MZmine 2: Modular framework for processing, visualizing, and analyzing mass spectrometry-based molecular profile data
TL;DR: A new generation of a popular open-source data processing toolbox, MZmine 2 is introduced, suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
Abstract: Mass spectrometry (MS) coupled with online separation methods is commonly applied for differential and quantitative profiling of biological samples in metabolomic as well as proteomic research. Such approaches are used for systems biology, functional genomics, and biomarker discovery, among others. An ongoing challenge of these molecular profiling approaches, however, is the development of better data processing methods. Here we introduce a new generation of a popular open-source data processing toolbox, MZmine 2. A key concept of the MZmine 2 software design is the strict separation of core functionality and data processing modules, with emphasis on easy usability and support for high-resolution spectra processing. Data processing modules take advantage of embedded visualization tools, allowing for immediate previews of parameter settings. Newly introduced functionality includes the identification of peaks using online databases, MSn data support, improved isotope pattern support, scatter plot visualization, and a new method for peak list alignment based on the random sample consensus (RANSAC) algorithm. The performance of the RANSAC alignment was evaluated using synthetic datasets as well as actual experimental data, and the results were compared to those obtained using other alignment algorithms. MZmine 2 is freely available under a GNU GPL license and can be obtained from the project website at: http://mzmine.sourceforge.net/
. The current version of MZmine 2 is suitable for processing large batches of data and has been applied to both targeted and non-targeted metabolomic analyses.
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TL;DR: The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions.
Abstract: We present a new update to MetaboAnalyst (version 4.0) for comprehensive metabolomic data analysis, interpretation, and integration with other omics data. Since the last major update in 2015, MetaboAnalyst has continued to evolve based on user feedback and technological advancements in the field. For this year's update, four new key features have been added to MetaboAnalyst 4.0, including: (1) real-time R command tracking and display coupled with the release of a companion MetaboAnalystR package; (2) a MS Peaks to Pathways module for prediction of pathway activity from untargeted mass spectral data using the mummichog algorithm; (3) a Biomarker Meta-analysis module for robust biomarker identification through the combination of multiple metabolomic datasets and (4) a Network Explorer module for integrative analysis of metabolomics, metagenomics, and/or transcriptomics data. The user interface of MetaboAnalyst 4.0 has been reengineered to provide a more modern look and feel, as well as to give more space and flexibility to introduce new functions. The underlying knowledgebases (compound libraries, metabolite sets, and metabolic pathways) have also been updated based on the latest data from the Human Metabolome Database (HMDB). A Docker image of MetaboAnalyst is also available to facilitate download and local installation of MetaboAnalyst. MetaboAnalyst 4.0 is freely available at http://metaboanalyst.ca.
2,857 citations
Cites methods from "MZmine 2: Modular framework for pro..."
...A number of excellent methods have been developed to deal with the first two tasks (26,27), which typically yield a list of ‘clean’ MS peaks....
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TL;DR: By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, the server has been able to substantially improve its performance, capacity and user interactivity.
Abstract: MetaboAnalyst (www.metaboanalyst.ca) is a web server designed to permit comprehensive metabolomic data analysis, visualization and interpretation. It supports a wide range of complex statistical calculations and high quality graphical rendering functions that require significant computational resources. First introduced in 2009, MetaboAnalyst has experienced more than a 50X growth in user traffic (>50 000 jobs processed each month). In order to keep up with the rapidly increasing computational demands and a growing number of requests to support translational and systems biology applications, we performed a substantial rewrite and major feature upgrade of the server. The result is MetaboAnalyst 3.0. By completely re-implementing the MetaboAnalyst suite using the latest web framework technologies, we have been able substantially improve its performance, capacity and user interactivity. Three new modules have also been added including: (i) a module for biomarker analysis based on the calculation of receiver operating characteristic curves; (ii) a module for sample size estimation and power analysis for improved planning of metabolomics studies and (iii) a module to support integrative pathway analysis for both genes and metabolites. In addition, popular features found in existing modules have been significantly enhanced by upgrading the graphical output, expanding the compound libraries and by adding support for more diverse organisms.
2,404 citations
Cites methods from "MZmine 2: Modular framework for pro..."
...Users are encouraged to use other dedicated and freely available tools such as XCMSOnline (30) and MZmine (31) for such tasks....
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TL;DR: This work reviews strategies for natural product screening that harness the recent technical advances that have reduced technical barriers and assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products.
Abstract: Natural products have been a rich source of compounds for drug discovery. However, their use has diminished in the past two decades, in part because of technical barriers to screening natural products in high-throughput assays against molecular targets. Here, we review strategies for natural product screening that harness the recent technical advances that have reduced these barriers. We also assess the use of genomic and metabolomic approaches to augment traditional methods of studying natural products, and highlight recent examples of natural products in antimicrobial drug discovery and as inhibitors of protein-protein interactions. The growing appreciation of functional assays and phenotypic screens may further contribute to a revival of interest in natural products for drug discovery.
1,822 citations
TL;DR: While the intrinsic complexity of natural product-based drug discovery necessitates highly integrated interdisciplinary approaches, the reviewed scientific developments, recent technological advances, and research trends clearly indicate that natural products will be among the most important sources of new drugs in the future.
1,760 citations
Additional excerpts
...Different open-source and commercial software packages are available for this task (Creek et al., 2011; Hartler et al., 2011; Jankevics et al., 2012; Kamleh et al., 2008; Kawaguchi et al., 2010; Pluskal et al., 2010; Smith et al., 2006)....
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TL;DR: The MetaboAnalyst 5.0 as mentioned in this paper is the latest version of the web-based platform for comprehensive metabolomics data analysis and interpretation, aiming to narrow the gap from raw data to functional insights for global metabolomics based on HRMS.
Abstract: Since its first release over a decade ago, the MetaboAnalyst web-based platform has become widely used for comprehensive metabolomics data analysis and interpretation. Here we introduce MetaboAnalyst version 5.0, aiming to narrow the gap from raw data to functional insights for global metabolomics based on high-resolution mass spectrometry (HRMS). Three modules have been developed to help achieve this goal, including: (i) a LC-MS Spectra Processing module which offers an easy-to-use pipeline that can perform automated parameter optimization and resumable analysis to significantly lower the barriers to LC-MS1 spectra processing; (ii) a Functional Analysis module which expands the previous MS Peaks to Pathways module to allow users to intuitively select any peak groups of interest and evaluate their enrichment of potential functions as defined by metabolic pathways and metabolite sets; (iii) a Functional Meta-Analysis module to combine multiple global metabolomics datasets obtained under complementary conditions or from similar studies to arrive at comprehensive functional insights. There are many other new functions including weighted joint-pathway analysis, data-driven network analysis, batch effect correction, merging technical replicates, improved compound name matching, etc. The web interface, graphics and underlying codebase have also been refactored to improve performance and user experience. At the end of an analysis session, users can now easily switch to other compatible modules for a more streamlined data analysis. MetaboAnalyst 5.0 is freely available at https://www.metaboanalyst.ca.
1,530 citations
References
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TL;DR: Using the four data sets to compare six freely available alignment algorithms proposed for the alignment of metabolomics and proteomics LC-MS measurements, it is found significant differences with respect to alignment quality, running time, and usability in general.
Abstract: Liquid chromatography coupled to mass spectrometry (LC-MS) has become a prominent tool for the analysis of complex proteomics and metabolomics samples. In many applications multiple LC-MS measurements need to be compared, e. g. to improve reliability or to combine results from different samples in a statistical comparative analysis. As in all physical experiments, LC-MS data are affected by uncertainties, and variability of retention time is encountered in all data sets. It is therefore necessary to estimate and correct the underlying distortions of the retention time axis to search for corresponding compounds in different samples. To this end, a variety of so-called LC-MS map alignment algorithms have been developed during the last four years. Most of these approaches are well documented, but they are usually evaluated on very specific samples only. So far, no publication has been assessing different alignment algorithms using a standard LC-MS sample along with commonly used quality criteria. We propose two LC-MS proteomics as well as two LC-MS metabolomics data sets that represent typical alignment scenarios. Furthermore, we introduce a new quality measure for the evaluation of LC-MS alignment algorithms. Using the four data sets to compare six freely available alignment algorithms proposed for the alignment of metabolomics and proteomics LC-MS measurements, we found significant differences with respect to alignment quality, running time, and usability in general. The multitude of available alignment methods necessitates the generation of standard data sets and quality measures that allow users as well as developers to benchmark and compare their map alignment tools on a fair basis. Our study represents a first step in this direction. Currently, the installation and evaluation of the "correct" parameter settings can be quite a time-consuming task, and the success of a particular method is still highly dependent on the experience of the user. Therefore, we propose to continue and extend this type of study to a community-wide competition. All data as well as our evaluation scripts are available at http://msbi.ipb-halle.de/msbi/caap
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173 citations
"MZmine 2: Modular framework for pro..." refers background or methods or result in this paper
...Two types of errors can be introduced during the alignment process [11]....
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...Table 3 Performance comparison of MZmine 2 alignment methods (right side of the table) to previously published results (left side of the table) obtained using several different software packages [11]...
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...The software has been applied to numerous metabolomic analyses [5-10] and comparative studies with other related software packages have been performed [9,11]....
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...[11], together with their tables of “ground truth” alignments and an evaluation script for calculating the alignment precision and recall values....
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TL;DR: The first global semi-quantitative analysis of the S. pombe metabolome using liquid chromatography high-resolution mass spectrometry confirms that the fission yeast Schizosaccharomyces pom be can be applied as an appropriate model to monitor metabolic responses to environmental conditions as well as genetic perturbations.
Abstract: Metabolomics is a rapidly growing branch of post-genomic chemical biology. The fission yeast Schizosaccharomyces pombe is an excellent eukaryotic model organism. Although the entire S. pombegenome has been sequenced and detailed transcriptomic analyses were performed, little metabolic profiling has been done. Here we report the first global semi-quantitative analysis of the S. pombe metabolome using liquid chromatographyhigh-resolution mass spectrometry. Procedures to obtain metabolic compounds from S. pombe extracts were established. One hundred and twenty-three distinct metabolites were identified while approximately 1900 peaks from the ∼6000 observed were assigned. A software system (MZviewer) was developed to visualize semi-quantitative metabolome data using a dynamically generated scatter plot. We examined the metabolome of S. pombe cells exponentially grown in synthetic culture medium (EMM2) at two different temperatures, 26 °C and 36 °C. The profiles were similar except for varying amounts of certain amino acids and a significant increase in several compounds at 36 °C, such as trehalose (200-fold), glycerophosphoethanolamine (50-fold), arabitol (16-fold), ribulose (8-fold), and ophthalmic acid (5-fold). Reproducibility was demonstrated using a deletion mutant sib1Δ that lacked ferrichrome synthetase and showed no significant metabolic effects except the disappearance of the hexapeptide ferrichrome and the appearance of a putative dipeptide precursor. Taking advantage of the metabolic profile similarity at 26 °C and 36 °C, we analyzed the metabolome of a temperature-sensitive hcs1-143 mutant defective in the HMG-CoA synthase. As expected, HMG-CoA was decreased. In addition, extensive secondary metabolic effects, including a decrease in urea cycle intermediates and an increase in acetylated compounds, were observed. These findings confirm that S. pombe can be applied as an appropriate model to monitor metabolic responses to environmental conditions as well as genetic perturbations.
79 citations
"MZmine 2: Modular framework for pro..." refers background in this paper
...The current version of the framework is already suitable for processing large batches of data, both for targeted and/or nontargeted analyses, and has been applied in metabolomic research [13,27]....
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...The scatter plot visualizer (Figure 2F) has proven to be very useful for efficient comparison of multiple samples [13]....
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TL;DR: Concomitant analyses with two different GC‐MS methods allowed not only crossvalidation of the quantitative results obtained by the various methods, but also led to a more comprehensive coverage of the E. coli metabolome.
Abstract: A CE-MS method was developed and validated for the quantitative analysis of negatively charged metabolites by making use of the high mass accuracy and the quantitation capabilities of a TOF mass analyzer in combination with automated feature extraction and database search. Metabolites of the central carbon metabolism were quantified with an LOD and lower LOQ (LLOQ) of 0.2-2 and 1-4 microM, respectively. The method was used to elucidate metabolic changes in the Escherichia coli deletion mutant PntAB-UdhA that lacks nicotinamide nucleotide transhydrogenase function, under both stationary and exponential growth conditions. The reproducibility of metabolite extraction and CE-TOF-MS analysis ranged from 3.7 to 22.7 and 7.9 to 22.6%, respectively, while the biological variance was 3.4-31.3%. We observed significant differences in metabolite abundance, particularly in the citrate cycle, between wild-type and mutant E. coli. Overall, more than 600 features were found by automated feature detection, which resulted in approximately 150 high-confidence metabolite identifications. Concomitant analyses with two different GC-MS methods allowed not only crossvalidation of the quantitative results obtained by the various methods, but also led to a more comprehensive coverage of the E. coli metabolome.
66 citations
TL;DR: Dinishment of lens phosphatidylcholines in the presence of gut microbiota suggests that the conventionally raised mice are exposed over time to more oxidative stress than germ-free mice, and their lifespan is also shorter.
48 citations
"MZmine 2: Modular framework for pro..." refers background in this paper
...The current version of the framework is already suitable for processing large batches of data, both for targeted and/or nontargeted analyses, and has been applied in metabolomic research [13,27]....
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TL;DR: The results imply that the connectivity of the system is being dynamically modulated in response to oxidative stress, progressively leading to the accumulation of (lipo)toxic lipids such as ceramides.
Abstract: In response to environmental challenges, biological systems respond with dynamic adaptive changes in order to maintain the functionality of the system. Such adaptations may lead to cumulative stress over time, possibly leading to global failure of the system. When studying such systems responses, it is therefore important to understand them in system-wide and dynamic context. Here we hypothesize that dynamic changes in the topology of functional modules of integrated biological networks reflect their activity under specific environmental challenges. We introduce topological enrichment analysis of functional subnetworks (TEAFS), a method for the analysis of integrated molecular profile and interactome data, which we validated by comprehensive metabolomic analysis of dynamic yeast response under oxidative stress. TEAFS identified activation of multiple stress response related mechanisms, such as lipid metabolism and phospholipid biosynthesis. We identified, among others, a fatty acid elongase IFA38 as a hub protein which was absent at all time points under oxidative stress conditions. The deletion mutant of the IFA38 encoding gene is known for the accumulation of ceramides. By applying a comprehensive metabolomic analysis, we confirmed the increased concentrations over time of ceramides and palmitic acid, a precursor of de novo ceramide biosynthesis. Our results imply that the connectivity of the system is being dynamically modulated in response to oxidative stress, progressively leading to the accumulation of (lipo)toxic lipids such as ceramides. Studies of local network topology dynamics can be used to investigate as well as predict the activity of biological processes and the system's responses to environmental challenges and interventions.
18 citations
"MZmine 2: Modular framework for pro..." refers methods in this paper
...The software has been applied to numerous metabolomic analyses [5-10] and comparative studies with other related software packages have been performed [9,11]....
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