Spatially Resolved Molecular Analysis of Host Response to Medical Device Implantation Using the 3D OrbiSIMS Highlights a Critical Role for Lipids.

A key goal for implanted medical devices is that they do not elicit a detrimental immune response. Macrophages play critical roles in the modulation of the host immune response and are the cells responsible for persistent inflammatory reactions to implanted biomaterials. Two novel immune-instructive polymers that stimulate pro- or anti-inflammatory responses from macrophages in vitro are investigated. These also modulate in vivo foreign body responses (FBR) when implanted subcutaneously in mice. Immunofluorescent staining of tissue abutting the polymer reveals responses consistent with pro- or anti-inflammatory responses previously described for these polymers. Three Dimensional OrbiTrap Secondary Ion Mass Spectrometry (3D OrbiSIMS) analysis to spatially characterize the metabolites in the tissue surrounding the implant, providing molecular histology insight into the metabolite response in the host is applied. For the pro-inflammatory polymer, monoacylglycerols (MG) and diacylglycerols (DG) are observed at increased intensity, while for the anti-inflammatory coating, the number of phospholipid species detected decreased, and pyridine and pyrimidine levels are elevated. Small molecule signatures from single-cell studies of M2 macrophages in vitro correlate with the in vivo observations, suggesting potential for prediction. Metabolite characterization by the 3D OrbiSIMS is shown to provide insight into the mechanism of bio-instructive materials as medical devices and to inform on the FBR to biomaterials.

Toward Comprehensive Analysis of the 3D Chemistry of Pseudomonas aeruginosa Biofilms.

Bacterial biofilms are structured communities consisting of cells enmeshed in a self-generated extracellular matrix usually attached to a surface. They contain diverse classes of molecules including polysaccharides, lipids, proteins, nucleic acids, and diverse small organic molecules (primary and secondary metabolites) which are organized to optimize survival and facilitate dispersal to new colonization sites. In situ characterization of the chemical composition and structure of bacterial biofilms is necessary to fully understand their development on surfaces relevant to biofouling in health, industry, and the environment. Biofilm development has been extensively studied using confocal microscopy using targeted fluorescent labels providing important insights into the architecture of biofilms. Recently, cryopreparation has been used to undertake targeted in situ chemical characterization using Orbitrap secondary ion mass spectrometry (OrbiSIMS), providing a label-free method for imaging biofilms in their native state. Although the high mass resolution of OrbiSIMS enables more confident peak assignments, it is still very challenging to assign most of the peaks in the spectra due to complexity of SIMS spectra and lack of automatic peak assignment methods. Here, we analyze the same OrbiSIMS depth profile data generated from the frozen-hydrated biofilm, but employ a new untargeted chemical filtering process utilizing mass spectral databases to assign secondary ions to decipher the large number of fragments present in the SIMS spectra. To move towards comprehensive analysis of different chemistries in the sample, we apply a molecular formula prediction approach which putatively assigns 81% of peaks in the 3D OrbiSIMS depth profile analysis. This enables us to catalog over 1000 lipids and their fragments, 3500 protein fragments, 71 quorum sensing-related molecules (2-alkyl-4-quinolones and N-acylhomoserine lactones), 150 polysaccharide fragments, and glycolipids simultaneously from one data set and map these separated molecular classes spatially through a Pseudomonas aeruginosa biofilm. Assignment of different chemistries in this sample facilitates identification of differences between biofilms grown on biofilm-promoting and biofilm-resistant polymers.

Molecular Formula Prediction for Chemical Filtering of 3D OrbiSIMS Datasets.

Modern mass spectrometry techniques produce a wealth of spectral data, and although this is an advantage in terms of the richness of the information available, the volume and complexity of data can prevent a thorough interpretation to reach useful conclusions. Application of molecular formula prediction (MFP) to produce annotated lists of ions that have been filtered by their elemental composition and considering structural double bond equivalence are widely used on high resolving power mass spectrometry datasets. However, this has not been applied to secondary ion mass spectrometry data. Here, we apply this data interpretation approach to 3D OrbiSIMS datasets, testing it for a series of increasingly complex samples. In an organic on inorganic sample, we successfully annotated the organic contaminant overlayer separately from the substrate. In a more challenging purely organic human serum sample we filtered out both proteins and lipids based on elemental compositions, 226 different lipids were identified and validated using existing databases, and we assigned amino acid sequences of abundant serum proteins including albumin, fibronectin, and transferrin. Finally, we tested the approach on depth profile data from layered carbonaceous engine deposits and annotated previously unidentified lubricating oil species. Application of an unsupervised machine learning method on filtered ions after performing MFP from this sample uniquely separated depth profiles of species, which were not observed when performing the method on the entire dataset. Overall, the chemical filtering approach using MFP has great potential in enabling full interpretation of complex 3D OrbiSIMS datasets from a plethora of material types.

Direct Immobilization of Engineered Nanobodies on Gold Sensors.

Single-domain antibodies, known as nanobodies, have great potential as biorecognition elements for sensors because of their small size, affinity, specificity, and robustness. However, facile and efficient methods of nanobody immobilization are sought that retain their maximum functionality. Herein, we describe the direct immobilization of nanobodies on gold sensors by exploiting a modified cysteine strategically positioned at the C-terminal end of the nanobody. The experimental data based on secondary ion mass spectrometry, circular dichroism, and surface plasmon resonance, taken together with a detailed computational work (molecular dynamics simulations), support the formation of stable and well-oriented nanobody monolayers. Furthermore, the nanobody structure and activity is preserved, wherein the nanobody is immobilized at a high density (approximately 1 nanobody per 13 nm2). The strategy for the spontaneous nanobody self-assembly is simple and effective and possesses exceptional potential to be used in numerous sensing platforms, ranging from clinical diagnosis to environmental monitoring.

Protein identification by 3D OrbiSIMS to facilitate in situ imaging and depth profiling.

Label-free protein characterization at surfaces is commonly achieved using digestion and/or matrix application prior to mass spectrometry. We report the assignment of undigested proteins at surfaces in situ using secondary ion mass spectrometry (SIMS). Ballistic fragmentation of proteins induced by a gas cluster ion beam (GCIB) leads to peptide cleavage producing fragments for subsequent OrbitrapTM analysis. In this work we annotate 16 example proteins (up to 272 kDa) by de novo peptide sequencing and illustrate the advantages of this approach by characterizing a protein monolayer biochip and the depth distribution of proteins in human skin.

Reversible, High-Affinity Surface Capturing of Proteins Directed by Supramolecular Assembly.

The ability to design surfaces with reversible, high-affinity protein binding sites represents a significant step forward in the advancement of analytical methods for diverse biochemical and biomedical applications. Herein, we report a dynamic supramolecular strategy to directly assemble proteins on surfaces based on multivalent host-guest interactions. The host-guest interactions are achieved by one-step nanofabrication of a well-oriented ß-cyclodextrin host-derived self-assembled monolayer on gold (ß-CD-SAM) that forms specific inclusion complexes with hydrophobic amino acids located on the surface of the protein. Cytochrome c, insulin, α-chymotrypsin, and RNase A are used as model guest proteins. Surface plasmon resonance and static time-of-flight secondary ion mass spectrometry studies demonstrate that all four proteins interact with the ß-CD-SAM in a specific manner via the hydrophobic amino acids on the surface of the protein. The ß-CD-SAMs bind the proteins with high nanomolar to single-digit micromolar dissociation constants ( KD). Importantly, while the proteins can be captured with high affinity, their release from the surface can be achieved under very mild conditions. Our results expose the great advantages of using a supramolecular approach for controlling protein immobilization, in which the strategy described herein provides unprecedented opportunities to create advanced bioanalytic and biosensor technologies.

Semiempirical Rules To Determine Drug Sensitivity and Ionization Efficiency in Secondary Ion Mass Spectrometry Using a Model Tissue Sample.

There is an increasing need in the pharmaceutical industry to reduce drug failure at late stage and thus reduce the cost of developing a new medicine. Since most drug targets are intracellular, this requires a better understanding of the drug disposition within a cell. Secondary ion mass spectrometry has been identified as a potentially important technique to do this, as it is label-free and allows imaging in 3D with subcellular resolution and recent studies have shown promise for amiodarone. An important analytical parameter is sensitivity, and we measure this in a bovine liver homogenate reference sample for 20 drugs representing important class types relevant to the pharmaceutical industry. We also measure the sensitivity for pure drug and show, for the first time, that the secondary ion mass spectrometry (SIMS) positive ionization efficiency for small molecules is a simple power-law relationship to the log P value. This discovery will be important for advancing the understanding of the SIMS ionization process in small molecules that has, until now, been elusive. This simple relationship is found to hold true for drug doped in the bovine liver homogenate reference sample, except for fluticasone, nicardipine, and sorafenib which suffer from severe matrix suppression. This relationship provides a simple semiempirical method to determine drug sensitivity for positive secondary ions. Furthermore, we show, on chosen models, how the use of different solvents during sample preparation can affect the ionization of analytes.