Approaching cellular resolution and reliable identification in mass spectrometry imaging of tryptic peptides.

On-tissue digestion has become the preferred method to identify proteins in mass spectrometry (MS) imaging. In this study, we report advances in data acquisition and protein identification for MS imaging after on-tissue digestion. Tryptic peptides in a coronal mouse brain section were measured at 50 µm pixel size and revealed detailed histological structures, e.g., the ependyma (consisting of one to two cell layers), which was confirmed by H&E staining. This demonstrates that MS imaging of tryptic peptides at or close to cellular resolution is within reach. We also describe a detailed identification workflow which resulted in the identification of 99 proteins (with 435 corresponding peptides), based on comparison with LC-MS/MS data and in silico digest. These results were obtained with stringent parameters, including high mass accuracy in imaging mode (RSME < 3 ppm) and at least two unique peptides per protein showing consistent spatial distribution. We identified almost 50% of proteins with at least four corresponding peptides. As there is no agreed approach for identification of proteins after on-tissue digestion yet, we discuss our workflow in detail and make the corresponding mass spectral data available as "open data" via ProteomeXchange (identifier PXD003172). With this, we would like to contribute to a more effective discussion and the development of new approaches for tryptic peptide identification in MS imaging. From an experimental point of view, we demonstrate the improvement due to the combination of high spatial resolution and high mass resolution/mass accuracy on a measurement at 25 µm pixel size in mouse cerebellum tissue. A whole body section of a mouse pub imaged at 50 µm pixel size (40 GB, 230,000 spectra) demonstrates the stability of our protocol. For this data set, we developed a workflow that is based on conversion to the common data format imzML and sequential application of freely available software tools. In combination, the presented results for spatial resolution, protein identification, and data processing constitute significant improvements for the field of on-tissue digestion. Graphical abstract MS imaging of coronal mouse brain cerebellum with a pixel size of 25 µm: A Optical image, B myelin staining, C H&E staining, and D MS image overlay (RGB) of tryptic peptides m/z = 726.4045 ± 0.005, HGFLPR + H+ (red), m/z = 536.3173 ± 0.005, AKPAK + Na+ (green), and m/z = 994.5436 ± 0.005, WRQLIEK + Na+ (blue).

Software tools of the Computis European project to process mass spectrometry images.

Among the needs usually expressed by teams using mass spectrometry imaging, one that often arises is that for user-friendly software able to manage huge data volumes quickly and to provide efficient assistance for the interpretation of data. To answer this need, the Computis European project developed several complementary software tools to process mass spectrometry imaging data. Data Cube Explorer provides a simple spatial and spectral exploration for matrix-assisted laser desorption/ionisation-time of flight (MALDI-ToF) and time of flight-secondary-ion mass spectrometry (ToF-SIMS) data. SpectViewer offers visualisation functions, assistance to the interpretation of data, classification functionalities, peak list extraction to interrogate biological database and image overlay, and it can process data issued from MALDI-ToF, ToF-SIMS and desorption electrospray ionisation (DESI) equipment. EasyReg2D is able to register two images, in American Standard Code for Information Interchange (ASCII) format, issued from different technologies. The collaboration between the teams was hampered by the multiplicity of equipment and data formats, so the project also developed a common data format (imzML) to facilitate the exchange of experimental data and their interpretation by the different software tools. The BioMap platform for visualisation and exploration of MALDI-ToF and DESI images was adapted to parse imzML files, enabling its access to all project partners and, more globally, to a larger community of users. Considering the huge advantages brought by the imzML standard format, a specific editor (vBrowser) for imzML files and converters from proprietary formats to imzML were developed to enable the use of the imzML format by a broad scientific community. This initiative paves the way toward the development of a large panel of software tools able to process mass spectrometry imaging datasets in the future.

High-resolution atmospheric pressure infrared laser desorption/ionization mass spectrometry imaging of biological tissue.

An atmospheric pressure laser desorption/ionization mass spectrometry imaging ion source has been developed that combines high spatial resolution and high mass resolution for the in situ analysis of biological tissue. The system is based on an infrared laser system working at 2.94 to 3.10 µm wavelength, employing a Nd:YAG laser-pumped optical parametrical oscillator. A Raman-shifted Nd:YAG laser system was also tested as an alternative irradiation source. A dedicated optical setup was used to focus the laser beam, coaxially with the ion optical axis and normal to the sample surface, to a spot size of 30 µm in diameter. No additional matrix was needed for laser desorption/ionization. A cooling stage was developed to reduce evaporation of physiological cell water. Ions were formed under atmospheric pressure and transferred by an extended heated capillary into the atmospheric pressure inlet of an orbital trapping mass spectrometer. Various phospholipid compounds were detected, identified, and imaged at a pixel resolution of up to 25 µm from mouse brain tissue sections. Mass accuracies of better than 2 ppm and a mass resolution of 30,000 at m/z = 400 were achieved for these measurements.

imzML--a common data format for the flexible exchange and processing of mass spectrometry imaging data.

The application of mass spectrometry imaging (MS imaging) is rapidly growing with a constantly increasing number of different instrumental systems and software tools. The data format imzML was developed to allow the flexible and efficient exchange of MS imaging data between different instruments and data analysis software. imzML data is divided in two files which are linked by a universally unique identifier (UUID). Experimental details are stored in an XML file which is based on the HUPO-PSI format mzML. Information is provided in the form of a 'controlled vocabulary' (CV) in order to unequivocally describe the parameters and to avoid redundancy in nomenclature. Mass spectral data are stored in a binary file in order to allow efficient storage. imzML is supported by a growing number of software tools. Users will be no longer limited to proprietary software, but are able to use the processing software best suited for a specific question or application. MS imaging data from different instruments can be converted to imzML and displayed with identical parameters in one software package for easier comparison. All technical details necessary to implement imzML and additional background information is available at www.imzml.org.

Protein identification by accurate mass matrix-assisted laser desorption/ionization imaging of tryptic peptides.

The spatial distribution of proteins in tissue sections can be used to identify potential markers for pathological processes. Tissue sections are often subjected to enzymatic digestion before matrix-assisted laser desorption/ionization (MALDI) imaging. This study is targeted at improving the on-tissue identification of tryptic peptides by accurate mass measurements and complementary off-line liquid chromatography coupled to electrospray ionization tandem mass spectrometry (LC/ESI-MS/MS) analysis. Two adjacent mouse brain sections were analyzed in parallel. The first section was spotted with trypsin and analyzed by MALDI imaging. Direct on-tissue MS/MS experiments of this section resulted in the identification of 14 peptides (originating from 4 proteins). The second tissue section was homogenized, fractionated by ultracentrifugation and digested with trypsin prior to LC/ESI-MS/MS analysis. The number of identified peptides was increased to 153 (corresponding to 106 proteins) by matching imaged mass peaks to peptides which were identified in these LC/ESI-MS/MS experiments. All results (including MALDI imaging data) were based on accurate mass measurements (RMS <2 ppm) and allow a confident identification of tryptic peptides. Measurements based on lower accuracy would have led to ambiguous or misleading results. MS images of identified peptides were generated with a bin width (mass range used for image generation) of Δm/z = 0.01. The application of accurate mass measurements and additional LC/MS measurements increased both the quality and the number of peptide identifications. The advantages of this approach for the analysis of biological tissue sections are demonstrated and discussed in detail. Results indicate that accurate mass measurements are needed for confident identification and specific image generation of tryptic peptides in tissue sections.

imzML: Imaging Mass Spectrometry Markup Language: A common data format for mass spectrometry imaging.

Imaging mass spectrometry is the method of scanning a sample of interest and generating an "image" of the intensity distribution of a specific analyte. The data sets consist of a large number of mass spectra which are usually acquired with identical settings. Existing data formats are not sufficient to describe an MS imaging experiment completely. The data format imzML was developed to allow the flexible and efficient exchange of MS imaging data between different instruments and data analysis software.For this purpose, the MS imaging data is divided in two separate files. The mass spectral data is stored in a binary file to ensure efficient storage. All metadata (e.g., instrumental parameters, sample details) are stored in an XML file which is based on the standard data format mzML developed by HUPO-PSI. The original mzML controlled vocabulary was extended to include specific parameters of imaging mass spectrometry (such as x/y position and spatial resolution). The two files (XML and binary) are connected by offset values in the XML file and are unambiguously linked by a universally unique identifier. The resulting datasets are comparable in size to the raw data and the separate metadata file allows flexible handling of large datasets.Several imaging MS software tools already support imzML. This allows choosing from a (growing) number of processing tools. One is no longer limited to proprietary software, but is able to use the processing software which is best suited for a specific question or application. On the other hand, measurements from different instruments can be compared within one software application using identical settings for data processing. All necessary information for evaluating and implementing imzML can be found at http://www.imzML.org .