 is sufficient to convert non-antagonistic cells into killers, we expressed the gene cassette in a DK1622-derived nonmotile strain, which lacks two Mx-alpha units (see Figure 2A), and does not cause swarm inhibition. As predicted, ectopic sitBAI1 expression allowed the nonmotile ∆Mx-alpha cells to inhibit DK1622, thus recapitulating the antagonistic phenotype exhibited by the nonmotile ancestor strain (Figure 1B, rows 7–8). These combined results suggest that sitBAI1 may function as a toxin/immunity system responsible for the antagonistic behaviors previously described (Pathak et al., 2013; Dey et al., 2016; Dey and Wall, 2014). Therefore, the loss of two Mx-alpha units, and thus the sitBAI1 operon (Figure 2A), during the construction of DK1622 from an ancestral DK101 strain explains why the latter strain antagonizes the former.
The three tandem Mx-alpha units in the ancestor strain are related and contain different alleles of >80 genes. This region therefore represents a rare bacterial polyploid element – that is, it contains three Mx-alpha prophage genomes with divergent gene allele sets (Dey et al., 2016). Inspection of the other two Mx-alpha units revealed additional putative sitBAI operons. The second Mx-alpha unit (absent from DK1622) carries sitA2 (MXF1DRAFT_07313), which encodes a putative lipoprotein with clear homology to the N-terminal region of SitA1, though the C-terminal domains are unrelated (Figure 2A). The sitA2 gene is flanked by a sitB1 homolog, sitB2, and a downstream candidate immunity gene, sitI2 (Figure 2A). The third Mx-alpha unit, which is shared between the ancestral strain and DK1622, also appears to contain a sitBAI operon. Although the sitA3 gene (MXF1DRAFT_05864 or MXAN_1899) has low sequence homology with sitA1 and sitA2, the three genes nevertheless share several key features: (1) sitA3 is preceded by sitB3, which is homologous to sitB1 and sitB2, (2) sitA3 occupies a similar position within its Mx-alpha unit as the other sitA genes, (3) sitA3 encodes an OM lipoprotein signal sequence, (4) sitA3 encodes a predicted C-terminal tRNase toxin domain, and (5) sitA3 is adjacent to a downstream putative immunity gene, sitI3 (Figure 2A). This analysis suggests that the three Mx-alpha units each contain distinct sitBAI toxin/immunity operons.
To determine whether SitA lipoproteins function as toxins, we expressed each sitBAI cassette in DK1622 and tested the competitive fitness of the resulting inhibitor strains against parental DK1622 target cells that lack the corresponding sitI gene. Target strains were labeled with fluorescent markers and co-cultured with inhibitor strains on agar for 24 hr. Competition outcomes were assessed by competitive index, which is the ratio of target cells to toxin-producing inhibitor cells at 24 hr relative to the starting ratio. For example, a competitive index of 0.01 indicates that the ratio of target cells to inhibitor cells decreased 100-fold. In all instances, sitBAI-expressing inhibitor cells significantly outcompeted target cells, whereas the mock-inhibitor did not (Figure 2B). Delivery of SitA1 and SitA2 over a 24 hr period induced filamentation and lysis of target cells, whereas SitA3 induced rounding and lysis of target cells (Figure 2—figure supplement 1). Furthermore, a ∆traA mutation in either the target or inhibitor strain abolished the inhibitor’s competitive advantage (Figure 2B). We note that assessing competitive index by microscopy gives a quick and reproducible metric of one strain’s ability to outcompete another, but does not capture the full dynamic range of competition because many enumerated target cells have severe morphological abnormalities and are likely not viable at the 24 hr time point. However, microscopy allows competitive indices to be determined for these otherwise WT strains, which are not easily amenable to enumeration as colony forming units (CFU) because they form extraordinarily cohesive biofilms in isogenic co-cultures (dependent on type IV pili). These results show that SitA lipoproteins provide a competitive advantage, conferring the ability to kill and/or inhibit the growth of competitors in a TraA-dependent manner.
To examine SitA localization, we generated an mCherry reporter that carries the N-terminal lipobox from SitA1. Cells expressing this fusion have membrane-localized fluorescence as expected for a lipoprotein (Figure 2C). The TraA-dependent function of SitA shown in Figure 2B suggests that the protein is delivered by OME. Therefore, we tested whether the reporter fusion is transferred between cells. We co-cultured the reporter strain with a target strain expressing cytoplasmic GFP (which is not exchanged [Wei et al., 2011]) and microscopically assayed for transfer of the reporter. At 6 hr of co-culture, we observed the mCherry signal present in the cell envelope of the GFP target strain, indicating cell-to-cell transfer of the SitA1-mCherry reporter (Figure 2C, upper panel). Deletion of traA in the GFP target strain prevented the acquisition of mCherry signal (Figure 2C, lower panel), recapitulating our earlier findings that OM-localized reporters are exchanged between cells in a TraA/B-dependent manner (Nudleman et al., 2005; Wei et al., 2011; Pathak et al., 2012). Because inner membrane lipoproteins are not transferred during OME (Wei et al., 2011), these data also suggest that the lipobox directs SitA1 to the OM. We confirmed that full-length SitA1 localizes to the cell envelope using immunofluorescence microscopy to detect FLAG epitope-tagged SitA1 in formaldehyde-fixed cells (Figure 2D). Taken together, these results demonstrate that SitA1 resides in the OM and is transferred cell-to-cell by OME.
The fact that sitI1 expression protects WT DK1622 cells from swarm inhibition suggests that this gene encodes an immunity protein that neutralizes SitA1 toxicity. To determine whether SitI proteins block SitA-mediated growth inhibition, we expressed each sitI allele individually in DK1622 ∆sitBAI3 cells and co-cultured the resulting strains with strains that express each of the three sitBAI cassettes. For each competition, only strains that express the cognate sitI were protected from growth inhibition (Figure 2E), consistent with immunity function.
Immunity proteins typically interact with the C-terminal domain of polymorphic toxins (Zhang et al., 2012; Poole et al., 2011). To test whether this was true for SitA, we expressed the predicted C-terminal toxin domains (CTD) of each SitA toxin in E. coli MG1655 under the inducible PBAD promoter. Expression of SitA1-CTD and SitA3-CTD blocked growth, but co-expression of cognate sitI from a second plasmid restored cell growth (Figure 2F). These results confirm that SitI proteins specifically neutralize cognate SitA toxins. In addition, because the SitA-CTD constructs lack secretion signal sequences, these data show that the domains exert their toxic effects in the cytoplasm. We also tested SitA2-CTD expression constructs, but none inhibited E. coli MG1655 growth. Because SitA2-mediated inhibition is obvious in M. xanthus competition co-cultures (Figure 2B and E), we tested the SitA-CTD expression constructs in M. xanthus and found that each inhibited cell growth (Figure 2—figure supplement 2A). Therefore, SitA2-CTD is indeed toxic when expressed in the cytoplasm of M. xanthus.
Given that sitBAI2 expression confers a significant advantage in competition co-culture (see Figure 2B), it is unclear why swarm inhibition was not observed with the sitA1– nonmotile ancestral strain (see Figure 1B, row 5), considering these cells should still deploy SitA2 and that DK1622 lacks the SitI2 immunity protein. Therefore, we tested whether nonmotile ∆Mx-alpha cells that ectopically express sitBAI2 are able to inhibit DK1622 swarming. In agreement with the prior result, we found that DK1622 motility was only partially inhibited by the sitBAI2-expressing strain (Figure 1C, row 1). This result confirms that SitA2 contributes to the swarm inhibition phenotype, but is not sufficiently potent by itself to block outward swarming of DK1622. Together, these results indicate that SitA1 is the major swarm-inhibition toxin. We note that SitA3 does not contribute to the originally observed swarm inhibition phenotype because both ancestor and DK1622 strains contain the sitBAI3 operon (see Figure 2A). However, we found that a nonmotile strain expressing sitBAI3 fully inhibits the motility of a DK1622 ∆sitBAI3 strain that lacks the sitI3 immunity gene (Figure 1C, row 2).
Homologous CTDs are often associated with different toxin delivery systems from phylogenetically distant bacteria (Zhang et al., 2012). SitA3-CTD is homologous to a previously characterized tRNase domain found at the C-terminus of CdiA from Burkholderia pseudomallei 1026b (Morse et al., 2012; Nikolakakis et al., 2012) and an orphan CdiA-CTD encoded by Yersinia pseudotuberculosis YPIII (Figure 3—figure supplement 1). To determine whether SitA3-CTD also has tRNase activity, we expressed the toxin in E. coli and compared its activity to the CDI toxins. Induction of SitA3-CTD expression inhibited cell growth in the same manner as the CdiA-CTD toxins (Figure 3A). Examination of tRNA from SitA3-CTD intoxicated cells revealed cleavage of tRNAUGCAla, similar to the specific tRNase activity of the B. pseudomallei toxin (Figure 3A).
Next, we investigated the toxic activities of SitA1-CTD and SitA2-CTD. We had previously observed that SitA1 induces cell filamentation and loss of DAPI staining in M. xanthus target cells, which is consistent with DNase activity mediated by the predicted Colicin-DNase domain (Pfam 12639, E = 6.7 e-21) containing the WHH motif (Zhang et al., 2011). To test this, we induced SitA1-CTD expression in E. coli and found that cells became filamentous and had reduced DAPI stain signal (Figure 3B). By contrast, E. coli cells that were intoxicated by SitA3-CTD retained DAPI staining, though their nucleoids became more compact (Figure 3B). Together, these results suggest that SitA1-CTD has DNase activity. HMM-HMM comparison (HHpred [Söding et al., 2005]) of C-terminal residues 699–783 of SitA2 revealed distant homology to another CdiA-CTD from Y. pseudotuberculosis YPIII (locus tag, Ga0077885_11586), which was previously characterized as a DNase (Morse et al., 2015). To examine this possibility, we expressed each SitA-CTD in M. xanthus under the control of an IPTG-inducible promoter. Expression of SitA2-CTD in M. xanthus resulted in cell filamentation and reduced DAPI staining (Figure 2—figure supplement 2B), suggesting that SitA2-CTD degrades DNA. Expression of SitA1-CTD and SitA3-CTD in the cytoplasm of M. xanthus cells yielded similar results as when they were expressed in E. coli (Figure 2—figure supplement 2B), although the DAPI signal from SitA3-CTD expressing cells was brighter than the control and many cells contained two distinct nucleoids (Figure 2—figure supplement 2B), suggesting a block in cell division.
To determine the phylogenetic distribution of SitA toxins, we conducted a BLAST search using the N-terminal domains of SitA1/2 (which are homologous) and SitA3 as query sequences. This search recovered >100 sitA orthologs that are common in the Myxococcales (Supplementary file 1). More sensitive search algorithms such as HMMER (Finn et al., 2011) failed to identify significant homologs outside of the Myxococcales. Consistent with the finding that SitA is delivered through OME, all orthologs contain lipoboxes and are only found in species that contain traAB. Moreover, SitA C-terminal domains are variable and typically show homology to nuclease domains when subjected to HMM-HMM comparison using HHpred (Supplementary file 3). Interestingly, many sitA genes are not linked to upstream sitB orthologs, particularly in species that are distantly related to M. xanthus (Supplementary file 1). This suggests that SitB may not be required for SitA function, or perhaps that SitB proteins, encoded at unlinked loci, function promiscuously between multiple SitA proteins. Notably, some sitA loci are found outside of Mx-alpha-like elements, however, these genes are typically adjacent to other mobile genetic elements. To test cross-genotype compatibility of SitA orthologs, we cloned two sitA gene cassettes from Myxococcus fulvus HW1 for heterologous expression in M. xanthus. One of these operons (sitAI3Mf1) does not contain a sitB gene. As predicted, M. xanthus cells that express heterologous sitAI3Mf1 or sitBAI1Mf1 outcompeted the parental strain in a traA-dependent manner (Figure 2—figure supplement 3). These results indicate that SitA toxin delivery is not limited by its specific species/strain of origin, and that the systems are functional after horizontal gene transfer (HGT) of a minimal set of components (sitAI).
Our results show that sitBAI-expressing cells inhibit OME-compatible strains that lack a cognate SitI immunity protein. We hypothesized that this antagonism should be sufficient to mediate territorial exclusion. Territorial exclusion promotes physical segregation of nonself organisms (Gibbs and Greenberg, 2011), which in turn drives both diversification and maintenance of cooperation (Papke and Ward, 2004; Velicer and Vos, 2009). Territorial exclusion between wild M. xanthus genotypes, including those that are closely related and that are isolated in close proximity to one another has been well studied, but the specific determinants underlying this behavior are unknown (Vos and Velicer, 2009; Rendueles et al., 2015; Vos and Velicer, 2006; Wielgoss et al., 2016). We tested whether SitA is sufficient for territorial exclusion by conducting colony merger assays with every combination of DK1622 strains expressing one of the five described sitAI alleles. In these assays, two liquid cultures are spotted next to one another on agar, and the colonies are allowed to swarm toward each other. If the converging swarms merge, then the strains are considered compatible. For each combination, the expression of different sitAI cassettes resulted in dramatic lines of demarcation between the two strains (Figure 4A), and the formation of these demarcation zones was traA-dependent (Figure 4B). These results show that otherwise isogenic strains are rendered socially incompatible and geographically isolated by the acquisition of a single sitAI cassette.
We previously found that swarm inhibition occurs efficiently even when motile cells outnumber the antagonistic nonmotile strain 40 to 1 (Dey and Wall, 2014). This observation suggests that an individual SitA-expressing cell can inhibit many targets. To further explore this phenomenon, we quantified viable target cells in a series of competition co-cultures in which the ratio of SitA producing cells to targets was progressively decreased by factors of 10. To facilitate CFU enumeration in these experiments, we used ∆pilA cells, which are unable form type IV pili-dependent biofilms. We found that target cell CFU were reduced approximately 106-fold when the strains were mixed at a 1:1 ratio (Figure 5A). The higher degree of killing reported here (compared to competitive index in Figure 2B) provides a clearer understanding of the killing efficiency because the CFU assay measures a broader dynamic range of viable cell number. Remarkably, the SitA-producing strain still reduced target cell viability >104-fold in co-cultures seeded at a 1:1000 ratio of inhibitors to target cells (Figure 5A). These observations imply that each inhibitor cell intoxicates several thousand target cells during co-culture. In one explanation we hypothesized that OME delivery allows a series of SitA transfer events from one target cell to other cells. We consider this serial transfer mechanism plausible if translocation of all toxin molecules from the target cell OM to the cytoplasm is not completed before subsequent OME events occur. This model predicts that SitA toxins could spread through the population like an infectious agent, intoxicating target cells that never made direct contact with the producer. To test this hypothesis, we conducted three-strain competitions with (1) a sitBAI1 inhibitor strain that contains M. fulvus traAB (traABMf) as its only traAB alleles, (2) a susceptible target strain that contains M. xanthus traABDK1622 alleles and thus is incompatible for OME with the inhibitor, and (3) a susceptible intermediary strain that carries both traABMf and traABDK1622 (Figure 5B). If serial toxin transfer occurs, the traAB merodiploid strain should act as an intermediary carrier/conduit to deliver toxin to traABDK1622 targets (Figure 5B). As a control, we first showed that traABMf inhibitors do not inhibit traABDK1622 targets (Figure 5C), consistent with the incompatibility of their traAB alleles. Importantly, inclusion of intermediary cells, which are inhibited (Figure 5D), also resulted in the inhibition of traABDK1622 target cells (Figure 5E). As expected, the intermediary strain (which lacks sitBAI1) did not inhibit traABDK1622 targets in co-cultures containing only those two strains (Figure 5F). To exclude a SitA-independent mechanism of target cell inhibition, we conducted the same three-strain competition, but provided traABDK1622 targets with the sitI1 immunity gene. In this latter co-culture, the intermediary strain was inhibited, but traABDK1622 targets were not (Figure 5G). Finally, we tested an intermediary strain that lacks traA and found that neither intermediary nor target cells were inhibited during co-culture (Figure 5H).
To directly visualize serial transfer, we co-cultured traABMf cells that express the SitA1-mCherry fusion (described in Figure 2) with traAB merodiploid intermediary cells that express cytoplasmic tdTomato, and GFP-labeled, traABDK1622 target cells. Microscopic examination of target cells at 6 hr revealed that all had acquired mCherry fluorescence, with the signal localized to the cell envelope (Figure 5I, left panels). By contrast, no SitA1-mCherry transfer was detected when the intermediary was absent from the co-culture (Figure 5I, right panels). Although these results are consistent with serial transfer of SitA, it is also possible that target cells acquire TraAMf and/or inhibitor cells acquire TraADK1622 by OME-dependent exchange of TraA with the intermediary strain, which would then allow direct transfer of SitA between inhibitor and target cells. To test if TraA is transferred during OME, we used a TraA-mCherry fusion to monitor transfer of TraA. The TraA fusion promoted efficient transfer of an OM sfGFP reporter (Figure 5—figure supplement 1A), demonstrating that it is functional to catalyze OME. However, TraA-mCherry itself was not transferred (Figure 5—figure supplement 1B). One explanation for why TraA does not transfer is that it interacts with TraB, which contains an OmpA domain known to bind the cell wall. For this reason, we suspect TraA is anchored to the cell envelope and is unable to transfer (Cao and Wall, 2017). Taken together, these results indicate that SitA1 can be transferred from the initial target to secondary recipients, supporting a model in which SitA acts like an infectious agent that disseminates through a population by OME.
In M. xanthus and its close relatives, sitA is typically accompanied by an overlapping sitB cistron. In the case of DK101 the genes overlap by 11 bp in all three sitBAI cassettes. SitB shows no significant homology to other proteins or domains using HMMER or HHpred, though it does contain a type I signal sequence (SignalP 4.1 [Petersen et al., 2011]). I-TASSER (Zhang, 2008) predicts that SitB adopts a transmembrane β-barrel structure characteristic of OM proteins. To examine the role of SitB1, we tested the activity of inhibitor cells that express either sitBAI1 or sitAI1 (cells lack sitB1) against a susceptible target strain. The inhibitors in these experiments also carried a ∆sitB3 mutation to eliminate the possibility of promiscuous interactions between SitB3 and SitA1. At a 1:1 (inhibitor to target) ratio, sitAI inhibitors had less of an advantage against targets than sitBAI inhibitors, but still retained activity compared to the mock inhibitor control (Figure 6A, left). The sitAI inhibitors were less effective at a 1:10 ratio, and at 1:100 were indistinguishable from mock inhibitors (Figure 6A). In contrast, sitBAI1 inhibitors were equally effective at outcompeting the target strain at each of the three ratios (Figure 6A). Thus, SitB1 contributes significantly to SitA1-mediated inhibition.
Progressive loss of function at increasing target to inhibitor ratios with the sitAI inhibitors could indicate defects in serial toxin transfer compared to sitBAI inhibitors. Therefore, we tested serial transfer using three-strain co-cultures as described in Figure 5B. To improve the sensitivity of this assay, we increased the inhibitor to intermediary to target strain ratio to 10:1:1 to compensate for the inhibition defect of sitAI1 cells. As observed in Figure 5, sitBAI1 cells outcompeted both the intermediary and target strains (Figure 6B). Because of the high inhibitor cell ratio, the sitAI1 cells outcompeted the intermediary strain to a similar extent as sitBAI cells, but importantly, sitAI cells had little to no effect on target cells (Figure 6B). We extended the experiment to 48 hr and also performed experiments with SitA-resistant intermediary cells, to increase the number of conduit cells, but again we did not observe SitAI-mediated antagonism of target cells. These results support the hypothesis that SitB promotes SitA transfer, including the serial transfer from primary to secondary target cells. Although SitB1 clearly contributes to SitA1-mediated inhibition, it is not strictly required, which may explain why many myxobacterial sitA genes are not linked to sitB. Finally, these results are congruent with our above conclusion that TraA is not transferred, because if it was, then direct transfer of SitA1 would occur between sitAI inhibitors and the target strain. However, this did not occur because the target strain was not inhibited.
M. xanthus uses multiple inhibitory mechanisms to antagonize non-kin. However, because SitA toxins are serially transferred between cells, we hypothesized that they should be powerful determinants of competitive outcomes during inter-genotype conflict. To test this hypothesis, we quantified the contribution of TraA and SitA to competitive outcomes in co-cultures of DK1622 with wild M. xanthus soil isolates. Isolates A66 and A88 (from Tübingen, Germany) (Vos and Velicer, 2006) and DK801 (from California, USA) (Martin et al., 1978) contain traA alleles in the same recognition group as DK1622 (originally isolated from Iowa, USA) (Pathak et al., 2013; Dey et al., 2016). We compared the fitness outcomes of WT, ∆traA, and ∆sitBAI3 genotypes when co-cultured with these environmental isolates by monitoring the ratio of fluorescently labeled DK1622-derived cells to isolate cells at 4, 8 and 24 hr. As a second metric, we enumerated CFU of the DK1622-derived strains at the 24 hr time point. In every case, mutant strains that cannot deploy SitA3 had dramatically decreased competitive fitness outcomes and viability compared to WT (Figure 7A). Remarkably, against all three isolates, the presence of traA was the determining factor in which strain prevailed, demonstrating up to a 106-fold swing in strain ratio (vs. A66) and a near 107-fold difference in CFU (vs. DK801) between WT and ∆traA strains (Figure 7A). These results indicate that the ability to deliver SitA3 is a dominant determinant of competitive fitness under these conditions. Not surprisingly, the finding that environmental isolates outcompeted and killed ∆traA strains (Figure 7A), confirms the existence of OME-independent killing mechanisms at play. Interestingly, these experiments revealed that ∆traA cells had less competitive fitness than ∆sitBAI3, indicating a competitive fitness defect in ∆traA cells beyond just the inability to deploy SitA3. As a control, we competed the DK1622 genotypes against isolates A23 and A47 (from Tübingen [Vos and Velicer, 2006]), which are outside the DK1622 TraA recognition group (Pathak et al., 2013). ∆traA and ∆sitBAI3 genotypes resulted in similar competitive outcomes as WT as would be expected when inter-strain OME does not occur and SitA3 cannot be deployed (Figure 7B). These results show that SitA contributes significantly to fitness during competition with TraA-compatible non-kin genotypes, and likely plays a key role in competition and survival in nature.
Here, we describe a novel family of proteins that carry polymorphic toxin domains and are delivered between myxobacteria by OME. SitA proteins are similar to other polymorphic toxins in that they carry diverse C-terminal domains, are neutralized by cognate immunity proteins, and are delivered in a cell contact-dependent manner. However, they are unique in their N-terminal domains, and in that they are lipoproteins transferred with other cargo during OME. To our knowledge, this is the first example of a polymorphic toxin system in which the toxin itself is a lipoprotein. Unlike CDI, T4SS, T6SS and T7SS toxins, there appears to be no requirement for a specialized apparatus to export the toxins. Instead, toxins are exchanged bi-directionally and simultaneously during OME. Therefore, SitA delivery likely only requires OM localization of the toxin and compatible TraA receptors. This discovery highlights the diversity of mechanisms used by bacteria to deliver polymorphic toxins.
Importantly, the SitA toxin family constitutes a second identity constraint upon OME with partner cells. For two cells to engage in OME, not only must they present compatible TraA receptors, but they must also contain immunity proteins to each other’s toxins. In this ‘recognize and verify’ system (Wall, 2016), if the latter constraint is not met, then the recipient of the toxin is poisoned. TraA homotypic interactions alone are considered kind or greenbeard recognition, in which social interactions are based on a single gene locus. The finding that myxobacteria verify relatedness with sitAI confirms the notion that myxobacteria apply a bona fide kin discrimination mechanism during OME by requiring identity verification at multiple polymorphic loci. Interestingly, this system allows TraA interactions to promote contrasting behaviors – cooperative or antagonistic – depending on relatedness. Either outcome makes OME potentially beneficial regardless of the partner by conferring the ability to both share goods with clonemates and poison non-kin.
SitA delivery range is restricted to within a single TraA recognition group. Considering traA allele diversity is high (Pathak et al., 2013), this significantly limits the use of SitA to related but nonself individuals. This suggests that one of the primary functions of SitA is the discrimination of exchange partners, consistent with the notion that sharing large amounts of goods with non-kin is costly. Within TraA recognition groups, OM material is a shared good; a resource to be guarded from exploitation by OME compatible, yet nonself populations. Myxobacteria achieve this safeguard by inextricably linking the delivery of these goods with the delivery of SitA toxins. Another example is the Burkholderia thailandensis CDI system, which couples a communication signal with polymorphic toxin delivery during biofilm formation (Anderson et al., 2014). Similarly, the CDI system of E. coli mediates both antagonism and cooperative intercellular adhesion to related cells (Ruhe et al., 2013, 2015). In Proteus mirabilis, IdsD/IdsE interactions communicate identity and may promote cooperative behaviors (Cardarelli et al., 2015). This intercellular communication is also coupled to toxic T6SS effector delivery (Wenren et al., 2013). In these examples, organisms link goods, signals, and/or cooperative behaviors to polymorphic toxin delivery, which ensures that potential cooperators are related.
Differential acquisition of antagonistic systems can affect cooperation compatibility between originally identical genotypes. We demonstrated that when two otherwise isogenic colonies express different SitA toxins, they are no longer able to merge swarms. The acquisition of a single sitAI operon would therefore alter strain identity and population structure between previously clonal cells. However, the impact of SitA on strain identity and population structure in natural soil habitats depends on two factors: (1) strains that belong to the same traA recognition group must exist in proximity, and (2) sitA loci must be sufficiently diverse to ensure different toxin/immunity types are represented at fine geographic scales. Velicer and colleagues have examined the compatibility of natural M. xanthus isolates obtained from a centimeter-scale plot of soil (Vos and Velicer, 2009; Wielgoss et al., 2016). Colony merger assays between these geographically proximal strains reveal compatibilities among the most closely related isolates, but also strong incompatibilities between strains that differ by only several dozens of mutations outside of the Mx-alpha region (Wielgoss et al., 2016). Indeed, these incompatibilities correlate with gene variation at hyper-variable Mx-alpha loci, where sitBAI genes commonly reside. Our analysis of their published sequences reveals 69 total and 15 unique sitA alleles distributed over 22 isolates (see Materials and methods for search criteria). Between these strains there are two traA alleles that are known to be incompatible (Pathak et al., 2013). Within each TraA recognition group we have observed an apparently high degree of correlation between the published colony merger compatibility of the strains (Wielgoss et al., 2016) and the sitA genes they possess. This suggests that sitBAI polymorphisms contribute to swarm incompatibility and inter-strain competition among natural soil isolates. We are currently investigating this possibility. Moreover, because Mx-alpha produces defective phage particles that promote specialized transduction (Starich and Zissler, 1989; Starich et al., 1985), these elements are apparent hotspots for HGT, perhaps explaining the high degree of Mx-alpha variation discovered between otherwise related isolates (Wielgoss et al., 2016). These variations likely contribute to the emergence of new compatibility types which underlie complex population structures, and explain the observation of rapidly evolving social antagonisms in M. xanthus (Velicer and Vos, 2009). Thus, TraA and SitA may act as powerful evolutionary drivers of myxobacteria diversification.
sitAI genes are often associated with prophage-like elements or other mobile elements and thus are likely acquired by HGT. By conferring a fitness advantage to their host, they may play an important role in transmission and retention of mobile DNA. For example, a HGT event into one cell in a population endowing it with a novel sitBAI operon allows that cell to infect its clonemates with toxins, thus ensuring the propagation of that element within the population. Similarly, the loss of the element would be lethal because the surrounding cells harbor this toxin-immunity pair would kill susceptible cells. Importantly, this model explains why many lab strains have stably maintained three large tandem repeats of Mx-alpha, which is expected to be genetically unstable (Starich and Zissler, 1989; Roth et al., 1996). In cases in which strains have spontaneously lost Mx-alpha units (Dey et al., 2016), those events likely occurred during propagation in liquid media, where OME cannot occur. Mx-alpha has the attributes of a selfish or addictive element that exploits the social nature of myxobacteria and OME. However, the origin of sitBAI loci is unclear because these genes also reside outside of selfish elements in myxobacterial genomes.
SitA toxins are uniquely powerful determinants of identity, likely because they are transmitted as infectious agents between recipient cells. The infectious model is consistent with the observations that individual M. xanthus cells typically make contact with multiple cells simultaneously within a swarm, OME is constitutively active, and that prodigious amounts of material are transferred during OME (Nudleman et al., 2005). Furthermore, SitA entry into the cytoplasm occurs by a secondary and uncoupled pathway to OME (Dey et al., 2016; Dey and Wall, 2014). Thus, it is possible that SitA lingers in the OM of the primary target long enough to allow transfer to secondary target cells through subsequent OME events (Figure 8A). Perhaps a cellular protein is required for SitA cell entry (Dey et al., 2016; Dey and Wall, 2014), but this protein is outnumbered by SitA molecules in the OM, making cytoplasmic entry a rate-limiting step. Based on these inferences, we propose two non-exclusive models that explain serial transfer: (1) Following transfer of SitA to a primary infected cell, OME with a secondary cell occurs before the full complement of SitA enters the cytoplasm of the initial recipient (Figure 8B); or (2) that three or more cells are engaged in OME simultaneously (Figure 8C). Our results suggest that SitB functions to promote serial transfer. Given that ∆sitB inhibitors have defects in direct transfer, serial transfer could be blocked simply by a decrease in number of SitA molecules delivered or a decrease in rate of delivery. Alternatively, SitB could stabilize SitA in the OM of the inhibitor and/or target cell, thereby increasing OM dwell times to promote serial transfer. The finding that SitB is an accessory protein is consistent with bioinformatics analysis in which many of the sitA genes that reside outside of the M. xanthus species are not linked with a sitB gene. In the case of M. xanthus isolates (Wielgoss et al., 2016), we found only 3 of 69 sitA genes were not associated with sitB. The mechanism of serial transfer, the function of SitB, and the ability of SitA to traverse the cell envelope are topics for future study. With respect to the latter point, in prior work we found that a mutation that disrupts the inner membrane protein, OmrA, renders target cells resistant to SitA1 (Dey et al., 2016; Dey and Wall, 2014). Thus, as proposed for CDI toxins, one possibility is that SitA toxins exploit inner-membrane proteins to gain access to the cytoplasm (Willett et al., 2015).
Remarkably, SitA appears to determine the competitive outcome of two-strain co-cultures between DK1622 and wild-isolates, despite the T6SS and a host of other antagonistic machinery at play (Konovalova et al., 2010; Smith and Dworkin, 1994). We hypothesize that the rapid spread of SitA by serial transfer may disrupt the antagonistic capabilities of competitors. When deployed between converging swarms, serial transfer provides a mechanism to inhibit cells behind the front-lines. Thus, SitA mediated antagonism results in the formation of distinct territorial boundaries (see Figure 4), which in turn minimize OME, resource sharing, and social interactions between non-clonal swarms.
The selective pressure from SitA antagonism within a TraA recognition group may help drive the generation and fixation of traA polymorphisms that determine recognition specificity. For instance, we recently showed that simply substituting a single amino acid residue in TraA can alter recognition specificity while retaining OME function (Cao and Wall, 2017). More broadly, it is a puzzle how organisms select and maintain genetic variation in social genes such as traA. Diversification of beneficial greenbeard genes is theorized to be selected against because social groups with more common alleles receive benefit more often than those with less common alleles. This pressure to possess the allele that gains the most benefit is thought to ultimately erode allele diversity that originally allowed discrimination. This problem is known as Crozier’s paradox (Strassmann et al., 2011; Crozier, 1986). Our results provide one solution to this paradox in that variation at a second locus (sitA, a ‘harming greenbeard' [Gardner and West, 2010]) exerts selective pressure to diversify TraA, a helping greenbeard (Wall, 2016). For example, if one strain is killed by another via SitA, a TraA mutation that alters specificity within the losing population would be immune and retain OME function, and would thus be selected for. We suggest that other greenbeard systems could involve a similar balance between antagonism and cooperation that promotes maintenance of diversity for beneficial greenbeard genes.
Our results provide a description of a novel polymorphic toxin system that helps direct cellular goods to clonemates to promote multicellular cooperation. Polymorphic toxin systems are widely prevalent in bacteria and their role in population structure, ecology and evolution of microbes is only beginning to be understood. Importantly, this study highlights the diversity of delivery mechanisms for these domains and how they have adapted to the lifestyle of their host genomes.
All strains are listed in Supplementary file 2A. M. xanthus was routinely grown in CTT medium [1% casitone; 10 mM Tris⋅HCl (pH 7.6); 8 mM MgSO4; 1 mM KH2PO4] in the dark at 33°C. E. coli TOP10 and MG1655 were grown in LB media at 37°C. As needed for selection or induction, media were supplemented with kanamycin (50 µg/mL), oxytetracycline (10 µg/mL), ampicillin (100 µg/mL), streptomycin (50 µg/mL), arabinose (0.2%), or IPTG (1 mM). TPM buffer (CTT without casitone) or PBS was used to wash cells. CTT or LB agar was used as a solid growth medium for routine strain maintenance. For all assays, strains were grown to logarithmic growth phase, washed, and re-suspended to the appropriate density.
All plasmids and primers are listed in Supplementary file 2B,C. Plasmids were constructed and maintained in E. coli and subsequently electroporated into M. xanthus. In the case of cloning IPTG-dependent sitA-CTDs, plasmids were maintained in XL1-Blue, which overexpresses LacI and reduces clone toxicity. Insertion mutations were created by amplifying an approximately 500 bp fragment of the gene of interest by PCR and cloning the fragment into the pCR-TOPO XL or pCR-TOPO 2.1 vectors (Invitrogen, Carlsbad, CA). For gene expression in M. xanthus, we cloned the appropriate gene(s) into pMR3487 using XbaI and NdeI restriction sites and T4 DNA ligase. If the gene(s) of interest contained these restriction sites, we used Gibson Assembly (Gibson et al., 2009) (New England Biolabs, Ipswich, MA) for plasmid construction. pMR3487 recombines at a specific site in the M. xanthus chromosome and expression is induced with IPTG (Iniesta et al., 2012). Traditional restriction endonuclease cloning was used to create pBAD30, pCH450 and pKSAT derived plasmids in which the sitA-CTD fragments had an ATG start codon engineered into the insert. Expression of sitI genes in pKSAT is constitutive, driven by the Kmr promoter. pCV10 for GFP expression was created by ligating tandem rRNA promoters, used for expressing lacI from the pMR3487 plasmid, with EGFP and the pSWU19 plasmid backbone. This plasmid recombines into the M. xanthus chromosome at the Mx8 phage attachment site. The deletion of sitBAI3 was constructed by cloning in-frame regions flanking and partially overlapping the start and stop codons of sitB3 and sitI3, respectively, into pBJ114 using Gibson Assembly. After recombination in M. xanthus, mutants were grown in CTT for 24 hr and plated on CTT containing 2% galactose to select for spontaneous loss of the galK marker. Deletion mutants were distinguished from WT by PCR with primers that flanked the deletion site.
Competition experiments, unless otherwise noted, were done using 1:1 strain mixtures of 3 × 108 cells per mL spotted (20 µL) on agar plates containing 0.5× CTT with 2 mM CaCl2 and 1 mM IPTG (competition media). Culture spots were harvested at 24 hr and observed on glass slides by microscopy to quantify strain ratios based on fluorescent labels. Typically, between 200 and 800 cells were counted. Competitive index in all assays was quantified by calculating the change in ratio of target to toxin-producing inhibitor cells over 24 hr. For example, if the 0 hr ratio was 1 to 1 and the 24 hr ratio was 1 to 100, the competitive index was. 01, indicating that the target strain was outcompeted. Swarm inhibition experiments were done identically but cells were not collected and instead were imaged after 72 hr. To determine the potency of killing, competition assays were conducted where the target cell volume and density were held constant (50 μL, 3 × 108 cells per mL) while the number of toxin producing cells were titrated 1 to 10 for each sample. Cells were harvested at 48 hr, serially diluted and plated on CTT containing Km to enumerate viable target cells.
For the SitA1 serial transfer assay, competition was done at 1:5 or 1:5:5 mixtures of inhibitors to target(s) using a culture density of 3 × 109 cells per mL. For competition with environmental isolates, liquid cultures of the DK1622-derived strain and the environmental isolate were adjusted to 3 × 109 cells per mL liquid culture, mixed (100 µL DK1622 to 50 µL isolate), and spread onto competition media to ensure there were enough non-lysed cells to count by fluorescent microscopy. At the indicated time points, 2 mL of TPM was added to the agar plate, agitated with a plate spreader, and collected by pipette. Cells were centrifuged at low speed to help prevent clumping and either cell ratio was quantified by microscopy (as above) or the cells were resuspended in 1 mL TPM for CFU determination. Clumping was not an issue due to a non-isogenic mix of strains and massive cell lysis interfering with cell-cell adhesion. CFU of DK1622-derived strains were enumerated by 1 to 10 serial dilution and plating on CTT with oxytetracycline. All figures that contain error bars indicate the experiments were done in triplicate on different days. All statistical tests comparing two results are unpaired, two-tailed t-tests.
To test for growth inhibition by toxin expression, overnight cultures of each strain grown in LB with appropriate antibiotics were adjusted to OD600 = 1.0 and back diluted 1 to 10 into fresh media containing 0.2% arabinose (to induce expression from pBAD), ampicillin 100 μg/mL and streptomycin 50 μg/mL. Cultures were then incubated in a shaker at 37°C for 5 hr. 1 to 10 serial dilutions of each culture were plated on LB with 0.2% arabinose and 100 μg/mL ampicillin and imaged after overnight growth at 37°C.
For DAPI staining, cells were grown as described above. At 0 hr and 6 hr post arabinose induction cells were adjusted to OD600 = 0.4 and 1 mL was collected by centrifugation. Cells were fixed in freshly prepared 4% (vol/vol) formaldehyde in PBS for 15 min, rotating at room temperature (RT). The reaction was quenched by addition of an equal volume of 250 mM glycine (pH 7.5) in PBS. Cells were collected and washed 3x and resuspended to 100 μL. Cells were then spotted on poly-L-lysine coated slides and incubated for 10 min. Excess liquid was removed and cells were rinsed with water. 5 μL of fluorogel-II with DAPI (Electron Microscopy Sciences, Hatfield, PA) was placed on cells, a coverslip was applied and cells were imaged at 100× magnification with a Nikon E800 microscope coupled to a digital imaging system (Wei et al., 2011).
To assess tRNA processing, total RNA was isolated from E. coli clones using guanidine isothiocyanate-phenol extraction as described (Garza-Sánchez et al., 2006). Here, cultures were grown to mid-log phase and then diluted to OD600 = 0.05 and grown for 30 min before 0.4% arabinose was added to induce toxin expression. tRNAs were analyzed by Northern blot hybridization using the following 5´-radiolabeled oligonucleotide probes: tRNAUGCAla (5´ - TCC TGC GTG CAA AGC AG), tRNAICGArg (5´ - CCT CCG ACC GCT CGG TTC G), tRNACGASer (5´ - GTA GAG TTG CCC CTA CTC CGG), and tRNAGCACys (5´ - GGA CTA GAC GGA TTT GCA A).
These assays used a modified competition media (replacing 1.5% agar with 1.0% agarose for imaging and addition of 5 μg/mL oxytetracycline). A multichannel pipette was used to simultaneously pipette competing strain suspensions (1.5 × 109 cells per mL) until culture spots were nearly touching. Aliquots were air dried and plates were then incubated in a humid chamber at 33°C for 3 days. Spots were viewed on an Olympus SZX10 stereomicroscope coupled to a digital imaging system.
To discover SitA homologs, we performed BLAST (Altschul et al., 1990) analysis against the IMG database (Markowitz et al., 2012), using the conserved N-terminal sequence (first 507 amino acids of SitA1 and the first 441 amino acids of SitA3) as queries. HMMER (Finn et al., 2011), HHPred (Söding et al., 2005) and I-TASSER (Zhang, 2008) analysis were performed as described above using default parameters.
To detect any correlation between colony merger and sitA genes from the referenced study (Wielgoss et al., 2016), we first identified SitA homologs by performing local BLAST analysis of the sequences published at http://www.odose.nl/u/michiel/h/22-myxo-genomes-w-annotation (Wielgoss et al., 2016) using SitB1 as the query. Any gene located downstream of a SitB homolog that contained the described features of SitA was considered a SitA homolog. We also used SitA homolog sequences as queries to find any sitA genes without an accompanying sitB. Redundant sequences were removed using NCBI FASTA Tools Unique Sequences webpage. The sequences were then clustered according to >96% pairwise amino acid identity and each cluster was considered a unique polymorphic toxin group. The two closest toxin groups were 90% identical. This analysis was done blind with respect to the published colony merger compatibility types (Wielgoss et al., 2016).
Log-phase reporter and target cell liquid cultures were adjusted to 1.5–3 × 109 cells per mL, mixed at the indicated ratios, and plated on ½ CTT agar with 2 mM CaCl2, +/- IPTG, as needed. Strains were incubated at 33°C for the indicated time-period, collected, and visualized by fluorescent microscopy as described (Wei et al., 2011).
Log phase cultures were resuspended to 6 × 108 cells per mL in reduced osmolarity PBS solution (“mPBS” = 7.2 mM NaCl, 5.4 mM KCl, 10 mM Na2HPO4, 1.8 mM KH2PO4). 100 μL of 10% paraformaldehyde solution (in mPBS) and 1 μL of 5% glutaraldehyde solution (in H2O) were added to 400 μL of cell suspension. Each mixture was spotted on a poly-lysine coated slide. Fixation proceeded for 30 min at RT. After rinsing with mPBS, cells were permeabilized with 0.025% Triton X-100 for 10 min and washed. Cells were blocked for 1 hr at RT with 4% BSA in mPBS, then probed with a 1:1000 final concentration of anti-FLAG antibody (in 4% BSA, Sigma, St. Louis, MO) for 1 hr at RT and subsequently washed 2× for 5 min and 1× for 10 min with mPBS. Cells were then probed with a 1:2000 final concentration of secondary antibody (in 4% BSA, Alexa Fluor 488-conjugated donkey anti-rabbit IgG; Jackson ImmunoResearch, Westgrove, PA) for 30 min at RT and subsequently washed as before. SlowFade Gold antifade reagent (Invitrogen) was added to the slide and the cells were visualized with a 100× objective lens. Western blot was performed according to standard protocols, using anti-FLAG antibody described above, and horseradish peroxidase-conjugated goat anti-rabbit secondary antibody (Thermo Scientific, Waltham, MA).
Each SitA-CTD was expressed from an IPTG-inducible promoter. For liquid growth-inhibition, cells were grown to log-phase and diluted to 5 × 107 cells per mL in two separate flasks containing fresh media (CTT, 2.5 μg/mL oxytetracycline). To one of two flasks, IPTG was added to 1.0 mM. Cells were grown in the dark with shaking at room temperature. Culture growth was monitored at the indicated time points by measuring turbidity using a Klett meter. For DAPI staining, cells were grown as above for 30 hr, washed and resuspended in mPBS to a concentration of 1.5 × 109 cells per mL. 1 μL of a 50 μg/mL DAPI solution (Life Technologies, Carlsbad, CA) was added for each mL of culture. Cells were incubated for 20 min in the dark with rotation, washed, concentrated, and visualized by fluorescent microscopy.
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Michael T LaubReviewing Editor; Massachusetts Institute of Technology, United States
In the interests of transparency, eLife includes the editorial decision letter and accompanying author responses. A lightly edited version of the letter sent to the authors after peer review is shown, indicating the most substantive concerns; minor comments are not usually included.
[Editors’ note: a previous version of this study was rejected after peer review, but the authors submitted for reconsideration. The first decision letter after peer review is shown below.]
Thank you for submitting your work entitled "Infectious polymorphic toxins delivered by outer membrane exchange discriminate kin in myxobacteria" for consideration by eLife. Your article has been reviewed by three peer reviewers, one of whom is a member of our Board of Reviewing Editors and the evaluation has been overseen by a Senior Editor. The following individuals involved in review of your submission have agreed to reveal their identity: John Whitney (Reviewer #2); Karine A. Gibbs (Reviewer #3).
Our decision has been reached after consultation between the reviewers. Based on these discussions and the individual reviews below, we regret to inform you that your work will not be considered further for publication in eLife at this time. However, the reviewers were all very enthusiastic about the topic and intrigued by the potential of serial transmission of an outer membrane toxin. The problem was that there were significant concerns that would have to be addressed experimentally, but could take longer than the usual two months offered for revised papers. If you are able to fully address each of the major concerns, we would welcome a resubmission. The full concerns of the reviewers are spelled out in the individual reviews below. To summarize briefly, four of the most significant concerns were a need to (i) demonstrate that the toxin domains of SitA1, SitA3, and SitA2 are toxic when expressed in Myxococcus, not just E. coli, (ii) better define the role of SitB, (iii) demonstrate that it is indeed the SitA-CTDs that are transferred, not TraA, and (iv) show directly somehow that SitA-CTDs are serially transferred in an infectious-like process.
This paper presents an interesting initial study of SitA toxins in Myxococcus xanthus. The authors present data indicating that these SitA toxins may contribute to kin recognition. They further posit that these toxins are serially transferred from cell to cell like an infectious agent. This latter point is potentially quite exciting, but the data to support it are incomplete. Overall, the paper was relatively straightforward and well done, but the deficiencies in fully demonstrating that SitA toxins are serially transferred are a current, major limitation.
Figure 3B: It's useful to see what happens when the SitA1 and SitA3 toxin domains are expressed in E. coli, but I think the authors must show what happens when they (and SitA2's toxin domain) are expressed in Myxococcus in terms of morphology, DAPI staining, etc.
The role of SitB was unclear to me. The authors should do experiments, like those in Figure 2, in which they test strains producing only SitA and SitI, without the cognate SitB, or SitB + SitI without the cognate SitA.
Figure 5A: The authors show here a 5-log drop in CFUs, but the results in Figure 2 showed only 1-2 logs drop in competitive index. This discrepancy needs to be clarified or experimentally addressed. (Also, Figure 5A should report the CFUs for the producer strain, and Figure 5A needs replicates) Perhaps the difference arises from the fact that sometimes the authors are measuring CFUs of producer and target strains and sometimes they're using fluorescence to assess competitive index?
Figure 5: The results in this figure, which are critical to the paper's primary conclusion and broad appeal about serial transfer of SitA toxins, are potentially very exciting, but incomplete. (1) The authors don't consider the possibility that the cells are exchanging Tra proteins, not SitA toxins, i.e. the intermediary strain could transfer a Tra protein to the target strain, which then enables it to be directly targeted by the producer strain. This is briefly mentioned in the Discussion, but should be addressed experimentally. (2) What happens if the intermediary carries the immunity protein, but the target strain does not? And on a related note: it's surprising how efficient the transmissibility is (e.g. Figure 5F) considering that the intermediary doesn't contain the immunity protein and so should be getting inhibited/killed in the process. And if non-immune cells are really such good transmitters of the toxin, then one would expect to see a wholly different pattern in the experiments in Figure 4 showing neighboring colonies, i.e. the toxin would lead to a gradient, not clean boundaries. This should be addressed. (3) There's no direct demonstration that the SitA proteins themselves are getting transferred – this needs to be addressed experimentally. In fact, I think the authors need to show (i) that SitA proteins get transferred and (ii) that they get serially transferred. It is not beyond the scope of this paper as it is so central to the most interesting element/conclusion of the manuscript.
Related to the last point above: how do the authors envision a lipoprotein getting released from the outer membrane such that it can be transferred to another cell?
Figure 6: I don't understand these data. In Figure 6A the competition with A66 leads to a 2-3 log drop in the tra- and sitBAI3- strains, and the CFU counts show these strains present at 10^2-10^3. In contrast, in the competition with A47, the CFUs are comparable to that with A66, but there's no drop in the DK1622/isolate ratio.
In this manuscript, Vassallo et al., examine the molecular mechanism of kin discrimination via the outer membrane exchange (OME) pathway of myxobacteria. In prior work, the authors showed that the first part of this process requires receptor compatibility via the TraA cell surface receptor. In the present study, the authors identify additional genetic criteria, in the form of toxin-immunity proteins, that determine cooperative versus antagonistic outcomes of OME. In addition, the authors provide evidence that two of these toxins, SitA1 and SitA3, possess DNase and tRNase activity, respectively, providing biochemical insight into kin discrimination. Using a three-strain competition setup and appropriate TraA/toxin-immunity alleles, the authors elegantly show that these toxins can be transferred through a TraA compatible, toxin-resistant strain to intoxicate a TraA incompatible, toxin-susceptible strain. Together, these findings represent a significant advance in our understanding of kin discrimination between bacteria facilitated by OME. Below are comments for the author's consideration:
1) The toxin-immunity concept has been well-established for several pathways involved in interbacterial antagonism. However, I'm very much intrigued by the SitB family of genes, which appear to be a unique component of Myxococcus OME toxin cassettes. While a detailed characterization of the proteins encoded by these ORFs is beyond the scope of this study, minimally the authors should examine whether SitB1 is required for SitA1-based antagonism and test if SitB proteins are themselves toxic when expressed heterologously. The authors mention in their concluding statement that this family of proteins is predicted to adopt a β-barrel fold. The authors should include the methods used to reach this prediction, clarify if this refers to a transmembrane or a soluble β-barrel protein and speculate on what the role of these proteins might be.
2) The lack of toxicity for SitA2 in the E. coli viability assays and the weak phenotype observed in competition experiments could be due to low expression of the protein. Perhaps this caveat should be mentioned in the interpretation of experiments examining SitA2-based toxicity. Alternatively, might SitA2 be toxic if expressed in the periplasm?
3) Figure 1C needs a scale bar.Ο
4) How do OME transferred toxins access the cytoplasm of recipient cells? In previous work, the authors identified mutations in omrA that blocked killing, however as noted by the authors, it is unclear if this resistance to killing is due to changes in membrane properties as a result of inactivation of OmrA enzymatic function or if OmrA is a specific receptor required for toxin import. It would be interesting to examine whether killing resistant omrA variants are resistant to intoxication by just a single SitA toxin or to all three SitA toxins. If the latter result is obtained it would provide preliminary evidence suggesting that these toxins may contain translocation domains that require specific membrane properties for cell entry.
5) It is not clear how OM tethered toxins reach the inner membrane of target cells prior to their entry into the cytoplasm. One possibility could be N-terminal cleavage of the lipid anchor, which would allow for diffusion of the toxin to the inner membrane. If the authors have an available antibody, it might be informative to look for proteolytic processing of the toxin during OME by western blot analysis.
This Vassallo et al., manuscript is a follow-up to earlier manuscripts (Dey et al., 2016, Vassallo et al., 2015, and Dey and Wall, 2014) and helps to close the chapter on one aspect of Myxococcus kin recognition by answering several open questions about the role of TraA compatibility and OME during within species kin selection. In this way, this manuscript as a whole is interesting and impactful, most significantly in the Myxococcus field.
Individual aspects are less novel, e.g., the coupling of toxic and non-toxic signal exchange in bacteria (termed here "test and verify") has been alluded to in multiple bacterial systems including Ruhe et al., 2013 and 2015, Wenren et al., 2013, and Anderson et al., 2014 (see –Discussion section). The SitA1 and A3 toxins themselves, as well as the chromosomal organization of the cassettes, has been discussed for Rhs, CDI, and T6SS. However, the infectious agent analogy is compelling, even though spread is limited by TraA alleles; could this mechanisms be applicable to other bacterial systems?
Key aspects that are currently missing include:
– The main conclusions of the manuscript, based on the Abstract, are difficult to understand in the main text. Perhaps the Introduction and Discussion could be streamlined, focusing on one or two main ideas.
– Show the data that TraA is not being transferred. (The authors allude to unpublished data supporting this –in the Discussion section). This is crucial for the idea that only the SitA proteins go cell-cell.
– I think the authors can directly test the idea of a "carrier" population that can spread the infection without becoming susceptible, which would strengthen their argument of the Sit toxins acting like infectious agents. Briefly, the authors have previously published an omr mutant (discussed –in the Discussion section) that is immune to the SitA toxins, likely due to an inability to import the toxin into the cytoplasm (Dey and Wall, 2014). The authors could, therefore, move the omr mutation into DW2428 (DK1622 missing all sitA genes and TraA+). This strain should be immune from toxins but be able to act as a carrier. First, this strain should have the same fitness as any TraA-compatible wild-type strain, further supporting that import into the cytoplasm is key for the toxin activity. More importantly, the authors could analyze mixtures of this strain with wild-type combinations (similar to those performed in Figure 5), specifically using two different sitA-containing natural isolates of one TraA compatible group and mix with the DK1622 carrier strain. The prediction is that the "carrier" strain would have the same fitness as the wild-type strains, if not higher. This would show that a carrier strain could pass toxicity from within its TraA compatible class to any other strain regardless of its own native sit locus, which would be expected from an infection. (Consider for example a conjugation strain in a tri-parental mating.) On these same lines, do the authors frequently find omr mutants naturally arising within their populations? And wouldn't a positive outcome from this assay question the idea that this OME-sharing of toxins is a selection for kin as opposed to a just being a "true" infection?
– The authors speak to a possible correlation between sitA and traA diversity (–Discussion section, S4). This assertion would be stronger with an analysis of the alleles and the differences between the degrees of variation found in those alleles. (Or remove this assertion from the manuscript.) – Determine SitA2 function or alternatively, remove from the manuscript. The lack of discussion of SitA2 is distracting and draws away from the main points. For example in Figure 1 and – in subsection “DK1622 ancestors contain three functional sitBAI toxin/immunity cassettes”, the SitA2 result is not fully discussed in the manuscript.
[Editors’ note: what now follows is the decision letter after the authors submitted for further consideration.]
Thank you for resubmitting your work entitled "Infectious polymorphic toxins delivered by outer membrane exchange discriminate kin in myxobacteria" for further consideration at eLife. Your revised article has been favorably evaluated by Gisela Storz (Senior editor) and three reviewers, one of whom is a member of our Board of Reviewing Editors.
The manuscript has been improved, and the reviewers generally agreed that the revised paper merits publication in eLife, provided you are willing to address a few remaining issues raised by one of the reviewers:
In the manuscript by Vassallo et al., the authors demonstrate that lethal activity of previously unknown toxins is a crucial component of kin discrimination. These toxins, which are located on the Mx-alpha region, are transferred during the process of outer membrane exchange (OME). The process of OME requires a separate kin-specific set of proteins, TraA and TraB. The authors propose a clever and rational model: that OME of toxic elements is similar to an infection that can spread across a bacterial population, ensuring that only those with the antidote (i.e., an inhibitor of the toxin) can survive. The authors speculate that this model could explain why TraA alleles are not sufficient to predict kin and non-kin populations and why a diversity of M. xanthus populations can exist in very close proximities in the wild. This is a well-executed piece of research and would be of broad scientific interest.
1) The use of the competitive index for the microscopy (Figure 2 and Figure 2—figure supplement 3) and its explanation are confusing. The authors state from –subsection “M. xanthus competition experiments”: "… if the 0 h ratio was one to one and the 24 h ratio was 1 to 1000, the competitive index was.001" and "Typically, between 200 and 500 cells were counted." In that case, 1000 cells were never counted so a competitive index of 0.001 should not be possible, but in Figure 2E, there is a data point at > 0.001 for sitI1+ versus sitBAI3+, which I presume means "0" cells were counted.
The authors' result is clear: the target strains are outcompeted greatly. With the current competitive index values, readers have to back-calculate to get the raw numbers. However, it seems that there were very few target cells visible (<10) in most of the competitions. Reporting the raw values (or the final ratios) would be equally compelling and less confusing to the reader.
2) The use of "swarm inhibition" throughout the text seems inaccurate given that the authors have already shown that the inhibition is due to death of the targeted cells. After introducing the historical name of the genes, as the authors do in the Results –, the authors then write, "Swarm inhibition was further demonstrated to be caused by cell death of the motile strain" (–subsection “SitA1 is the swarm inhibition toxin”). After that point, it would be more accurate to refer to the inhibition as "growth inhibition" or "cell death," which are the precise mechanisms (and would further emphasize the functional mechanisms of the Sit toxins). This is especially true for Figure 2—figure supplement 2, because these assays were performed in liquid (not in swarms).
The authors used the lack of swarming ("inhibition") as a read-out for genetic analyses to characterize which genes were needed for inhibitory activity (Figure 1). Stating this more concisely in discussing Figure 1 would be helpful for the reader.
3) The terminology "*novel* polymorphic toxin" or "features that make them *unique among* polymorphic toxin systems" (emphases added by this reviewer) seems a bit inaccurate. The authors state that there are many systems with polymorphic toxins, and it appears from the text that the SitA1, SitA2, and SitA3 proteins each contain motifs homologous to known toxin proteins. It seems that the greatest novelty is the delivery by OME and the striking serial transfer mechanism.
4) The authors mention that sit-like genes are found in regions outside the Mx-alpha region in other myxobacteria (–subsection”Polymorphic SitA toxins are conserved in myxobacteria”). A potential hypothesis for why these regions contain sit genes should be stated. Are these regions known to have high rates of horizontal gene transfer?https://doi.org/10.7554/eLife.29397.019
- Daniel Wall
- Daniel Wall
The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.
We would like to thank Dr. Greg Velicer and Dr. Sébastien Wielgoss for constructive comments.
- Michael T Laub, Reviewing Editor, Massachusetts Institute of Technology, United States
- Received: June 7, 2017
- Accepted: July 13, 2017
- Version of Record published: August 18, 2017 (version 1)
© 2017, Vassallo 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.