DC Field | Value | Language |
---|---|---|
dc.contributor.author | Hyewon Lee | - |
dc.contributor.author | Ji In Baek | - |
dc.contributor.author | Su Jin Kim | - |
dc.contributor.author | Kil Koang Kwon | - |
dc.contributor.author | Eugene Rha | - |
dc.contributor.author | S J Yeom | - |
dc.contributor.author | Haseong Kim | - |
dc.contributor.author | Dae-Hee Lee | - |
dc.contributor.author | D M Kim | - |
dc.contributor.author | Seung Goo Lee | - |
dc.date.accessioned | 2020-09-24T03:00:07Z | - |
dc.date.available | 2020-09-24T03:00:07Z | - |
dc.date.issued | 2020 | - |
dc.identifier.issn | 2296-4185 | - |
dc.identifier.uri | https://oak.kribb.re.kr/handle/201005/22612 | - |
dc.description.abstract | Methanotrophs with soluble methane monooxygenase (sMMO) show high potential for various ecological and biotechnological applications. Here, we developed a high throughput method to identify sMMO-producing microbes by integrating droplet microfluidics and a genetic circuit-based biosensor system. sMMO-producers and sensor cells were encapsulated in monodispersed droplets with benzene as the substrate and incubated for 5 h. The sensor cells were analyzed as the reporter for phenol-sensitive transcription activation of fluorescence. Various combinations of methanotrophs and biosensor cells were investigated to optimize the performance of our droplet-integrated transcriptional factor biosensor system. As a result, the conditions to ensure sMMO activity to convert the starting material, benzene, into phenol, were determined. The biosensor signals were sensitive and quantitative under optimal conditions, showing that phenol is metabolically stable within both cell species and accumulates in picoliter-sized droplets, and the biosensor cells are healthy enough to respond quantitatively to the phenol produced. These results show that our system would be useful for rapid evaluation of phenotypes of methanotrophs showing sMMO activity, while minimizing the necessity of time-consuming cultivation and enzyme preparation, which are required for conventional analysis of sMMO activity. | - |
dc.publisher | Frontiers Media Sa | - |
dc.title | Sensitive and rapid phenotyping of microbes with soluble methane monooxygenase using a droplet-based assay | - |
dc.title.alternative | Sensitive and rapid phenotyping of microbes with soluble methane monooxygenase using a droplet-based assay | - |
dc.type | Article | - |
dc.citation.title | Frontiers in Bioengineering and Biotechnology | - |
dc.citation.number | 0 | - |
dc.citation.endPage | 358 | - |
dc.citation.startPage | 358 | - |
dc.citation.volume | 8 | - |
dc.contributor.affiliatedAuthor | Hyewon Lee | - |
dc.contributor.affiliatedAuthor | Ji In Baek | - |
dc.contributor.affiliatedAuthor | Su Jin Kim | - |
dc.contributor.affiliatedAuthor | Kil Koang Kwon | - |
dc.contributor.affiliatedAuthor | Eugene Rha | - |
dc.contributor.affiliatedAuthor | Haseong Kim | - |
dc.contributor.affiliatedAuthor | Dae-Hee Lee | - |
dc.contributor.affiliatedAuthor | Seung Goo Lee | - |
dc.contributor.alternativeName | 이혜원 | - |
dc.contributor.alternativeName | 백지인 | - |
dc.contributor.alternativeName | 김수진 | - |
dc.contributor.alternativeName | 권길광 | - |
dc.contributor.alternativeName | 나유진 | - |
dc.contributor.alternativeName | 염수진 | - |
dc.contributor.alternativeName | 김하성 | - |
dc.contributor.alternativeName | 이대희 | - |
dc.contributor.alternativeName | 김동명 | - |
dc.contributor.alternativeName | 이승구 | - |
dc.identifier.bibliographicCitation | Frontiers in Bioengineering and Biotechnology, vol. 8, pp. 358-358 | - |
dc.identifier.doi | 10.3389/fbioe.2020.00358 | - |
dc.subject.keyword | cellcell communication | - |
dc.subject.keyword | large-scale phenotyping | - |
dc.subject.keyword | microfluidics | - |
dc.subject.keyword | synthetic biology | - |
dc.subject.keyword | transcriptional factor-based biosensors | - |
dc.subject.local | cellcell communication | - |
dc.subject.local | large-scale phenotyping | - |
dc.subject.local | microfluidics | - |
dc.subject.local | Microfluidics | - |
dc.subject.local | synthetic biology | - |
dc.subject.local | Synthetic Biology | - |
dc.subject.local | Synthetic biology | - |
dc.subject.local | transcriptional factor-based biosensors | - |
dc.description.journalClass | Y | - |
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