Multiple Enzymatic Digestion for Enhanced Sequence Coverage of Proteins in Complex Proteomic Mixtures Using Capillary LC with Ion Trap MS/MS

Choudhary, Gargi; Wu, Shiaw‐Lin; Shieh, Paul; Hancock, William S.

doi:10.1021/pr025557n

Cited by 151 publications

(129 citation statements)

References 12 publications

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“…Higher protein coverage, which leads to improved ability to differentiate between protein isoforms and to identify sites of post-translational modifications, in some cases can be achieved by using multiple digestion enzymes (98,99). Another strategy is based on generation of synthetic peptides that are unique to a particular isoform of interest (59,60,100).…”

Section: Discussionmentioning

confidence: 99%

Interpretation of Shotgun Proteomic Data

Nesvizhskii

Aebersold

2005

Molecular & Cellular Proteomics

938

888

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The shotgun proteomic strategy based on digesting proteins into peptides and sequencing them using tandem mass spectrometry and automated database searching has become the method of choice for identifying proteins in most large scale studies. However, the peptide-centric nature of shotgun proteomics complicates the analysis and biological interpretation of the data especially in the case of higher eukaryote organisms. The same peptide sequence can be present in multiple different proteins or protein isoforms. Such shared peptides therefore can lead to ambiguities in determining the identities of sample proteins. In this article we illustrate the difficulties of interpreting shotgun proteomic data and discuss the need for common nomenclature and transparent informatic approaches. We also discuss related issues such as the state of protein sequence databases and their role in shotgun proteomic analysis, interpretation of relative peptide quantification data in the presence of multiple protein isoforms, the integration of proteomic and transcriptional data, and the development of a computational infrastructure for the integration of multiple diverse datasets. Molecular & Cellular Proteomics 4:1419 -1440, 2005.An explicit goal of proteomics is the identification and quantification of all the proteins expressed in a cell or tissue (1).Although not yet at the levels of data throughput and automation achieved in other genomic analyses such as DNA sequencing or microarray gene expression analysis, global protein profiling methods are rapidly evolving. This has been possible because of recent improvements in MS instrumentation, protein and peptide separation techniques, computational data analysis tools, and the availability of complete sequence databases for many species. As a result, analysis of complex protein mixtures using shotgun proteomics, a strategy based on the combination of protein digestion and MS/ MS-based peptide sequencing (2-4), has become widely adopted. The method allows protein identifications and, when combined with stable isotope labeling, quantification of the changes in the protein expression levels for hundreds of proteins in a single experiment (1).Compared with other MS-based proteomic technologies such as intact proteins sequencing (5, 6) or 2D 1 gel-based protein analysis (7), shotgun proteomic analysis has achieved a relatively high throughput. This is the result of a combination of several factors. Proteolytic digestion of proteins into shorter peptides simplifies MS/MS sequencing (peptides are easier to fragment in the mass spectrometer than intact proteins), whereas elimination of the 2D gel-based separation at the protein level simplifies sample handling and increases the overall data throughput. At the same time, computational analysis and interpretation of the data become more challenging (8 -13). The first and foremost computational challenge is the need to process large volumes of acquired MS/MS data with the purpose of identifying peptides that gave rise to observed spectra. This ch...

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Section: Discussionmentioning

confidence: 99%

Interpretation of Shotgun Proteomic Data

Nesvizhskii

Aebersold

2005

Molecular & Cellular Proteomics

938

888

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“…Trypsin is a common choice for digestion in proteomics because of its specific cleavage of peptide C-terminal arginine and lysine residues. The combination of trypsin with other proteases such as endoproteinase Lys-C is commonly used to enhance protein sequence coverage (33). Lys-C enzymes are tolerant to denaturants and only one labeled amino acid in isotope-labeled quantification experiments is required.…”

Section: Discussionmentioning

confidence: 99%

Choice of LC-MS Methods for the Absolute Quantification of Drug-Metabolizing Enzymes and Transporters in Human Tissue: a Comparative Cost Analysis

Feteisi

Achour

Barber

et al. 2015

AAPS J

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Abstract. The quantification of drug-metabolizing enzymes and transporters is important for in vitro-in vivo extrapolation (IVIVE) of xenobiotic clearance, which has become an integral part of drug development. There are different mass spectrometry-based techniques used for quantitative proteomics, and as more laboratories are opting for the use of these methods, selecting the most appropriate tool is becoming a concern. For the first time, we attempt to determine the significance of cost of different LC-MS methods of quantitative analysis of these proteins and to present a framework to objectively assess the choice of the techniques. Based on our analysis, quantification using labeled internal standards is more expensive per sample but provides higher quality data than label-free quantification. Quantification using absolute quantification synthetic peptides is the approach of choice for analyzing less than nine proteins, whereas when quantifying a defined set of proteins (10-50), such as enzymes, in a reasonably large number of samples (20-100), the quantification concatemer technique is more economical, followed by label-free quantification. When analyzing proteomes or sub-proteomes (≥500 proteins), label-free quantification is more cost-effective than the use of labeled internal standards. A cost-benefit approach is described to assess the choice of the most appropriate mass spectrometrybased approach for the quantification of proteins relevant to IVIVE.

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“…For this reason, parallel digestions using different enzymes can improve sequence coverage by identifying more peptides resulting in increases confidence in protein identification in proteome profiling. 168,169 Digital microfluidics seems well-suited to such tasks, given that droplets containing samples can be manipulated, split, and delivered to multiple locations in a device in parallel. To test this idea, we developed a parallel digestion scheme in which an initial droplet was reduced and alkylated, and was then split and delivered to two different gel microreactors --one containing trypsin, and one containing pepsin.…”

Section: Multiplexed Digestionmentioning

confidence: 99%

A Digital Microfluidic Approach to Proteomic Sample Processing

2009

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Proteome profiling is the identification and quantitation of all proteins in biological samples. An important application of proteome profiling that has received much attention is clinical proteomics, a field that promises the discovery of biomarkers that will be useful for early diagnosis and prognosis of diseases. While clinical proteomic methods vary widely, a common characteristic is the need for (i) extraction of proteins from complex biological fluids and (ii) extensive biochemical processing (reduction, alkylation and enzymatic digestion) prior to analysis. However, the lack of standardized sample handling and processing in proteomics is a major limitation for the field. The conventional macroscale manual sample handling requires multiple containers and transfers, which often leads to sample loss and contamination. For clinical proteomics to be adopted as a gold standard for clinical measures, the issue of irreproducibility needs to be addressed. A potential solution to this problem is to form integrated systems for sample handling and processing, and in this dissertation, I describe my work towards realizing this goal using digital microfluidics (DMF). DMF is a technique characterized by the manipulation of discrete droplets (100 nL -10 L) on an array of electrodes by the application of electrical fields. It is well-suited for carrying out rapid, sequential, miniaturized automated biochemical assays. This thesis demonstrates how DMF can be a powerful tool capable of automating several protein handling and processing steps used in proteomics.iii Methods for implementing proteomic multi-step solution-phase processes (reduction, alkylation, and digestion) on DMF were developed. This was accompanied by the development of heterogenous enzymatic microreactors for efficient protein digestion. Strategies for reducing non-specific adsorption were developed. Finally, in proof-of-concept work, a combination of protein extraction and protein processing was demonstrated on DMF devices.iv ACKNOWLEDGEMENTS

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Multiple Enzymatic Digestion for Enhanced Sequence Coverage of Proteins in Complex Proteomic Mixtures Using Capillary LC with Ion Trap MS/MS

Cited by 151 publications

References 12 publications

Interpretation of Shotgun Proteomic Data

Interpretation of Shotgun Proteomic Data

Choice of LC-MS Methods for the Absolute Quantification of Drug-Metabolizing Enzymes and Transporters in Human Tissue: a Comparative Cost Analysis

A Digital Microfluidic Approach to Proteomic Sample Processing

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