Influence of sustainability and immigration in assembling bacterial populations of known size and function

Microbial immigration in wastewater treatment systems: analytical considerations and process implications

Microbial immigration from sewers to wastewater treatment systems is attracting increasing attention for understanding community assembly mechanisms, and improving process modeling and operation. While there is no consensus on approaches to analyze immigration, we suggest to classify them as relevant to either rare (non-observable) diffusive immigration or to time-continuous high-rate mass flow immigration (i.e. mass effects). When analyzed by a mass flow approach, heterotrophs appear to be strongly influenced by deterministic selection, suggesting that the heterotrophs should be subdivided into several functional guilds when assessing their assembly mechanisms. Conversely, nitrifiers appear to transfer neutrally from sewer to activated sludge, and this immigration can restore full nitrification in otherwise non-nitrifying reactors. With further refinement, these findings could be included in predictive process models with various objectives.

Neutral and selective dynamics in a synthetic microbial community

We created a synthetic microbial community to help understand how evolution and selection pressure change the species diversity of an ecosystem. Our results show that there is a clear transition between neutral and selective regimes that depends on the rate of immigration as well as the fitness differences.

Ecologists debate the relative importance of selective vs. neutral processes in understanding biodiversity. This debate is especially pertinent to microbial communities, which play crucial roles in areas such as health, disease, industry, and the environment. Here, we created a synthetic microbial community using heritable genetic barcodes and tracked community composition over repeated rounds of subculture with immigration. Consistent with theory, we find a transition exists between neutral and selective regimes, and the crossover point depends on the fraction of immigrants and the magnitude of fitness differences. Neutral models predict an increase in diversity with increased carrying capacity, while our selective model predicts a decrease in diversity. The community here lost diversity with an increase in carrying capacity, highlighting that using the correct model is essential for predicting community response to change. Together, these results emphasize the importance of including selection to obtain realistic models of even simple systems.

Bacterial community dynamics in full-scale activated sludge bioreactors: operational and ecological factors driving community assembly and performance

The assembling of bacterial communities in conventional activated sludge (CAS) bioreactors was thought, until recently, to be chaotic and mostly unpredictable. Studies done over the last decade have shown that specific, and often, predictable random and non-random factors could be responsible for that process. These studies have also motivated a “structure–function” paradigm that is yet to be resolved. Thus, elucidating the factors that affect community assembly in the bioreactors is necessary for predicting fluctuations in community structure and function. For this study activated sludge samples were collected during a one-year period from two geographically distant CAS bioreactors of different size. Combining community fingerprinting analysis and operational parameters data with a robust statistical analysis, we aimed to identify relevant links between system performance and bacterial community diversity and dynamics. In addition to revealing a significant β-diversity between the bioreactors’ communities, results showed that the largest bioreactor had a less dynamic but more efficient and diverse bacterial community throughout the study. The statistical analysis also suggests that deterministic factors, as opposed to stochastic factors, may have a bigger impact on the community structure in the largest bioreactor. Furthermore, the community seems to rely mainly on mechanisms of resistance and functional redundancy to maintain functional stability. We suggest that the ecological theories behind the Island Biogeography model and the species-area relationship were appropriate to predict the assembly of bacterial communities in these CAS bioreactors. These results are of great importance for engineers and ecologists as they reveal critical aspects of CAS systems that could be applied towards improving bioreactor design and operation.

Balance of neutral and deterministic components in the dynamics of activated sludge floc assembly

Understanding the processes that generate patterns of community structure is a central focus of ecological research. With that aim, we manipulated the structure of bacterial activated sludge to test the influence of the species richness and composition of bacterial communities on the dynamics of activated sludge floc assembly in lab-scale bioreactors. Bacterial community structure was analyzed using denaturing gradient gel electrophoresis of RT-PCR amplified 16S rRNA. Fingerprinting of four parallel reactors, started with the same source communities added in different proportions, converged to patterns that were more similar than expected by chance, suggesting a deterministic selection in floc development. Evidence for neutral dynamics was suggested by the dependence of the rate of replacement of species (bacterial taxa-time relationships) on the number of available species in the source community. Further indication of stochastic dynamics was obtained by the application of the Sloan neutral model for prokaryotes. The fitting of the observed data to the model predictions revealed that the importance of the stochastic component increased with the size of the reservoir of species richness from which the community is drawn. Taken together, the results illustrate how both neutral and deterministic dynamics operate simultaneously in the assembly of the bacterial floc and show that the balance of the two depends on the richness of the source community.

Nonrandom assembly of bacterial populations in activated sludge flocs

The aim of this work was to investigate the dynamics of assembly of bacterial populations in activated sludge flocs. We approached this question by following the development of active bacterial populations during floc development in four replicated lab-scale activated sludge reactors, in which solid retention time (SRT) was set at 4 days. The null hypothesis was that the similarities in community composition could be accounted for by the probability that the same organisms occur in more than one replicated reactor. Microscopic imaging showed that the size of flocs in reactors with biomass retention increased during the first few days until a steady-state size was reached. The diversity and community structure of the sludge in all reactors were analyzed during a period of up to ten SRT, using denaturing gradient gel electrophoresis (DGGE) of reverse-transcription polymerase chain reaction-amplified 16S rRNA. High rates of change in DGGE profiles from consecutive sampling points suggested a high level of dynamics in all reactors. This conclusion was confirmed by the application of the Raup and Crick probability-based similarity index (S(RC)) for the comparison of rRNA-based fingerprinting patterns, which indicated that bacterial communities within reactors were not significantly similar after three SRT (0.05 < S(RC) < 0.95) and became significantly dissimilar after five SRT (S(RC) < 0.05). More importantly, significant similarity between replicate reactors was observed at all times analyzed (S(RC) > 0.95). The fact that the patterns between replicates were more reproducible than expected by chance under highly dynamic conditions allowed us to reject the null hypothesis that activated sludge floc communities assemble randomly from the available source pool of bacteria. We suggest that communities progressively recruit from the available pool of bacterial species, each with particular ecological requirements that determine their time of emergence into the community.

Bacterial feeders, the nematode Caenorhabditis elegans and the flagellate Cercomonas longicauda, have different effects on outcome of competition among the Pseudomonas biocontrol strains CHA0 and DSS73

How bacterial feeding fauna affects colonization and survival of bacteria in soil is not well understood, which constrains the applicability of bacterial inoculants in agriculture. This study aimed to unravel how food quality of bacteria and bacterial feeders with different feeding habits (the selective feeding flagellate Cercomonas longicauda versus the non-selective feeding nematode Caenorhabditis elegans) influence the abundance of two bacteria that compete for resources in simple model communities. Microcosms consisted of either one gfp-tagged bacterial strain (Pseudomonas fluorescens DSM50090 or one of two biocontrol strains P. fluorescens CHA0 or Pseudomonas sp. DSS73) or combinations of two bacterial strains. DSM50090 is a suitable food bacterium, DSS73 is of intermediate food quality, and CHA0 is inedible to the bacterial feeders. Bacterial and protozoan cell numbers were measured by flow cytometry. In the presence of flagellates, CHA0 increased its abundance as compared to the other biocontrol strain DSS73 or to DSM50090, which were both eaten by the flagellates. In contrast, the number of CHA0 declined as compared to DSS73 when the model community was subjected to nematode predation pressure. Hence, the results suggested that the outcome of competition among bacteria depended on their ability to cope with the prevailing bacterial predator.

Dynamics of neutral biodiversity

Hubbell's neutral model has become a major paradigm in ecology. Whereas the steady-state structure is well understood, results about the dynamical aspects of the model are scarce. Here we derive dynamical equations for the Simpson diversity index. Both mean and variance of the diversity are proven to satisfy stable linear system dynamics. We show that in the stationary limit we indeed recover previous results, and we supplement this with numerical simulations to validate the dynamical part of our analytical computations. These findings are especially relevant for experiments in microbial ecology, where the Simpson diversity index can be accurately measured as a function of time.