Heeren, R.M.

Correlating MALDI and SIMS imaging mass spectrometric datasets of biological tissue surfaces (Article)

2009-08-01T00:00:00Z

Imaging mass spectrometry (IMS) is a rapidly evolving tool for combined chemical and spatial analysis of biological tissues. The complexity of the biological data requires various analytical methods to process the raw datasets. In this article, we report on the 'semi-automated' correlation of two imaging MS datasets obtained with secondary ion mass spectrometry (SIMS) and matrix-assisted laser desorption/ionization (MALDI) on the same, single brain tissue sample. Prior to statistical analysis, the raw datasets are preprocessed with novel algorithms for baseline correction and peak picking. Principal component analysis (PCA) and canonical correlation analysis (CCA) are used in concert to extract the maximum amount of information about the location of different biochemical molecules on the tissue surface. More importantly, the results show that combining the information from MALDI and SIMS, by using CCA, enables us to correlate and improve the individual results of these two imaging MS experiments. Copyright

Sample preparation issues for tissue imaging by imaging MS (Article)

2009-05-01T00:00:00Z

Imaging MS is a powerful technique that combines the chemical and spatial analysis of surfaces. It allows spatial localization of multiple different compounds that are recorded in parallel without the need of a label. It is currently one of the rapidly developing techniques in the proteomics toolbox. Different complementary imaging MS methods, i.e. MALDI and secondary ion MS imaging for direct tissue analysis, can be applied on exactly the same tissue sample. This allows the identification of small molecules, peptides and proteins present on the same sample surface. Sample preparation is crucial to obtain high quality, reliable and reproducible complementary molecular images. It is essential to optimize the conditions for each step in the sample preparation protocol, ranging from sample collection and storage to surface modification. In this article, we review and discuss the importance of correct sample treatment in case of MALDI and secondary ion MS imaging experiments and describe the experimental requirements for optimal sample preparation.

Specific peptides identified by mass spectrometry in placental tissue from pregnancies complicated by early onset preeclampsia attained by laser capture dissection (Article)

2007-03-01T00:00:00Z

Preeclampsia is a common pregnancy-specific syndrome that is diagnosed by the appearance of both increased blood pressure and proteinuria. Preeclampsia is associated with significant fetal and maternal morbidity and mortality. Although the etiology of preeclampsia is unknown, it is evident that abnormal placentation and trophoblast metabolism plays an important role. We therefore analyzed, identified, and verified specific proteins of villous trophoblast and villous stroma in small numbers of microdissected cells (approximately 125 cells) from seven placentas of women with pregnancies complicated by preeclampsia (cases) and seven uncomplicated pregnancies (controls). Tryptic peptide profiling by MALDI-TOF MS was used for comparison and identification of significantly expressed peptides. The data were analyzed by ClinProTools (Bruker Daltonics) and by principal component analysis. Subsequently, a subset of placental tissues were homogenized and separated on a NanoLC system to obtain sequencing information (MS/MS spectra). We identified specific peptide patterns in the different cell types: villous stroma and trophoblast cells and differences in these cells of placentas from women with pregnancies complicated by early compared to late onset preeclampsia (<34 and > 34 wk gestation, respectively) and controls. Principal component analysis revealed significant differences between the groups. The comparison with placental tissue after preterm delivery with unknown cause revealed that placental peptide patterns in early onset preeclampsia could not be explained by preterm delivery per se. Subsequently, specific, discriminating proteins for early onset preeclampsia compared to controls were identified including calcyclin, surfeit locus protein, and choriomammotropin A precursor. The expression of calcyclin was verified in early onset preeclamptic placental sections by immunohistochemistry. These data suggest that in early onset preeclampsia trophoblastic choriomammotropin regulation is abnormal, possibly through abnormal calcyclin expression and regulation.

Identification of leptomeningeal metastasis-related proteins in cerebrospinal fluid of patients with breast cancer by a combination of MALDI-TOF, MALDI-FTICR and nanoLC-FTICR MS (Article)

2007-02-01T00:00:00Z

Leptomeningeal metastasis (LM) is a devastating complication occurring in 5% of breast cancer patients. However, the current 'gold standard' of diagnosis, namely microscopic examination of the cerebrospinal fluid (CSF), is false-negative in 25% of patients at the first lumbar puncture. In a previous study, we analyzed a set of 151 CSF samples (tryptic digests) by MALDI-TOF and detected peptide masses that were differentially expressed in breast cancer patients with LM. In the present study, we obtain for a limited number of samples exact masses for these peptides by MALDI-FTICR MS measurements. Identification of these peptides was performed by electrospray FTICR MS after separation by nano-scale LC. The database results were confirmed by targeted high mass accuracy measurements of the fragment ions in the FTICR cell. The combination of automated high-throughput MALDI-TOF measurements and analysis by FTICR MS leads to the identification of 17 peptides corresponding to 9 proteins. These include proteins that are operative in host-disease interaction, inflammation and immune defense (serotransferrin, alpha 1-antichymotrypsin, hemopexin, haptoglobin and transthyretin). Several of these proteins have been mentioned in the literature in relation to cancer. The identified proteins alphal-antichymotrypsin and apolipoprotein E have been described in relation to Alzheimer's disease and brain cancer.

A database application for pre-processing, storage and comparison of mass spectra derived from patients and controls. (Article)

2006-09-05T00:00:00Z

BACKGROUND: Statistical comparison of peptide profiles in biomarker discovery requires fast, user-friendly software for high throughput data analysis. Important features are flexibility in changing input variables and statistical analysis of peptides that are differentially expressed between patient and control groups. In addition, integration the mass spectrometry data with the results of other experiments, such as microarray analysis, and information from other databases requires a central storage of the profile matrix, where protein id's can be added to peptide masses of interest. RESULTS: A new database application is presented, to detect and identify significantly differentially expressed peptides in peptide profiles obtained from body fluids of patient and control groups. The presented modular software is capable of central storage of mass spectra and results in fast analysis. The software architecture consists of 4 pillars, 1) a Graphical User Interface written in Java, 2) a MySQL database, which contains all metadata, such as experiment numbers and sample codes, 3) a FTP (File Transport Protocol) server to store all raw mass spectrometry files and processed data, and 4) the software package R, which is used for modular statistical calculations, such as the Wilcoxon-Mann-Whitney rank sum test. Statistic analysis by the Wilcoxon-Mann-Whitney test in R demonstrates that peptide-profiles of two patient groups 1) breast cancer patients with leptomeningeal metastases and 2) prostate cancer patients in end stage disease can be distinguished from those of control groups. CONCLUSION: The database application is capable to distinguish patient Matrix Assisted Laser Desorption Ionization (MALDI-TOF) peptide profiles from control groups using large size datasets. The modular architecture of the application makes it possible to adapt the application to handle also large sized data from MS/MS- and Fourier Transform Ion Cyclotron Resonance (FT-ICR) mass spectrometry experiments. It is expected that the higher resolution and mass accuracy of the FT-ICR mass spectrometry prevents the clustering of peaks of different peptides and allows the identification of differentially expressed proteins from the peptide profiles.