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Characterizing Microbiome Dynamics – Flow Cytometry Based Workflows from Pure Cultures to Natural Communities
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GeoChip-based analysis of the microbial community functional structures in simultaneous desulfurization and
Hao Yu1, Chuan Chen2, Jincai Ma3
1School of Environmental Science and Engineering, Liaoning Technical University, Fuxin 123000, China; State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology, Harbin 150090, China.
Journal of Environmental Sciences (China)
|August 1, 2014
Summary
The denitrifying sulfide removal (DSR) model achieved 91.1% elemental sulfur recovery, significantly outperforming the integrated simultaneous desulfurization and denitrification (ISDD) model. Microbial analysis revealed distinct community structures and functional genes linked to higher sulfur conversion in the DSR model.
Area of Science:
- Environmental Science
- Microbiology
- Biotechnology
Background:
- Simultaneous desulfurization and denitrification (SDD) processes are crucial for treating industrial wastewater.
- Elemental sulfur (S°) recovery is a key performance indicator in SDD systems.
- Understanding microbial community dynamics is essential for optimizing SDD efficiency.
Purpose of the Study:
- To evaluate elemental sulfur recovery in two distinct SDD models: denitrifying sulfide removal (DSR) and integrated simultaneous desulfurization and denitrification (ISDD).
- To analyze the functional diversity, structure, and metabolic potential of microbial communities in response to different SDD configurations.
- To elucidate the microbial mechanisms influencing S° conversion rates in the presence of nitrate.
Main Methods:
- Comparative analysis of S° conversion rates under specific sulfide and nitrate loading rates.
- Utilized functional gene array (GeoChip 2.0) for comprehensive microbial community profiling.
- Assessed diversity indices (Simpson's, Shannon-Weaver) and abundance of key functional genes, including dsr and those associated with nitrate-reducing sulfide-oxidizing bacteria (NR-SOB).
Main Results:
- The DSR model demonstrated significantly higher S° conversion (91.1%) compared to the ISDD model (25.6%).
- Microbial communities exhibited distinct structures and functional gene abundances between the two models.
- Elevated loading rates led to decreased functional diversity in ISDD but increased diversity in DSR.
- Specific NR-SOB genes (e.g., Thiobacillus denitrificans, Sulfurimonas denitrificans, Paracoccus pantotrophus) were more abundant in the DSR model, correlating with higher S° conversion.
Conclusions:
- The DSR model offers superior performance for elemental sulfur recovery in SDD processes.
- Microbial community composition and functional gene expression are critical determinants of SDD efficiency.
- Targeting specific NR-SOB may enhance S° recovery and overall SDD process optimization.
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