Cardinal is an R package for statistical analysis of mass spectrometry-based imaging (MSI) experiments of biological samples such as tissues. Cardinal supports both Matrix-Assisted Laser Desorption/Ionization (MALDI) and Desorption Electrospray Ionization-based MSI workflows, and experiments with multiple tissues and complex designs. The main analytical functionalities include (1) image segmentation, which partitions a tissue into regions of homogeneous chemical composition, selects the number of segments and the subset of informative ions, and characterizes the associated uncertainty and (2) image classification, which assigns locations on the tissue to pre-defined classes, selects the subset of informative ions, and estimates the resulting classification error by (cross-) validation. The statistical methods are based on mixture modeling and regularization.Contact: o.vitek@neu.eduAvailability and implementation: The code, the documentation, and examples are available open-source at www.cardinalmsi.org under the Artistic-2.0 license. The package is available at www.bioconductor.org.

Desorption electrospray ionization mass spectrometry (DESI-MS) imaging of biological samples allows untargeted analysis and structural characterization of lipids ionized from the near-surface region of a sample under ambient conditions. DESI is a powerful and sensitive MS ionization method for 2D and 3D imaging of lipids from direct and unmodified complex biological samples. This review describes the strengths and limitations of DESI-MS for lipid characterization and imaging together with the technical workflow and a survey of applications. Included are discussions of lipid mapping and biomarker discovery as well as a perspective on the future of DESI imaging.

We report the high throughput analysis of reaction mixture arrays using methods and data handling routines that were originally developed for biological tissue imaging.

BACKGROUND:One driving motivation in the development of point-of-care (POC) diagnostics is to conveniently and immediately provide information upon which healthcare decisions can be based, while the patient is on site. Ambient ionization mass spectrometry (MS) allows direct chemical analysis of unmodified and complex biological samples. This suite of ionization techniques was introduced a decade ago and now includes a number of techniques, all seeking to minimize or eliminate sample preparation. Such approaches provide new opportunities for POC diagnostics and rapid measurements of exogenous and endogenous molecules (e.g., drugs, proteins, hormones) in small volumes of biological samples, especially when coupled with miniature mass spectrometers.CONTENT: Ambient MS-based techniques are applied in diverse fields such as forensics, pharmaceutical development, reaction monitoring, and food analysis. Clinical applications of ambient MS are at an early stage but show promise for POC diagnostics. This review provides a brief overview of various ambient ionization techniques providing background, examples of applications, and the current state of translation to clinical practice. The primary focus is on paper spray (PS) ionization, which allows quantification of analytes in complex biofluids. Current developments in the miniaturization of mass spectrometers are discussed.

Imaging mass spectrometry (MS) is a powerful technique for mapping the spatial distributions of a wide range of chemical compounds simultaneously from a tissue section. Co-localization of the distribution of individual molecular species including particular lipids and proteins, and correlation with the morphological features of a single tissue section is highly desirable for comprehensive tissue analysis and disease diagnosis. We now report on the use, in turn, of desorption electrospray ionization (DESI), matrix assisted laser desorption ionization (MALDI) and then optical microscopy to image lipid and protein distributions in a single tissue section. This is possible through the use of histologically compatible DESI solvent systems, which allow for sequential analyses of the same section by DESI then MALDI. Hematoxylin and Eosin (H&E) staining was performed on the same section after removal of the MALDI matrix. This workflow allowed chemical information to be unambiguously matched to histological features in mouse brain tissue sections. The lipid sulfatide(24:1), detected at m/z 888.8 by DESI imaging, was co-localized with the protein MBP isoform 8, detected at m/z 14117 by MALDI imaging, in regions corresponding to the corpus callosum substructure of the mouse brain, as confirmed in the H&E images. Correlation of lipid and protein distributions with histopathological features was also achieved for human brain cancer samples. Higher tumor cell density was observed in regions demonstrating higher relative abundances of oleic acid, detected by DESI imaging at m/z 281.4, and the protein calcyclin, detected by MALDI at m/z 10085, for a human glioma sample. Since correlation between molecular signatures and disease state can be achieved, we expect that this methodology will significantly enhance the value of MS imaging in molecular pathology for diagnosis.