Mass Dynamics 1.0: A Streamlined, Web-Based Environment for Analyzing, Sharing, and Integrating Label-Free Data

Bloom, Joseph; Triantafyllidis, Aaron; Quaglieri, Anna; Ngov, Paula Burton; Infusini, Giuseppe; Webb, Andrew I.

doi:10.1021/acs.jproteome.1c00683

Cited by 4 publications

(10 citation statements)

References 25 publications

(37 reference statements)

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“…The LFQ processing workflow uses the same approach as outlined previously for MD 1.0 12 and summarised in the steps below:…”

Section: Mass Dynamics Label-free Quantitation (Lfq) Data Processingmentioning

confidence: 99%

“…The downstream differential expression analysis is performed using the same workflow adopted for label-free quantitation data 12 .…”

Section: Dia Input Workflowsmentioning

confidence: 99%

“…MD 1.0 introduced the functionality for over-representation analysis (ORA) via the Reactome API content service, using protein lists generated from the pairwise comparisons results 12 . MD 2.0 now extends this service through a more comprehensive coverage of the Reactome database by including the disease and interactors databases and addition of new interactive visualisations.…”

Section: 0 Integrates New Biological Pathways and Visualisations To T...mentioning

confidence: 99%

“…To address this growing need, Mass Dynamics 1.0 (MD 1.0) 6 was released in 2021 to provide a web-based data processing and analysis environment that is easy to use, reliable, and offers;…”

Section: Introductionmentioning

confidence: 99%

“…To address this growing need, Mass Dynamics 1.0 (MD 1.0) 6 was released in 2021 to provide a web-based data processing and analysis environment that is easy to use, reliable, and offers; On-the-fly, comprehensive quality control, Analyses of label-free quantitative (LFQ) proteomics data, and Straightforward collaboration and sharing capabilities. …”

Section: Introductionmentioning

confidence: 99%

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Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Quaglieri¹,

Bloom²,

Triantafyllidis³

et al. 2022

Preprint

Self Cite

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Data processing is essential to reliably generate knowledge from proteomics studies. The complexity of the proteomics data, as well as the ability of research teams to adopt complex analysis pipelines, have proven to be an obstacle to effective collaboration and more efficient biological insight generation. Here, we introduce MD 2.0, a cloud- and web-based platform for quantitative proteomics data, which implements a novel analysis workspace where statistical analyses, visualizations, and external knowledge generation are integrated into a modular framework. This modularity enables researchers the flexibility to test different hypotheses, and customize and template complex proteomics analyses, thereby expediting insight generation for complex datasets. The extensible MD 2.0 environment has been built with a scalable architecture to allow rapid development of future analysis modules and enhanced tools for remote collaboration, like experiment sharing and a live chat capability. The new drag-and-drop modules allow researchers to easily and quickly assess different aspects of an experiment, including quality control, differential expression and enrichment analysis. The modularity of MD 2.0 lays the foundation to support broader community-based analytical template generation and optimized sharing and collaboration between proteomics experts and biologists, thereby accelerating research teams' abilities to extract knowledge from complex proteomics datasets.

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“…The LFQ processing workflow uses the same approach as outlined previously for MD 1.0 12 and summarised in the steps below:…”

Section: Mass Dynamics Label-free Quantitation (Lfq) Data Processingmentioning

confidence: 99%

“…The downstream differential expression analysis is performed using the same workflow adopted for label-free quantitation data 12 .…”

Section: Dia Input Workflowsmentioning

confidence: 99%

Section: 0 Integrates New Biological Pathways and Visualisations To T...mentioning

confidence: 99%

“…To address this growing need, Mass Dynamics 1.0 (MD 1.0) 6 was released in 2021 to provide a web-based data processing and analysis environment that is easy to use, reliable, and offers;…”

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Quaglieri¹,

Bloom²,

Triantafyllidis³

et al. 2022

Preprint

Self Cite

View full text Add to dashboard Cite

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Identification of a Protein Arginine Methyltransferase 7 (PRMT7)/Protein Arginine Methyltransferase 9 (PRMT9) Inhibitor

Feoli,

Iannelli,

Cipriano

et al. 2023

J. Med. Chem.

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Less studied than the other protein arginine methyltransferase isoforms, PRMT7 and PRMT9 have recently been identified as important therapeutic targets. Yet, most of their biological roles and functions are still to be defined, as well as the structural requirements that could drive the identification of selective modulators of their activity. We recently described the structural requirements that led to the identification of potent and selective PRMT4 inhibitors spanning both the substrate and the cosubstrate pockets. The reanalysis of the data suggested a PRMT7 preferential binding for shorter derivatives and prompted us to extend these structural studies to PRMT9. Here, we report the identification of the first potent PRMT7/9 inhibitor and its binding mode to the two PRMT enzymes. Label-free quantification mass spectrometry confirmed significant inhibition of PRMT activity in cells. We also report the setup of an effective AlphaLISA assay to screen small molecule inhibitors of PRMT9.

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CURTAIN—A unique web-based tool for exploration and sharing of MS-based proteomics data

Phung,

Berndsen,

Shastry

et al. 2024

Proc. Natl. Acad. Sci. U.S.A.

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To facilitate analysis and sharing of mass spectrometry (MS)-based proteomics data, we created online tools called CURTAIN ( https://curtain.proteo.info ) and CURTAIN-PTM ( https://curtainptm.proteo.info ) with an accompanying series of video tutorials ( https://www.youtube.com/@CURTAIN-me6hl ). These are designed to enable non-MS experts to interactively peruse volcano plots and deconvolute primary experimental data so that replicates can be visualized in bar charts or violin plots and exported in publication-ready format. They also allow assessment of overall experimental quality by correlation matrix and profile plot analysis. After making a selection of protein "hits", the user can analyze known domain structure, AlphaFold predicted structure, reported interactors, relative expression as well as disease links. CURTAIN-PTM permits analysis of all identified PTM sites on protein(s) of interest with selected databases. CURTAIN-PTM also links with the Kinase Library to predict upstream kinases that may phosphorylate sites of interest. We provide examples of the utility of CURTAIN and CURTAIN-PTM in analyzing how targeted degradation of the PPM1H Rab phosphatase that counteracts the Parkinson’s LRRK2 kinase impacts cellular protein levels and phosphorylation sites. We also reanalyzed a ubiquitylation dataset, characterizing the PINK1-Parkin pathway activation in primary neurons, revealing data of interest not highlighted previously. CURTAIN and CURTAIN-PTM are free to use and open source, enabling researchers to share and maximize the impact of their proteomics data. We advocate that MS data published in volcano plot format be reported containing a shareable CURTAIN weblink, thereby allowing readers to better analyze and exploit the data.

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Mass Dynamics 1.0: A Streamlined, Web-Based Environment for Analyzing, Sharing, and Integrating Label-Free Data

Cited by 4 publications

References 25 publications

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Mass Dynamics 2.0: An improved modular web-based platform for accelerated proteomics insight generation and decision making

Identification of a Protein Arginine Methyltransferase 7 (PRMT7)/Protein Arginine Methyltransferase 9 (PRMT9) Inhibitor

CURTAIN—A unique web-based tool for exploration and sharing of MS-based proteomics data

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