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http://10.1.7.192:80/jspui/handle/123456789/10471| Title: | Development of Bioprocess for Identification of Pollutant levels in Industrial Wastewater by |
| Authors: | Patel, Rushika |
| Keywords: | Science Theses Theses 2020 14FTPHDS31 Industrial Wastewater |
| Issue Date: | Feb-2020 |
| Publisher: | Institute of Science, Nirma University |
| Series/Report no.: | ;ST000073 |
| Abstract: | Gujarat is known as a petrochemical hub of India and is contributing 62% of total petrochemicals production in the country. The process from manufacturing till disposal of such petrochemical products discharges aromatic hydrocarbon compounds into the environment from effluents generated through chemical processing industries and ports. The introduction of such hazardous compounds into natural water bodies creates considerable disturbances in aquatic life and causes a threat to human-beings. Owing to increasing concerns regarding pollution problems, there is a high demand for better environmental monitoring. Thus, it is essential to detect and quantify pollutants at various stages from wastewater generation till treatment and their disposal in natural aquatic environments. Also it is required to monitor pollutant levels in the receiving water bodies. This study reports the development of “biosensing strains” for detection of aromatic hydrocarbon compounds in aqueous solutions. This study was initiated with the characterization of environmental and industrial wastewater samples for type and concentration of aromatic hydrocarbon compounds by GC-MS method. Contaminated environmental water samples were collected from Kharicut canal and industrial wastewater samples were collected from CETPs of Vatva and Odhav regions, Ahmedabad, Gujarat, India. GC-MS analysis revealed that mono-aromatic and poly-aromatic compounds were present in the range of 8.26-39.5 mM and 0.8-34.5 mM, respectively, in collected water samples. For on-line detection of aromatic hydrocarbon pollutants in aqueous environments, biosensing strains can be developed with fusion of gene responsible for pollutant sensing protein (regulatory protein and their inducible promoter) with a reporter gene. Regulatory proteins TbuT, HbpR and PhnR are such proteins for recognizing one-, two- and three-rings aromatic hydrocarbon compounds, respectively, for which the binding efficiency of compounds is not known till date. The first step was to predict the structure of proteins and to determine their in-silico interaction with an array of pollutants. Structure prediction of proteins was performed using I-TASSER and Phyre2 and obtained models were refined with ModRefiner and 3DRefine. Total 14 models were obtained for each protein and the best model had more than 95% coverage in the Ramachandran plot region. After successful structure prediction, molecular interaction of proteins with respective aromatic hydrocarbon pollutants iii was studied. That study suggested, regulatory proteins were able to interact efficiently with respective aromatic hydrocarbon compounds. A novel approach in the present study was aimed at tagging of each regulatory proteins with a unique fluorescent protein-based reporter gene to obtained different signal output and hence three different fluorescent protein based reporter genes (gfp, rfp and cfp) were selected. Two vectors were designed with a fusion of tbuT-gfp and phnR-cfp for the quantification of monoand poly-aromatic hydrocarbons, respectively. The designed vectors were transformed into E. coli DH5α, and these strains were designated as E. coli DH5α 2296-gfp (containing pPROBETbut-RBS-gfp-npt) and E. coli DH5α 2301-cfp (containing pPROBE-phn-RBS-cfp-npt). Both the developed recombinant strains were capable of successfully detecting mono- and polyaromatic hydrocarbons in the range of 0.1–100 μM. The sensing capacity of recombinant strains was successfully validated with actual wastewater samples against available physico-chemical analytical techniques. Till date, cloning of hbp cassette into pAmCherry vector is not achieved, however study is under progress. The developed strains were successfully immobilized in agarose and sodium alginate matrices. Survival rate and expression of strains were also monitored under immobilized conditions. Stability of immobilized biosensing strains was found to be 37 days and 18 days in normal saline and industrial wastewater, respectively. The lower expression level of reporter genes was observed in immobilized conditions as compared to suspended cells of strains. As the survival rate of environmental strains is expected to be high as compared to recombinant strains, hence survival rate of a wastewater isolate Pseudomonas citronellolis was monitored under immobilized condition. Immobilized Pseudomonas citronellolis was stable up to 66 days and 18 days under sodium alginate and agarose matrices, respectively, when stored in industrial wastewater. The cloned vector pPROBE-Tbut-RBS-gfp-npt and pPROBE-phn-RBS-cfp-npt from strains was transformed into wastewater isolate Pseudomonas citronellolis by electroporation method. After transformation, the expression level of Pseudomonas citronellolis strain and E. coli DH5α were compared in suspended cells. The lower expression values were observed in Pseudomonas citronellolis strain as compared to E. coli DH5α. Thus, E. coli DH5α strains were suggested to be more suitable for sensing devise construction and future applications. Imaging of mono- and poly-aromatic hydrocarbon induced cells was also observed under inverted fluorescence microscope. The cells of E. coli DH5α 2296-gfp (containing pPROBETbut-RBS-gfp-npt) and E. coli DH5α 2301-cfp (containing pPROBE-phn-RBS-cfp-npt) were iv showing a clear difference in signal output in presence of mono- and poly-aromatic hydrocarbon compounds, respectively. Development of such recombinant microbial strains indicates a bright future for online contaminant detection, wastewater treatment quality monitoring and assisting in protection of aquatic flora and fauna. |
| Description: | ST000073 |
| URI: | http://10.1.7.192:80/jspui/handle/123456789/10471 |
| Appears in Collections: | Theses, IS |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| ST000073.pdf | ST000073 | 11.57 MB | Adobe PDF |  View/Open |
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