SMART: A data reporting standard for mass spectrometry imaging By Ying Xi,Alexandria L. Sohn,Alena N. Joignant,Stephanie M. Cologna,Boone M. Prentice and David C. Muddiman

Mass spectrometry imaging (MSI) is an important analytical technique that simultaneously reports the spatial location and abundance of detected ions in biological, chemical, clinical, and pharmaceutical studies. As MSI grows in popularity, it has become evident that data reporting varies among different research groups and between techniques. The lack of consistency in data reporting inherently creates additional challenges in comparing intra- and inter-laboratory MSI data. In this tutorial, we propose a unified data reporting system, SMART, based on the common features shared between techniques. While there are limitations to any reporting system, SMART was decided upon after significant discussion to more easily understand and benchmark MSI data. SMART is not intended to be comprehensive but rather capture essential baseline information for a given MSI study; this could be within a study (e.g., effect of spot size on the measured ion signals) or between two studies (e.g., different MSI platform technologies applied to the same tissue type). This tutorial does not attempt to address the confidence with which annotations are made nor does it deny the importance of other parameters that are not included in the current SMART format. Ultimately, the goal of this tutorial is to discuss the necessity of establishing a uniform reporting system to communicate MSI data in publications and presentations in a simple format to readily interpret the parameters and baseline outcomes of the data.     

Time of acquisition and high spatial resolution mass spectrometry imaging

The field of mass spectrometry imaging (MSI) is constantly evolving to analyze a diverse array of biological systems. A common goal is the need to resolve cellular and subcellular heterogeneity with high spatial resolution. As the field continues to progress towards high spatial resolution, other parameters must be considered when developing a practical method. Here, we discuss the impacts of high spatial resolution on the time of acquisition and the associated implications they have on an MSI analysis (e.g., area of the region of interest). This work presents a brief tutorial serving to evaluate high spatial resolution MSI relative to time of acquisition and data file size.     

Profiling monoterpenol glycoconjugation in Vitis vinifera L. cv. Muscat of Alexandria using a novel putative compound database approach,high resolution mass spectrometry and collision induced dissociation fragmentation analysis

In this work we present a novel approach for the identification of plant metabolites using ultrahigh performance liquid chromatography coupled to accurate mass time-of-flight mass spectrometry. The workflow involves developing an in-house compound database consisting of exact masses of previously identified as well as putative compounds. The database is used to screen accurate mass spectrometry (MS) data to identify possible compound matches. Subsequent tandem MS data is acquired for possible matches and used for structural elucidation. The methodology is applied to profile monoterpene glycosides in Vitis vinifera cv. Muscat of Alexandria grape berries over three developmental stages. Monoterpenes are a subclass of terpenes, the largest class of plant secondary metabolites, and are found in two major forms in the plant, “bound” to one or more sugar moieties or “free” of said sugar moieties. In the free form, monoterpenes are noted for their fragrance and play important roles in plant defense and as attractants for pollinators. However, glycoconjugation renders these compounds odorless, and it is this form that the plant uses for monoterpene storage. In order to gain insight into monoterpene biochemistry and their fate in the plant an analysis of intact glycosides is essential. Eighteen monoterpene glycosides were identified including a monoterpene trisaccharide glycoside, which is tentatively identified here for this first time in any plant. Additionally, while previous studies have identified monoterpene malonylated glucosides in other grapevine tissue, we tentatively identify them for the first time in grape berries. This analytical approach can be readily applied to other plants and the workflow approach can also be used for other classes of compounds. This approach, in general, provides researchers with data to support the identification of putative compounds, which is especially useful when no standard is available.