In Vitro Community Synergy between Bacterial Soil Isolates Can Be Facilitated by pH Stabilization of the Environment
ABSTRACT
The composition and development of naturally occurring microbial communities are defined by a complex interplay between the community and the surrounding environment and by interactions between community members. Intriguingly, these interactions can in some cases cause synergies, where the community is able to outperform its single-species constituents. However, the underlying mechanisms driving community interactions are often unknown and difficult to identify due to high community complexity. Here, we show how opposite pH drift induced by specific community members leads to pH stabilization of the microenvironment, acting as a positive interspecies interaction, driving in vitro community synergy in a model consortium of four coisolated soil bacteria, Microbacterium oxydans, Xanthomonas retroflexus, Stenotrophomonas rhizophila, and Paenibacillus amylolyticus. We use microsensor pH measurements to show how individual species change the local pH microenvironment and how cocultivation leads to a stabilized pH regime over time. Specifically, in vitro acid production from P. amylolyticus and alkali production primarily from X. retroflexus led to an overall pH stabilization of the local environment over time, which in turn resulted in enhanced community growth. This specific type of interspecies interaction was found to be highly dependent on medium type and concentration; however, similar pH drift from the individual species could be observed across medium variants.
IMPORTANCE Understanding interspecies interactions in bacterial communities is important for unraveling species dynamics in naturally occurring communities. These dynamics are fundamental for identifying evolutionary drivers and for the development of efficient biotechnological industry applications. Recently, pH interplay among community members has been identified as a factor affecting community development, and pH stabilization has been demonstrated to result in enhanced community growth. The use of model communities in which the effect of changing pH level can be attributed to specific species contributes to the investigation of community developmental drivers. This contributes to assessment of the extent of emergent behavior and members' contributions to community development. Here, we show that pH stabilization of the microenvironment in vitro in a synthetic coisolated model community results in synergistic growth. This observation adds to the growing diversity of community interactions leading to enhanced community growth and hints toward pH as a strong driver for community development in diverse environments.
INTRODUCTION
Microbial communities are ubiquitous in natural and man-made environments and are routinely being applied for, e.g., crop management (1), bioremediation (2), wastewater treatment (3), and bioenergy production (4, 5). Hence, in terms of biotechnological applicability and environmental ecology, understanding key factors affecting microbial community development is indispensable (6). The actively growing community in a natural habitat is predominantly defined in diversity and composition by abiotic factors, e.g., O2, pH, salinity, and temperature (7–11), where the chemical microenvironment is characterized by steep gradients susceptible to rapid changes. For example, pH is recognized as an important factor for species composition in, e.g., soil (11–13), as different species prefer specific pH regimes (14, 15). Albeit the strong environmental effect, microbial interactions also influence community composition, e.g., through molecular mechanisms, such as cooperative cross-feeding (16–18) and cross-protection from antibiotics (19, 20), or through competition by toxin secretion (21). An additional mode of interaction is based on the ability of bacteria to alter their local environment, e.g., by changing O2 and pH, by consumption of specific resources, by secretion of metabolites, or through the biochemical processes from metabolic activity causing a proton turnover (22, 23). Local microbial pH drift is well known from several types of host-associated environments, such as the human-associated vaginal (24) and oral (25) microbiomes, as well as the well-known syntrophic relationship of industrial yogurt production by Lactobacillus bulgaricus and Streptococcus thermophilus (26–29). Recently, Ratzke et al. showed through in vitro studies that in unique cases, bacteria may even cause pH drift to such an extent that it becomes detrimental for the population, a phenomenon termed ecological suicide (15). As pH is an important parameter for microbial life, changing the pH in the local environment will affect both the microbial population responsible for the change and the closest community members; such pH interactions in cocultures have been elegantly documented in vitro and modeled by Ratzke and Gore (14). Using specific laboratory isolates, Ratzke and Gore showed that the outcome of pH-driven interactions can be predicted when the pH drift and optimal growth pH are known for the interaction partners. The outcome of the interaction could then be categorized as, e.g., bistability, successive growth, extended suicide, or stabilization of growth. By example, stabilization defines the scenario where two bacteria, which on their own would change pH with detrimental consequences, can coexist by canceling each other's pH-drifting effects on the environment.
Diverse interactions occurring in bacterial communities often facilitate emergent properties, which are only observed in a community setting and not in monocultures of community members. These properties are commonly referred to as community-intrinsic properties (30). An example of a community-intrinsic property is the synergistic biofilm formation recorded by Ren et al. (31) for a model community consisting of four coisolated soil bacteria, Stenotrophomonas rhizophila, Xanthomonas retroflexus, Microbacterium oxydans, and Paenibacillus amylolyticus. Work on this community has established that cocultivation leads to enhanced biofilm formation, that all four species increase in biomass through biofilm cocultivation, and that all four species are indispensable for the synergy to occur (31). The synergy can be linked to a specific spatial organization of community members during cocultivation in biofilms (32), and metatranscriptomics (33) and metaproteomics (34) studies have identified amino acid cross-feeding as a potential driver of the synergy. However, the impact of the community on its surrounding environment and the mutual community-environment interplay have not been explored. In the present study, we applied high-resolution microsensor measurements of pH and O2 (35, 36) in liquid cultures and solid surfaces to elucidate the role of the chemical microenvironment on the observed community synergy within this model community. In line with observations from Ratzke and Gore, we find that three community members individually drive pH to unfavorable conditions hampering their own growth, whereas cocultivation leads to a stabilization of the environment, promoting community synergy.
RESULTS
Bacterial interactions on an agar plate.
The species were spotted in pairs of two on agar plates (50% tryptic soy agar [TSA] with Congo red and Coomassie brilliant blue G250, referred to as Congo red plates) to screen for interactions between the species. Interactions were detected by visual changes in colony morphology. After 2 days of incubation, the colony morphology of P. amylolyticus changed when spotted against X. retroflexus, S. rhizophila, or M. oxydans (Fig. 1), compared to that when spotted against itself. The changed P. amylolyticus colony became increasingly red, indicating enhanced binding of Congo red, and the colony texture was disordered in the peripheral part opposing the other species. The visually disordered part displayed directional growth toward the opposing colony, indicating attraction. The reaction was strongest toward X. retroflexus. No visible interactions were observed among the other species pairs, as judged by colony morphology (see Fig. S1 in the supplemental material).
FIG 1
Chemical microenvironment in the agar.
As the morphological change of P. amylolyticus indicated directional growth, it was hypothesized that X. retroflexus (and to a lesser extent, S. rhizophila and M. oxydans) modified the chemical environment in the agar causing attraction of P. amylolyticus. To probe the chemical microenvironment of the interaction zone between the colonies on agar plates, the zone was mapped in a 2.5 by 2.5-mm grid structure using O2 and pH microsensors mounted on a three-dimensional (3D) motorized micromanipulator (Fig. 2). The experimental setup is presented in Fig. S2. A visible morphological change of the P. amylolyticus colony occurred from days one to two. According to the pH map (Fig. 2), the pH changed after 1 and 2 days of incubation. After 1 day of incubation, pH increased in the area around X. retroflexus and S. rhizophila, compared to the pH of 50% TSA medium-based agar (indicated by black arrow, Fig. 2). Simultaneously, the pH in parts of the P. amylolyticus colony periphery not facing the interaction zone decreased to ∼pH 6.5. No change in pH was observed close to M. oxydans colonies. After 2 days of incubation, the pH in the interaction zone increased to >8. At the periphery of the P. amylolyticus colony opposite the interaction zone, the pH was still below pH 8. The pH data showed that X. retroflexus and S. rhizophila alkalized the environment when cultured with tryptic soy broth (TSB) as the nutrient source, whereas P. amylolyticus acidified its environment. No clear trend was observed for M. oxydans.
FIG 2
The O2 concentration map indicated strong O2 depletion by S. rhizophila, X. retroflexus, and M. oxydans after 1 and 2 days of incubation, where the central parts of these colonies reached anoxia. In contrast, only a weak O2 depletion was recorded near the periphery of the P. amylolyticus colony after both 1 and 2 days of incubation.
Measurement of pH and growth in liquid cocultures.
With the opposing trend of pH drift from S. rhizophila and X. retroflexus compared to that of P. amylolyticus, it was hypothesized that environmental pH stabilization, similar to that observed by Gore and colleagues (14, 15), could also be a driver for the observed community synergy observed by Ren et al. (31) and Hansen et al. (33) in static liquid cultures. Mono-, dual- and four-species cultures were grown in 24-well polystyrene plates with measured endpoint pH and individual counts of CFU from all species. In contrast to Ren et al. (31), who specifically quantified the biofilm constituents (bacterial biofilm cells and biofilm matrix), the present study quantified cell content in the entire well, as selective pH measurements in the biofilm fraction of 24-well plates were impractical. In line with the observations by Ren et al. (31), X. retroflexus was the most abundant member of the four-species community, contributing >95% of the total cell counts (Fig. 3a). The four-species consortium yielded higher total CFU counts than the best single-species culture, i.e., for X. retroflexus, and the counts equaled the sum of single species, indicating some level of community synergy (Fig. 3b). Cell counts of X. retroflexus and P. amylolyticus were higher in the four-species consortium than in their respective monocultures. In contrast, cell counts of S. rhizophila and M. oxydans were reduced when included in the four-species consortium (Fig. 3c). Similar to the observations from agar plates, X. retroflexus and S. rhizophila alkalized the medium, reaching pH ≥8 when cultured individually in TSB, whereas P. amylolyticus acidified the medium to pH <6 (Fig. 3d and e and S3). In contrast to the observations from agar plates, a slight acidification by M. oxydans was detected in static liquid TSB cultures (Fig. S3).
FIG 3
When relating the endpoint pH and CFU counts of individual species in mono-, dual-, and four-species cultures, it was apparent that different species compositions resulted in unique endpoint pH and CFU counts for each culture, as seen by, e.g., endpoint pH and CFU counts of X. retroflexus and P. amylolyticus (Fig. 3d and e, respectively). For X. retroflexus, the monoculture or cocultivation with either S. rhizophila or M. oxydans resulted in an endpoint pH ≥8 and lower CFU counts of X. retroflexus than in cultures including the acid-producing P. amylolyticus. Cocultivation of X. retroflexus and P. amylolyticus or as part of the four-species consortium resulted in significantly higher CFU and lower endpoint pH. In support, a Spearman's ranked correlation showed a significant (P = 0.0058) weak negative correlation (ρSpearman = −0.38) between pH and CFU, indicating that higher pH led to reduced CFU counts (Fig. 3d).
For P. amylolyticus (Fig. 3e), an opposite trend was observed, as cocultivation with alkali producers S. rhizophila or X. retroflexus yielded higher CFU counts, and cocultivation in the four-species consortium resulted in the significantly highest P. amylolyticus CFU counts observed. A strong positive (ρSpearman = 0.82) and significant (P < 0.0001) Spearman's ranked correlation indicated a positive relationship between endpoint pH and CFU. While cocultivation of X. retroflexus or P. amylolyticus with other species or each other generally resulted in increased CFU counts, cocultivation of S. rhizophila or M. oxydans with other species generally affected the growth of S. rhizophila or M. oxydans negatively (Fig. S3a and b). Hence, factors other than pH are also important for the community growth. No statistically significant Spearman's ranked correlation was found between pH and CFU counts for M. oxydans and S. rhizophila.
Stabilization of pH over time.
Measurements of endpoint pH and CFU showed a general trend that cocultivation of P. amylolyticus and X. retroflexus stabilized pH between the observed extremes of their respective monocultures while simultaneously yielding increased CFU counts. To verify that the pH stabilization occurred throughout the cultivation period and was not just an endpoint artifact, pH was measured over time in monocultures of X. retroflexus, P. amylolyticus, and the four-species culture, with measurements every 5 min over 48 h. In X. retroflexus monocultures, the pH increased to above 8 within the first day, while P. amylolyticus monocultures acidified the environment to pH 5 within the same time frame. In contrast, growth of the four-species consortium stabilized pH between 6 and 8 (Fig. 3f). To evaluate the optimal pH growth range of the individual species, each species was spotted onto pH-stabilized 50% TSA plates (Fig. S4). S. rhizophila and X. retroflexus were able to grow at pH 6 to 8, with no visible growth below pH 6 and above pH 8. M. oxydans and P. amylolyticus grew well between pH 6 and 8, with reduced growth between pH 8 and 9. No growth was observed for M. oxydans or P. amylolyticus below pH 6.
As X. retroflexus and P. amylolyticus were also able to mutually enhance each other's growth in dual culture, pH was continuously measured in this dual culture to verify that they would also cause pH stabilization over time. Such pH stabilization was indeed observed, indicating that at least part of the pH stabilization was facilitated through the combined growth of these two species (Fig. S5). Complementary measurements showed that the pH stabilization occurred simultaneously throughout the well, as no spatial pH gradients were found between the top and bottom (Fig. S6).
As tryptic soy broth (TSB) is rich in peptides, the observed pH increases for X. retroflexus and S. rhizophila cultures were believed to be caused by the release of ammonia from peptide degradation. Ammonia production was quantified by performing endpoint ammonium measurements after 2 days of growth, as proton uptake by ammonia would lead to the formation of ammonium (see the supplemental material on “Nitrogen flux and its impact on community composition,” specifically Table S1 and Fig. S7). Monocultures of X. retroflexus and S. rhizophila contained significantly higher concentrations of ammonium (P < 0.05, Table S1 and Fig. S7) than those found in TSB, indicating that the change in pH was caused by active degradation of amino acids and release of ammonia. A significantly higher concentration of ammonium was also measured for the four-species consortium (Table S1 and Fig. S7). Nitrogen flux of ammonium, nitrate, nitrite, and nitrous oxide was measured in the cultures and has been summarized in the supplemental text section “Nitrogen flux and its impact on community composition,” including Table S1 and Fig. S7, S8, and S9 and a short genome comparison of the species' capability for turnover of different nitrogen sources. In short, X. retroflexus, P. amylolyticus, and M. oxydans were found to respire on nitrate, potentially allowing continued growth of these species after O2 depletion.
We expect the observed pH decrease in P. amylolyticus cultures to be the result of a fermentative metabolism. When grown and assessed in Hugh-Leifson medium, P. amylolyticus was shown to produce acid under anaerobic conditions, supporting its ability to perform fermentation (Fig. S10), and in accordance, genome analysis revealed the genomic potential for fermentative lactate production (Fig. S11). As a potential fermentative metabolism would be favored in an anoxic environment, O2 concentration profiles in the 24-well plates were measured over time. Oxygen concentration profiles showed that O2 was depleted within 2 h of inoculation for all single- and the four-species cultures in 24-well plates (Fig. S12). Additionally, O2 was found to only be available in the top layer of the well after initial O2 depletion (Fig. S13). As the environment turned anoxic, growth of the nonfermenting species of X. retroflexus, S. rhizophila, and M. oxydans would have to rely on alternative electron acceptors.
Stability of the pH-related interaction.
The observed pH-related interaction resembled that reported by Gore and colleagues (14, 15), where bacteria with opposite pH effects on their environment can stabilize each other's growth. To address the stability of the pH-related interaction, counts of individual species and endpoint pH were measured for mono- and cocultures in various strengths of TSB and with M9 and LB media containing alternative nutrient sources. LB medium was included due to its complexity to address if the pH-dependent synergy would prevail in other types of complex media. M9 medium was made with 0.5% tryptone and 0.5% glucose to include a defined and simple growth medium. CFU and pH were assessed for mono- and four-species cultures after both 24 and 48 h of incubation, whereas CFU and pH for dual-species combinations were only assessed at 48 h. Glucose concentrations found in the tested media were within the range of carbohydrates in soil (0.1% [37] to 10% [38]), with M9 containing 0.5% glucose and TSB containing 0.25% glucose.
Across medium variants and time points, X. retroflexus was generally among the species with the highest single-species CFU counts (Fig. S14), and in the four-species community, it was one of the most abundant members (Fig. S15). X. retroflexus (Fig. 4a and b and S16) and S. rhizophila (Fig. S17) increased pH in all tested media after 48 h, while P. amylolyticus (Fig. 4c and d and S18) caused acidification in both TSB and LB media but not in M9 medium. M. oxydans (Fig. S19) slightly acidified TSB-based medium and increased the pH in LB medium. No clear trend was observed in M9 medium for M. oxydans. The observed synergy in full-strength TSB medium was found to cease with decreasing TSB concentrations, with summed CFU counts of the four-species community in 50% and 20% TSB not being significantly higher than counts of the best single species. After 48 h in 50% TSB, the four-species community still resulted in higher average cell counts than the best single species, indicating a persisting synergistic interaction (Fig. S20). The synergy based on CFU counts was detected in LB medium after 24 h but not after 48 h of incubation. No synergy was observed when the four-species community was grown in M9 medium. Hence, the synergy seemed highly medium and concentration dependent.
FIG 4
As X. retroflexus and P. amylolyticus were hypothesized to be the main drivers behind the observed pH interaction, mediating synergy, analysis of endpoint pH and CFU across cocultures and media for these two species was conducted to determine if the pH-related effect ceased with decreasing medium concentration. For X. retroflexus (Fig. 4a and b), the positive effect observed during cocultivation in full-strength TSB was not detected in 50% and 20% TSB, yielding comparable CFU counts for mono- and cocultures. Hence, the pH-related effect ceased with decreasing medium concentration for X. retroflexus. For P. amylolyticus (Fig. 4c and d), a significant Spearman's ranked correlation (ρSpearman = 0.539, P < 0.001) was found between CFU and pH in 50% TSB, with cocultures of, e.g., S. rhizophila and the four-species culture also providing significantly higher CFU counts. Combined, this indicated a continued relationship between pH stabilization and increased CFU. For 20% TSB, the pH-mediated interaction was also absent for P. amylolyticus, as cocultivation yielded CFU counts comparable to those of the monocultures.
X. retroflexus and P. amylolyticus were found to be the main drivers of community synergy via a pH-stabilizing interaction when grown in full-strength TSB medium. However, the pH-related interaction between X. retroflexus and P. amylolyticus was both medium type and concentration dependent, with high nutrient loads being required for the interaction to occur. In support of an interaction between X. retroflexus and P. amylolyticus, the CFU of X. retroflexus and P. amylolyticus showed a significant strong positive Pearson's correlation (ρPearson = 0.87; P < 0.001) between resulting CFU and increasing concentrations of TSB (Fig. 4e), indicating that these two species followed each other's growth when cocultured as part of the four-species community. In contrast, counts of neither X. retroflexus nor P. amylolyticus showed a correlation with counts of S. rhizophila (Fig. S21). To further emphasize the relationship between X. retroflexus and P. amylolyticus, the growth of these organisms showed strong positive significant Pearson's correlations with each other across time points in the four-species community when cultured in full-strength TSB and 50% TSB (Fig. 4f). This kind of relationship, with a coincrease in counts across time and across different strengths of TSB, was unique for X. retroflexus and P. amylolyticus and could not be identified for any other combination of organisms in the four-species community (Fig. S22). For 20% TSB, the positive interaction between these two species was not detected, and higher CFU of X. retroflexus led to decreased P. amylolyticus counts over time.
Of all the four species, P. amylolyticus responded most strongly to pH alterations in the cultures, with a positive correlation between pH and CFU for full-strength TSB and 50% TSB. In additional support of the pH trend for P. amylolyticus, counts of CFU in LB and M9 media decreased with increasing pH (for pH >7.5 to 8) (Fig. S18), emphasizing that the growth of P. amylolyticus was tightly linked to pH.
Bacterium-induced pH drift in soil.
Currently, the pH-mediated interaction has only been presented for in vitro systems and as such is only speculative for in situ settings, e.g., the rhizosphere-associated biofilm communities. To address whether the four species could cause pH alternations in the more natural-like systems, pH drift was investigated in bulk soil inoculated with high concentrations of either of the single-species or the four-species cultures. The individual species and the four-species community were inoculated in 5 g of sieved soil with a total cell load of 109 cells per gram of soil. Samples were incubated for 8 days with a vortex-induced redistribution of the soil every second day, before pH was measured in bulk soil (Fig. 5a). All four bacterial species and the four-species consortium were found to significantly increase the pH in bulk soil after 8 days of incubation, with X. retroflexus promoting the highest increase relative to the control without added bacteria. Plate spreading of the samples allowed a visual verification of the presence of all four single species in their respective soil samples by their individual colony morphology. Similarly, X. retroflexus, S. rhizophila, and M. oxydans could be identified from the plated soil sample inoculated with the four-species consortium.
FIG 5
Observation of the pH drift over time in the four-species community and in monospecies cultures of X. retroflexus with different cell loads showed that most of the pH drift occurred on the first day after inoculation (Fig. 5b). High cell loads were required for the effect to occur in bulk soil, as cell loads below 109 cells per gram of X. retroflexus did not provide a significantly increased pH at day 8. Selective CFU counts of X. retroflexus were acquired over time to follow the X. retroflexus population in monospecies inoculations in the soil or when inoculated into the soil as part of the four-species community. Counts showed that the X. retroflexus population was stable from days 0 to 2 and thereafter declined (Fig. S23). Inoculation of either X. retroflexus (109 cells per gram) and or the four-species community (with a total of 109 cells per gram) in autoclaved soil also yielded an increased pH in bulk soil after 8 days of incubation (Fig. S24). X. retroflexus could be selectively isolated from the autoclaved soil samples after inoculation and over time, and it also showed a changed pH profile in the soil over time (Fig. S25).
DISCUSSION
In the present study, we explored the potential drivers behind a previously observed synergistic interaction between four coisolated soil bacteria. Opposite pH effects on the external environment by key community members were found to stabilize pH during cocultivation, promoting enhanced growth of selected community members. This mechanism is very much in line with the type of stabilization presented by Ratzke and Gore (14). However, other mechanisms besides pH stabilization could also be in play for the observed synergy in full-strength TSB, as the four-species community showed higher total cell counts than in the dual-species combination of X. retroflexus and P. amylolyticus, where pH stabilization was also observed. The low cell counts of M. oxydans and S. rhizophila in the four-species community are expected to cause only a negligible pH drift, and the presence of these two isolates might cause additional emergent functions in the community. Liu et al. (32) thus showed that inclusion of the M. oxydans caused a unique spatial organization in the four-species community when grown as biofilms under continuous flow. Additionally, cross-feeding on specific amino acids has been suggested as a driver for this community in earlier studies (33, 34).
We speculate that S. rhizophila was the least fit to thrive in the community, as it lacked the ability to perform either anaerobic dissimilatory nitrate respiration or fermentation, compared to the other species (Table S1 and Fig. S7, S8, S10, and S11). We are uncertain as to why M. oxydans only contributes little to the total cell counts of the community, and further investigations will focus on dissecting its role in the community.
Application of microsensors to study chemical gradients is a long-established technique which has seen diverse application, e.g., within soil sediments (39) or microbial encapsulation in alginate beads (40, 41). Application of a custom-built x-y-z motorized micromanipulator setup for microsensors enabled us to easily map the chemical microenvironment in relation to the distribution of community members spotted on agar plates. Agar plates are routinely used to screen for bacterial interactions, and with the diverse range of bacteria which cause pH drift in standard laboratory media (15), one should remember to evaluate the likelihood of pH-mediated interactions. Future efforts could apply supporting techniques directly on the agar plates to identify the metabolites causing the interaction, e.g., by utilizing imaging mass spectrometry (42, 43) or chemical imaging (44, 45).
Cellular pH homeostasis is crucial for maintaining functional cells, as intracellular proteins function optimally within distinct pH ranges, and because the proton motive force is crucial for bacterial respiration (46, 47). Thus, pH stress can lead to reduced or impaired growth due to defective proteins, a disrupted membrane potential, or the energy cost of maintaining pH homeostasis (46, 48, 49). Changes in pH within the local environment through bacterial growth and its effect on growth of cocultured bacteria are well described, with one of the best examples being the proto-cooperative relationship of Lactobacillus bulgaricus and Streptococcus thermophilus during yogurt production (26–29). Hence, the fact that bacteria affect each other by altering the pH environment through their metabolism is not surprising. Nevertheless, the formulation and predictability of pH drift as a mediator of interspecies interaction in cocultures were not properly established until the recent study by Ratzke and Gore (14). Whether this type of interaction is relevant for natural settings needs to be further established, as Ratzke and Gore performed in vitro studies with selected model laboratory organisms with known optimal growth pH and drift.
Unlike the observations presented by Ratzke and Gore (14), our isolates did not undergo ecological suicide when tested as single species, but cell counts of monocultures of X. retroflexus and P. amylolyticus were reduced compared to those in cocultures of, e.g., X. retroflexus and P. amylolyticus or the four-species community. We found that the pH-related interaction was highly growth medium specific and only occurred under high nutrient concentrations. For example, in high medium concentrations (full-strength TSB), both X. retroflexus and P. amylolyticus benefitted from cocultivation with partners with opposite pH drift (Fig. 3). With medium-strength TSB, only P. amylolyticus significantly benefitted from cocultivation with members with opposite pH drift, e.g., S. rhizophila or as part of the four-species community (Fig. 4). Hence, with decreasing medium strength, the interaction faded, suggesting that this type of positive interaction occurs under nutrient-replete conditions. When nutrient concentrations are lowered, competition for nutrients may become a stronger driver in the community than the positive effects from pH stabilization. Notably, this type of interaction might be stronger in structured systems, such as biofilms, as cooperation is known to be reinforced in structured environments (17), and cooperating biofilm members tend to evenly mix or colocalize (32, 50, 51). In support of this, previous biofilm studies have shown that steep pH gradients can occur within (52) and on the outside of (53) biofilms, generating suitable microniches for a diverse set of community members (54).
In association with the observations by Ratzke and Gore (14), and hinting toward the relevance of this type of interaction in natural systems, we observed that pH stabilization was at least part of the driver behind a previously observed community synergy between our four coisolated species which are known to form biofilms. As these species were coisolated from the same decomposing leaf (55), it is likely that the community members also occur together in nature and might be able to favor each other's growth through pH stabilization in microenvironments under the right conditions. Furthermore, we observed a pH drive in bulk soil when inoculated with high concentrations of cells, which indicates that (i) these bacteria can utilize the nutrients in soil to cause pH drift, and (ii) a strong pH drift can occur in the immediate vicinity (the local microenvironment) of the bacteria in the soil, as microbial growth will be centralized around aggregates of nutrients in the soil. Hence, we speculate that pH stabilization might act as a driver for community growth in natural systems, where colocalization of members creating suitable pH niches for growth can enhance their fitness in the community.
MATERIALS AND METHODS
Bacterial cultures and strains.
The investigated four-species model community was composed of Stenotrophomonas rhizophila, Xanthomonas retroflexus, Microbacterium oxydans, and Paenibacillus amylolyticus. These isolates were identified during a previous study on plasmid transfer among soil isolates (55) and were later found to exhibit synergistic biofilm formation (31). Bacterial isolates were stored as glycerol stocks at −80°C. From the stocks, the bacterial isolates were streaked onto tryptic soy agar (TSA) plates containing 1.5% agar-agar (VWR) and 30 g · liter−1 tryptic soy broth (TSB) (VWR). Plates were incubated for 48 h at 24°C. Single colonies were used to inoculate 5 ml tryptic soy broth and 30 g · liter−1 TSB (VWR). Five-milliliter cultures were incubated overnight at 250 rpm and 24°C.
Cultivation in 24-well plates.
For experiments with full-strength TSB, overnight bacterial cultures were directly diluted in TSB to an optical density at 600 nm (OD600) of 0.15 before use. For testing the effect of medium composition, diluted variants of TSB were included along with LB broth and a mixed minimal medium (M9). LB (25 g · liter−1 LB broth [Miller; VWR]) was included due to its complexity to address if the pH synergy would occur in other complex medium types. M9 (10.5 g · liter−1 M9 broth; Sigma-Aldrich) was complemented with 0.5% (wt/vol) tryptone (tryptone enzymatic digest from casein; Sigma-Aldrich) and 0.5% (wt/vol) glucose [d(+)-glucose; Merck] as the nitrogen and carbon sources to include a defined medium. For preparation of cell cultures for the different medium variants, cells from overnight cultures were precipitated by centrifugation at 5,000 × g for 5 min. The supernatant was discarded and cells were washed in 0.9% NaCl (wt/vol) before redissolving the cells. Cells were reprecipitated by centrifugation, and the supernatant was discarded before the cells were redissolved in the appropriate medium. Cultures were then adjusted in the appropriate medium to an OD600 of 0.15 before use. OD600-adjusted cell cultures were used to inoculate 24-well plates with mono- and cocultures. All wells contained a total of 2 ml of OD600-adjusted culture. For monospecies cultures, 2 ml of the single-species culture was used, while equal volumes of each species were used for cocultures. Inoculated plates were incubated under static conditions for up to 48 h at 24°C.
For CFU counts from 24-well plates, cultures were homogenized with a pipette and diluted in 1× PBS. The diluted culture was plated on TSA (15 g · liter−1 agar powder [VWR] and 30 g · liter−1 tryptic soy broth [Sigma-Aldrich]) plates complemented with 40 μg · ml−1 Congo red (Fluka) and 20 μg · ml−1 Coomassie brilliant blue G250 (Sigma-Aldrich). CFU was counted after 48 h of incubation at 24°C by differentiating species based on dissimilar colony morphology.
Agar plates.
All experiments, including pH and O2 measurements, performed on agar plate colonies were performed on 50% TSA plates (15 g · liter−1 agar powder [VWR] and 15 g · liter−1 tryptic soy broth [Sigma-Aldrich]). Plates for visualization of morphological changes were 50% TSA plates complemented with 40 μg · ml−1 Congo red (Fluka) and 20 μg · ml−1 Coomassie brilliant blue G250 (Sigma-Aldrich), referred to as Congo red plates.
Colony spotting for pH and O2 measurements was done with a fixed distance between colony centers. The spotting (interaction zone) area was divided into a grid, with each grid square being 2.5 by 2.5 mm. Colonies were spotted with an approximate distance of 1.25 cm between colony centers. Five microliters of cultures adjusted to an OD600 of 0.15 (prepared as previously described) was used for spotting bacterial colonies. Similarly, two-species interaction studies were performed with an approximate distance of 1.25 cm between the centers of the colonies. Five microliters of cultures adjusted to an OD600 of 0.15 (prepared as previously described) was spotted.
Buffer-stabilized 50% TSA agar plates complemented with 200 mM sodium acetate (pH 5 and 5.5), potassium phosphate (pH 6, 6.5, and 7), Trizma base (pH 7.5, 8, 8.5, and 9), and sodium carbonate (pH 9.5 and 10.5) buffers were used.
Data analysis and plotting.
Boxplots were plotted using the ggplot2 R package. For boxplots with CFU and pH, the box width was set to 2× the standard error of the measured pH within each group. Statistical significance was inferred between groups, e.g., on log2 CFU counts, with a generalized linear model with Tukey pairwise comparison and multiple hypothesis testing by single-step method using the multcomp package in the R environment (referred to as GLM) (56). Spearman's ranked correlations were used to infer correlations between CFU and endpoint pH, and Pearson's correlations were used to infer correlations between CFU counts of two species. Trendlines were made by making total least-squared regression on the data.
Soil samples.
Soil from a Danish research field (Taastrup, Denmark, 55.669762, 12.300498) was sieved for particles of <2 mm, and the soil was stored cold until use. This soil was chosen, as the bacterial isolates were originally isolated from soil obtained from the same research facility. The soil samples contained 5 g soil contained in 50-ml Falcon tubes. The soil was inoculated with 2 ml of bacterial culture with various inoculation sizes of bacteria. Cells from overnight bacterial cultures in TSB were precipitated by centrifugation at 5,000 × g for 5 min, and the supernatant was discarded. Cells were washed in phosphate-buffered saline (1× PBS) and reprecipitated by centrifugation. Cells were redissolved in 2 ml of 1× PBS, and cultures were adjusted to the appropriate OD600 to provide a 2-ml cell suspension to yield 109 cells per gram of soil. For mixed cultures, cells were mixed in equal proportions to yield a total of 109 cells per gram of soil. Cell suspensions were used to inoculate the 5-g soil samples. The addition of a 2-ml solution left the soil with a very thin water film on top of the soil. Samples were vortexed for 5 s to distribute liquid and bacteria in the soil. Samples were incubated at 24°C under static conditions. On every second day, the tubes were briefly vortexed to redistribute nutrients and cells in the soil. Blank samples without inoculation of bacteria were prepared by inoculating the soil with 2 ml of 1× PBS. For sampling, 5 ml sterile water was added to the tubes, and the tubes were shaken for 10 min before the pH was measured in the water fraction of the sample. To verify the presence of the inoculated species in the soil, 100 μl of the water suspension was serially diluted in 1× PBS and plate spread on TSA plates complemented with Congo red and Coomassie brilliant blue G250, as described for the 24-well plates. The inoculated species could be recognized by their unique colony morphology. For selective counts of X. retroflexus, agar plates were further complemented with 20 μg · ml−1 kanamycin.
Microsensor measurements.
Two-dimensional (2D) microsensor measurements of pH and O2 concentration transects across agar plates were conducted with the microsensors mounted in a custom-built x-y-z motorized micromanipulator setup fixed to a heavy stand (57). Similar motorized x-y-z micromanipulator setups can be obtained from commercial sources, e.g., Pyro-Science GmbH, Aachen, Germany, or Unisense A/S, Aarhus, Denmark.
For O2 measurements, a fiber-optic O2 microsensor (OXR50-HS; tip diameter, 50 μm) was connected to an O2 meter (FireStingO2); both components were obtained from Pyro-Science GmbH Aachen, Germany. Calibration of the microsensor was performed as specified by the manufacturer by measurements in air-saturated and O2-free water.
For pH measurements, we used a pH glass microelectrode (tip diameter, 50 μm; pH 50; Unisense A/S) in combination with a reference electrode (tip diameter, ∼5 mm; Unisense A/S) immersed in the agar plate. Both sensors were connected to a high-impedance pH/mV-meter (Unisense A/S). Before measurements commenced, the pH microelectrode was linearly calibrated from sensor millivolt readings in three preknown pH buffers (pH 4, 7, and 9) showing a log-linear response to [H+] of ∼51 mV/pH unit at experimental temperature (24°C ± 0.5°C).
For N2O measurements, a microsensor (tip diameter, 50 μm; N2O50; Unisense A/S) was connected to a PA2000 picoamperometer (discontinued product from Unisense A/S). The sensor was preactivated, polarized, and calibrated as stated in the manual using sensor readings in N2O-free water and then after the addition of known amounts of N2O-saturated water.
A USB microscope (model AM7515MZTL; Dino-Lite [dino-lite.eu]) was used to determine when the microsensor tip touched the surface of the agar plate. All 2D measurements (pH and O2) were conducted at a depth of ≈100 μm below the surface. A custom-made profiling software (Volfix; programmed by Roland Thar) was used to control the x-y-z motorized micromanipulator and to read out both sensor signals. A similar software, Profix, can be downloaded free of charge from the Pyro-Science website. An analog to digital converter (ADC-101; Pico Technology, UK) had to be used in order to interface the profiling software with the O2 meter (using the analog output of the FireStingO2) and the pH/mV meter. Time-course measurements of, e.g., O2, in static culture were recorded with free logging software (SensorTrace logger; Unisense A/S).
ACKNOWLEDGMENTS
We thank Annette Løth for assistance with medium preparation, Maja Holm Wahlgren and Anders Primé for their assistance with nitrous oxide measurements, and Peter Østrup Jensen for assistance with microsensor equipment. We thank Esben Nielsen and Gosha Sylvester for their assistance with ammonium and nitrate/nitrite measurements. Last, we thank Jakob Russel for assistance with data handling in the R environment.
The project was funded by the Danish Council for Independent Research, Natural Sciences (FNU) & Technology and Production Sciences (FTP) (identification [ID] DFF–1335-00071, DFF–4184-00515, and DFF–12-133360) and by the Villum Foundation (YIP, project no. 10098).
We declare no conflicts of interest.
Supplemental Material
File (zam021188817s1.pdf)
- Download
- 3.61 MB
REFERENCES
1.
Grover M, Ali SZ, Sandhya V, Rasul A, Venkateswarlu B. 2011. Role of microorganisms in adaptation of agriculture crops to abiotic stresses. World J Microbiol Biotechnol 27:1231–1240.
2.
Edwards SJ, Kjellerup BV. 2013. Applications of biofilms in bioremediation and biotransformation of persistent organic pollutants, pharmaceuticals/personal care products, and heavy metals. Appl Microbiol Biotechnol 97:9909–9921.
3.
Wagner M, Loy A. 2002. Bacterial community composition and function in sewage treatment systems. Curr Opin Biotechnol 13:218–227.
4.
Steidl RJ, Lampa-Pastirk S, Reguera G. 2016. Mechanistic stratification in electroactive biofilms of Geobacter sulfurreducens mediated by pilus nanowires. Nat Commun 7:12217.
5.
Read ST, Dutta P, Bond PL, Keller J, Rabaey K. 2010. Initial development and structure of biofilms on microbial fuel cell anodes. BMC Microbiol 10:98.
6.
Lindemann SR, Bernstein HC, Song H-S, Fredrickson JK, Fields MW, Shou W, Johnson DR, Beliaev AS. 2016. Engineering microbial consortia for controllable outputs. ISME J 10:2077–2084.
7.
Cao H, Chen R, Wang L, Jiang L, Yang F, Zheng S, Wang G, Lin X. 2016. Soil pH, total phosphorus, climate and distance are the major factors influencing microbial activity at a regional spatial scale. Sci Rep 6:25815.
8.
de Wit R, Bouvier T. 2006. “Everything is everywhere, but, the environment selects”; what did Baas Becking and Beijerinck really say? Environ Microbiol 8:755–758.
9.
Becking LGMB, Canfield DE. 2015. Baas Becking's geobiology. John Wiley & Sons, Ltd., Chichester, United Kingdom.
10.
He Z, Piceno Y, Deng Y, Xu M, Lu Z, Desantis T, Andersen G, Hobbie SE, Reich PB, Zhou J. 2012. The phylogenetic composition and structure of soil microbial communities shifts in response to elevated carbon dioxide. ISME J 6:259–272.
11.
Rousk J, Brookes PC, Baath E. 2009. Contrasting soil pH effects on fungal and bacterial growth suggest functional redundancy in carbon mineralization. Appl Environ Microbiol 75:1589–1596.
12.
Liu S, Ren H, Shen L, Lou L, Tian G, Zheng P, Hu B. 2015. pH levels drive bacterial community structure in the Qiantang River as determined by 454 pyrosequencing. Front Microbiol 6:285.
13.
Tripathi BM, Stegen JC, Kim M, Dong K, Adams JM, Lee YK. 2018. Soil pH mediates the balance between stochastic and deterministic assembly of bacteria. ISME J 1072–1083.
14.
Ratzke C, Gore J. 2018. Modifying and reacting to the environmental pH can drive bacterial interactions. PLoS Biol 16:e2004248.
15.
Ratzke C, Denk J, Gore J. 2018. Ecological suicide in microbes. Nat Ecol Evol 2:867–872.
16.
Rhee S-K, Lee S-G, Hong S-P, Choi Y-H, Park J-H, Kim C-J, Sung M-H. 2000. A novel microbial interaction: obligate commensalism between a new Gram-negative thermophile and a thermophilic Bacillus strain. Extremophiles 4:131–136.
17.
Pande S, Kaftan F, Lang S, Svato A, Germerodt S, Kost C. 2016. Privatization of cooperative benefits stabilizes mutualistic cross-feeding interactions in spatially structured environments. ISME J 10:1413–1423.
18.
Pande S, Merker H, Bohl K, Reichelt M, Schuster S, de Figueiredo LF, Kaleta C, Kost C. 2014. Fitness and stability of obligate cross-feeding interactions that emerge upon gene loss in bacteria. ISME J 8:953–962.
19.
Yurtsev EA, Conwill A, Gore J. 2016. Oscillatory dynamics in a bacterial cross-protection mutualism. Proc Natl Acad Sci U S A 113:6236–6241.
20.
Lee KWK, Periasamy S, Mukherjee M, Xie C, Kjelleberg S, Rice SA. 2014. Biofilm development and enhanced stress resistance of a model, mixed-species community biofilm. ISME J 8:894–907.
21.
Kerr B, Riley MA, Feldman MW, Bohannan BJM. 2002. Local dispersal promotes biodiversity in a real-life game of rock-paper-scissors. Nature 418:171–174.
22.
Soetaert K, Hofmann AF, Middelburg JJ, Meysman FJR, Greenwood J. 2007. The effect of biogeochemical processes on pH. Mar Chem 105:30–51.
23.
Schmidt MWI, Torn MS, Abiven S, Dittmar T, Guggenberger G, Janssens IA, Kleber M, Kögel-Knabner I, Lehmann J, Manning DA, Nannipieri CP, Rasse DP, Weiner S, Trumbore SE. 2011. Persistence of soil organic matter as an ecosystem property. Nature 478:49–56.
24.
Ravel J, Brotman RM. 2016. Translating the vaginal microbiome: gaps and challenges. Genome Med 8:35.
25.
Burne RA, Marquis RE. 2000. Alkali production by oral bacteria and protection against dental caries. FEMS Microbiol Lett 193:1–6.
26.
Driessen FM, Kingma F, Stadhouders J. 1982. Evidence that Lactobacillus bulgaricus in yogurt is stimulated by carbon dioxide produced by Streptococcus thermophilus. Netherlands Milk Dairy J 36:135–144.
27.
Angelov M, Kostov G, Simova E, Beshkova D, Koprinkova-Hristova P. 2009. Proto-cooperation factors in yogurt starter cultures. Rev Génie Ind 3:4–12.
28.
Béal C, Spinnler HE, Corrieu G. 1994. Comparison of growth, acidification and productivity of pure and mixed cultures of Streptococcus salivarius subsp. thermophilus 404 and Lactobacillus delbrueckii subsp. bulgaricus 398. Appl Microbiol Biotechnol 41:95–98.
29.
Sieuwerts S, Molenaar D, van Hijum SAFT, Beerthuyzen M, Stevens MJA, Janssen PWM, Ingham CJ, de Bok FAM, De Vos WM, van Hylckama Vlieg JET. 2010. Mixed-culture transcriptome analysis reveals the molecular basis of mixed-culture growth in Streptococcus thermophilus and Lactobacillus bulgaricus. Appl Environ Microbiol 76:7775–7784.
30.
Madsen JS, Sørensen SJ, Burmølle M. 2018. Bacterial social interactions and the emergence of community-intrinsic properties. Curr Opin Microbiol 42:104–109.
31.
Ren D, Madsen JS, Sørensen SJ, Burmølle M. 2015. High prevalence of biofilm synergy among bacterial soil isolates in cocultures indicates bacterial interspecific cooperation. ISME J 9:81–89.
32.
Liu W, Russel J, Røder HL, Madsen JS, Burmølle M, Sorensen SJ. 2017. Low-abundant species facilitates specific spatial organization that promotes multispecies biofilm formation. Environ Microbiol 7:2893–2905.
33.
Hansen LBS, Ren D, Burmølle M, Sørensen SJ. 2016. Distinct gene expression profile of Xanthomonas retroflexus engaged in synergistic multispecies biofilm formation. ISME J 11:300–303.
34.
Herschend J, Damholt ZBV, Marquard AM, Svensson B, Sørensen SJ, Hägglund P, Burmølle M. 2017. A meta-proteomics approach to study the interspecies interactions affecting microbial biofilm development in a model community. Sci Rep 7:16483.
35.
Kühl M. 2005. Optical microsensors for analysis of microbial communities. Methods Enzymol 397:166–199.
36.
Revsbech NP. 2005. Analysis of microbial communities with electrochemical microsensors and microscale biosensors. Methods Enzymol 397:147–166.
37.
Safařík I, Santruckova H. 1992. Direct determination of total soil carbohydrate content. Plant Soil 143:109–114.
38.
Mehta NC, Dubach P, Deuel H. 1962. Carbohydrates in the soil. Adv Carbohydr Chem 16:335–355.
39.
Walpersdorf E, Kühl M, Elberling B, Andersen TJ, Hansen BU, Pejrup M, Glud RN. 2017. In situ oxygen dynamics and carbon turnover in an intertidal sediment (Skallingen, Denmark). Mar Ecol Prog Ser 566:49–65.
40.
Behrendt L, Schrameyer V, Qvortrup K, Lundin L, Sørensen SJ, Larkum AWD, Kühl M. 2012. Biofilm growth and near-infrared radiation-driven photosynthesis of the chlorophyll d-containing cyanobacterium Acaryochloris marina. Appl Environ Microbiol 78:3896–3904.
41.
Sønderholm M, Kragh KN, Koren K, Jakobsen TH, Darch SE, Alhede M, Jensen PØ, Whiteley M, Kühl M, Bjarnsholt T. 2017. Pseudomonas aeruginosa aggregate formation in an alginate bead model system exhibits in vivo-like characteristics. Appl Environ Microbiol 83:e00113-17.
42.
Watrous JD, Dorrestein PC. 2011. Imaging mass spectrometry in microbiology. Nat Rev Microbiol 9:683–694.
43.
Yang JY, Phelan VV, Simkovsky R, Watrous JD, Trial RM, Fleming TC, Wenter R, Moore BS, Golden SS, Pogliano K, Dorrestein PC. 2012. Primer on agar-based microbial imaging mass spectrometry. J Bacteriol 194:6023–6028.
44.
Koren K, Jakobsen SL, Kühl M. 2016. In-vivo imaging of O2 dynamics on coral surfaces spray-painted with sensor nanoparticles. Sensors Actuators B Chem 237:1095–1101.
45.
Elgetti Brodersen K, Koren K, Lichtenberg M, Kühl M. 2016. Nanoparticle-based measurements of pH and O2 dynamics in the rhizosphere of Zostera marina L.: effects of temperature elevation and light-dark transitions. Plant Cell Environ 39:1619–1630.
46.
Krulwich TA, Sachs G, Padan E. 2011. Molecular aspects of bacterial pH sensing and homeostasis. Nat Rev Microbiol 9:330–343.
47.
Baker-Austin C, Dopson M. 2007. Life in acid: pH homeostasis in acidophiles. Trends Microbiol 15:165–171.
48.
Salmond CV, Kroll RG, Booth IR. 1984. The effect of food preservatives on pH homeostasis in Escherichia coli. Microbiology 130:2845–2850.
49.
Bunse C, Lundin D, Karlsson CMG, Vila-Costa M, Palovaara J, Akram N, Svensson L, Holmfeldt K, González JM, Calvo E, Pelejero C, Marrasé C, Dopson M, Gasol JM, Pinhassi J. 2016. Response of marine bacterioplankton pH homeostasis gene expression to elevated CO2. Nat Clim Chang 1:483–487.
50.
Momeni B, Brileya KA, Fields MW, Shou W. 2013. Strong inter-population cooperation leads to partner intermixing in microbial communities. Elife Sci 2:e00230.
51.
Liu W, Røder HL, Madsen JS, Bjarnsholt T, Sørensen SJ, Burmølle M. 2016. Interspecific bacterial interactions are reflected in multispecies biofilm spatial organization. Front Microbiol 7:1366.
52.
Vroom JM, De Grauw KJ, Gerritsen HC, Bradshaw DJ, Marsh PD, Watson GK, Birmingham JJ, Allison C. 1999. Depth penetration and detection of pH gradients in biofilms by two-photon excitation microscopy. Appl Environ Microbiol 65:3502–3511.
53.
Schlafer S, Raarup MK, Meyer RL, Sutherland DS, Dige I, Nyengaard JR, Nyvad B. 2011. pH landscapes in a novel five-species model of early dental biofilm. PLoS One 6:e25299.
54.
Flemming H-C, Wingender J, Szewzyk U, Steinberg P, Rice SA, Kjelleberg S. 2016. Biofilms: an emergent form of bacterial life. Nat Rev Microbiol 14:563–575.
55.
de la Cruz-Perera CI, Ren D, Blanchet M, Dendooven L, Marsch R, Sørensen SJ, Burmølle M. 2013. The ability of soil bacteria to receive the conjugative IncP1 plasmid, pKJK10, is different in a mixed community compared to single strains. FEMS Microbiol Lett 338:95–100.
56.
Hothorn T, Bretz F, Westfall P. 2008. Simultaneous inference in general parametric models. Biometrical J 50:346–363.
57.
Lichtenberg M, Nørregaard RD, Kühl M. 2017. Diffusion or advection? Mass transfer and complex boundary layer landscapes of the brown alga Fucus vesiculosus. J R Soc Interface 14:20161015.
Information & Contributors
Information
Published In
Applied and Environmental Microbiology
Volume 84 • Number 21 • 1 November 2018
eLocator: e01450-18
Editor: Shuang-Jiang Liu, Chinese Academy of Sciences
PubMed: 30143509
Copyright
© 2018 American Society for Microbiology. All Rights Reserved.
History
Received: 13 June 2018
Accepted: 19 August 2018
Published online: 17 October 2018
Keywords
Contributors
Editor
Shuang-Jiang Liu
Editor
Chinese Academy of Sciences
Metrics & Citations
Metrics
Note:
- For recently published articles, the TOTAL download count will appear as zero until a new month starts.
- There is a 3- to 4-day delay in article usage, so article usage will not appear immediately after publication.
- Citation counts come from the Crossref Cited by service.
Citations
Citation
2018.
In Vitro Community Synergy between Bacterial Soil Isolates Can Be Facilitated by pH Stabilization of the Environment. Appl Environ Microbiol
84:e01450-18.
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. For an editable text file, please select Medlars format which will download as a .txt file. Simply select your manager software from the list below and click Download.