Michael R. Hoopmann

Comet: An open‐source MS/MS sequence database search tool

Proteomics research routinely involves identifying peptides and proteins via MS/MS sequence database search. Thus the database search engine is an integral tool in many proteomics research groups. Here, we introduce the Comet search engine to the existing landscape of commercial and open‐source database search tools. Comet is open source, freely available, and based on one of the original sequence database search tools that has been widely used for many years.

Comparison of Database Search Strategies for High Precursor Mass Accuracy MS/MS Data

In shotgun proteomics, the analysis of tandem mass spectrometry data from peptides can benefit greatly from high mass accuracy measurements. In this study, we have evaluated two database search strategies which use high mass accuracy measurements of the peptide precursor ion. Our results indicate that peptide identifications are improved when spectra are searched with a wide mass tolerance window and precursor mass is used as a filter to discard incorrect matches. Database searches with a peptide data set constrained to peptides within a narrow mass window resulted in fewer peptide identifications but a significantly faster database search time.

Deconvolution of mixture spectra from ion-trap data-independent-acquisition tandem mass spectrometry

Data-independent tandem mass spectrometry isolates and fragments all of the molecular species within a given mass-to-charge window, regardless of whether a precursor ion was detected within the window. For shotgun proteomics on complex protein mixtures, data-independent MS/MS offers certain advantages over the traditional data-dependent MS/MS: identification of low-abundance peptides with insignificant precursor peaks, more direct relative quantification, free of biases caused by competing precursors and dynamic exclusion, and faster throughput due to simultaneous fragmentation of multiple peptides. However, data-independent MS/MS, especially on low-resolution ion-trap instruments, strains standard peptide identification programs, because of less precise knowledge of the peptide precursor mass and large numbers of spectra composed of two or more peptides. Here we describe a computer program called DeMux that deconvolves mixture spectra and improves the peptide identification rate by approximately 25%. We compare the number of identifications made by data-independent and data-dependent MS/MS at the peptide and protein levels: conventional data-dependent MS/MS makes a greater number of identifications but is less reproducible from run to run.

The 5300-year-old Helicobacter pylori genome of the Iceman

Stomach ache for a European mummy Five thousand years ago in the European Alps, a man was shot by an arrow, then clubbed to death. His body was subsequently mummified by ice until glacier retreat exhumed him in 1991. Subsequently, this ancient corpse has provided a trove of intriguing information about copper-age Europeans. Now, Maixner et al. have identified the human pathogen Helicobacter pylori within the mummys stomach contents. The strain the “Iceman” hosted appears to most closely resemble pathogenic Asian strains found today in Central and Southern Asia. Science, this issue p. 162 Mummified remains from the Alps reveal an unexpected history for a human pathogen. The stomach bacterium Helicobacter pylori is one of the most prevalent human pathogens. It has dispersed globally with its human host, resulting in a distinct phylogeographic pattern that can be used to reconstruct both recent and ancient human migrations. The extant European population of H. pylori is known to be a hybrid between Asian and African bacteria, but there exist different hypotheses about when and where the hybridization took place, reflecting the complex demographic history of Europeans. Here, we present a 5300-year-old H. pylori genome from a European Copper Age glacier mummy. The “Iceman” H. pylori is a nearly pure representative of the bacterial population of Asian origin that existed in Europe before hybridization, suggesting that the African population arrived in Europe within the past few thousand years.

Cross-linking measurements of in vivo protein complex topologies.

Identification and measurement of in vivo protein interactions pose critical challenges in the goal to understand biological systems. The measurement of structures and topologies of proteins and protein complexes as they exist in cells is particularly challenging, yet critically important to improve understanding of biological function because proteins exert their intended function only through the structures and interactions they exhibit in vivo. In the present study, protein interactions in E. coli cells were identified in our unbiased cross-linking approach, yielding the first in vivo topological data on many interactions and the largest set of identified in vivo cross-linked peptides produced to date. These data show excellent agreement with protein and complex crystal structures where available. Furthermore, our unbiased data provide novel in vivo topological information that can impact understanding of biological function, even for cases where high resolution structures are not yet available.

The Fasted/Fed Mouse Metabolic Acetylome: N6-Acetylation Differences Suggest Acetylation Coordinates Organ-Specific Fuel Switching

The elucidation of extra-nuclear lysine acetylation has been of growing interest, as the cosubstrate for acetylation, acetyl CoA, is at a key metabolic intersection. Our hypothesis was that mitochondrial and cytoplasmic protein acetylation may be part of a fasted/re-fed feedback control system for the regulation of the metabolic network in fuel switching, where acetyl CoA would be provided by fatty acid oxidation, or glycolysis, respectively. To test this, we characterized the mitochondrial and cytoplasmic acetylome in various organs that have a high metabolic rate relative to their mass, and/or switch fuels, under fasted and re-fed conditions (brain, kidney, liver, skeletal muscle, heart muscle, white and brown adipose tissues). Using immunoprecipitation, coupled with LC-MS/MS label free quantification, we show there is a dramatic variation in global quantitative profiles of acetylated proteins from different organs. In total, 733 acetylated peptides from 337 proteins were identified and quantified, out of which 31 acetylated peptides from the metabolic proteins that may play organ-specific roles were analyzed in detail. Results suggest that fasted/re-fed acetylation changes coordinated by organ-specific (de)acetylases in insulin-sensitive versus -insensitive organs may underlie fuel use and switching. Characterization of the tissue-specific acetylome should increase understanding of metabolic conditions wherein normal fuel switching is disrupted, such as in Type II diabetes.

Accurate peptide fragment mass analysis: multiplexed peptide identification and quantification.

Fourier transform-all reaction monitoring (FT-ARM) is a novel approach for the identification and quantification of peptides that relies upon the selectivity of high mass accuracy data and the specificity of peptide fragmentation patterns. An FT-ARM experiment involves continuous, data-independent, high mass accuracy MS/MS acquisition spanning a defined m/z range. Custom software was developed to search peptides against the multiplexed fragmentation spectra by comparing theoretical or empirical fragment ions against every fragmentation spectrum across the entire acquisition. A dot product score is calculated against each spectrum to generate a score chromatogram used for both identification and quantification. Chromatographic elution profile characteristics are not used to cluster precursor peptide signals to their respective fragment ions. FT-ARM identifications are demonstrated to be complementary to conventional data-dependent shotgun analysis, especially in cases where the data-dependent method fails because of fragmenting multiple overlapping precursors. The sensitivity, robustness, and specificity of FT-ARM quantification are shown to be analogous to selected reaction monitoring-based peptide quantification with the added benefit of minimal assay development. Thus, FT-ARM is demonstrated to be a novel and complementary data acquisition, identification, and quantification method for the large scale analysis of peptides.

Assessing the dynamic range and peak capacity of nanoflow LC-FAIMS-MS on an ion trap mass spectrometer for proteomics.

Proteomics experiments on complex mixtures have benefited greatly from the advent of fast-scanning ion trap mass spectrometers. However, the complexity and dynamic range of mixtures analyzed using shotgun proteomics is still beyond what can be sampled by data-dependent acquisition. Furthermore, the total liquid chromatography-mass spectrometry (LC-MS) peak capacity is not sufficient to resolve the precursors within these mixtures, let alone acquire tandem mass spectra on all of them. Here we describe the application of a high-field asymmetric waveform ion mobility spectrometry (FAIMS) device as an interface to an ion trap mass spectrometer. The dynamic range and peak capacity of the nanoflow LC-FAIMS-MS analysis was assessed using a complex tryptic digest of S. cerevisiae proteins. By adding this relatively simple device to the front of the mass spectrometer, we obtain an increase in peak capacity >8-fold and an increase in dynamic range of >5-fold, without increasing the length of the LC-MS analysis. Thus, the addition of FAIMS to the front of a table-top mass spectrometer can obtain the peak capacity of multidimensional protein identification technology (MudPIT) while increasing the throughput by a factor of 12.

Label-Free Comparative Analysis of Proteomics Mixtures Using Chromatographic Alignment of High-Resolution μLC-MS Data

Label-free relative quantitative proteomics is a powerful tool for the survey of protein level changes between two biological samples. We have developed and applied an algorithm using chromatographic alignment of microLC-MS runs to improve the detection of differences between complex protein mixtures. We demonstrate the performance of our software by finding differences in E. coli protein abundance upon induction of the lac operon genes using isopropyl beta-D-thiogalactopyranoside. The use of our alignment gave a 4-fold decrease in mean relative retention time error and a 6-fold increase in the number of statistically significant differences between samples. Using a conservative threshold, we have identified 5290 total microLC-MS regions that have a different abundance between these samples. Of the detected difference regions, only 23% were mapped to MS/MS peptide identifications. We detected 74 proteins that had a greater relative abundance in the induced sample and 21 with a greater abundance in the uninduced sample. We have developed an effective tool for the label-free detection of differences between samples and demonstrate an increased sensitivity following chromatographic alignment.

Post analysis data acquisition for the iterative MS/MS sampling of proteomics mixtures

The identification of peptides by microcapillary liquid chromatography-tandem mass spectrometry (microLC-MS/MS) has become routine because of the development of fast scanning mass spectrometers, data-dependent acquisition, and database searching algorithms. However, many peptides within the detection limit of the mass spectrometer remain unidentified because of limitations in MS/MS sampling speed despite the dynamic range and peak capacity of the instrument. We have developed an automated approach that uses the mass spectra from high resolution microLC-MS data to define the molecular species present in the mixture and directs the acquisition of MS/MS spectra to precursors that were missed in prior analyses. This approach increases the coverage of the molecular species sampled by MS/MS and consequently the number of peptides and proteins identified during the acquisition of technical or biological replicates using a simple one-dimensional chromatographic separation. The combination of a unique workflow and custom software contribute to the improved identification of molecular features detected in proteomics experiments of complex protein mixtures.