Imaging mass spectrometry: viewing the future.

Imaging mass spectrometry (IMS) technology is an effective tool that is able to assess complex molecular mixtures in cells, tissues, or other sample types with high chemical specificity, allowing concurrent analysis of a variety of molecular species in a wide mass range, from small metabolites to large macromolecules such as proteins. Simultaneous localization of molecules, detection of post-translational modifications, and relative quantitative information can be obtained in a single experiment. Images generated by MS are unique because they are derived from direct molecular measurements and do not rely on target-specific reagents such as antibodies. Thus, the ability to map spatial distributions coupled with the mass accuracy and chemical specificity for MS-based detection makes IMS an effective discovery tool. Further structural assessment of compounds, including MS/MS fragmentation analysis, can be utilized in an imaging experiment to achieve accurate molecular identifications.

Streamlining plant sample preparation: the use of high-throughput robotics to process echinacea samples for biomarker profiling by MALDI-TOF mass spectrometry.

Several species in the genus Echinacea are beneficial herbs popularly used for many ailments. The most popular Echinacea species for cultivation, wild collection, and herbal products include E. purpurea (L.) Moench, E. pallida (Nutt.) Nutt., and E. angustifolia (DC). Product adulteration is a key concern for the natural products industry, where botanical misidentification and introduction of other botanical and nonbotanical contaminants exist throughout the formulation and production process. Therefore, rapid and cost-effective methods that can be used to monitor these materials for complex product purity and consistency are of benefit to consumers and producers. The objective of this continuing research was to develop automated, high-throughput processing methods that, teamed with matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) analysis, differentiate Echinacea species by their mass profiles. Small molecules, peptide, and proteins from aerial parts (leaf/stem/flowers), seeds, and roots from E. purpurea and E. angustifolia; seeds and roots from E. pallida; and off-the-shelf Echinacea supplements were extracted and analyzed by MS using methods developed on the ProPrep liquid handling system (Genomic Solutions). Analysis of these samples highlighted key MS signal patterns from both small molecules and proteins that characterized the individual Echinacea materials analyzed. Based on analysis of pure Echinacea samples, off-the-shelf products containing Echinacea could then be evaluated in a streamlined process. Corresponding analysis of dietary supplements was used to monitor for product composition, including Echinacea species and plant materials used. These results highlight the potential for streamlined, automated approaches for agricultural species differentiation and botanical product evaluation.

Genomic and proteomic analysis of mammary tumors arising in transgenic mice.

Transforming growth factor-beta (TGF-beta) is the prototype of a large family of signaling molecules. TGF-beta signaling profoundly influences tumor development as demonstrated in several engineered mouse models. The present study was designed to identify differences by cDNA microarray and MALDI-TOF MS analyses in mammary carcinomas with and without TGF-beta signaling. The results demonstrate a significant potential for combination of profiling technologies to further understand the molecular mechanisms of breast cancer.

Proteomic-based prognosis of brain tumor patients using direct-tissue matrix-assisted laser desorption ionization mass spectrometry.

Clinical diagnosis and treatment decisions for a subset of primary human brain tumors, gliomas, are based almost exclusively on tissue histology. Approaches for glioma diagnosis can be highly subjective due to the heterogeneity and infiltrative nature of these tumors and depend on the skill of the neuropathologist. There is therefore a critical need to develop more precise, non-subjective, and systematic methods to classify human gliomas. To this end, mass spectrometric analysis has been applied to these tumors to determine glioma-specific protein patterns. Protein profiles have been obtained from human gliomas of various grades through direct analysis of tissue samples using matrix-assisted laser desorption ionization mass spectrometry (MS). Statistical algorithms applied to the MS profiles from tissue sections identified protein patterns that correlated with tumor histology and patient survival. Using a data set of 108 glioma patients, two patient populations, a short-term and a long-term survival group, were identified based on the tissue protein profiles. In addition, a subset of 57 patients diagnosed with high-grade, grade IV, malignant gliomas were analyzed and a novel classification scheme that segregated short-term and long-term survival patients based on the proteomic profiles was developed. The protein patterns described served as an independent indicator of patient survival. These results show that this new molecular approach to monitoring gliomas can provide clinically relevant information on tumor malignancy and is suitable for high-throughput clinical screening.

Direct profiling of the cerebellum by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry: A methodological study in postnatal and adult mouse.

Matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI MS) can detect substantial changes in expression of proteins in tissues, such as cancer cells. A more challenging problem is detecting the smaller changes expected in normal development or complex diseases. Here we address methodological issues regarding the acquisition and analysis of MALDI MS data from tissue sections, in a study of mouse cerebellum at different stages of development. Sections of the cerebellar cortex were analyzed at the peak of granule neuron production [postnatal day (P) 7], during synapse formation (P14), and in adults. Data were acquired (Voyager-DEtrade mark STR Biospectrometry Workstation; seven acquisitions of 50 shots per section, 3.5-50 kDa), preprocessed (Data Explorer 4.3), and averaged. Among 846 peaks detected, in at least 50% of at least one group, 122 showed significant group differences (Kruskal-Wallis ANOVA) after Bonferroni correction. Factor analyses revealed two age-related factors, possibly reflecting gradients of expression during development. Predictive analysis of microarrays generated a model from half of the sample that correctly predicted developmental groups for the second half. Intraclass correlation coefficients, measuring within-mouse consistency of peak heights from three tissue sections, were acceptable at lower m/z and for larger peaks at higher m/z. Low mass was the best predictor of significant group differences. The analysis demonstrates that MALDI MS of normal tissue sections at different ages can detect consistent, significant group differences. Further work is needed to increase the sensitivity of the methods and to apply them reliably to brain regions and to subproteomes with relevance to diverse brain functions and diseases.

Imaging mass spectrometry: principles and potentials.

Direct tissue profiling and imaging mass spectrometry (MS) allow for detailed mapping of the complex protein pattern across a tissue sample. Utilization of these tools provides spatial information across a tissue section for target protein expression and can be used to correlate changes in expression levels with specific disease states or drug response. Protein patterns can be directly correlated to known histological regions within the tissue, allowing for the direct monitoring of proteins specific for morphological regions within a tissue sample. Profiling and imaging MS have been used to characterize multiple tissues, including human gliomas and lung cancers, as well as tumor response to specific therapeutics, suggesting the use of proteomic information in assessing disease progression as well as predicting patient response to specific treatments. This article discusses both the technology and methods involved in analyzing proteins directly from tissue samples as well as several MS applications, including profiling human tumors, characterizing protein differences between tumor grades, and monitoring protein changes due to drug therapy.

Assessing protein patterns in disease using imaging mass spectrometry.

Direct tissue profiling and imaging mass spectrometry (MS) provides a detailed assessment of the complex protein pattern within a tissue sample. MALDI MS analysis of thin tissue sections results in over of 500 individual protein signals in the mass range of 2 to 70 kDa that directly correlate with protein composition within a specific region of the tissue sample. To date, profiling and imaging MS has been applied to multiple diseased tissues, including human gliomas and nonsmall cell lung cancer. Interrogation of the resulting complex MS data sets has resulted in identification of both disease-state and patient-prognosis specific protein patterns. These results suggest the future usefulness of proteomic information in assessing disease progression, prognosis, and drug efficacy.

Protein profiling in brain tumors using mass spectrometry: feasibility of a new technique for the analysis of protein expression.

PURPOSE: The purpose of this research was to perform a preliminary assessment of protein patterns in primary brain tumors using a direct-tissue mass spectrometric technique to profile and map biomolecules. EXPERIMENTAL DESIGN: We examined 20 prospectively collected, snap-frozen normal brain and brain tumor specimens using matrix-assisted laser desorption/ionization (MALDI) mass spectrometry (MS), and compared peptide and protein expression in primary brain tumor and nontumor brain tissues. RESULTS: MS can be used to identify protein expression patterns in human brain tissue and tumor specimens. The mass spectral patterns can reliably identify glial neoplasms of similar histological grade and differentiate them from tumors of different histological grades as well as from nontumor brain tissues. Initial bioinformatics cluster analysis algorithms classified tumor and nontumor tissues into similar groups comparable with their histological grade. CONCLUSIONS: We describe a novel tool for the analysis of protein expression patterns in human glial neoplasms. Initial results demonstrate that MALDI-MS technology can significantly aid in the process of unraveling and understanding the molecular complexities of gliomas. MALDI-MS accurately and reliably identified normal and neoplastic tissues, and could be used to discriminate between tumors of increasing grades.

Integrating histology and imaging mass spectrometry.

MALDI (matrix-assisted laser desorption/ionization) imaging mass spectrometry (IMS) is a new technology that generates molecular profiles and two-dimensional ion density maps of peptide and protein signals directly from the surface of thin tissue sections. This allows specific information to be obtained on the relative abundance and spatial distribution of proteins. One important aspect of this is the opportunity to correlate these specific ion images with histological features observed by optical microscopy. To facilitate this, we have developed protocols that allow MALDI mass spectrometry imaging and optical microscopy to be performed on the same section. Key components of these protocols involve the use of conductive glass slides as sample support for the tissue sections and MS-friendly tissue staining protocols. We show the effectiveness of these with protein standards and with several types of tissue sections. Although stain-specific intensity variations occur, the overall protein pattern and spectrum quality remain consistent between stained and control tissue samples. Furthermore, imaging mass spectrometry experiments performed on stained sections showed good image quality with minimal delocalization of proteins resulting from the staining protocols.

Direct tissue analysis using matrix-assisted laser desorption/ionization mass spectrometry: practical aspects of sample preparation.

Practical guidelines for the preparation of tissue sections for direct analysis by matrix-assisted laser desorption/ionization (MALDI) mass spectrometry are presented. Techniques for proper sample handling including tissue storage, sectioning and mounting are described. Emphasis is placed on optimizing matrix parameters such as the type of matrix molecule used, matrix concentration, and solvent composition. Several different techniques for matrix application are illustrated. Optimal instrument parameters and the necessity for advanced data analysis approaches with regards to direct tissue analysis are also discussed.

Imaging mass spectrometry: a new tool to investigate the spatial organization of peptides and proteins in mammalian tissue sections.

MALDI MS imaging mass spectrometry can be used to map the distribution of targeted compounds in tissue sections with a spatial resolution currently of about 50 microm, providing important molecular information in many areas of biological research. After matrix application, a raster of a section by the laser beam yields ions from compounds in a tissue mass-to-charge range from 1000 to over 100000. Two-dimensional intensity maps can then be reconstructed to provide specific molecular images of a tissue.