Single-Stranded DNA as a Cleavable Linker for Bioorthogonal Click Chemistry-Based Proteomics

Zheng, Tianqing; Jiang, Hao; Wu, Peng

doi:10.1021/bc400093x

Cited by 18 publications

(7 citation statements)

References 31 publications

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“…In summary,t he multifunctional capture reagents reported herein enable robust identification of metabolically-tagged myristoylated proteomes,w ith unprecedented confidence resulting from the combination of chemicalprobe-based enrichment and release and direct detection of lipid-modified peptides by MS.P reviously reported reagents [13] typically required an extra proteolytic step and their capacity to enable the detection of lipidated peptides has not been demonstrated. Herein, we report the largest database (87 counts) of experimentally validated human proteins that are myristoylated at an endogenous level in living cells.…”

Section: Methodsmentioning

confidence: 99%

Multifunctional Reagents for Quantitative Proteome‐Wide Analysis of Protein Modification in Human Cells and Dynamic Profiling of Protein Lipidation During Vertebrate Development

et al. 2015

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Novel multifunctional reagents were applied in combination with al ipid probe for affinity enrichment of myristoylated proteins and direct detection of lipid-modified tryptic peptides by mass spectrometry.T his method enables high-confidence identification of the myristoylated proteome on an unprecedented scale in cell culture,and allowed the first quantitative analysis of dynamic changes in protein lipidation during vertebrate embryonic development.

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Section: Methodsmentioning

confidence: 99%

Multifunctional Reagents for Quantitative Proteome‐Wide Analysis of Protein Modification in Human Cells and Dynamic Profiling of Protein Lipidation During Vertebrate Development

et al. 2015

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“…Alkenes and alkynes have been used to tag proteins, DNA, RNA, lipids, and sugars, enabling their labeling with tetrazine-fluorophore conjugates for imaging ( Agarwal et al., 2015 , Asare-Okai et al., 2014 , Busskamp et al., 2014 , Denk et al., 2014 , Kurra et al., 2014 , Lang et al., 2012a , Lang et al., 2012b , Nikic et al., 2014 , Patterson et al., 2014 , Pyka et al., 2014 , Selvaraj et al., 2015 , Uttamapinant et al., 2015 , Yang et al., 2012 ). However, while azide-alkyne reactions form the basis of strategies to enrich tagged biomolecules for their identification by mass spectrometry (MS) ( Bagert et al., 2016 , Chesarino et al., 2014 , Dieterich et al., 2006 , Dieterich et al., 2007 , Kleiner et al., 2015 , Smeekens et al., 2015 , Vanbeselaere et al., 2012 , Zhang et al., 2013 , Zheng et al., 2013 ), there are currently no methods for enriching and identifying biomolecules labeled with strained alkenes or alkynes through inverse electron-demand Diels-Alder reactions.…”

Section: Introductionmentioning

confidence: 99%

Tagging and Enriching Proteins Enables Cell-Specific Proteomics

Elliott

Bianco

Townsley

et al. 2016

Cell Chemical Biology

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SummaryCell-specific proteomics in multicellular systems and whole animals is a promising approach to understand the differentiated functions of cells and tissues. Here, we extend our stochastic orthogonal recoding of translation (SORT) approach for the co-translational tagging of proteomes with a cyclopropene-containing amino acid in response to diverse codons in genetically targeted cells, and create a tetrazine-biotin probe containing a cleavable linker that offers a way to enrich and identify tagged proteins. We demonstrate that SORT with enrichment, SORT-E, efficiently recovers and enriches SORT tagged proteins and enables specific identification of enriched proteins via mass spectrometry, including low-abundance proteins. We show that tagging at distinct codons enriches overlapping, but distinct sets of proteins, suggesting that tagging at more than one codon enhances proteome coverage. Using SORT-E, we accomplish cell-specific proteomics in the fly. These results suggest that SORT-E will enable the definition of cell-specific proteomes in animals during development, disease progression, and learning and memory.

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“…Several chemoproteomic approaches have been developed for identifying specific sites in proteins that undergo S -sulfenylation [ 6 – 10 ]. Nevertheless, these experimental methods are often expensive and time-consuming.…”

Section: Introductionmentioning

confidence: 99%

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

Bui

Weng

et al. 2016

BMC Genomics

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BackgroundProtein S-sulfenylation is a type of post-translational modification (PTM) involving the covalent binding of a hydroxyl group to the thiol of a cysteine amino acid. Recent evidence has shown the importance of S-sulfenylation in various biological processes, including transcriptional regulation, apoptosis and cytokine signaling. Determining the specific sites of S-sulfenylation is fundamental to understanding the structures and functions of S-sulfenylated proteins. However, the current lack of reliable tools often limits researchers to use expensive and time-consuming laboratory techniques for the identification of S-sulfenylation sites. Thus, we were motivated to develop a bioinformatics method for investigating S-sulfenylation sites based on amino acid compositions and physicochemical properties.ResultsIn this work, physicochemical properties were utilized not only to identify S-sulfenylation sites from 1,096 experimentally verified S-sulfenylated proteins, but also to compare the effectiveness of prediction with other characteristics such as amino acid composition (AAC), amino acid pair composition (AAPC), solvent-accessible surface area (ASA), amino acid substitution matrix (BLOSUM62), position-specific scoring matrix (PSSM), and positional weighted matrix (PWM). Various prediction models were built using support vector machine (SVM) and evaluated by five-fold cross-validation. The model constructed from hybrid features, including PSSM and physicochemical properties, yielded the best performance with sensitivity, specificity, accuracy and MCC measurements of 0.746, 0.737, 0.738 and 0.337, respectively. The selected model also provided a promising accuracy (0.693) on an independent testing dataset. Additionally, we employed TwoSampleLogo to help discover the difference of amino acid composition among S-sulfenylation, S-glutathionylation and S-nitrosylation sites.ConclusionThis work proposed a computational method to explore informative features and functions for protein S-sulfenylation. Evaluation by five-fold cross validation indicated that the selected features were effective in the identification of S-sulfenylation sites. Moreover, the independent testing results demonstrated that the proposed method could provide a feasible means for conducting preliminary analyses of protein S-sulfenylation. We also anticipate that the uncovered differences in amino acid composition may facilitate future studies of the extensive crosstalk among S-sulfenylation, S-glutathionylation and S-nitrosylation.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-2299-1) contains supplementary material, which is available to authorized users.

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Single-Stranded DNA as a Cleavable Linker for Bioorthogonal Click Chemistry-Based Proteomics

Cited by 18 publications

References 31 publications

Multifunctional Reagents for Quantitative Proteome‐Wide Analysis of Protein Modification in Human Cells and Dynamic Profiling of Protein Lipidation During Vertebrate Development

Multifunctional Reagents for Quantitative Proteome‐Wide Analysis of Protein Modification in Human Cells and Dynamic Profiling of Protein Lipidation During Vertebrate Development

Tagging and Enriching Proteins Enables Cell-Specific Proteomics

SOHSite: incorporating evolutionary information and physicochemical properties to identify protein S-sulfenylation sites

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