Principal component analysis of normalized full spectrum mass spectrometry data in multiMS‐toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains

Cejnar, Pavel; Kučková, Štěpánka; Procházka, Aleš; Karamonová, Ludmila; Svobodová, Barbora

doi:10.1002/rcm.8110

Cited by 20 publications

(17 citation statements)

References 47 publications

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“…Public statistical R software, multiMS-toolbox and Mass Spectrum Analysis and Data Conversion Tool [4] , [5] were used. Mass spectra of each sample treated by the tested agent from all three replications and measured dots were exported using FlexAnalysis 3.4 Compass 1.4 (Bruker Daltonics, Bremen, Germany).…”

Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Data on low-molecular weight proteins of Escherichia coli treated by essential oils components, tetracycline, chlorine and peroxide by MALDI-TOF MS

et al. 2018

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In this dataset we provide MALDI-TOF MS spectra of Escherichia coli. The data presented in this article are related to the article entitled “Stress response of Escherichia coli to essential oil components – insights on low-molecular-weight proteins from MALDI-TOF” (Božik et al., 2018) [1]. Essential oils and their components are known for their antibacterial effect. Many studies evaluated the effect of essential oil components (EOCs) on the cell wall, bacterial membranes, and energetic metabolism. But data about low molecular weight proteins (<20 kDa) are limited. Provided data are focused on bacterial response to EOCs; tetracycline, peroxide and chlorine was used as control as common antibiotic and disinfectant agents used against bacteria. These data describe the effect of tested substances to bacterial protein synthesis.

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Section: Experimental Design Materials and Methodsmentioning

confidence: 99%

Data on low-molecular weight proteins of Escherichia coli treated by essential oils components, tetracycline, chlorine and peroxide by MALDI-TOF MS

et al. 2018

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“…The measured MALDI spectra were processed using the software mMass and analysis of the main components of the PCA, using mathematical software R and the MultiMS toolbox, which is available free of charge from http://uprt.vscht.cz/ms . Mass spectra were adjusted using Mass Spectrum Analysis and Data Conversion Tool.…”

Section: Methodsmentioning

confidence: 99%

Verification of cheeses authenticity by mass spectrometry

Kučková

Zitkova

Novotný

et al. 2019

J of Separation Science

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Cheeses are a group of fermented dairy products that are produced all over the world in various forms and flavours. Milk, especially sheep or goat milk, is still regarded as an expensive raw material in the world, which makes milk and milk products highly attractive as a fraud target. Most often, such fraud includes partial or complete substitution with cheaper sorts of milk (e.g. bovine milk). The aim of this work was to verify the authenticity of 27 cheeses commonly emerging on the Czech food market. The cheeses were distinguished on the basis of milk animal species origin. For this purpose, two mass spectrometry techniques were used: matrix‐assisted laser desorption/ionization with time of flight mass spectrometry together with principal component analysis method and liquid chromatography coupled with electrospray ionization and quadrupole time‐of‐flight mass spectrometry. The results were a partial success, because the cheeses could only be partially distinguished with the first mass spectrometry technique probably because of the influence of some protein additive materials in cheeses. The second technique allowed for collecting higher quality results and thus appears to be highly suitable for the research task.

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“…ms‐alone , a Python‐based utility for MS data preprocessing and peak extraction, and the multiMS‐toolbox , an R software tool for advanced peak registration and detailed explorative statistical analysis, are available .…”

Section: Tools For Analytical Platformsmentioning

confidence: 99%

Tools and resources for metabolomics research community: A 2017–2018 update

Misra¹,

Mohapatra

2018

Electrophoresis

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The scale at which MS‐ and NMR‐based platforms generate metabolomics datasets for both research, core, and clinical facilities to address challenges in the various sciences—ranging from biomedical to agricultural—is underappreciated. Thus, metabolomics efforts spanning microbe, environment, plant, animal, and human systems have led to continual and concomitant growth of in silico resources for analysis and interpretation of these datasets. These software tools, resources, and databases drive the field forward to help keep pace with the amount of data being generated and the sophisticated and diverse analytical platforms that are being used to generate these metabolomics datasets. To address challenges in data preprocessing, metabolite annotation, statistical interrogation, visualization, interpretation, and integration, the metabolomics and informatics research community comes up with hundreds of tools every year. The purpose of the present review is to provide a brief and useful summary of more than 95 metabolomics tools, software, and databases that were either developed or significantly improved during 2017–2018. We hope to see this review help readers, developers, and researchers to obtain informed access to these thorough lists of resources for further improvisation, implementation, and application in due course of time.

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Principal component analysis of normalized full spectrum mass spectrometry data in multiMS‐toolbox: An effective tool to identify important factors for classification of different metabolic patterns and bacterial strains

Cited by 20 publications

References 47 publications

Data on low-molecular weight proteins of Escherichia coli treated by essential oils components, tetracycline, chlorine and peroxide by MALDI-TOF MS

Data on low-molecular weight proteins of Escherichia coli treated by essential oils components, tetracycline, chlorine and peroxide by MALDI-TOF MS

Verification of cheeses authenticity by mass spectrometry

Tools and resources for metabolomics research community: A 2017–2018 update

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