Estrada DG, Gómez PJA, Hernández MAA

Language: Spanish
References: 14
Page:
PDF size: 422.17 Kb.

ABSTRACT

At last decade, MALDI Mass Spectrometry Imaging (MALDI-MSI) has demostrated being a powerful tool in proteomics field. Because of high dimensionality of the acquired datasets in MALDI-MSI experiments and the inherent variabilities to the acquisition process, present in them, it´s necessary carry out a pre-processing stage, which reduces these distortions. This paper proposes a processing methodology of data MALDI-MSI supported in applications developed in MATLAB, Qt4 Library, as well as the visualization tool Datacube Explorer. Among the results obtained, it can be highlighted the changes in the intensities of the pixels of the reconstructed images after introducing noise, as well as the increasing of Signal-Noise Ratio after applying the denoising methods Kaiser, Savitzky-Golay and "sliding average", highlighting Kaiser over the other techniques, which can be interpreted as a decreasing of the distortion levels in each pixel´s spectrum. The reconstruction of example image and its visualization with Datacube Explorer tool were satisfactory.

REFERENCES

1. McDonnell LA, Heeren RM. Imaging mass spectrometry. Mass Spectrom Rev. 2007; 26(4): 606-43.

2. Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal Chem. 1997; 69(23): 4751-60.

3. Watrous JD, Alexandrov T, Dorrestein PC. The evolving field of imaging mass spectrometry and its impact on future biological research. J Mass Spectrom. 2011; 46(2): 209-22.

4. Seeley EH, Caprioli RM. Molecular imaging of proteins in tissues by mass spectrometry. PNAS. 2008; 105(47): 18126-18131.

5. Sauve AC, Speed TP. Normalization, baseline correction and alignment of high-throughput mass spectrometry data. Proceedings of the Genomic Signal Processing and Statistics; 2004.

6. Fonville JM, et al. Robust data processing and normalization strategy for MALDI mass spectrometric imaging. Anal Chem. 2012; 84(3): 1310-9.

7. Estrada G. Pre-procesamiento de datos de Espectrometría de Masas (MALDI) para mejorar el análisis directo de muestras de tejidos. La Habana: ISPJAE, Dpto. de Bioingeniería; 2012: 77.

8. Balluff B, Rauser S, Meding S, Elsner M, Schone C, Feuchtinger A, et al. MALDI imaging identifies prognostic seven-protein signature of novel tissue markers in intestinal-type gastric cancer. Am J Pathol. 2011 Dec; 179(6):2720-9.

9. Balluff B, Schone C, Hofler H, Walch A. MALDI imaging mass spectrometry for direct tissue analysis: technological advancements and recent applications. Histochem Cell Biol. 2011 Sep; 136(3):227-44.

10. Matsumoto J, Sugiura Y, Yuki D, Hayasaka T, Goto-Inoue N, Zaima N, et al. Abnormal phospholipids distribution in the prefrontal cortex from a patient with schizophrenia revealed by matrix-assisted laser desorption/ionization imaging mass spectrometry. Anal Bioanal Chem. 2011 Jun;400(7):1933-43.

11. Murphy AJ, Axt JR, de Caestecker C, Pierce J, Correa H, Seeley EH, et al. Molecular characterization of Wilms' tumor from a resource-constrained region of sub-Saharan Africa. Int J Cancer. 2012 Sep 15;131(6):E983-94.

12. Lazova R, Seeley EH, Keenan M, Gueorguieva R, Caprioli RM. Imaging mass spectrometry --a new and promising method to differentiate Spitz nevi from Spitzoid malignant melanomas. Am J Dermatopathol. 2012 Feb; 34(1):82-90.

13. Norris, JL, et al. Processing MALDI Mass Spectra to Improve Mass Spectral Direct Tissue Analysis. Int J Mass Spectrom, 2007. 260(2-3): 212-221.

14. Stoeckli, M. MALDI-MSI. [Citado 25 Mayo 2011]; Disponible en: http://tissue.ms/maldi-msi/