MSI.R scripts reveal volatile and semi-volatile features in low-temperature plasma mass spectrometry imaging (LTP-MSI) of chilli (Capsicum annuum)
- 592 Downloads
In cartography, the combination of colour and contour lines is used to express a three-dimensional landscape on a two-dimensional map. We transferred this concept to the analysis of mass spectrometry imaging (MSI) data and developed a collection of R scripts for the efficient evaluation of .imzML archives in a four-step strategy: (1) calculation of the density distribution of mass-to-charge ratio (m/z) signals in the .imzML file and assembling of a pseudo-master spectrum with peak list, (2) automated generation of mass images for a defined scan range and subsequent visual inspection, (3) visualisation of individual ion distributions and export of relevant .mzML spectra and (4) creation of overlay graphics of ion images and photographies. The use of a Hue-Chroma-Luminance (HCL) colour model in MSI graphics takes into account the human perception for colours and supports the correct evaluation of signal intensities. Further, readers with colour blindness are supported. Contour maps promote the visual recognition of patterns in MSI data, which is particularly useful for noisy data sets. We demonstrate the scalability of MSI.R scripts by running them on different systems: on a personal computer, on Amazon Web Services (AWS) instances and on an institutional cluster. By implementing a parallel computing strategy, the execution speed for .imzML data scanning with image generation could be improved by more than an order of magnitude. Applying our MSI.R scripts (http://www.bioprocess.org/MSI.R) to low-temperature plasma (LTP)-MSI data shows the localisation of volatile and semi-volatile compounds in the cross-cut of a chilli (Capsicum annuum) fruit. The subsequent identification of compounds by gas and liquid chromatography coupled to mass spectrometry (GC-MS, LC-MS) proves that LTP-MSI enables the direct measurement of volatile organic compound (VOC) distributions from biological tissues.
KeywordsMass spectrometry imaging Ambient ionisation Chilli Volatiles Semi-volatiles Low-temperature plasma
We cordially thank Alejandro González Tokman for creating the access to the computer cluster ‘Hypatia’ of the LAICBIO lab and Sebastian Gibb for his valuable support concerning the use of the MALDIquant/MALDIquantForeign package. We appreciate the information provided by Dr. Sören Deininger (Bruker Daltonik GmbH, Germany) about the FT-MSI dataset. The study was funded by the CONACYT basic science grant I0017/CB-2010-01/151596, FINNOVA I010/260/2014 and the CINVESTAV. RGB thanks for his CONACYT scholarship.
- 12.Schramm T, Hester A, Klinkert I, Both J-P, Heeren RMA, Brunelle A, Laprévote O, Desbenoit N, Robbe M-F, Stoeckli M, Spengler B, Römpp A (2012) imzML—a common data format for the flexible exchange and processing of mass spectrometry imaging data. J Proteomics 75:5106–5110. doi: 10.1016/j.jprot.2012.07.026 CrossRefGoogle Scholar
- 13.Mirion—a software package for automatic processing of mass spectrometric images. Springer. doi: 10.1007/s13361-013-0667-0
- 14.Parry RM, Galhena AS, Gamage CM, Bennett RV, Wang MD, Fernández FM (2013) omniSpect: an open MATLAB-based tool for visualization and analysis of matrix-assisted laser desorption/ionization and desorption electrospray ionization mass spectrometry images. J Am Soc Mass Spectrom 24:646–649. doi: 10.1007/s13361-012-0572-y CrossRefGoogle Scholar
- 17.Klinkert I, Chughtai K, Ellis SR, Heeren RMA. Methods for full resolution data exploration and visualization for large 2D and 3D mass spectrometry imaging datasets. Int J Mass Spectrom. doi: 10.1016/j.ijms.2013.12.012
- 24.Horai H, Arita M, Kanaya S, Nihei Y, Ikeda T, Suwa K, Ojima Y, Tanaka K, Tanaka S, Aoshima K, Oda Y, Kakazu Y, Kusano M, Tohge T, Matsuda F, Sawada Y, Hirai MY, Nakanishi H, Ikeda K, Akimoto N, Maoka T, Takahashi H, Ara T, Sakurai N, Suzuki H, Shibata D, Neumann S, Iida T, Tanaka K, Funatsu K, Matsuura F, Soga T, Taguchi R, Saito K, Nishioka T (2010) MassBank: a public repository for sharing mass spectral data for life sciences. J Mass Spectrom 45:703–714. doi: 10.1002/jms.1777 CrossRefGoogle Scholar
- 29.Race AM, Bunch J (2015) Optimisation of colour schemes to accurately display mass spectrometry imaging data based on human colour perception. Anal Bioanal Chem 1–8. doi: 10.1007/s00216-014-8404-5
- 32.Ihaka R, Murrell P, Hornik K, Fisher JC, Zeileis A (2013) Colorspace: color space manipulationGoogle Scholar
- 33.Schmidberger M, Morgan M, Eddelbuettel D, Yu H, Tierney L, Mansmann U (2009) State of the art in parallel computing with R. J Stat Softw 31:1–27Google Scholar
- 34.Bogusz Junior S, Tavares AM, Filho JT, Zini CA, Godoy HT (2012) Analysis of the volatile compounds of Brazilian chilli peppers (Capsicum spp.) at two stages of maturity by solid phase micro-extraction and gas chromatography-mass spectrometry. Food Res Int 48:98–107. doi: 10.1016/j.foodres.2012.02.005 CrossRefGoogle Scholar
- 37.Taira S, Shimma S, Osaka I, Kaneko D, Ichiyanagi Y, Ikeda R, Konishi-Kawamura Y, Zhu S, Tsuneyama K, Komatsu K (2012) Mass spectrometry imaging of the capsaicin localization in the capsicum fruits. Int J Biotechnol Wellness Ind 1:61–66Google Scholar