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Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra.

ABSTRACT: Motivation:Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI) facilitates the analysis of large organic molecules. However, the complexity of biological samples and MALDI data acquisition leads to high levels of variation, making reliable quantification of samples difficult. We present a new analysis approach that we believe is well-suited to the properties of MALDI mass spectra, based upon an Independent Component Analysis derived for Poisson sampled data. Simple analyses have been limited to studying small numbers of mass peaks, via peak ratios, which is known to be inefficient. Conventional PCA and ICA methods have also been applied, which extract correlations between any number of peaks, but we argue makes inappropriate assumptions regarding data noise, i.e. uniform and Gaussian. Results:We provide evidence that the Gaussian assumption is incorrect, motivating the need for our Poisson approach. The method is demonstrated by making proportion measurements from lipid-rich binary mixtures of lamb brain and liver, and also goat and cow milk. These allow our measurements and error predictions to be compared to ground truth. Availability and implementation:Software is available via the open source image analysis system TINA Vision, www.tina-vision.net. Contact:paul.tar@manchester.ac.uk. Supplementary information:Supplementary data are available at Bioinformatics online.

SUBMITTER: Deepaisarn S

PROVIDER: S-EPMC5860625 | biostudies-literature | 2018 Mar

REPOSITORIES: biostudies-literature

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Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra.

Deepaisarn S S Tar P D PD Thacker N A NA Seepujak A A McMahon A W AW

Bioinformatics (Oxford, England) 20180301 6

<h4>Motivation</h4>Matrix-assisted laser desorption/ionisation time-of-flight mass spectrometry (MALDI) facilitates the analysis of large organic molecules. However, the complexity of biological samples and MALDI data acquisition leads to high levels of variation, making reliable quantification of samples difficult. We present a new analysis approach that we believe is well-suited to the properties of MALDI mass spectra, based upon an Independent Component Analysis derived for Poisson sampled da ...[more]

PMID: 29091994

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Project description:BackgroundFor the purpose of epidemiological surveillance, the Hospital University Institute Méditerranée infection has implemented since 2013 a system named MIDaS, based on the systematic collection of routine activity materials, including MALDI-TOF spectra, and results. The objective of this paper is to present the pipeline we use for processing MALDI-TOF spectra during epidemiological surveillance in order to disclose proteinic cues that may suggest the existence of epidemic processes in complement of incidence surveillance. It is illustrated by the analysis of an alarm observed for Streptococcus pneumoniae.MethodsThe MALDI-TOF spectra analysis process looks for the existence of clusters of spectra characterized by a double time and proteinic close proximity. This process relies on several specific methods aiming at contrasting and clustering the spectra, presenting graphically the results for an easy epidemiological interpretation, and for determining the discriminating spectra peaks with their possible identification using reference databases.ResultsThe use of this pipeline in the case of an alarm issued for Streptococcus pneumoniae has made it possible to reveal a cluster of spectra with close proteinic and temporal distances, characterized by the presence of three discriminant peaks (5228.8, 5917.8, and 8974.3 m/z) and the absence of peak 4996.9 m/z. A further investigation on UniProt KB showed that peak 5228.8 is possibly an OxaA protein and that the absent peak may be a transposase.ConclusionThis example shows this pipeline may support a quasi-real time identification and characterization of clusters that provide essential information on a potentially epidemic situation. It brings valuable information for epidemiological sensemaking and for deciding on the continuation of the epidemiological investigation, in particular the involving of additional costly resources to confirm or invalidate the alarm.Clinical trials registrationNCT03626987.

Dataset Information

Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra.

Publications

Quantifying biological samples using Linear Poisson Independent Component Analysis for MALDI-ToF mass spectra.

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