Assessment of Microbial Community Structure and Function in Serially Passaged Wastewater Electro-Bioreactor Sludge: An Approach to Enhance Sludge Settleability
Bibliographic record
Abstract
Abstract Several studies have been carried out to understand bulking phenomena and the importance of environmental factors on sludge settling characteristics. The main objective of this study was to carry out functional characterization of microbial community structure of wastewater electro-bioreactor sludge as it undergoes serial passaging in the presence or absence of a current density over 15 days. Illumina MiSeq sequencing and QIIME were used to assess sludge microbial community shifts over time. (α) and (β) diversity analysis were conducted to assess the microbial diversity in electro-bioreactors. A phylogeny-based weighted UniFrac distance analysis was used to compare between bacterial communities while BIO-ENV trend and Spearman’s rank correlation analysis were performed to investigate how reactor operational parameters correlated with bacterial community diversity. Results showed that the removal efficiency of soluble chemical oxygen demand (sCOD) ranged from 91–97%, while phosphorous (PO 4 3− -P) removal was approximately 99%. Phylogenetic analysis revealed stark differences in the development of sludge microbial communities in the control and treatment reactor. There was no mention of any studies aimed at characterizing functional microbial communities under electric field and the results communicated here are the first, to our knowledge, that address this gap in the literature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 teacher head, 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".