Our Research in Images: Imaging Innovation
In this series of images, scientists from the UK's National Centre of Excellence in Mass Spectrometry Imaging (NiCE-MSI) showcase the potential for MSI in a wide range of fields.
GRAPHENE GRAPHICS - By measuring carbon impurities in Cu foils before graphene growth with time-of-flight secondary ion MS (ToF-SIMS) and correlating this with graphene nucleation density (GND) after graphene growth, we can track how carbon distribution within the untreated Cu foil impacts GND. Here, the surface ToFSIMS maps of C₂ ion signal (green) from the Cu foil surface show how graphene nucleates along a preferred direction. This corresponds to areas of high carbon concentration located along rolling striations of the Cu foil (1).
PICTURING POLYMERS - SIMS can image novel devices and biological tissue in both 2D and 3D, at an elemental and molecular level. Images a-c show 3D ToF-SIMS imaging of polymer multilayer films using argon cluster sputter depth profiling (2), while d – a 3D molecular image of a novel reference material – shows how the “delta” layers – less than 2 nm thick – are sandwiched between layers of another organic molecule (3). The depth resolution of this technique is a remarkable 5 nm.
SPOT THE DIFFERENCE - MS imaging (MSI) is a powerful tool for relating molecular phenotype to tissue structure. Here, matrix assisted laser desorption ionization (MALDI) MSI was applied to “swiss roll” prepared colon samples with genetic modifications and deletions to APC, KRAS, and GPT2 genes. A machine-learning algorithm – T-distributed stochastic neighbor embedding – allowed us to visualize and interpret these highly dimensional, complex data. Here, similar colors reflect the level of similarly in the molecular composition of tissues, highlighting how different the APC/KRAS model is compared to the wild-type (WT) and other models.
Credit: Rory T. Steven, Andrew Campbell, Alex Dexter, Spencer Thomas, Kenneth N. Robinson, Alan M. Race, Rasmus Havelund, Ian S. Gilmore, Owen Sansom, Zoltan Takats, Josephine Bunch (as part of the CRUK funded Rosetta consortium.)
KEEPING IT COMPLEMENTARY - In MSI, there isn’t a one-size-fits-all instrument; instead, the complementary characteristics of several instruments are often required to build the most complete picture of tissue structure. In this image, MALDI MSI was first used to analyze the tissue from a human colon biopsy (a), before secondary ion MS (SIMS) was applied to further investigate regions of interest (b,c,d,e). This multi-modal approach ensures that there is both reliable detection of certain molecular classes and accurate analysis of the fine structure at high spatial resolution.
Credit: Rory T. Steven, Andrew Campbell, Alex Dexter, Spencer Thomas, Kenneth N. Robinson, Alan M. Race, Rasmus Havelund, Ian S. Gilmore, Owen Sansom, Zoltan Takats, Josephine Bunch (as part of the CRUK funded Rosetta consortium.)
NANOSIMS RAINBOW - This image conveys the mechanism of an antimicrobial peptide on a lipid bilayer, revealing that the peptide is concentrated at the pore boundary. This is made possible with the help of a NanoSIMS 50L instrument that has a spatial resolution of less than 50 nm. The rainbow scale ranges from blue, representing the antimicrobial peptide’s natural abundance ratio of 0.37 percent, to red, which represents an abundance of over 100 times the natural ratio (4).
- P Braeuninger-Weimer et al., “Understanding and controlling cu catalyzed graphene nucleation: the role of impurities, roughness, and oxygen scavenging”, Chem Mater, 28, 8905–8915 (2016). DOI: 10.1021/acs.chemmater.6b03241.
- J Bailey et al., “3D ToF-SIMS imaging of polymer multilayer films using argon cluster sputter depth profiling”, ACS Appl Mater Interfaces, 7, 2654–2659 (2015). DOI: 10.1021/am507663v.
- AG Shard et al., “Argon cluster ion beams for organic depth profiling: results from a VAMAS interlaboratory study”, Anal Chem, 84, 7865–7873 (2012). DOI: 10.1021/ac301567t.
- PD Rakowska et al., “Nanoscale imaging reveals laterally expanding antimicrobial pores in lipid bilayers”, Proc Natl Acad Sci USA, 110, 8918–8923 (2013). DOI: 10.1073/pnas.1222824110
