Multi-dimensional TOF-SIMS analysis for effective profiling of disease-related ions from the tissue surface

Screening of important metabolites and KRAS genotypes in colon cancer using secondary ion mass spectrometry

Time-of-flight secondary ion mass spectrometry (TOF-SIMS) is an imaging-based analytical technique that can characterize the surfaces of biomaterials. We used TOF-SIMS to identify important metabolites and oncogenic KRAS mutation expressed in human colorectal cancer (CRC). We obtained 540 TOF-SIMS spectra from 180 tissue samples by scanning cryo-sections and selected discriminatory molecules using the support vector machine (SVM) algorithm. Each TOF-SIMS spectrum contained nearly 860,000 ion profiles and hundreds of spectra were analyzed; therefore, reducing the dimensionality of the original data was necessary. We performed principal component analysis after preprocessing the spectral data, and the principal components (20) of each spectrum were used as the inputs of the SVM algorithm using the R package. The performance of the algorithm was evaluated using the receiver operating characteristic (ROC) area under the curve (AUC) (0.9297). Spectral peaks (m/z) corresponding to discriminatory molecules used to classify normal and tumor samples were selected according to p-value and were assigned to arginine, α-tocopherol, and fragments of glycerophosphocholine. Pathway analysis using these discriminatory molecules showed that they were involved in gastrointestinal disease and organismal abnormalities. In addition, spectra were classified according to the expression of KRAS somatic mutation, with 0.9921 AUC. Taken together, TOF-SIMS efficiently and simultaneously screened metabolite biomarkers and performed KRAS genotyping. In addition, a machine learning algorithm was provided as a diagnostic tool applied to spectral data acquired from clinical samples prepared as frozen tissue slides, which are commonly used in a variety of biomedical tests.

Biological tissue sample preparation for time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging

Time-of-flight secondary ion mass spectrometry (ToF-SIMS) imaging is an analytical technique rapidly expanding in use in biological studies. This technique is based on high spatial resolution (50-100 nm), high surface sensitivity (1-2 nm top-layer), and statistical analytic power. In mass spectrometry imaging (MSI), sample preparation is a crucial step to maintaining the natural state of the biomolecules and providing accurate spatial information. However, a number of problems associated with temperature changes in tissue samples such as loss of original distribution due to undesired molecular migration during the sample preparation or reduced ionization efficiency make it difficult to accurately perform MSI. Although frozen hydrate analysis is the ideal sample preparation method to eliminate the effects of temperature, this approach is hindered by mechanical limitations. Alternatively, an adhesive-tape-supported mounting and freeze-drying preparation has been proposed. This paper provides a concise review of the sample preparation procedures, a review of current issues, and proposes efficacious solutions for ToF-SIMS imaging in biological research.

The Chemistry of Plant-Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance

Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant-plant and plant-microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground 'signalomics', and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial - and priming events.

TOF-SIMS analysis of an isocitrate dehydrogenase 1 mutation-associated oncometabolite in cancer cells

The development of analytical tools for accurate and sensitive detection of intracellular metabolites associated with mutated metabolic enzymes is important in cancer diagnosis and staging. The gene encoding the metabolic enzyme isocitrate dehydrogenase 1 (IDH1) is mutated in various cancers, and mutant IDH1 could represent a good biomarker and potent target for cancer therapy. Owing to a mutation in an important arginine residue in the catalytic pocket, mutant IDH1 catalyzes the production of 2-hydroxyglutarate (2-HG) instead of its wild type product α-ketoglutarate (α-KG), which is involved in multiple cellular pathways involving the hydroxylation of proteins, ribonucleic acid, and deoxyribose nucleic acid (DNA). Since 2-HG is an α-KG antagonist, inhibiting normal α-KG-dependent metabolism, high intracellular levels of 2-HG result in abnormal histone and DNA methylation. Therefore, accurate and sensitive analytical tools for the direct detection of 2-HG in cancer cells expressing mutant IDH1 would benefit this field, as it would minimize the need both for complicated experimental procedures and for large amounts of biological samples. Here, the authors describe a useful analytical method for the direct detection of 2-HG in lysates from a mutant IDH1-expressing cell line by time-of-flight secondary ion mass spectrometry (TOF-SIMS) analysis, a powerful surface analysis tool. In addition, the authors verified the efficacy of the specific mutant IDH1 inhibitor AGI-5198 by tracking the intracellular 2-HG concentration, which decreased in a dose-dependent manner. Our results demonstrate the large potential of TOF-SIMS as an analytical tool for the simple, direct detection of oncometabolites during cancer diagnosis, and for verifying the efficiency of the targeted cancer drugs.

Imaging mass spectrometry for metabolites: technical progress, multimodal imaging, and biological interactions

Imaging mass spectrometry (IMS) allows the study of the spatial distribution of small molecules in biological samples. IMS is able to identify and quantify chemicals in situ from whole tissue sections to single cells. Both vacuum mass spectrometry (MS) and ambient MS systems have advanced considerably over the last decade; however, some limitations are still hard to surmount. Sample pretreatment, matrix or solvent choices, and instrument improvement are the key factors that determine the successful application of IMS to different samples and analytes. IMS with innovative MS analyzers, powerful MS spectrum databases, and analysis tools can efficiently dereplicate, identify, and quantify natural products. Moreover, multimodal imaging systems and multiple MS-based systems provide additional structural, chemical, and morphological information and are applied as complementary tools to explore new fields. IMS has been applied to reveal interactions between living organisms at molecular level. Recently, IMS has helped solve many previously unidentifiable relations between bacteria, fungi, plants, animals, and insects. Other significant interactions on the chemical level can also be resolved using expanding IMS techniques. WIREs Syst Biol Med 2017, 9:e1387. doi: 10.1002/wsbm.1387 For further resources related to this article, please visit the WIREs website.

An unsupervised MVA method to compare specific regions in human breast tumor tissue samples using ToF-SIMS

Imaging time-of-flight secondary ion mass spectrometry (ToF-SIMS) and principal component analysis (PCA) were used to investigate two sets of pre- and post-chemotherapy human breast tumor tissue sections to characterize lipids associated with tumor metabolic flexibility and response to treatment. The micron spatial resolution imaging capability of ToF-SIMS provides a powerful approach to attain spatially-resolved molecular and cellular data from cancerous tissues not available with conventional imaging techniques. Three ca. 1 mm(2) areas per tissue section were analyzed by stitching together 200 μm × 200 μm raster area scans. A method to isolate and analyze specific tissue regions of interest by utilizing PCA of ToF-SIMS images is presented, which allowed separation of cellularized areas from stromal areas. These PCA-generated regions of interest were then used as masks to reconstruct representative spectra from specifically stromal or cellular regions. The advantage of this unsupervised selection method is a reduction in scatter in the spectral PCA results when compared to analyzing all tissue areas or analyzing areas highlighted by a pathologist. Utilizing this method, stromal and cellular regions of breast tissue biopsies taken pre- versus post-chemotherapy demonstrate chemical separation using negatively-charged ion species. In this sample set, the cellular regions were predominantly all cancer cells. Fatty acids (i.e. palmitic, oleic, and stearic), monoacylglycerols, diacylglycerols and vitamin E profiles were distinctively different between the pre- and post-therapy tissues. These results validate a new unsupervised method to isolate and interpret biochemically distinct regions in cancer tissues using imaging ToF-SIMS data. In addition, the method developed here can provide a framework to compare a variety of tissue samples using imaging ToF-SIMS, especially where there is section-to-section variability that makes it difficult to use a serial hematoxylin and eosin (H&E) stained section to direct the SIMS analysis.