Jimmy K. Eng

Bio: Jimmy K. Eng is an academic researcher from University of Washington. The author has contributed to research in topics: Proteome & Mass spectrometry. The author has an hindex of 77, co-authored 168 publications receiving 35701 citations. Previous affiliations of Jimmy K. Eng include Oregon Health & Science University & Fred Hutchinson Cancer Research Center.

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

Abstract: 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-kappaB and stimulates tumour necrosis factor-alpha 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

Abstract: 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.

Integrated genomic and proteomic analyses of a systematically perturbed metabolic network.

Abstract: We demonstrate an integrated approach to build, test, and refine a model of a cellular pathway, in which perturbations to critical pathway components are analyzed using DNA microarrays, quantitative proteomics, and databases of known physical interactions. Using this approach, we identify 997 messenger RNAs responding to 20 systematic perturbations of the yeast galactose-utilization pathway, provide evidence that approximately 15 of 289 detected proteins are regulated posttranscriptionally, and identify explicit physical interactions governing the cellular response to each perturbation. We refine the model through further iterations of perturbation and global measurements, suggesting hypotheses about the regulation of galactose utilization and physical interactions between this and a variety of other metabolic pathways.

Method to Correlate Tandem Mass Spectra of Modified Peptides to Amino Acid Sequences in the Protein Database

Abstract: A method to correlate uninterpreted tandem mass spectra of modified peptides, produced under low-energy (10-50 eV) collision conditions, with amino acid sequences in a protein database has been developed. The fragmentation patterns observed in the tandem mass spectra of peptides containing covalent modifications is used to directly search and fit linear amino acid sequences in the database. Specific information relevant to sites of modification is not contained in the character-based sequence information of the databases. The search method considers each putative modification site as both modified and unmodified in one pass through the database and simultaneously considers up to three different sites of modification. The search method will identify the correct sequence if the tandem mass spectrum did not represent a modified peptide. This approach is demonstrated with peptides containing modifications such as S-carboxymethylated cysteine, oxidized methionine, phosphoserine, phosphothreonine, or phosphotyrosine. In addition, a scanning approach is used in which neutral loss scans are used to initiate the acquisition of product ion MS/MS spectra of doubly charged phosphorylated peptides during a single chromatographic run for data analysis with the database-searching algorithm. The approach described in this paper provides a convenient method to match the nascent tandem mass spectra of modified peptides to sequences in a protein database and thereby identify previously unknown sites of modification.

MaxQuant enables high peptide identification rates, individualized p.p.b.-range mass accuracies and proteome-wide protein quantification.

Abstract: Efficient analysis of very large amounts of raw data for peptide identification and protein quantification is a principal challenge in mass spectrometry (MS)-based proteomics. Here we describe MaxQuant, an integrated suite of algorithms specifically developed for high-resolution, quantitative MS data. Using correlation analysis and graph theory, MaxQuant detects peaks, isotope clusters and stable amino acid isotope-labeled (SILAC) peptide pairs as three-dimensional objects in m/z, elution time and signal intensity space. By integrating multiple mass measurements and correcting for linear and nonlinear mass offsets, we achieve mass accuracy in the p.p.b. range, a sixfold increase over standard techniques. We increase the proportion of identified fragmentation spectra to 73% for SILAC peptide pairs via unambiguous assignment of isotope and missed-cleavage state and individual mass precision. MaxQuant automatically quantifies several hundred thousand peptides per SILAC-proteome experiment and allows statistically robust identification and quantification of >4,000 proteins in mammalian cell lysates.

Probability-based protein identification by searching sequence databases using mass spectrometry data.

Abstract: Several algorithms have been described in the literature for protein identification by searching a sequence database using mass spectrometry data. In some approaches, the experimental data are peptide molecular weights from the digestion of a protein by an enzyme. Other approaches use tandem mass spectrometry (MS/MS) data from one or more peptides. Still others combine mass data with amino acid sequence data. We present results from a new computer program, Mascot, which integrates all three types of search. The scoring algorithm is probability based, which has a number of advantages: (i) A simple rule can be used to judge whether a result is significant or not. This is particularly useful in guarding against false positives. (ii) Scores can be compared with those from other types of search, such as sequence homology. (iii) Search parameters can be readily optimised by iteration. The strengths and limitations of probability-based scoring are discussed, particularly in the context of high throughput, fully automated protein identification.

Innate Immune Recognition

Abstract: ▪ Abstract The innate immune system is a universal and ancient form of host defense against infection. Innate immune recognition relies on a limited number of germline-encoded receptors. These receptors evolved to recognize conserved products of microbial metabolism produced by microbial pathogens, but not by the host. Recognition of these molecular structures allows the immune system to distinguish infectious nonself from noninfectious self. Toll-like receptors play a major role in pathogen recognition and initiation of inflammatory and immune responses. Stimulation of Toll-like receptors by microbial products leads to the activation of signaling pathways that result in the induction of antimicrobial genes and inflammatory cytokines. In addition, stimulation of Toll-like receptors triggers dendritic cell maturation and results in the induction of costimulatory molecules and increased antigen-presenting capacity. Thus, microbial recognition by Toll-like receptors helps to direct adaptive immune responses ...

Toll-like receptor signalling

Abstract: One of the mechanisms by which the innate immune system senses the invasion of pathogenic microorganisms is through the Toll-like receptors (TLRs), which recognize specific molecular patterns that are present in microbial components. Stimulation of different TLRs induces distinct patterns of gene expression, which not only leads to the activation of innate immunity but also instructs the development of antigen-specific acquired immunity. Here, we review the rapid progress that has recently improved our understanding of the molecular mechanisms that mediate TLR signalling.