Cooperative interactions between invader and resident microbial community members weaken the negative diversity-invasion relationship.

The negative diversity-invasion relationship observed in microbial invasion studies is commonly explained by competition between the invader and resident populations. However, whether this relationship is affected by invader-resident cooperative interactions is unknown. Using ecological and mathematical approaches, we examined the survival and functionality of Aminobacter niigataensis MSH1 to mineralize 2,6-dichlorobenzamide (BAM), a groundwater micropollutant affecting drinking water production, in sand microcosms when inoculated together with synthetic assemblies of resident bacteria. The assemblies varied in richness and in strains that interacted pairwise with MSH1, including cooperative and competitive interactions. While overall, the negative diversity-invasion relationship was retained, residents engaging in cooperative interactions with the invader had a positive impact on MSH1 survival and functionality, highlighting the dependency of invasion success on community composition. No correlation existed between community richness and the delay in BAM mineralization by MSH1. The findings suggest that the presence of cooperative residents can alleviate the negative diversity-invasion relationship.

Food biodiversity: Quantifying the unquantifiable in human diets.

Dietary diversity is an established public health principle, and its measurement is essential for studies of diet quality and food security. However, conventional between food group scores fail to capture the nutritional variability and ecosystem services delivered by dietary richness and dissimilarity within food groups, or the relative distribution (i.e., evenness or moderation) of e.g., species or varieties across whole diets. Summarizing food biodiversity in an all-encompassing index is problematic. Therefore, various diversity indices have been proposed in ecology, yet these require methodological adaption for integration in dietary assessments. In this narrative review, we summarize the key conceptual issues underlying the measurement of food biodiversity at an edible species level, assess the ecological diversity indices previously applied to food consumption and food supply data, discuss their relative suitability, and potential amendments for use in (quantitative) dietary intake studies. Ecological diversity indices are often used without justification through the lens of nutrition. To illustrate: (i) dietary species richness fails to account for the distribution of foods across the diet or their functional traits; (ii) evenness indices, such as the Gini-Simpson index, require widely accepted relative abundance units (e.g., kcal, g, cups) and evidence-based moderation weighting factors; and (iii) functional dissimilarity indices are constructed based on an arbitrary selection of distance measures, cutoff criteria, and number of phylogenetic, nutritional, and morphological traits. Disregard for these limitations can lead to counterintuitive results and ambiguous or incorrect conclusions about the food biodiversity within diets or food systems. To ensure comparability and robustness of future research, we advocate food biodiversity indices that: (i) satisfy key axioms; (ii) can be extended to account for disparity between edible species; and (iii) are used in combination, rather than in isolation.Supplemental data for this article is available online at https://doi.org/10.1080/10408398.2022.2051163 .

Interspecies Interactions of the 2,6-Dichlorobenzamide Degrading Aminobacter sp. MSH1 with Resident Sand Filter Bacteria: Indications for Mutual Cooperative Interactions That Improve BAM Mineralization Activity.

Bioaugmentation often involves an invasion process requiring the establishment and activity of a foreign microbe in the resident community of the target environment. Interactions with resident micro-organisms, either antagonistic or cooperative, are believed to impact invasion. However, few studies have examined the variability of interactions between an invader and resident species of its target environment, and none of them considered a bioremediation context. Aminobacter sp. MSH1 mineralizing the groundwater micropollutant 2,6-dichlorobenzamide (BAM), is proposed for bioaugmentation of sand filters used in drinking water production to avert BAM contamination. We examined the nature of the interactions between MSH1 and 13 sand filter resident bacteria in dual and triple species assemblies in sand microcosms. The residents affected MSH1-mediated BAM mineralization without always impacting MSH1 cell densities, indicating effects on cell physiology rather than on cell number. Exploitative competition explained most of the effects (70%), but indications of interference competition were also found. Two residents improved BAM mineralization in dual species assemblies, apparently in a mutual cooperation, and overruled negative effects by others in triple species systems. The results suggest that sand filter communities contain species that increase MSH1 fitness. This opens doors for assisting bioaugmentation through co-inoculation with "helper" bacteria originating from and adapted to the target environment.

Guiding Mineralization Co-Culture Discovery Using Bayesian Optimization.

Many disciplines rely on testing combinations of compounds, materials, proteins, or bacterial species to drive scientific discovery. It is time-consuming and expensive to determine experimentally, via trial-and-error or random selection approaches, which of the many possible combinations will lead to desirable outcomes. Hence, there is a pressing need for more rational and efficient experimental design approaches to reduce experimental effort. In this work, we demonstrate the potential of machine learning methods for the in silico selection of promising co-culture combinations in the application of bioaugmentation. We use the example of pollutant removal in drinking water treatment plants, which can be achieved using co-cultures of a specialized pollutant degrader with combinations of bacterial isolates. To reduce the experimental effort needed to discover high-performing combinations, we propose a data-driven experimental design. Based on a dataset of mineralization performance for all pairs of 13 bacterial species co-cultured with MSH1, we built a Gaussian process regression model to predict the Gompertz mineralization parameters of the co-cultures of two and three species, based on the single-strain parameters. We subsequently used this model in a Bayesian optimization scheme to suggest potentially high-performing combinations of bacteria. We achieved good performance with this approach, both for predicting mineralization parameters and for selecting effective co-cultures, despite the limited dataset. As a novel application of Bayesian optimization in bioremediation, this experimental design approach has promising applications for highlighting co-culture combinations for in vitro testing in various settings, to lessen the experimental burden and perform more targeted screenings.

Three-species competition with non-deterministic outcomes.

Theoretical and experimental research studies have shown that ecosystems governed by non-transitive competition networks tend to maintain high levels of biodiversity. The theoretical body of work, however, has mainly focused on competition networks in which the outcomes of competition events are predetermined and hence deterministic, and where all species are identical up to their competitive relationships, an assumption that may limit the applicability of theoretical results to real-life situations. In this paper, we aim to probe the robustness of the link between biodiversity and non-transitive competition by introducing a three-dimensional winning probability parameter space, making the outcomes of competition events in a three-species in silico ecosystem uncertain. While two degenerate points in this parameter space have been the subject of previous studies, we investigate the remaining settings, which equip the species with distinct competitive abilities. We find that the impact of this modification depends on the spatial dimension of the system. When the system is well mixed, it collapses to monoculture, as is also the case in the non-transitive deterministic setting. In one dimension, chaotic patterns emerge, which tend to maintain biodiversity, and a power law relates the time that species manage to coexist to the degree of uncertainty regarding competition event outcomes. In two dimensions, the formation of spiral wave patterns ensures that biodiversity is maintained for moderate degrees of uncertainty, while considerable deviations from the non-transitive deterministic setting have strong negative effects on species coexistence. It can hence be concluded that non-transitive competition can still produce coexistence when the assumption of deterministic competition is abandoned. When the system collapses to monoculture, one observes a "survival of the strongest" law, as the species that has the highest probability of defeating its competitors has the best odds to become the sole survivor.

The impact of resource dependence of the mechanisms of life on the spatial population dynamics of an in silico microbial community.

Biodiversity has a critical impact on ecosystem functionality and stability, and thus the current biodiversity crisis has motivated many studies of the mechanisms that sustain biodiversity, a notable example being non-transitive or cyclic competition. We therefore extend existing microscopic models of communities with cyclic competition by incorporating resource dependence in demographic processes, characteristics of natural systems often oversimplified or overlooked by modellers. The spatially explicit nature of our individual-based model of three interacting species results in the formation of stable spatial structures, which have significant effects on community functioning, in agreement with experimental observations of pattern formation in microbial communities.

The impact of initial evenness on biodiversity maintenance for a four-species in silico bacterial community.

Initial community evenness has been shown to be a key factor in preserving the functional stability of an ecosystem, but has not been accounted for in previous modelling studies. We formulate a model that allows the initial evenness of the community to be varied in order to investigate the consequent impact on system diversity. We consider a community of four interacting bacterial species, and present a stochastic, spatial individual-based model simulating the ecosystem dynamics. Interactions take place on a two-dimensional lattice. The model incorporates three processes: reproduction, competition and mobility. In addition to variable initial evenness, multiple competition schemes are implemented, modelling various possible communities, which results in diverse coexistence and extinction scenarios. Simulations show that long-term system behaviour is strongly dependent on initial evenness and competition structure. The system is generally unstable; higher initial evenness has a small stabilizing effect on ecosystem dynamics by extending the time until the first extinction.

Temperature-driven dynamics: unraveling the impact of climate change on cryptic species interactions within the Litoditis marina complex.

Anthropogenic climate change and the associated increase in sea temperatures are projected to greatly impact marine ecosystems. Temperature variation can influence the interactions between species, leading to cascading effects on the abundance, diversity and composition of communities. Such changes in community structure can have consequences on ecosystem stability, processes and the services it provides. Therefore, it is important to better understand the role of species interactions in the development of communities and how they are influenced by environmental factors like temperature. The coexistence of closely related cryptic species, with significant biological and ecological differences, makes this even more complex. This study investigated the effect of temperature on species growth and both intra- and interspecific interactions of three species within the free-living nematode Litoditis marina complex. To achieve this, closed microcosm experiments were conducted on the L. marina species Pm I, Pm III and Pm IV in monoculture and combined cultures at two temperature treatments of 15 °C and 20 °C. A population model was constructed to elucidate and quantify the effects of intra- and interspecific interactions on nematode populations. The relative competitive abilities of the investigated species were quantified using the Modern Coexistence Theory (MCT) framework. Temperature had strong and disparate effects on the population growth of the distinct L. marina species. This indicates temperature could play an important role in the distribution of these cryptic species. Both competitive and facilitative interactions were observed in the experiments. Temperature affected both the type and the strength of the species interactions, suggesting a change in temperature could impact the coexistence of these closely related species, alter community dynamics and consequently affect ecosystem processes and services.

Regulation of HGF and SDF-1 expression by oral fibroblasts--implications for invasion of oral cancer.

Invasion and metastasis of oral squamous cell carcinoma (OSCC) is dependent on signals received from stromal fibroblasts present in the surrounding connective tissue. The aim of this study was to investigate the regulation of expression of two important signaling molecules--HGF and SDF-1--by both stromal fibroblasts and their 'activated' form, myofibroblasts, and to determine the role of these two factors in stimulating OSCC cell invasion in vitro. Fibroblasts and myofibroblasts produced similar levels of HGF and SDF-1. IL-1alpha and OSCC cell conditioned medium both stimulated HGF and SDF-1 expression, while TGF-beta(1) inhibited production of each factor. Myofibroblast-derived conditioned medium stimulated OSCC cell invasion through matrigel. Blocking antibodies to both HGF and SDF-1 reduced the level of invasion. In fibroblast-free organotypic raft cultures, addition of HGF and SDF-1 stimulated OSCC cell invasion into the underlying collagen gel, although the pattern of invasion differed from that induced by fibroblasts. Fibroblast-derived HGF and SDF-1 appear to play central roles in the reciprocal interactions between OSCC cells and underlying stromal fibroblasts leading to the local invasion of oral cancer.

In silico substrate dependence increases community productivity but threatens biodiversity.

The critical role that biodiversity plays in ecosystem functioning has motivated many studies of the mechanisms that sustain biodiversity, a notable example being cyclic competition. We extend existing models of communities with cyclic competition by incorporating variable community evenness and resource dependence in demographic processes, two features that have generally been neglected. In this way, we align previous approaches more closely with real-world microbial ecosystems. We demonstrate the existence of a trade-off between increasing biomass production and maintaining biodiversity. This supports experimental observations of a net negative biodiversity effect on biomass productivity, due to competition effects suffered by highly productive species in diverse communities. Our results also support the important role assigned by microbial ecologists to evenness in maintaining ecosystem stability, thus far largely overlooked in in silico approaches.