OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data

Röst, Hannes L.; Rosenberger, George; Navarro, Pedro J.; Gillet, Ludovic; Miladinović, Saša M.; Schubert, Olga T.; Wolski, Witold; Collins, Ben C.; Malmström, Johan; Malmström, Lars; Aebersold, Ruedi

doi:10.1038/nbt.2841

Cited by 727 publications

(823 citation statements)

References 37 publications

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“…For targeted extraction, a custom SWATH‐library was built using standard parameters,26 and all SWATH assays deposited into a publically available SWATH library 27. SWATH‐MS maps were analysed using OpenSWATH workflow28 (Supporting Information SWATH analysis). Protein abundance values were calculated with two peptides per protein minimum using aLFQ29 for in vitro myogenesis experiments, while mapDIA v2.2.030 was used for statistical analysis of patient data.…”

Section: Methodsmentioning

confidence: 99%

Comprehensive proteome analysis of human skeletal muscle in cachexia and sarcopenia: a pilot study

Ebhardt

Degen

Tadini

et al. 2017

J cachexia sarcopenia muscle

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BackgroundCancer cachexia (cancer‐induced muscle wasting) is found in a subgroup of cancer patients leaving the patients with a poor prognosis for survival due to a lower tolerance of the chemotherapeutic drug. The cause of the muscle wasting in these patients is not fully understood, and no predictive biomarker exists to identify these patients early on. Skeletal muscle loss is an inevitable consequence of advancing age. As cancer frequently occurs in old age, identifying and differentiating the molecular mechanisms mediating muscle wasting in cancer cachexia vs. age‐related sarcopenia are a challenge. However, the ability to distinguish between them is critical for early intervention, and simple measures of body weight may not be sufficiently sensitive to detect cachexia early.MethodsWe used a range of omics approaches: (i) undepleted proteome was quantified using advanced high mass accuracy mass spectrometers in SWATH‐MS acquisition mode; (ii) phospho epitopes were quantified using protein arrays; and (iii) morphology was assessed using fluorescent microscopy.ResultsWe quantified the soluble proteome of muscle biopsies from cancer cachexia patients and compared them with cohorts of cancer patients and healthy individuals with and without age‐related muscle loss (aka age‐related sarcopenia). Comparing the proteomes of these cohorts, we quantified changes in muscle contractile myosins and energy metabolism allowing for a clear identification of cachexia patients. In an in vitro time lapse experiment, we mimicked cancer cachexia and identified signal transduction pathways governing cell fusion to play a pivotal role in preventing muscle regeneration.ConclusionsThe work presented here lays the foundation for further understanding of muscle wasting diseases and holds the promise of overcoming ambiguous weight loss as a measure for defining cachexia to be replaced by a precise protein signature.

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Section: Methodsmentioning

confidence: 99%

Comprehensive proteome analysis of human skeletal muscle in cachexia and sarcopenia: a pilot study

Ebhardt

Degen

Tadini

et al. 2017

J cachexia sarcopenia muscle

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“…Case studies Some recent examples where researchers have used OpenMS to build complex analysis tools include improvements to a label-free quantification pipeline [1] , the development of a metabolomics workflow [33] , the integration of RNA cross-linking workflows [34] and the addition of a workflow for targeted data analysis using SWATH-MS [35] . In addition, OpenMS has been extended to include a probabilistic scoring engine [36] , SILAC analysis [37] , isobaric quantification, random-access XML file parsing [38] and an MS simulation framework [39] .…”

Section: Reproducible Researchmentioning

confidence: 99%

“…For maximal sensitivity, the authors chose a targeted analysis strategy for SWATH-MS data [41] which was developed previously using the OpenMS software library. In particular, the OpenSWATH analysis module [35] was developed using existing algorithms and data structures for file parsing, RT alignment and signal processing. The developers could thus rely on the well-tested OpenMS framework for core tasks and focus their efforts on the development of novel algorithms.…”

Section: Swath Data Analysismentioning

confidence: 99%

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

et al. 2016

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“…In section "Results and discussion", we compare the performance of the proposed symmetric difference scoring model with the widely used shared peaks count scoring model. We consider experimental mass spectrometric data from synthesized peptides of known sequences (SWATH Gold Standard dataset [9]). The proof-of-concept implementation is available under a BSD license [10] and we plan to integrate it into the OpenMS framework [11].…”

Section: Introductionmentioning

confidence: 99%

A Better Scoring Model for De Novo Peptide Sequencing: The Symmetric Difference Between Explained and Measured Masses

Gillet

Rösch

Tschager

et al. 2016

Lecture Notes in Computer Science

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Background: Given a peptide as a string of amino acids, the masses of all its prefixes and suffixes can be found by a trivial linear scan through the amino acid masses. The inverse problem is the ideal de novo peptide sequencing problem: Given all prefix and suffix masses, determine the string of amino acids. In biological reality, the given masses are measured in a lab experiment, and measurements by necessity are noisy. The (real, noisy) de novo peptide sequencing problem therefore has a noisy input: a few of the prefix and suffix masses of the peptide are missing and a few other masses are given in addition. For this setting, we ask for an amino acid string that explains the given masses as accurately as possible.Results: Past approaches interpreted accuracy by searching for a string that explains as many masses as possible. We feel, however, that it is not only bad to not explain a mass that appears, but also to explain a mass that does not appear. We propose to minimize the symmetric difference between the set of given masses and the set of masses that the string explains. For this new optimization problem, we propose an efficient algorithm that computes both the best and the k best solutions. Proof-of-concept experiments on measurements of synthesized peptides show that our approach leads to better results compared to finding a string that explains as many given masses as possible. Conclusions:We conclude that considering the symmetric difference as optimization goal can improve the identification rates for de novo peptide sequencing. A preliminary version of this work has been presented at WABI 2016.

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OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data

Abstract: OpenSWATH enables automated, targeted analysis of data-independent acquisition MS data.

Cited by 727 publications

References 37 publications

Comprehensive proteome analysis of human skeletal muscle in cachexia and sarcopenia: a pilot study

Comprehensive proteome analysis of human skeletal muscle in cachexia and sarcopenia: a pilot study

OpenMS: a flexible open-source software platform for mass spectrometry data analysis

A Better Scoring Model for De Novo Peptide Sequencing: The Symmetric Difference Between Explained and Measured Masses

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