Journal
JOURNAL OF MICROSCOPY
Volume 261, Issue 2, Pages 157-166Publisher
WILEY
DOI: 10.1111/jmi.12215
Keywords
Artefacts; biological sample preparation; electron microscopy; resin embedding; silver nanomaterials; staining; sulfidation; toxicity
Categories
Funding
- NIEHS [U19ES019536]
- US EPA/NERC (EPA STAR) [RD83469301]
- NERC
- ERC [257182]
- Elsie Widdowson Fellowship from Imperial College London
- EPSRC [EP/K039946/1] Funding Source: UKRI
- MRC [G0700926] Funding Source: UKRI
- Engineering and Physical Sciences Research Council [EP/K039946/1] Funding Source: researchfish
- Medical Research Council [G0700926] Funding Source: researchfish
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Electron microscopy has been applied widely to study the interaction of nanomaterials with proteins, cells and tissues at nanometre scale. Biological material is most commonly embedded in thermoset resins to make it compatible with the high vacuum in the electron microscope. Room temperature sample preparation protocols developed over decades provide contrast by staining cell organelles, and aim to preserve the native cell structure. However, the effect of these complex protocols on the nanomaterials in the system is seldom considered. Any artefacts generated during sample preparationmay ultimately interfere with the accurate prediction of the stability and reactivity of the nanomaterials. As a case study, we review steps in the room temperature preparation of cells exposed to silver nanomaterials (AgNMs) for transmission electron microscopy imaging and analysis. In particular, embedding and staining protocols, which can alter the physicochemical properties of AgNMs and introduce artefacts thereby leading to a misinterpretation of silver bioreactivity, are scrutinized. Recommendations are given for the application of cryogenic sample preparation protocols, which simultaneously fix both particles and diffusible ions. By being aware of the advantages and limitations of different sample preparation methods, compromises or selection of different correlative techniques can be made to draw more accurate conclusions about the data.
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