David Schieltz

Bio: David Schieltz is an academic researcher from University of Washington. The author has contributed to research in topics: Mass spectrometry & SAGA complex. The author has an hindex of 23, co-authored 34 publications receiving 8208 citations. Previous affiliations of David Schieltz include University of California, Berkeley.

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.

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.

Proteasomal Proteomics: Identification of Nucleotide-sensitive Proteasome-interacting Proteins by Mass Spectrometric Analysis of Affinity-purified Proteasomes

Abstract: Ubiquitin-dependent proteolysis is catalyzed by the 26S proteasome, a dynamic complex of 32 different proteins whose mode of assembly and mechanism of action are poorly understood, in part due to the difficulties encountered in purifying the intact complex. Here we describe a one-step affinity method for purifying intact 26S proteasomes, 19S regulatory caps, and 20S core particles from budding yeast cells. Affinity-purified 26S proteasomes hydrolyze both model peptides and the ubiquitinated Cdk inhibitor Sic1. Affinity purifications performed in the absence of ATP or presence of the poorly hydrolyzable analog ATP-gamma -S unexpectedly revealed that a large number of proteins, including subunits of the skp1-cullin-F-box protein ligase (SCF) and anaphase-promoting complex (APC) ubiquitin ligases, copurify with the 19S cap. To identify these proteasome-interacting proteins, we used a recently developed method that enables the direct analysis of the composition of large protein complexes (DALPC) by mass spectrometry. Using DALPC, we identified more than 24 putative proteasome-interacting proteins, including Ylr421c (Daq1), which we demonstrate to be a new subunit of the budding yeast 19S cap, and Ygr232w (Nas6), which is homologous to a subunit of the mammalian 19S cap (PA700 complex). Additional PIPs include the heat shock proteins Hsp70 and Hsp82, the deubiquitinating enzyme Ubp6, and proteins involved in transcriptional control, mitosis, tubulin assembly, RNA metabolism, and signal transduction. Our data demonstrate that nucleotide hydrolysis modulates the association of many proteins with the 26S proteasome, and validate DALPC as a powerful tool for rapidly identifying stoichiometric and substoichiometric components of large protein assemblies.

Chd1 chromodomain links histone H3 methylation with SAGA- and SLIK-dependent acetylation

Abstract: The specific post-translational modifications to histones influence many nuclear processes including gene regulation, DNA repair and replication. Recent studies have identified effector proteins that recognize patterns of histone modification and transduce their function in downstream processes. For example, histone acetyltransferases (HATs) have been shown to participate in many essential cellular processes, particularly those associated with activation of transcription. Yeast SAGA (Spt-Ada-Gcn5 acetyltransferase) and SLIK (SAGA-like) are two highly homologous and conserved multi-subunit HAT complexes, which preferentially acetylate histones H3 and H2B and deubiquitinate histone H2B. Here we identify the chromatin remodelling protein Chd1 (chromo-ATPase/helicase-DNA binding domain 1) as a component of SAGA and SLIK. Our findings indicate that one of the two chromodomains of Chd1 specifically interacts with the methylated lysine 4 mark on histone H3 that is associated with transcriptional activity. Furthermore, the SLIK complex shows enhanced acetylation of a methylated substrate and this activity is dependent upon a functional methyl-binding chromodomain, both in vitro and in vivo. Our study identifies the first chromodomain that recognizes methylated histone H3 (Lys 4) and possibly identifies a larger subfamily of chromodomain proteins with similar recognition properties.

Direct analysis and identification of proteins in mixtures by LC/MS/MS and database searching at the low-femtomole level.

Abstract: A method to directly identify proteins contained in mixtures by microcolumn reversed-phase liquid chromatography electrospray ionization tandem mass spectrometry (LC/MS/MS) is studied. In this method, the mixture of proteins is digested with a proteolytic enzyme to produce a large collection of peptides. The complex peptide mixture is then separated on-line with a tandem mass spectrometer, acquiring large numbers of tandem mass spectra. The tandem mass spectra are then used to search a protein database to identify the proteins present. Results from standard protein mixtures show that proteins present in simple mixtures can be readily identified with a 30-fold difference in molar quantity, that the identifications are reproducible, and that proteins within the mixture can be identified at low femtomole levels. Based on these studies, methodology has been developed for direct LC/MS/MS analysis of proteins enriched by immunoaffinity precipitation, specific interaction with a protein−protein fusion product, a...

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.

Mass spectrometry-based proteomics

Abstract: Recent successes illustrate the role of mass spectrometry-based proteomics as an indispensable tool for molecular and cellular biology and for the emerging field of systems biology. These include the study of protein-protein interactions via affinity-based isolations on a small and proteome-wide scale, the mapping of numerous organelles, the concurrent description of the malaria parasite genome and proteome, and the generation of quantitative protein profiles from diverse species. The ability of mass spectrometry to identify and, increasingly, to precisely quantify thousands of proteins from complex samples can be expected to impact broadly on biology and medicine.

Functional organization of the yeast proteome by systematic analysis of protein complexes

Abstract: Most cellular processes are carried out by multiprotein complexes. The identification and analysis of their components provides insight into how the ensemble of expressed proteins (proteome) is organized into functional units. We used tandem-affinity purification (TAP) and mass spectrometry in a large-scale approach to characterize multiprotein complexes in Saccharomyces cerevisiae. We processed 1,739 genes, including 1,143 human orthologues of relevance to human biology, and purified 589 protein assemblies. Bioinformatic analysis of these assemblies defined 232 distinct multiprotein complexes and proposed new cellular roles for 344 proteins, including 231 proteins with no previous functional annotation. Comparison of yeast and human complexes showed that conservation across species extends from single proteins to their molecular environment. Our analysis provides an outline of the eukaryotic proteome as a network of protein complexes at a level of organization beyond binary interactions. This higher-order map contains fundamental biological information and offers the context for a more reasoned and informed approach to drug discovery.