Deciphering stratified structure and microbiota assembly of biofilms from a pyrite-based biofilter driven by mixotrophic denitrification

The precise structure and assembly process of pyrite-based biofilms remain poorly understood. The polysaccharides (PN), proteins (PS), and extracellular DNA were enriched in the soluble extracellular polymeric substance (EPS), loosely bound EPS, and tightly bound EPS, respectively, indicating a significant stratified structure of biofilms. The tryptophan facilitated mixotrophic metabolic processes. Both dominant (>1%) and rare species (<0.01 %) harbored core bacteria, including sulfur autotrophic bacteria, sulfate-reducing bacteria, and heterotrophic bacteria. Furthermore, partial least-squares path modeling quantified the contributions of total phosphorus (TP) (λ = 0.32), dissolved organic matter (DOC) (λ = 0.29), and NH<sub>4</sub><sup>+</sup>-N (λ = 0.26) to variations in the microbial community. Nonmetric multidimensional scaling analysis revealed three distinct stages in biofilm development: colonization (0-36 d), succession (36-149 d), and maturation/old (149-215 d). Furthermore, neutral community model indicated that stochastic processes drove the colonization and maturation/old stages, while deterministic processes dominated the succession stage. This study offered valuable insights into the regulation of pyrite-based engineered ecosystems.

Authors

Institutions

Publication Details

Journal
Bioresource Technology
Published
2024-10-02
DOI
https://doi.org/10.1016/j.biortech.2024.131568
Citations
11
Primary Topic
Wastewater Treatment and Nitrogen Removal
Type
article
Field-Weighted Citation Impact
1.46
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Deciphering stratified structure and microbiota assembly of biofilms from a pyrite-based biofilter driven by mixotrophic denitrification

Qi Zhou, Yuanwei Li, Lixia Jia, Jianlong Wang et al.
11 citations
Bioresource Technology
Wastewater Treatment and Nitrogen Removal
1.46
article

Deciphering stratified structure and microbiota assembly of biofilms from a pyrite-based biofilter driven by mixotrophic denitrification

Qi Zhou, Yuanwei Li, Lixia Jia, Jianlong Wang, Weizhong Wu
article en
11 citations

Abstract

The precise structure and assembly process of pyrite-based biofilms remain poorly understood. The polysaccharides (PN), proteins (PS), and extracellular DNA were enriched in the soluble extracellular polymeric substance (EPS), loosely bound EPS, and tightly bound EPS, respectively, indicating a significant stratified structure of biofilms. The tryptophan facilitated mixotrophic metabolic processes. Both dominant (>1%) and rare species (<0.01 %) harbored core bacteria, including sulfur autotrophic bacteria, sulfate-reducing bacteria, and heterotrophic bacteria. Furthermore, partial least-squares path modeling quantified the contributions of total phosphorus (TP) (λ = 0.32), dissolved organic matter (DOC) (λ = 0.29), and NH<sub>4</sub><sup>+</sup>-N (λ = 0.26) to variations in the microbial community. Nonmetric multidimensional scaling analysis revealed three distinct stages in biofilm development: colonization (0-36 d), succession (36-149 d), and maturation/old (149-215 d). Furthermore, neutral community model indicated that stochastic processes drove the colonization and maturation/old stages, while deterministic processes dominated the succession stage. This study offered valuable insights into the regulation of pyrite-based engineered ecosystems.

Bioresource TechnologyVol. 414
Peking University (CN), Tsinghua University (CN)
Openalex Percentile: Top 20%
Wastewater Treatment and Nitrogen Removal
1.46
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.