Jimmy K. Eng

An approach to correlate tandem mass spectral data of peptides with amino acid sequences in a protein database

A method to correlate the uninterpreted tandem mass spectra of peptides produced under low energy (10–50 eV) collision conditions with amino acid sequences in the Genpept database has been developed. In this method the protein database is searched to identify linear amino acid sequences within a mass tolerance of ±1 u of the precursor ion molecular weight A cross-correlation function is then used to provide a measurement of similarity between the mass-to-charge ratios for the fragment ions predicted from amino acid sequences obtained from the database and the fragment ions observed in the tandem mass spectrum. In general, a difference greater than 0.1 between the normalized cross-correlation functions of the first- and second-ranked search results indicates a successful match between sequence and spectrum. Searches of species-specific protein databases with tandem mass spectra acquired from peptides obtained from the enzymatically digested total proteins of E. coli and S. cerevisiae cells allowed matching of the spectra to amino acid sequences within proteins of these organisms. The approach described in this manuscript provides a convenient method to interpret tandem mass spectra with known sequences in a protein database.

The innate immune response to bacterial flagellin is mediated by Toll-like receptor 5

The innate immune system recognizes pathogen-associated molecular patterns (PAMPs) that are expressed on infectious agents, but not on the host. Toll-like receptors (TLRs) recognize PAMPs and mediate the production of cytokines necessary for the development of effective immunity. Flagellin, a principal component of bacterial flagella, is a virulence factor that is recognized by the innate immune system in organisms as diverse as flies, plants and mammals. Here we report that mammalian TLR5 recognizes bacterial flagellin from both Gram-positive and Gram-negative bacteria, and that activation of the receptor mobilizes the nuclear factor NF-κB and stimulates tumour necrosis factor-α production. TLR5-stimulating activity was purified from Listeria monocytogenes culture supernatants and identified as flagellin by tandem mass spectrometry. Expression of L. monocytogenes flagellin in non-flagellated Escherichia coli conferred on the bacterium the ability to activate TLR5, whereas deletion of the flagellin genes from Salmonella typhimurium abrogated TLR5-stimulating activity. All known TLRs signal through the adaptor protein MyD88. Mice challenged with bacterial flagellin rapidly produced systemic interleukin-6, whereas MyD88-null mice did not respond to flagellin. Our data suggest that TLR5, a member of the evolutionarily conserved Toll-like receptor family, has evolved to permit mammals specifically to detect flagellated bacterial pathogens.

Direct analysis of protein complexes using mass spectrometry

We describe a rapid, sensitive process for comprehensively identifying proteins in macromolecular complexes that uses multidimensional liquid chromatography (LC) and tandem mass spectrometry (MS/MS) to separate and fragment peptides. The SEQUEST algorithm, relying upon translated genomic sequences, infers amino acid sequences from the fragment ions. The method was applied to the Saccharomyces cerevisiae ribosome leading to the identification of a novel protein component of the yeast and human 40S subunit. By offering the ability to identify >100 proteins in a single run, this process enables components in even the largest macromolecular complexes to be analyzed comprehensively.

Quantitative profiling of differentiation-induced microsomal proteins using isotope-coded affinity tags and mass spectrometry

An approach to the systematic identification and quantification of the proteins contained in the microsomal fraction of cells is described. It consists of three steps: (1) preparation of microsomal fractions from cells or tissues representing different states; (2) covalent tagging of the proteins with isotope-coded affinity tag (ICAT) reagents followed by proteolysis of the combined labeled protein samples; and (3) isolation, identification, and quantification of the tagged peptides by multidimensional chromatography, automated tandem mass spectrometry, and computational analysis of the obtained data. The method was used to identify and determine the ratios of abundance of each of 491 proteins contained in the microsomal fractions of naïve and in vitro– differentiated human myeloid leukemia (HL-60) cells. The method and the new software tools to support it are well suited to the large-scale, quantitative analysis of membrane proteins and other classes of proteins that have been refractory to standard proteomics technology.

Integrated Genomic and Proteomic Analyses of Gene Expression in Mammalian Cells

Using DNA microarrays together with quantitative proteomic techniques (ICAT reagents, two-dimensional DIGE, and MS), we evaluated the correlation of mRNA and protein levels in two hematopoietic cell lines representing distinct stages of myeloid differentiation, as well as in the livers of mice treated for different periods of time with three different peroxisome proliferative activated receptor agonists. We observe that the differential expression of mRNA (up or down) can capture at most 40% of the variation of protein expression. Although the overall pattern of protein expression is similar to that of mRNA expression, the incongruent expression between mRNAs and proteins emphasize the importance of posttranscriptional regulatory mechanisms in cellular development or perturbation that can be unveiled only through integrated analyses of both proteins and mRNAs.

Complementary Profiling of Gene Expression at the Transcriptome and Proteome Levels in Saccharomyces cerevisiae

Using an integrated genomic and proteomic approach, we have investigated the effects of carbon source perturbation on steady-state gene expression in the yeast Saccharomyces cerevisiae growing on either galactose or ethanol. For many genes, significant differences between the abundance ratio of the messenger RNA transcript and the corresponding protein product were observed. Insights into the perturbative effects on genes involved in respiration, energy generation, and protein synthesis were obtained that would not have been apparent from measurements made at either the messenger RNA or protein level alone, illustrating the power of integrating different types of data obtained from the same sample for the comprehensive characterization of biological systems and processes.

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.

A guided tour of the Trans‐Proteomic Pipeline

The Trans‐Proteomic Pipeline (TPP) is a suite of software tools for the analysis of MS/MS data sets. The tools encompass most of the steps in a proteomic data analysis workflow in a single, integrated software system. Specifically, the TPP supports all steps from spectrometer output file conversion to protein‐level statistical validation, including quantification by stable isotope ratios. We describe here the full workflow of the TPP and the tools therein, along with an example on a sample data set, demonstrating that the setup and use of the tools are straightforward and well supported and do not require specialized informatic resources or knowledge.

The PeptideAtlas project

The completion of the sequencing of the human genome and the concurrent, rapid development of high-throughput proteomic methods have resulted in an increasing need for automated approaches to archive proteomic data in a repository that enables the exchange of data among researchers and also accurate integration with genomic data. PeptideAtlas () addresses these needs by identifying peptides by tandem mass spectrometry (MS/MS), statistically validating those identifications and then mapping identified sequences to the genomes of eukaryotic organisms. A meaningful comparison of data across different experiments generated by different groups using different types of instruments is enabled by the implementation of a uniform analytic process. This uniform statistical validation ensures a consistent and high-quality set of peptide and protein identifications. The raw data from many diverse proteomic experiments are made available in the associated PeptideAtlas repository in several formats. Here we present a summary of our process and details about the Human, Drosophila and Yeast PeptideAtlas builds.

Complementary Profiling of Gene Expression at the Transcriptome and Proteome Levels in S. cerevisiae

Using an integrated genomic and proteomic approach, we have investigated the effects of carbon source perturbation on steady-state gene expression in the yeast Saccharomyces cerevisiae growing on either galactose or ethanol. For many genes, significant differences between the abundance ratio of the messenger RNA transcript and the corresponding protein product were observed. Insights into the perturbative effects on genes involved in respiration, energy generation, and protein synthesis were obtained that would not have been apparent from measurements made at either the messenger RNA or protein level alone, illustrating the power of integrating different types of data obtained from the same sample for the comprehensive characterization of biological systems and processes.