Cooperative growth in microbial communities is a driver of multistability.

Microbial communities often exhibit more than one possible stable composition for the same set of external conditions. In the human microbiome, these persistent changes in species composition and abundance are associated with health and disease states, but the drivers of these alternative stable states remain unclear. Here we experimentally demonstrate that a cross-kingdom community, composed of six species relevant to the respiratory tract, displays four alternative stable states each dominated by a different species. In pairwise coculture, we observe widespread bistability among species pairs, providing a natural origin for the multistability of the full community. In contrast with the common association between bistability and antagonism, experiments reveal many positive interactions within and between community members. We find that multiple species display cooperative growth, and modeling predicts that this could drive the observed multistability within the community as well as non-canonical pairwise outcomes. A biochemical screening reveals that glutamate either reduces or eliminates cooperativity in the growth of several species, and we confirm that such supplementation reduces the extent of bistability across pairs and reduces multistability in the full community. Our findings provide a mechanistic explanation of how cooperative growth rather than competitive interactions can underlie multistability in microbial communities.

Biodiversity is enhanced by sequential resource utilization and environmental fluctuations via emergent temporal niches.

How natural communities maintain their remarkable biodiversity and which species survive in complex communities are central questions in ecology. Resource competition models successfully explain many phenomena but typically predict only as many species as resources can coexist. Here, we demonstrate that sequential resource utilization, or diauxie, with periodic growth cycles can support many more species than resources. We explore how communities modify their own environments by sequentially depleting resources to form sequences of temporal niches, or intermediately depleted environments. Biodiversity is enhanced when community-driven or environmental fluctuations modulate the resource depletion order and produce different temporal niches on each growth cycle. Community-driven fluctuations under constant environmental conditions are rare, but exploring them illuminates the temporal niche structure that emerges from sequential resource utilization. With environmental fluctuations, we find most communities have more stably coexisting species than resources with survivors accurately predicted by the same temporal niche structure and each following a distinct optimal strategy. Our results thus present a new niche-based approach to understanding highly diverse fluctuating communities.

Interfacial morphodynamics of proliferating microbial communities.

In microbial communities, various cell types often coexist by occupying distinct spatial domains. What determines the shape of the interface between such domains-which in turn influences the interactions between cells and overall community function? Here, we address this question by developing a continuum model of a 2D spatially-structured microbial community with two distinct cell types. We find that, depending on the balance of the different cell proliferation rates and substrate friction coefficients, the interface between domains is either stable and smooth, or unstable and develops finger-like protrusions. We establish quantitative principles describing when these different interfacial behaviors arise, and find good agreement both with the results of previous experimental reports as well as new experiments performed here. Our work thus helps to provide a biophysical basis for understanding the interfacial morphodynamics of proliferating microbial communities, as well as a broader range of proliferating active systems.

Strong ethanol- and frequency-dependent ecological interactions in a community of wine-fermenting yeasts.

Natural wine fermentation depends on a complex consortium of native microorganisms rather than inoculation of industrial yeast strains. While this diversity of yeasts can result in an increased repertoire of wine flavors and aromas, it can also result in the inhibition of Saccharomyces cerevisiae, which is uniquely able to complete fermentation. Understanding how yeast species interact with each other within the wine-fermenting community and disentangling ecological interactions from environmental impacts on growth rates, is key to developing synthetic communities that can provide the sensory benefits of natural fermentation while lowering the risk of stuck ferments. Here, we co-culture all pairwise combinations of five commonly isolated wine-fermenting yeasts and show that competitive outcomes are a strong function of ethanol concentration, with frequency-dependent bistable interactions common at low alcohol and an increasingly transitive competitive hierarchy developing as alcohol increases. We also show that pairwise outcomes are predictive of five-species community outcomes, and that frequency dependence in pairwise interactions propagates to alternative states in the full community, highlighting the importance of species abundance as well as composition. We also observe that monoculture growth rates are only weakly predictive of competitive success, highlighting the need to incorporate ecological interactions when designing synthetic fermenting communities.

Caenorhabditis elegans foraging patterns follow a simple rule of thumb.

Rules of thumb are behavioral algorithms that approximate optimal behavior while lowering cognitive and sensory costs. One way to reduce these costs is by simplifying the representation of the environment: While the theoretically optimal behavior may depend on many environmental variables, a rule of thumb may use a smaller set of variables that performs reasonably well. Experimental proof of this simplification requires an exhaustive mapping of all relevant combinations of several environmental parameters, which we performed for Caenorhabditis elegans foraging by covering systematically combinations of food density (across 4 orders of magnitude) and food type (across 12 bacterial strains). We found that worms' response is dominated by a single environmental variable: food density measured as number of bacteria per unit surface. They disregard other factors such as biomass content or bacterial strain. We also measured experimentally the impact on fitness of each type of food, determining that the rule is near-optimal and therefore constitutes a rule of thumb that leverages the most informative environmental variable. These results set the stage for further investigations into the underlying genetic and neural mechanisms governing this simplification process, and into its role in the evolution of decision-making strategies.

Resource competition can explain simplicity in microbial community assembly.

Predicting the composition and diversity of communities is a central goal in ecology. While community assembly is considered hard to predict, laboratory microcosms often follow a simple assembly rule based on the outcome of pairwise competitions. This assembly rule predicts that a species that is excluded by another species in pairwise competition cannot survive in a multispecies community with that species. Despite the empirical success of this bottom-up prediction, its mechanistic origin has remained elusive. In this study, we elucidate how this simple pattern in community assembly can emerge from resource competition. Our geometric analysis of a consumer-resource model shows that trio community assembly is always predictable from pairwise outcomes when one species grows faster than another species on every resource. We also identify all possible trio assembly outcomes under three resources and find that only two outcomes violate the assembly rule. Simulations demonstrate that pairwise competitions accurately predict trio assembly with up to 100 resources and the assembly of larger communities containing up to twelve species. We then further demonstrate accurate quantitative prediction of community composition using the harmonic mean of pairwise fractions. Finally, we show that cross-feeding between species does not decrease assembly rule prediction accuracy. Our findings highlight that simple community assembly can emerge even in ecosystems with complex underlying dynamics.

Warmer temperatures favor slower-growing bacteria in natural marine communities.

Earth's life-sustaining oceans harbor diverse bacterial communities that display varying composition across time and space. While particular patterns of variation have been linked to a range of factors, unifying rules are lacking, preventing the prediction of future changes. Here, analyzing the distribution of fast- and slow-growing bacteria in ocean datasets spanning seasons, latitude, and depth, we show that higher seawater temperatures universally favor slower-growing taxa, in agreement with theoretical predictions of how temperature-dependent growth rates differentially modulate the impact of mortality on species abundances. Changes in bacterial community structure promoted by temperature are independent of variations in nutrients along spatial and temporal gradients. Our results help explain why slow growers dominate at the ocean surface, during summer, and near the tropics and provide a framework to understand how bacterial communities will change in a warmer world.

Community interactions drive the evolution of antibiotic tolerance in bacteria.

The emergence of antibiotic tolerance (prolonged survival against exposure) in natural bacterial populations is a major concern. Since it has been studied primarily in isogenic populations, we do not yet understand how ecological interactions in a diverse community impact the evolution of tolerance. To address this, we studied the evolutionary dynamics of a synthetic bacterial community composed of two interacting strains. In this community, an antibiotic-resistant strain protected the other, susceptible strain by degrading the antibiotic ampicillin in the medium. Surprisingly, we found that in the presence of antibiotics, the susceptible strain evolved tolerance. Tolerance was typified by an increase in survival as well as an accompanying decrease in the growth rate, highlighting a trade-off between the two. A simple mathematical model explained that the observed decrease in the death rate, even when coupled with a decreased growth rate, is beneficial in a community with weak protective interactions. In the presence of strong interactions, the model predicted that the trade-off would instead be detrimental, and tolerance would not emerge, which we experimentally verified. By whole genome sequencing the evolved tolerant isolates, we identified two genetic hot spots which accumulated mutations in parallel lines, suggesting their association with tolerance. Our work highlights that ecological interactions can promote antibiotic tolerance in bacterial communities, which has remained understudied.

Enhancing nutritional niche and host defenses by modifying the gut microbiome.

The gut microbiome is essential for processing complex food compounds and synthesizing nutrients that the host cannot digest or produce, respectively. New model systems are needed to study how the metabolic capacity provided by the gut microbiome impacts the nutritional status of the host, and to explore possibilities for altering host metabolic capacity via the microbiome. Here, we colonized the nematode Caenorhabditis elegans gut with cellulolytic bacteria that enabled C. elegans to utilize cellulose, an otherwise indigestible substrate, as a carbon source. Cellulolytic bacteria as a community component in the worm gut can also support additional bacterial species with specialized roles, which we demonstrate by using Lactobacillus plantarum to protect C. elegans against Salmonella enterica infection. This work shows that engineered microbiome communities can be used to endow host organisms with novel functions, such as the ability to utilize alternate nutrient sources or to better fight pathogenic bacteria.

Emergent phases of ecological diversity and dynamics mapped in microcosms.

From tropical forests to gut microbiomes, ecological communities host notably high numbers of coexisting species. Beyond high biodiversity, communities exhibit a range of complex dynamics that are difficult to explain under a unified framework. Using bacterial microcosms, we performed a direct test of theory predicting that simple community-level features dictate emergent behaviors of communities. As either the number of species or the strength of interactions increases, we show that microbial ecosystems transition between three distinct dynamical phases, from a stable equilibrium in which all species coexist to partial coexistence to emergence of persistent fluctuations in species abundances, in the order predicted by theory. Under fixed conditions, high biodiversity and fluctuations reinforce each other. Our results demonstrate predictable emergent patterns of diversity and dynamics in ecological communities.

Dynamic clustering of passive colloids in dense suspensions of motile bacteria.

Mixtures of active and passive particles are predicted to exhibit a variety of nonequilibrium phases. Here we report a dynamic clustering phase in mixtures of colloids and motile bacteria. We show that colloidal clustering results from a balance between bond breaking due to persistent active motion and bond stabilization due to torques that align active particle velocity tangentially to the passive particle surface. Furthermore, dynamic clustering spans a broad regime between diffusivity-based and motility-induced phase separation that subsumes typical bacterial motility parameters.

A Dynamic Threshold Approach for Tarnished Plant Bug (Hemiptera: Miridae) Management in the Midsouthern U.S. Cotton.

One of the most economically important pests of cotton, Gossypium hirsutum L., in the midsouth region of the United States is the tarnished plant bug, Lygus lineolaris (Palisot de Beauvois, Hemiptera: Miridae). Tarnished plant bug populations across the region have exhibited widespread resistance to numerous insecticide classes. To minimize late season resistance development, reducing unwarranted applications during the late flowering period can aid in resistance management and potentially reduce input costs. Trials were conducted during 2019 and 2020 to evaluate the impacts of tarnished plant bug populations in the later flowering period of cotton by modifying or terminating threshold regimes during the later weeks of bloom. Results showed that dynamic thresholds altered at the fourth week of bloom or later can reduce the number of late season applications made with no penalty to yield. Additionally, when utilizing a week of bloom termination approach, no significant yield losses were seen when terminating applications after the fourth week of bloom. These data may offer an alternative method to managing tarnished plant bug populations during the later flowering period of midsouth cotton.

Diauxic lags explain unexpected coexistence in multi-resource environments.

How the coexistence of species is affected by the presence of multiple resources is a major question in microbial ecology. We experimentally demonstrate that differences in diauxic lags, which occur as species deplete their own environments and adapt their metabolisms, allow slow-growing microbes to stably coexist with faster-growing species in multi-resource environments despite being excluded in single-resource environments. In our focal example, an Acinetobacter species (Aci2) competitively excludes Pseudomonas aurantiaca (Pa) on alanine and on glutamate. However, they coexist on the combination of both resources. Experiments reveal that Aci2 grows faster but Pa has shorter diauxic lags. We establish a tradeoff between Aci2's fast growth and Pa's short lags as their mechanism for coexistence. We model this tradeoff to accurately predict how environmental changes affect community composition. We extend our work by surveying a large set of competitions and observe coexistence nearly four times as frequently when the slow-grower is the fast-switcher. Our work illustrates a simple mechanism, based entirely on supplied-resource growth dynamics, for the emergence of multi-resource coexistence.

Fast growth can counteract antibiotic susceptibility in shaping microbial community resilience to antibiotics.

Microbial communities often face external perturbations that can induce lasting changes in their composition and functions. Our understanding of how multispecies communities respond to perturbations such as antibiotics is limited, with susceptibility assays performed on individual, isolated species our primary guide in predicting community transitions. Here, we studied how bacterial growth dynamics can overcome differences in antibiotic susceptibility in determining community resilience: the recovery of the original community state following antibiotic exposure. We used an experimental community containing Corynebacterium ammoniagenes and Lactobacillus plantarum that displays two alternative stable states as a result of mutual inhibition. Although C. ammoniagenes was more susceptible to chloramphenicol in monocultures, we found that chloramphenicol exposure nonetheless led to a transition from the L. plantarum-dominated to the C. ammoniagenes-dominated community state. Combining theory and experiments, we demonstrated that growth rate differences between the two species made the L. plantarum-dominated community less resilient to several antibiotics with different mechanisms of action. Taking advantage of an observed cooperativity­a dependence on population abundance­in the growth of C. ammoniagenes, we next analyzed in silico scenarios that could compromise the high resilience of the C. ammoniagenes-dominated state. The model predicted that lowering the dispersal rate, through interacting with the growth at low population densities, could make the C. ammoniagenes state fragile against virtually any kind of antibiotic, a prediction that we confirmed experimentally. Our results highlight that species susceptibility to antibiotics is often uninformative of community resilience, as growth dynamics in the wake of antibiotic exposure can play a dominant role.

Slow expanders invade by forming dented fronts in microbial colonies.

Most organisms grow in space, whether they are viruses spreading within a host tissue or invasive species colonizing a new continent. Evolution typically selects for higher expansion rates during spatial growth, but it has been suggested that slower expanders can take over under certain conditions. Here, we report an experimental observation of such population dynamics. We demonstrate that mutants that grow slower in isolation nevertheless win in competition, not only when the two types are intermixed, but also when they are spatially segregated into sectors. The latter was thought to be impossible because previous studies focused exclusively on the global competitions mediated by expansion velocities, but overlooked the local competitions at sector boundaries. Local competition, however, can enhance the velocity of either type at the sector boundary and thus alter expansion dynamics. We developed a theory that accounts for both local and global competitions and describes all possible sector shapes. In particular, the theory predicted that a slower on its own, but more competitive, mutant forms a dented V-shaped sector as it takes over the expansion front. Such sectors were indeed observed experimentally, and their shapes matched quantitatively with the theory. In simulations, we further explored several mechanisms that could provide slow expanders with a local competitive advantage and showed that they are all well-described by our theory. Taken together, our results shed light on previously unexplored outcomes of spatial competition and establish a universal framework to understand evolutionary and ecological dynamics in expanding populations.

Best Management Practices to Delay the Evolution of Bt Resistance in Lepidopteran Pests Without High Susceptibility to Bt Toxins in North America.

Canadian and United States (US) insect resistance management (IRM) programs for lepidopteran pests in Bacillus thuriengiensis (Bt)-expressing crops are optimally designed for Ostrinia nubilalis Hübner in corn (Zea mays L.) and Chloridea virescens Fabricius in cotton (Gossypium hirsutum L.). Both Bt corn and cotton express a high dose for these pests; however, there are many other target pests for which Bt crops do not express high doses (commonly referred to as nonhigh dose pests). Two important lepidopteran nonhigh dose (low susceptibility) pests are Helicoverpa zea Boddie (Lepidoptera: Noctuidae) and Striacosta albicosta Smith (Lepidoptera: Noctuidae). We highlight both pests as cautionary examples of exposure to nonhigh dose levels of Bt toxins when the IRM plan was not followed. Moreover, IRM practices to delay Bt resistance that are designed for these two ecologically challenging and important pests should apply to species that are more susceptible to Bt toxins. The purpose of this article is to propose five best management practices to delay the evolution of Bt resistance in lepidopteran pests with low susceptibility to Bt toxins in Canada and the US: 1) better understand resistance potential before commercialization, 2) strengthen IRM based on regional pest pressure by restricting Bt usage where it is of little benefit, 3) require and incentivize planting of structured corn refuge everywhere for single toxin cultivars and in the southern US for pyramids, 4) integrate field and laboratory resistance monitoring programs, and 5) effectively use unexpected injury thresholds.

Positive interactions are common among culturable bacteria.

Interspecies interactions shape the structure and function of microbial communities. In particular, positive, growth-promoting interactions can substantially affect the diversity and productivity of natural and engineered communities. However, the prevalence of positive interactions and the conditions in which they occur are not well understood. To address this knowledge gap, we used kChip, an ultrahigh-throughput coculture platform, to measure 180,408 interactions among 20 soil bacteria across 40 carbon environments. We find that positive interactions, often described to be rare, occur commonly and primarily as parasitisms between strains that differ in their carbon consumption profiles. Notably, nongrowing strains are almost always promoted by strongly growing strains (85%), suggesting a simple positive interaction­mediated approach for cultivation, microbiome engineering, and microbial consortium design.

Environmental fluctuations reshape an unexpected diversity-disturbance relationship in a microbial community.

Environmental disturbances have long been theorized to play a significant role in shaping the diversity and composition of ecosystems. However, an inability to specify the characteristics of a disturbance experimentally has produced an inconsistent picture of diversity-disturbance relationships (DDRs). Here, using a high-throughput programmable culture system, we subjected a soil-derived bacterial community to dilution disturbance profiles with different intensities (mean dilution rates), applied either constantly or with fluctuations of different frequencies. We observed an unexpected U-shaped relationship between community diversity and disturbance intensity in the absence of fluctuations. Adding fluctuations increased community diversity and erased the U-shape. All our results are well-captured by a Monod consumer resource model, which also explains how U-shaped DDRs emerge via a novel 'niche flip' mechanism. Broadly, our combined experimental and modeling framework demonstrates how distinct features of an environmental disturbance can interact in complex ways to govern ecosystem assembly and offers strategies for reshaping the composition of microbiomes.