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Quantifying platinum binding on protein-functionalized magnetic microparticles using single particle-ICP-TOF-MS

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6 Scopus citations

Abstract

This work describes an analytical procedure, single particle-inductively coupled plasma-time-of-flight-mass spectrometry (SP-ICP-TOF-MS), that was developed to determine the platinum binding efficiency of protein-coated magnetic microparticles. SP-ICP-TOF-MS is advantageous due to its ability to quasi-simultaneously detect all nuclides (7Li-242Pu), allowing for both platinum and iron (composition of magnetic microparticles) to be measured concurrently. This method subsequently allows for the differentiation between bound and unbound platinum. The 1 μm magnetic microparticles were fully characterized for their iron concentration, particle concentration, and trace element composition by bulk digestion-ICP-MS and SP-ICP-TOF-MS. The results of both approaches agreed with the certificate values. Using the single particle methodology the platinum loading was quantified to be to 0.18 ± 0.02 fg per particle and 0.32 ± 0.02 fg per particle, for the streptavidin-coated and azurin-coated microparticles, respectively. Both streptavidin-coated and the azurin-coated microparticles had a particle-platinum association of >65%. Platinum bound samples were also analyzed via bulk digestion-based ICP-MS. The bulk ICP-MS results overestimated platinum loading due to free platinum in the samples. This highlights the importance of single particle analysis for a closer inspection of platinum binding performance. The SP-ICP-TOF-MS approach offers advantages over typical bulk digestion methods by eliminating laborious sample preparation, enabling differentiation between bound/unbound platinum in a solution, and quantification of platinum on a particle-by-particle basis. The procedure presented here enables quantification of metal content per particle, which could be broadly implemented for other single particle applications.

Original languageEnglish
Pages (from-to)3192-3201
Number of pages10
JournalAnalytical Methods
Volume16
Issue number20
DOIs
StatePublished - Apr 15 2024

Funding

This work was supported by the Laboratory Directed Research and Development Program of Oak Ridge National Laboratory, managed by UT-Battelle, LLC, for the U.S. Department of Energy under contract DE-AC-05-00OR22725. The authors would like to acknowledge Mark Boris for the assistance with optical images presented within this manuscript and Jacquelyn DeMink for assistance with graphics.

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