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Analysis of Microbial Communities in Membrane Bioreactors with and without Quorum Quenching : 하폐수 처리용 분리막 생물반응기에서 정족수 감지 억제 유무에 따른 미생물 군집 분석
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.advisor | 이정학 | - |
| dc.contributor.author | 조성준 | - |
| dc.date.accessioned | 2017-07-13T08:44:47Z | - |
| dc.date.available | 2017-07-13T08:44:47Z | - |
| dc.date.issued | 2016-08 | - |
| dc.identifier.other | 000000136508 | - |
| dc.identifier.uri | https://hdl.handle.net/10371/119805 | - |
| dc.description | 학위논문 (박사)-- 서울대학교 대학원 : 화학생물공학부, 2016. 8. 이정학. | - |
| dc.description.abstract | Membrane bioreactors (MBRs) are hampered particularly by membrane biofouling, resulting from microbial growth on the membrane surface and microbial production of membrane foulants in activated sludge. To mitigate biofouling, quorum quenching (QQ) has been stand out as an innovative technique in MBRs. Although the biological understanding of the effect of QQ and biofouling mechanism is crucial for the development of biofouling control strategies, the information of the microbial ecology is not sufficient in both QQ-MBR and full-scale MBRs. Therefore the investigation of microbial community in QQ-MBR and full-scale MBRs are required for the successful biofouling control in real MBRs.
Firstly, the microbial communities were investigated in relation to the QQ effect on biofilm in an anoxic/oxic (A/O) MBR. Two laboratory-scale MBRs with and without QQ-beads (QQ-bacteria encapsulated in bead) were operated in parallel. TMP (transmembrane pressure) rise-up in QQ-MBR was delayed by approximately 100~110% compared with those in conventional-and vacant (bead without QQ-bacteria)-MBRs. The principal coordinate analysis based on weighted UniFrac distance matric revealed that QQ had effect on microbial community in biofilm. The results of correspondence analysis revealed that QQ had effect on both bacterial composition and the change rate of bacterial composition in biofilm. Secondly, the microbial communities of activated sludge were investigated in relation to the effect of QQ on A/O MBR for 91 days. The system performance (e.g., COD, TN removal efficiency) was stable over the period regardless of the presence of QQ beads. However, the average floc size in the QQ-MBR was substantially lower than that in the control-MBR (p<0.05). QQ affected the bacterial compositions of activated sludge. The network analysis revealed that QQ had effects on the microbial interactions of activated sludge. Lastly, the microbial communities of biofilm and activated sludge were scrutinized from 10 full-scale MBR plants. Overall, Flavobacterium, Dechloromonas and Nitrospira were abundant in order of abundance in biofilm, whereas Dechloromonas, Flavobacterium and Haliscomenobacter in activated sludge. The proportions of known quorum sensing bacterial genera ranged 1.39 to 11.57% in biofilm and 3.19 to 12.14% in activated sludge. Effects of ten environmental factors on community change were investigated using Spearman correlation. MLSS, HRT, F/M ratio and SADm explained the variation of microbial composition in the biofilm, whereas only MLSS did in the activated sludge. Microbial networks were constructed with the 10 environmental factors. The network results revealed that there were different topological characteristics between the biofilm and activated sludge networks. These results indicated that the different microbial associations were responsible for the variation of community composition between the biofilm and activated sludge. The information of microbial communities in QQ-MBR and full-scale MBRs could provide new insights to develop biofouling control strategies in real MBRs. | - |
| dc.description.tableofcontents | Chapter I. Introduction 1
I.1. Backgrounds 3 I.2. Objectives 5 Chapter II. Literature Review 7 II.1. Biological wastewater treatment 9 II.1.1. History of biological wastewater treatment 9 II.1.2. Biological nitrogen removal process 11 II.2. Membrane bioreactor (MBR) 16 II.2.1. MBR for advanced wastewater treatment 16 II.2.2. History of MBR 21 II.2.3. MBR trends 26 II.2.4. Membrane fouling in MBR 28 II.2.5. Biofilm in MBR 34 II.2.6. Fouling control in MBRs 36 II.3. Quorum sensing (QS) 41 II.3.1. Definition and mechanism 41 II.4. Quorum quenching (QQ) 63 II.4.1. The strategy of QQ 63 II.4.2. Application of QQ to the control of biofouling in MBRs 84 II.5. Genomic analysis of microbial community 95 II.5.1. What is microbial ecology? 95 II.5.2. Metagenomics 96 II.5.3. Sequencing technologies for the microbial identification 100 II.5.4. Software for analyzing molecular sequences and statistical analysis for understanding microbial community 108 II.5.5 The main reference resources for metagenomics 114 II.5.6. Microbial network analysis 117 II.5.7. Prediction of metabolic pathway from microbial community 124 Chapter III. QQ Effect on the Microbial Community of Biofilm in an Anoxic-Oxic MBR 125 III.1. Introduction 127 III.2. Materials and methods 129 III.2.1. Materials 129 III.2.2. MBR systems 129 III.2.3. Preparation of the QQ-beads 134 III.2.4. Bioassay of AHL-degrading activity 134 III.2.5. Analytical methods 135 III.2.6. Sampling for analysis of microbial community in biofilm 137 III.2.7. DNA extraction, PCR amplification and Miseq platform sequencing 138 III.2.8. Data analysis for bacterial community 139 III.2.9. Statistical analysis 140 III.3. Results and discussion 141 III.3.1. QQ activity of the QQ-beads and effect of QQ on MBR biofouling 141 III.3.2. Principal coordinate analysis based on UniFrac distance matric 145 III.3.3. Correspondence analysis 147 III.3.4. Microbial composition in biofilm 152 III.4. Conclusions 159 Chapter IV. QQ Effect on the Microbial Community of Activated Sludge in an Anoxic-Oxic MBR 161 IV.1. Introduction 163 IV.2. Materials and methods 165 IV.2.1. Analytical methods 165 IV.2.2. Sampling for analysis of microbial community in activated sludge 165 IV.2.3. DNA extraction, PCR amplification and Miseq platform sequencing 165 IV.2.4. Data analysis for bacterial community 166 IV.2.5. Network analysis 167 IV.2.6. Prediction of metabolic pathway 168 IV.2.7. Statistical analysis 170 IV.3. Results and discussion 171 IV.3.1. Performance of the A/O MBR with QQ 171 IV.3.2. Microbial composition in the A/O MBR with QQ 179 IV.3.3. Microbial network in the A/O MBR with QQ 186 IV.3.4. Prediction of metabolic pathway in activated sludge 197 IV.4. Conclusions 200 Chapter V. Survey of Microbial Community in Full-Scale MBRs for Wastewater Treatment 201 V.1. Introduction 203 V.2. Materials and methods 205 V.2.1. Sampling sites and methods 205 V.2.2. DNA extraction, PCR amplification and Miseq platform sequencing 206 V.2.3. Data analysis for bacterial community 206 V.2.4. Network analysis 209 V.2.5. Statistical analysis 210 V.2.6. Calculation of the relative proportion of quorum sensing related bacteria 211 V.3. Results and discussion 214 V.3.1. Community diversity 214 V.3.2. Microbial community composition in 10 MBRs 219 V.3.3 Microbial Network 237 V.4. Conclusions 254 Chapter VI. Conclusions 257 Chapter VII. 국문초록 261 References 264 | - |
| dc.format | application/pdf | - |
| dc.format.extent | 7191047 bytes | - |
| dc.format.medium | application/pdf | - |
| dc.language.iso | en | - |
| dc.publisher | 서울대학교 대학원 | - |
| dc.subject | Membrane bioreactor (MBR) | - |
| dc.subject | Quorum sensing | - |
| dc.subject | Quorum quenching | - |
| dc.subject | Biofilm | - |
| dc.subject | Activated sludge | - |
| dc.subject | Biofouling control | - |
| dc.subject | Microbial community | - |
| dc.subject.ddc | 660 | - |
| dc.title | Analysis of Microbial Communities in Membrane Bioreactors with and without Quorum Quenching | - |
| dc.title.alternative | 하폐수 처리용 분리막 생물반응기에서 정족수 감지 억제 유무에 따른 미생물 군집 분석 | - |
| dc.type | Thesis | - |
| dc.description.degree | Doctor | - |
| dc.citation.pages | 282 | - |
| dc.contributor.affiliation | 공과대학 화학생물공학부 | - |
| dc.date.awarded | 2016-08 | - |
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