Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags

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Lanthanide binding tags (LBTs) have been engineered onto native Escherichia coli (E. coli) bacterial surfaces to enhance extraction and recovery of rare earth elements (REEs). Three strains of E. coli were studied: (1) the native E. coli surface, (2) a mutant E. coli surface with hindered, non-binding lanthanide binding tags, and (3) an LBT E. coli surface with fully functioning lanthanide binding tags. A three discrete site, constant capacitance surface complexation modeling approach was taken in studying these strains with an ultimate goal of comparing site type affinities to the model rare earth, Terbium. Our results show a possible increase in native carboxyl functional groups when the LBTs are overexpressed on the cell surface. LBTs are confirmed to have a higher stability constant with Terbium than that of the native functional groups. Incorporation of LBTs into the E. coli cell wall poses two major benefits: (1) the presence of a high-affinity, low-capacity LBT site for selective Terbium binding at low metal loading regions, and (2) a lower-affinity carboxyl site that increases the sorption capacity of the native bacterial surface during sorption at higher metal loading regions.

Citation Formats

Lawrence Livermore National Laboratory. (2018). Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags [data set]. Retrieved from https://gdr.openei.org/submissions/1080.
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Jiao, Yongqin. Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags. United States: N.p., 01 Apr, 2018. Web. https://gdr.openei.org/submissions/1080.
Jiao, Yongqin. Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags. United States. https://gdr.openei.org/submissions/1080
Jiao, Yongqin. 2018. "Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags". United States. https://gdr.openei.org/submissions/1080.
@div{oedi_1080, title = {Surface Complexation Modeling of Terbium Biosorption onto E. Coli Bacterial Surfaces with Lanthanide Binding Tags}, author = {Jiao, Yongqin.}, abstractNote = {Lanthanide binding tags (LBTs) have been engineered onto native Escherichia coli (E. coli) bacterial surfaces to enhance extraction and recovery of rare earth elements (REEs). Three strains of E. coli were studied: (1) the native E. coli surface, (2) a mutant E. coli surface with hindered, non-binding lanthanide binding tags, and (3) an LBT E. coli surface with fully functioning lanthanide binding tags. A three discrete site, constant capacitance surface complexation modeling approach was taken in studying these strains with an ultimate goal of comparing site type affinities to the model rare earth, Terbium. Our results show a possible increase in native carboxyl functional groups when the LBTs are overexpressed on the cell surface. LBTs are confirmed to have a higher stability constant with Terbium than that of the native functional groups. Incorporation of LBTs into the E. coli cell wall poses two major benefits: (1) the presence of a high-affinity, low-capacity LBT site for selective Terbium binding at low metal loading regions, and (2) a lower-affinity carboxyl site that increases the sorption capacity of the native bacterial surface during sorption at higher metal loading regions.
}, doi = {}, url = {https://gdr.openei.org/submissions/1080}, journal = {}, number = , volume = , place = {United States}, year = {2018}, month = {04}}

Details

Data from Apr 1, 2018

Last updated Aug 9, 2018

Submitted Jul 30, 2018

Organization

Lawrence Livermore National Laboratory

Contact

Yongqin Jiao

925.422.4482

Authors

Yongqin Jiao

Lawrence Livermore National Laboratory

DOE Project Details

Project Name Extraction of Rare Earth Metals from Geothermal Fluids using Bioengineered Microbes

Project Lead Josh Mengers

Project Number LLNL FY17 AOP 25112

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