Dataset Information

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification.

ABSTRACT: A major challenge in proteomics is the absolute accurate quantification of large numbers of proteins. QconCATs, artificial proteins that are concatenations of multiple standard peptides, are well established as an efficient means to generate standards for proteome quantification. Previously, QconCATs have been expressed in bacteria, but we now describe QconCAT expression in a robust, cell-free system. The new expression approach rescues QconCATs that previously were unable to be expressed in bacteria and can reduce the incidence of proteolytic damage to QconCATs. Moreover, it is possible to cosynthesize QconCATs in a highly-multiplexed translation reaction, coexpressing tens or hundreds of QconCATs simultaneously. By obviating bacterial culture and through the gain of high level multiplexing, it is now possible to generate tens of thousands of standard peptides in a matter of weeks, rendering absolute quantification of a complex proteome highly achievable in a reproducible, broadly deployable system.

SUBMITTER: Takemori N

PROVIDER: S-EPMC5724179 | biostudies-literature | 2017 Dec

REPOSITORIES: biostudies-literature

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Publications

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification.

Takemori Nobuaki N Takemori Ayako A Tanaka Yuki Y Endo Yaeta Y Hurst Jane L JL Gómez-Baena Guadalupe G Harman Victoria M VM Beynon Robert J RJ

Molecular & cellular proteomics : MCP 20171020 12

A major challenge in proteomics is the absolute accurate quantification of large numbers of proteins. QconCATs, artificial proteins that are concatenations of multiple standard peptides, are well established as an efficient means to generate standards for proteome quantification. Previously, QconCATs have been expressed in bacteria, but we now describe QconCAT expression in a robust, cell-free system. The new expression approach rescues QconCATs that previously were unable to be expressed in bac ...[more]

PMID: 29055021

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Project description:Despite data-independent acquisition (DIA) has been increasingly used for relative protein quantification, DIA-based label-free absolute quantification method has not been fully established. Here we present a novel DIA method using the TPA algorithm (DIA-TPA) for the absolute quantification of protein expressions in human liver microsomal and S9 samples. To validate this method, both data-dependent acquisition (DDA) and DIA experiments were conducted on 36 individual human liver microsome and S9 samples. The MS2-based DIA-TPA was able to quantify approximately twice as many proteins as the MS1-based DDA-TPA method, whereas protein concentrations determined by the two approaches were comparable. To evaluate the accuracy of the DIA-TPA method, we absolutely quantified carboxylesterase 1 concentrations in human liver S9 fractions using an established SILAC internal standard-based proteomic assay; the SILAC results were consistent with those obtained from DIA-TPA analysis. Finally, we employed a unique algorithm in DIA-TPA to distribute the MS signals from shared peptides to individual proteins or isoforms and successfully applied the method to the absolute quantification of several drug-metabolizing enzymes in human liver microsomes. In sum, the DIA-TPA method not only can absolutely quantify entire proteomes and specific proteins, but also has the capability quantifying proteins with shared peptides. SIGNIFICANCE: Data independent acquisition (DIA) has emerged as a powerful approach for relative protein quantification at the whole proteome level. However, DIA-based label-free absolute protein quantification (APQ) method has not been fully established. In the present study, we present a novel DIA-based label-free APQ approach, named DIA-TPA, with the capability absolutely quantifying proteins with shared peptides. The method was validated by comparing the quantification results of DIA-TPA with that obtained from stable isotope-labeled internal standard-based proteomic assays.

Dataset Information

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification.

Publications

MEERCAT: Multiplexed Efficient Cell Free Expression of Recombinant QconCATs For Large Scale Absolute Proteome Quantification.

Similar Datasets

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