Xiao-jun Li

A uniform proteomics MS/MS analysis platform utilizing open XML file formats

The analysis of tandem mass (MS/MS) data to identify and quantify proteins is hampered by the heterogeneity of file formats at the raw spectral data, peptide identification, and protein identification levels. Different mass spectrometers output their raw spectral data in a variety of proprietary formats, and alternative methods that assign peptides to MS/MS spectra and infer protein identifications from those peptide assignments each write their results in different formats. Here we describe an MS/MS analysis platform, the Trans‐Proteomic Pipeline, which makes use of open XML file formats for storage of data at the raw spectral data, peptide, and protein levels. This platform enables uniform analysis and exchange of MS/MS data generated from a variety of different instruments, and assigned peptides using a variety of different database search programs. We demonstrate this by applying the pipeline to data sets generated by ThermoFinnigan LCQ, ABI 4700 MALDI‐TOF/TOF, and Waters Q‐TOF instruments, and searched in turn using SEQUEST, Mascot, and COMET.

Quantitative phosphoproteome analysis using a dendrimer conjugation chemistry and tandem mass spectrometry

We present a robust and general method for the identification and relative quantification of phosphorylation sites in complex protein mixtures. It is based on a new chemical derivatization strategy using a dendrimer as a soluble polymer support and tandem mass spectrometry (MS/MS). In a single step, phosphorylated peptides are covalently conjugated to a dendrimer in a reaction catalyzed by carbodiimide and imidazole. Modified phosphopeptides are released from the dendrimer via acid hydrolysis and analyzed by MS/MS. When coupled with an initial antiphosphotyrosine protein immunoprecipitation step and stable-isotope labeling, in a single experiment, we identified all known tyrosine phosphorylation sites within the immunoreceptor tyrosine-based activation motifs (ITAM) of the T-cell receptor (TCR) CD3 chains, and previously unknown phosphorylation sites on total 97 tyrosine phosphoproteins and their interacting partners in human T cells. The dynamic changes in phosphorylation were quantified in these proteins.

Identification of TFB5, a new component of general transcription and DNA repair factor IIH

We previously described the use of quantitative proteomics to study macromolecular complexes. Applying the method to analyze a yeast RNA polymerase II preinitiation complex, we identified a new 8-kDa protein, encoded by the uncharacterized open reading frame YDR079c-a, as a potential new component of the preinitiation complex. Here we show that YDR079c-a is a bona fide component of polymerase II preinitiation complexes and investigate its role in transcription. YDR079c-a is recruited to promoters both in vivo and in vitro and is required for efficient transcription in vitro and for normal induction of GAL genes. In addition, YDR079c-a is a core component of general transcription and DNA repair factor IIH and is required for efficient recruitment of TFIIH to a promoter. Yeast lacking YDR079c-a grow slowly, and, like strains carrying mutations in core TFIIH subunits, are sensitive to ultraviolet radiation. YDR079c-a is conserved throughout evolution, and mutations in the human ortholog account for a DNA repair–deficient form of the tricothiodystrophy disorder called TTD-A2. The identification of a new, evolutionarily conserved, core TFIIH subunit is essential for our understanding of TFIIH function in transcription, DNA repair and human disease.

The Application of New Software Tools to Quantitative Protein Profiling Via Isotope-coded Affinity Tag (ICAT) and Tandem Mass Spectrometry II. Evaluation of Tandem Mass Spectrometry Methodologies for Large-Scale Protein Analysis, and the Application of Statistical Tools for Data Analysis and Interpretation

Proteomic approaches to biological research that will prove the most useful and productive require robust, sensitive, and reproducible technologies for both the qualitative and quantitative analysis of complex protein mixtures. Here we applied the isotope-coded affinity tag (ICAT) approach to quantitative protein profiling, in this case proteins that copurified with lipid raft plasma membrane domains isolated from control and stimulated Jurkat human T cells. With the ICAT approach, cysteine residues of the two related protein isolates were covalently labeled with isotopically normal and heavy versions of the same reagent, respectively. Following proteolytic cleavage of combined labeled proteins, peptides were fractionated by multidimensional chromatography and subsequently analyzed via automated tandem mass spectrometry. Individual tandem mass spectrometry spectra were searched against a human sequence database, and a variety of recently developed, publicly available software applications were used to sort, filter, analyze, and compare the results of two repetitions of the same experiment. In particular, robust statistical modeling algorithms were used to assign measures of confidence to both peptide sequences and the proteins from which they were likely derived, identified via the database searches. We show that by applying such statistical tools to the identification of T cell lipid raft-associated proteins, we were able to estimate the accuracy of peptide and protein identifications made. These tools also allow for determination of the false positive rate as a function of user-defined data filtering parameters, thus giving the user significant control over and information about the final output of large-scale proteomic experiments. With the ability to assign probabilities to all identifications, the need for manual verification of results is substantially reduced, thus making the rapid evaluation of large proteomic datasets possible. Finally, by repeating the experiment, information relating to the general reproducibility and validity of this approach to large-scale proteomic analyses was also obtained.