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Articles

Metabolomic method to detect a metabolite corona on amino-functionalized polystyrene nanoparticles

, , , ORCID Icon & ORCID Icon
Pages 783-794 | Received 05 Oct 2018, Accepted 23 Jan 2019, Published online: 16 May 2019
 

Abstract

Protein coronas on nanoparticles (NPs) affect their physicochemical properties, cellular uptake, and toxicity, and have been described extensively. To date, studies of the occurrence of small molecule (metabolite) coronas are limited. We sought to determine whether a metabolite corona forms on NPs, using high-sensitivity metabolomics combined with a model system for freshwater ecotoxicology (Daphnia magna feeding on Chlorella vulgaris). Using amino-functionalized polystyrene NPs (NH2-pNPs), we showed the impact of this material on Daphnia feeding to provide a rationale for the detailed molecular investigations. We then employed a targeted LC-MS/MS approach for sodium dodecyl sulfate (SDS) as an analog to signaling molecules known to occur in our freshwater model system and optimized a corona extraction method for this representative metabolite. Next, we performed an untargeted discovery-based metabolomics study – using high-sensitivity nanoelectrospray direct infusion mass spectrometry (DIMS) – to enable an unbiased assessment of the metabolite corona of NH2-pNPs in the freshwater model system. Our results demonstrate that SDS was successfully recovered from NH2-pNPs, confirming that the extraction protocol was fit-for-purpose. Untargeted DIMS metabolomics reproducibly detected 100 s of small molecule peaks extracted from NH2-pNPs exposed to conditioned media from the D. magna–C. vulgaris model system. Attempts to annotate these extracted metabolites, including by using van Krevelen and Kendrick Mass Defect plots, indicate a diverse range of metabolites that were not clustered into any particular class. Overall we demonstrate the existence of an ecologically relevant metabolite corona on the surface of NPs through application of a high-sensitivity, untargeted mass spectrometry metabolomics workflow.

Acknowledgments

The authors acknowledge the use of the University of Birmingham’s Daphnia research facility.

Disclosure statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest. All authors listed, have made a substantial, direct contribution to the work, designed and approved it for publication and declare there is no potential conflict of interest.

Additional information

Funding

The authors would like to thank the EU FP7 project FutureNanoNeeds - Framework to respond to regulatory needs of future nanomaterials and markets (Grant Agreement No. 604602). This work was supported in part through a NERC PhD studentship (NE/L002493/1).

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