Dataset Information

High-throughput peptide quantification using mTRAQ reagent triplex.

ABSTRACT: BACKGROUND: Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents. METHODS AND RESULTS: Here we propose a novel data analysis algorithm for peptide quantification in triplex mTRAQ experiments. It improved the accuracy of quantification in two features. First, it identified and separated triplex isotopic clusters of a peptide in each full MS scan. We designed a schematic model of triplex overlapping isotopic clusters, and separated triplex isotopic clusters by solving cubic equations, which are deduced from the schematic model. Second, it automatically determined the elution areas of peptides. Some peptides have similar atomic masses and elution times, so their elution areas can have overlaps. Our algorithm successfully identified the overlaps and found accurate elution areas. We validated our algorithm using standard protein mixture experiments. CONCLUSIONS: We showed that our algorithm was able to accurately quantify peptides in triplex mTRAQ experiments. Its software implementation is compatible with Trans-Proteomic Pipeline (TPP), and thus enables high-throughput analysis of proteomics data.

SUBMITTER: Yoon JY

PROVIDER: S-EPMC3044303 | biostudies-other | 2011

REPOSITORIES: biostudies-other

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High-throughput peptide quantification using mTRAQ reagent triplex.

Yoon Joo Young JY Yeom Jeonghun J Lee Heebum H Kim Kyutae K Na Seungjin S Park Kunsoo K Paek Eunok E Lee Cheolju C

BMC bioinformatics 20110215

<h4>Background</h4>Protein quantification is an essential step in many proteomics experiments. A number of labeling approaches have been proposed and adopted in mass spectrometry (MS) based relative quantification. The mTRAQ, one of the stable isotope labeling methods, is amine-specific and available in triplex format, so that the sample throughput could be doubled when compared with duplex reagents.<h4>Methods and results</h4>Here we propose a novel data analysis algorithm for peptide quantific ...[more]

PMID: 21342578

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Project description:In this work, we used our recently developed method Spec-seq to characterize the binding specificity of Glucocorticoid receptor in vitro. This GR Spec-seq experiment has been run twice separately (Dec 2014 and Mar 2015) with different library compositions. The basic workflow is the same as our previous work for lac repressor published in Genetics 198.3 (2014): 1329-1343. Recombinant human GR protein was used to facilitate in vitro DNA-binding and separation experiments. Bound and Unbound DNA fragments were separated in EMSA gels, purified, barcoded for further Illumina sequencing. An initial experiment was performed using the putative consensus sequence: AGAACA GGG TGTTCT; randomized library 1: AGAACN NSN NGTTCT [diversity =512]; randomized library 2: AGAANN GGG NNNTCT [diversity = 1024]; randomized library 3: AGAACA GGG TGNNNN [diversity =256]; randomized library 4: AGAACA GGGC NNNTCT [diversity = 64]. The initial total library diversity was ~1853 with a library composition of 10% positive control sequence + randomized libraries 1-4 + 5% negative control sequence. A 5th library containing 2304 sequences based on DDNACW KKN KGTTCT, where D="not C", N="any base", W="A or T" and K="G or T" was subsequently prepared and analyzed using similar ratios of control sequences. Binding conditions for EMSA were 100ng FAM-labelled dsDNA+ 0/0.5/1/2/4uM GR DBD protein for each lane, 1X NEB buffer 4. GR DBD was prepared as previously described. The EMSA was performed using a 9% 33:1 acrylamide gel and TB buffer, and was run at 200V for 30mins @ 0 degrees C. The 2uM protein lane used for final sequencing. Bound/unbound fractions resulting from EMSA of these libraries and conditions were used to generate PWMs as described. The GR PWM that was generated through this analysis was used to define relative binding energies using the patser program (35), which can be accessed online at (http://stormo.wustl.edu/consensus/cgi-bin/Server/Interface/patser.cgi ). Derived binding affinities are proportional to the inverse of the natural log of the calculated energies.

Dataset Information

High-throughput peptide quantification using mTRAQ reagent triplex.

Publications

High-throughput peptide quantification using mTRAQ reagent triplex.

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