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Title: Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags

Abstract

© 2019 Elsevier Ltd Lanthanide binding tags (LBTs) have been engineered onto the cell surface of E. coli to enhance biosorption and recovery of rare earth elements (REEs). The protonation behavior of the bacterial surfaces before and after LBT-display was compared by modeling acid-base titration data. A multiple discrete site, constant capacitance surface complexation model was constructed to examine rare earth (Tb) binding to cell surface functional groups, comparing wild type and LBT-engineered surfaces. Our acid-base titrations show similar pKa values between the two strains, suggesting induction of LBTs does not significantly alter cell surface protonation behavior. Tb sorption onto the wild type cell surface can be captured by a one-site carboxyl model. The LBT strain exhibited a higher metal loading that can be explained by the increase of sorption sites in the form of lanthanide binding tags. Furthermore, carboxyl site concentrations between wild type and LBT-induced cells were statistically indistinguishable. We thus attribute the engineered strains’ increase in Tb adsorption capacity and affinity to the addition of lanthanide binding tags to the cell surface. The Tb stability constant with the LBT site is two orders of magnitude higher than that with the carboxyl functional group. As a result, atmore » low metal loading <10 μM, the Tb binding to the cell surface of the LBT-strain is controlled by the presence of high-affinity, but lower capacity, LBT sites. At higher metal loadings >10 μM, a more abundant but low affinity functional group becomes the main source of adsorption that results in an overall higher sorption capacity. This work demonstrates how surface complexation modeling can be implemented for bacterial surfaces engineered with a known protein tag to optimize REE recovery from fluids with variable pH and metal loadings.« less

Authors:
 [1];  [2];  [2];  [2]; ORCiD logo [1]
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  1. Univ. of California, Berkeley, CA (United States)
  2. Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Publication Date:
Research Org.:
Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States); Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC)
OSTI Identifier:
1630399
Alternate Identifier(s):
OSTI ID: 1580311; OSTI ID: 1619150
Report Number(s):
LLNL-JRNL-774812
Journal ID: ISSN 0883-2927; 967119
Grant/Contract Number:  
AC52-07NA27344; AC02-05CH11231; 1752814
Resource Type:
Accepted Manuscript
Journal Name:
Applied Geochemistry
Additional Journal Information:
Journal Volume: 112; Journal Issue: C; Journal ID: ISSN 0883-2927
Publisher:
Elsevier
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; surface complexation modeling; rare earth elements; REE; biosorption; bioadsorption; surface complexation; lanthanide binding tag

Citation Formats

Chang, Elliot, Brewer, Aaron W., Park, Dan M., Jiao, Yongqin, and Lammers, Laura N. Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags. United States: N. p., 2019. Web. doi:10.1016/j.apgeochem.2019.104478.
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Chang, Elliot, Brewer, Aaron W., Park, Dan M., Jiao, Yongqin, & Lammers, Laura N. Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags. United States. https://doi.org/10.1016/j.apgeochem.2019.104478
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Chang, Elliot, Brewer, Aaron W., Park, Dan M., Jiao, Yongqin, and Lammers, Laura N. Thu . "Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags". United States. https://doi.org/10.1016/j.apgeochem.2019.104478. https://www.osti.gov/servlets/purl/1630399.
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@article{osti_1630399,
title = {Surface complexation model of rare earth element adsorption onto bacterial surfaces with lanthanide binding tags},
author = {Chang, Elliot and Brewer, Aaron W. and Park, Dan M. and Jiao, Yongqin and Lammers, Laura N.},
abstractNote = {© 2019 Elsevier Ltd Lanthanide binding tags (LBTs) have been engineered onto the cell surface of E. coli to enhance biosorption and recovery of rare earth elements (REEs). The protonation behavior of the bacterial surfaces before and after LBT-display was compared by modeling acid-base titration data. A multiple discrete site, constant capacitance surface complexation model was constructed to examine rare earth (Tb) binding to cell surface functional groups, comparing wild type and LBT-engineered surfaces. Our acid-base titrations show similar pKa values between the two strains, suggesting induction of LBTs does not significantly alter cell surface protonation behavior. Tb sorption onto the wild type cell surface can be captured by a one-site carboxyl model. The LBT strain exhibited a higher metal loading that can be explained by the increase of sorption sites in the form of lanthanide binding tags. Furthermore, carboxyl site concentrations between wild type and LBT-induced cells were statistically indistinguishable. We thus attribute the engineered strains’ increase in Tb adsorption capacity and affinity to the addition of lanthanide binding tags to the cell surface. The Tb stability constant with the LBT site is two orders of magnitude higher than that with the carboxyl functional group. As a result, at low metal loading <10 μM, the Tb binding to the cell surface of the LBT-strain is controlled by the presence of high-affinity, but lower capacity, LBT sites. At higher metal loadings >10 μM, a more abundant but low affinity functional group becomes the main source of adsorption that results in an overall higher sorption capacity. This work demonstrates how surface complexation modeling can be implemented for bacterial surfaces engineered with a known protein tag to optimize REE recovery from fluids with variable pH and metal loadings.},
doi = {10.1016/j.apgeochem.2019.104478},
journal = {Applied Geochemistry},
number = C,
volume = 112,
place = {United States},
year = {Thu Nov 28 00:00:00 EST 2019},
month = {Thu Nov 28 00:00:00 EST 2019}
}
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https://doi.org/10.1016/j.apgeochem.2019.104478
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