Multiplexed Quantification for Data-Independent Acquisition

Minogue, Catherine E.; Hebert, Alexander S.; Rensvold, Jarred W.; Westphall, Michael S.; Pagliarini, David J.; Coon, Joshua J.

doi:10.1021/ac503593d

Cited by 48 publications

(66 citation statements)

References 22 publications

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“…no. CRL-1772) myoblasts and differentiated myotubes 19 , and in theory any cell that is auxotroph for lysine would be suitable for NeuCode labeling experiments.<CAUTION> The cell lines used in your research should be regularly checked to ensure they are authentic and are not infected with mycoplasma.SILAC DMEM Flex Media, no glucose, no phenol red (Thermo Fisher Scientific, cat. no.…”

Section: Methodsmentioning

confidence: 99%

“…no. CRL-1772) myoblasts and differentiated myotubes 19 , and in theory any cell that is auxotroph for lysine would be suitable for NeuCode labeling experiments.…”

Section: Methodsmentioning

confidence: 99%

“…Since 2013, NeuCode SILAC has been applied to a number of different experimental models including yeast 4,11 , adherent cell lines 19 , nematodes 20 , and mice 21 . In this protocol we highlight the use of NeuCode for adherent cell lines and mouse models; however, application of the method to other model systems is straight forward and simply requires the dietary replacement of normal lysine with NeuCode lysine isotopologues.…”

Section: Applications Of Neucode Silacmentioning

confidence: 99%

“…NeuCode can also be used for other proteomics strategies including data-independent acquisition 19 , targeted proteomics 25 , and even top-down approaches 26,27 . In this protocol we will focus only on data-dependent shotgun proteomic applications and refer readers to the documents cited above for alternative proteomics applications.…”

Section: Applications Of Neucode Silacmentioning

confidence: 99%

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Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice

et al. 2018

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We describe a protocol for multiplexed proteomic analysis using neutron-encoded (NeuCode) stable isotope labeling of amino acids in cells (SILAC) or mice (SILAM)). This method currently enables simultaneous comparison of up to 9 treatment and control proteomes. Another important advantage over traditional SILAC/SILAM is that shorter labeling times are required. Exploiting the small mass differences that correspond to subtle differences in neutron binding energies of different isotopes, the amino acids used in NeuCode SILAC/SILAM differ in mass by just a few milliDaltons. Isotopologues of lysine are introduced to cells or mammals, via the culture medium or diet, respectively, to metabolically label the proteome. Labeling time is approximately two weeks for cultured cells and 3-4 weeks for mammals. The proteins are then extracted, relevant samples are combined, and these are enzymatically digested with lysyl endopeptidase (Lys-C). The resultant peptides are chromatographically separated and then mass analyzed. During MS data acquisition, high resolution MS1 spectra (≥240,000 resolving power @ m/z 400) reveal the embedded isotopic signatures, enabling relative quantification, while tandem mass spectra, collected at lower resolutions provide peptide identities. Both types of spectra are processed using NeuCode-enabled MaxQuant software. In total, the approximate completion time is 3-5 weeks.

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Section: Methodsmentioning

confidence: 99%

“…no. CRL-1772) myoblasts and differentiated myotubes 19 , and in theory any cell that is auxotroph for lysine would be suitable for NeuCode labeling experiments.…”

Section: Methodsmentioning

confidence: 99%

Section: Applications Of Neucode Silacmentioning

confidence: 99%

Section: Applications Of Neucode Silacmentioning

confidence: 99%

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Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice

et al. 2018

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“…Unlike DDA, DIA methods are inherently not applicable to use of metabolic or chemical labels. This limitation is being overcome with approaches such as NeuCoDIA for multiplex analysis [57].…”

Section: Addressing the Challenges And Perspectivesmentioning

confidence: 99%

Advances in proteomics for production strain analysis

Landels

Evans

Noirel

et al. 2015

Current Opinion in Biotechnology

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Highlights Proteomics is widely used in production strain analysis  The value of specific strategies is discussed with reference to case studies  Methodologies often based on prior application to eukaryotic systems  New developments target quantitative accuracy and proteome coverage AbstractProteomics is the large-scale study and analysis of proteins, directed to analysing protein function in a cellular context. Since the vast majority of the processes occurring in a living cell rely on protein activity, proteomics offer a unique vantage point from which researchers can dissect, characterise, understand and manipulate biological systems. When developing a production strain, proteomics offers a versatile toolkit of analytical techniques. In this commentary, we highlight a number of recent developments in this field using three industrially relevant case studies: targeted proteomic analysis of heterologous pathways in E. coli, biofuel production in Synechocystis PCC6803 and proteomic investigations of lignocellulose degradation. We conclude by discussing future developments in proteomics that will impact upon metabolic engineering and process monitoring of bio-producer strains.

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Chemical isotope labeling for quantitative proteomics

Tian

Permentier

Bischoff

2021

Mass Spectrometry Reviews

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Advancements in liquid chromatography and mass spectrometry over the last decades have led to a significant development in mass spectrometry-based proteome quantification approaches. An increasingly attractive strategy is multiplex isotope labeling, which significantly improves the accuracy, precision and throughput of quantitative proteomics in the data-dependent acquisition mode.Isotope labeling-based approaches can be classified into MS1-based and MS2based quantification. In this review, we give an overview of approaches based on chemical isotope labeling and discuss their principles, benefits, and limitations with the goal to give insights into fundamental questions and provide a useful reference for choosing a method for quantitative proteomics. As a perspective, we discuss the current possibilities and limitations of multiplex, isotope labeling approaches for the data-independent acquisition mode, which is increasing in popularity.

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Multiplexed Quantification for Data-Independent Acquisition

Cited by 48 publications

References 22 publications

Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice

Multiplexed proteome analysis with neutron-encoded stable isotope labeling in cells and mice

Advances in proteomics for production strain analysis

Chemical isotope labeling for quantitative proteomics

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