Activated Sludge Microbial Community Assembly: The Role of Influent Microbial Community Immigration
Bibliographic record
Abstract
Abstract Wastewater treatment plants (WWTPs) are host to diverse microbial communities and receive a constant influx of microbes from influent wastewater, however the impact of immigrants on the structure and activities of the activated sludge (AS) microbial community remains unclear. To gain insight on this phenomenon known as perpetual community coalescence, the current study utilised controlled manipulative experiments that decoupled the influent wastewater composition from the microbial populations to reveal the fundamental mechanisms involved in immigration between sewers and AS-WWTP. The immigration dynamics of heterotrophs were analysed by harvesting wastewater biomass solids from 3 different sewer systems and adding to synthetic wastewater. Immigrating influent populations were observed to contribute up to 25 % of the sequencing reads in the AS. By modelling the net growth rate of taxa, it was revealed that immigrants primarily exhibited low or negative net growth rates. By developing a protocol to reproducibly grow AS-WWTP communities in the lab, we have laid down the foundational principals for the testing of operational factors creating community variations with low noise and appropriate replication. Understanding the processes that drive microbial community diversity and assembly is a key question in microbial ecology. In the future, this knowledge can be used to manipulate the structure of microbial communities and improve system performance in WWTPs. Importance In biological wastewater treatment processes, the microbial community composition is essential in the performance and stability of the system. To allow future process optimisation to meet new treatment goals, we need a better understanding of factors influencing the microbial community assembly in WWTPs. This study developed a reproducible protocol to investigates the impact of influent immigration (or perpetual coalescence of the sewer and activated sludge communities) with appropriate reproducibility and controls. We demonstrate herein that influent immigration contributed up to 25 % of the sequencing reads in the activated sludge under the studied conditions, highlighting the need to consider this process in future WWTP modelling and design.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".