Matthew J. P. Rush

Mitochondrial protein functions elucidated by multi-omic mass spectrometry profiling

Mitochondrial dysfunction is associated with many human diseases, including cancer and neurodegeneration, that are often linked to proteins and pathways that are not well-characterized. To begin defining the functions of such poorly characterized proteins, we used mass spectrometry to map the proteomes, lipidomes, and metabolomes of 174 yeast strains, each lacking a single gene related to mitochondrial biology. 144 of these genes have human homologs, 60 of which are associated with disease and 39 of which are uncharacterized. We present a multi-omic data analysis and visualization tool that we use to find covariance networks that can predict molecular functions, correlations between profiles of related gene deletions, gene-specific perturbations that reflect protein functions, and a global respiration deficiency response. Using this multi-omic approach, we link seven proteins including Hfd1p and its human homolog ALDH3A1 to mitochondrial coenzyme Q (CoQ) biosynthesis, an essential pathway disrupted in many human diseases. This Resource should provide molecular insights into mitochondrial protein functions.

Coupling Capillary Zone Electrophoresis with Electron Transfer Dissociation and Activated Ion Electron Transfer Dissociation for Top-Down Proteomics

Top-down proteomics offers the potential for full protein characterization, but many challenges remain for this approach, including efficient protein separations and effective fragmentation of intact proteins. Capillary zone electrophoresis (CZE) has shown great potential for separation of intact proteins, especially for differentially modified proteoforms of the same gene product. To date, however, CZE has been used only with collision-based fragmentation methods. Here we report the first implementation of electron transfer dissociation (ETD) with online CZE separations for top-down proteomics, analyzing a mixture of four standard proteins and a complex protein mixture from the Mycobacterium marinum bacterial secretome. Using a multipurpose dissociation cell on an Orbitrap Elite system, we demonstrate that CZE is fully compatible with ETD as well as higher energy collisional dissociation (HCD), and that the two complementary fragmentation methods can be used in tandem on the electrophoretic time scale for improved protein characterization. Furthermore, we show that activated ion electron transfer dissociation (AI-ETD), a recently introduced method for enhanced ETD fragmentation, provides useful performance with CZE separations to greatly increase protein characterization. When combined with HCD, AI-ETD improved the protein sequence coverage by more than 200% for proteins from both standard and complex mixtures, highlighting the benefits electron-driven dissociation methods can add to CZE separations.

Cerebellar Ataxia and Coenzyme Q Deficiency through Loss of Unorthodox Kinase Activity

The UbiB protein kinase-like (PKL) family is widespread, comprising one-quarter of microbial PKLs and five human homologs, yet its biochemical activities remain obscure. COQ8A (ADCK3) is a mammalian UbiB protein associated with ubiquinone (CoQ) biosynthesis and an ataxia (ARCA2) through unclear means. We show that mice lacking COQ8A develop a slowly progressive cerebellar ataxia linked to Purkinje cell dysfunction and mild exercise intolerance, recapitulating ARCA2. Interspecies biochemical analyses show that COQ8A and yeast Coq8p specifically stabilize a CoQ biosynthesis complex through unorthodox PKL functions. Although COQ8 was predicted to be a protein kinase, we demonstrate that it lacks canonical protein kinase activity in trans. Instead, COQ8 has ATPase activity and interacts with lipid CoQ intermediates, functions that are likely conserved across all domains of life. Collectively, our results lend insight into the molecular activities of the ancient UbiB family and elucidate the biochemical underpinnings of a human disease.

The Negative Mode Proteome with Activated Ion Negative Electron Transfer Dissociation (AI-NETD)

The field of proteomics almost uniformly relies on peptide cation analysis, leading to an underrepresentation of acidic portions of proteomes, including relevant acidic posttranslational modifications. Despite the many benefits negative mode proteomics can offer, peptide anion analysis remains in its infancy due mainly to challenges with high-pH reversed-phase separations and a lack of robust fragmentation methods suitable for peptide anion characterization. Here, we report the first implementation of activated ion negative electron transfer dissociation (AI-NETD) on the chromatographic timescale, generating 7,601 unique peptide identifications from Saccharomyces cerevisiae in single-shot nLC-MS/MS analyses of tryptic peptides—a greater than 5-fold increase over previous results with NETD alone. These improvements translate to identification of 1,106 proteins, making this work the first negative mode study to identify more than 1,000 proteins in any system. We then compare the performance of AI-NETD for analysis of peptides generated by five proteases (trypsin, LysC, GluC, chymotrypsin, and AspN) for negative mode analyses, identifying as many as 5,356 peptides (1,045 proteins) with LysC and 4,213 peptides (857 proteins) with GluC in yeast—characterizing 1,359 proteins in total. Finally, we present the first deep-sequencing approach for negative mode proteomics, leveraging offline low-pH reversed-phase fractionation prior to online high-pH separations and peptide fragmentation with AI-NETD. With this platform, we identified 3,467 proteins in yeast with trypsin alone and characterized a total of 3,730 proteins using multiple proteases, or nearly 83% of the expressed yeast proteome. This work represents the most extensive negative mode proteomics study to date, establishing AI-NETD as a robust tool for large-scale peptide anion characterization and making the negative mode approach a more viable platform for future proteomic studies.

A Calibration Routine for Efficient ETD in Large-Scale Proteomics

AbstractElectron transfer dissociation (ETD) has been broadly adopted and is now available on a variety of commercial mass spectrometers. Unlike collisional activation techniques, optimal performance of ETD requires considerable user knowledge and input. ETD reaction duration is one key parameter that can greatly influence spectral quality and overall experiment outcome. We describe a calibration routine that determines the correct number of reagent anions necessary to reach a defined ETD reaction rate. Implementation of this automated calibration routine on two hybrid Orbitrap platforms illustrate considerable advantages, namely, increased product ion yield with concomitant reduction in scan rates netting up to 75% more unique peptide identifications in a shotgun experiment. Graphical Abstractᅟ

High-Resolution Filtering for Improved Small Molecule Identification via GC/MS

Gas chromatography/mass spectrometry (GC/MS) has long been considered one of the premiere analytical tools for small molecule analysis. Recently, a number of GC/MS systems equipped with high-resolution mass analyzers have been introduced. These systems provide analysts with a new dimension of information, accurate mass measurement to the third or fourth decimal place; however, existing data processing tools do not capitalize on this information. Beyond that, GC/MS spectral reference libraries, which have been curated over the last several decades, contain almost exclusively unit resolution MS spectra making integration of accurate mass data dubious. Here we present an informatic approach, called high-resolution filtering (HRF), which bridges this gap. During HRF, high-resolution mass spectra are assigned putative identifications through traditional spectral matching at unit resolution. Once candidate identities have been assigned, all unique combinations of atoms from these candidate precursors are generated and matched to m/z peaks using narrow mass tolerances. The total amount of measured signal that is annotated is used as a metric of plausibility for the presumed identification. Here we demonstrate that the HRF approach is both feasible and highly specific toward correct identifications.

Top-Down Characterization of Proteins with Intact Disulfide Bonds Using Activated-Ion Electron Transfer Dissociation

Here we report the fragmentation of disulfide linked intact proteins using activated-ion electron transfer dissociation (AI-ETD) for top-down protein characterization. This fragmentation method is then compared to the alternative methods of beam-type collisional activation (HCD), electron transfer dissociation (ETD), and electron transfer and higher-energy collision dissociation (EThcD). We analyzed multiple precursor charge states of the protein standards bovine insulin, α-lactalbumin, lysozyme, β-lactoglobulin, and trypsin inhibitor. In all cases, we found that AI-ETD provides a boost in protein sequence coverage information and the generation of fragment ions from within regions enclosed by disulfide bonds. AI-ETD shows the largest improvement over the other techniques when analyzing highly disulfide linked and low charge density precursor ions. This substantial improvement is attributed to the concurrent irradiation of the gas phase ions while the electron-transfer reaction is taking place, mitigating nondissociative electron transfer, helping unfold the gas phase protein during the electron transfer event, and preventing disulfide bond reformation. We also show that AI-ETD is able to yield comparable sequence coverage information when disulfide bonds are left intact relative to proteins that have been reduced and alkylated. This work demonstrates that AI-ETD is an effective fragmentation method for the analysis of proteins with intact disulfide bonds, dramatically enhancing sequence ion generation and total sequence coverage compared to HCD and ETD.