A preliminary and qualitative study of resource ratio theory to nitrifying lab-scale bioreactors

Assessing mechanisms for microbial taxa and community dynamics using process models

Disentangling the assembly mechanisms controlling community composition, structure, distribution, functions, and dynamics is a central issue in ecology. Although various approaches have been proposed to examine community assembly mechanisms, quantitative characterization is challenging, particularly in microbial ecology. Here, we present a novel approach for quantitatively delineating community assembly mechanisms by combining the consumer-resource model with a neutral model in stochastic differential equations. Using time-series data from anaerobic bioreactors that target microbial 16S rRNA genes, we tested the applicability of three ecological models: the consumer-resource model, the neutral model, and the combined model. Our results revealed that model performances varied substantially as a function of population abundance and/or process conditions. The combined model performed best for abundant taxa in the treatment bioreactors where process conditions were manipulated. In contrast, the neutral model showed the best performance for rare taxa. Our analysis further indicated that immigration rates decreased with taxa abundance and competitions between taxa were strongly correlated with phylogeny, but within a certain phylogenetic distance only. The determinism underlying taxa and community dynamics were quantitatively assessed, showing greater determinism in the treatment bioreactors that aligned with the subsequent abnormal system functioning. Given its mechanistic basis, the framework developed here is expected to be potentially applicable beyond microbial ecology.

Comparison of the Performance and Microbial Community Structure of Two Outdoor Pilot-Scale Photobioreactors Treating Digestate

This study aimed at examining and comparing the nutrient removal efficiency, biomass productivity and microbial community structure of two outdoor pilot-scale photobioreactors, namely a bubble column and a raceway pond, treating the liquid fraction of an agricultural digestate. Bacterial and eukaryotic communities were characterized using a metabarcoding approach and quantitative PCR. The abundance, composition, diversity, and dynamics of the main microbes were then correlated to the environmental conditions and operational parameters of the reactors. Both photobioreactors were dominated either by Chlorella sp. or Scenedesmus sp. in function of temperature, irradiance and the nitrogen compounds derived by nitrification. Other species, such as Chlamydomonas and Planktochlorella, were sporadically present, demonstrating that they have more specific niche requirement. Pseudomonas sp. always dominated the bacterial community in both reactors, except in summertime, when a bloom of Calothrix occurred in the raceway pond. In autumn, the worsening of the climate conditions decreased the microalgal growth, promoting predation by Vorticella sp. The study highlights the factors influencing the structure and dynamics of the microbial consortia and which ecological mechanisms are driving the microbial shifts and the consequent reactor performance. On these bases, control strategies could be defined to optimize the management of the microalgal-based technologies.

Elucidating the Competition between Heterotrophic Denitrification and DNRA Using the Resource-Ratio Theory

Heterotrophic denitrification and dissimilatory nitrate reduction to ammonium (DNRA) are two microbial processes competing for two shared resources, namely, nitrate and organic carbon (COD). Their competition has great implications for nitrogen loss, conservation, and greenhouse gas emissions. Nevertheless, a comprehensive and mechanistic understanding of the governing factors for this competition is still lacking. We applied the resource-ratio theory to study this competition and validated the theory with experimental data from continuous cultures reported in the literature. Based on this theory, we revealed that influent COD/N ratio alone was not sufficient to predict the competition outcome as the boundary values for different competition outcomes changed substantially with influent resource concentrations. The stoichiometry of the two processes was determinative for the boundaries, whereas the affinity for the shared resources (K_S), maximum specific growth rate (μ_max) of the two species, and the dilution rate had significant impacts as well but mainly at low influent resource concentrations (e.g., <100 μM nitrate). The presented approach allows for a more comprehensive understanding of the parameters controlling microbial competition. The computational comparison between continuous and batch cultures could explain seemingly conflicting experimental results as to the impact of the COD/N ratio. The results also include testable hypotheses and tools for understanding and managing the fate of nitrate in ecosystems, which could also be applied more widely to other species competing for two shared resources.

Management of Microbial Communities through Transient Disturbances Enhances the Functional Resilience of Nitrifying Gas-Biofilters to Future Disturbances

Microbial communities have a key role for the performance of engineered ecosystems such as waste gas biofilters. Maintaining constant performance despite fluctuating environmental conditions is of prime interest, but it is highly challenging because the mechanisms that drive the response of microbial communities to disturbances still have to be disentangled. Here we demonstrate that the bioprocess performance and stability can be improved and reinforced in the face of disturbances, through a rationally predefined strategy of microbial resource management (MRM). This strategy was experimentally validated in replicated pilot-scale nitrifying gas-biofilters, for the two steps of nitrification. The associated biological mechanisms were unraveled through analysis of functions, abundances and community compositions for the major actors of nitrification in these biofilters, that is, ammonia-oxidizing bacteria (AOB) and Nitrobacter-like nitrite-oxidizers (NOB). Our MRM strategy, based on the application of successive, transient perturbations of increasing intensity, enabled to steer the nitrifier community in a favorable way through the selection of more resistant AOB and NOB sharing functional gene sequences close to those of, respectively, Nitrosomonas eutropha and Nitrobacter hamburgensis that are well adapted to high N load. The induced community shifts resulted in significant enhancement of nitrification resilience capacity following the intense perturbation.

Synthetic Ecology of Microbes: Mathematical Models and Applications

As the indispensable role of natural microbial communities in many aspects of life on Earth is uncovered, the bottom-up engineering of synthetic microbial consortia with novel functions is becoming an attractive alternative to engineering single-species systems. Here, we summarize recent work on synthetic microbial communities with a particular emphasis on open challenges and opportunities in environmental sustainability and human health. We next provide a critical overview of mathematical approaches, ranging from phenomenological to mechanistic, to decipher the principles that govern the function, dynamics and evolution of microbial ecosystems. Finally, we present our outlook on key aspects of microbial ecosystems and synthetic ecology that require further developments, including the need for more efficient computational algorithms, a better integration of empirical methods and model-driven analysis, the importance of improving gene function annotation, and the value of a standardized library of well-characterized organisms to be used as building blocks of synthetic communities.