Top-down mass spectrometry of native proteoforms and their complexes: a community study.

The combination of native electrospray ionization with top-down fragmentation in mass spectrometry (MS) allows simultaneous determination of the stoichiometry of noncovalent complexes and identification of their component proteoforms and cofactors. Although this approach is powerful, both native MS and top-down MS are not yet well standardized, and only a limited number of laboratories regularly carry out this type of research. To address this challenge, the Consortium for Top-Down Proteomics initiated a study to develop and test protocols for native MS combined with top-down fragmentation of proteins and protein complexes across 11 instruments in nine laboratories. Here we report the summary of the outcomes to provide robust benchmarks and a valuable entry point for the scientific community.

A multi-iron enzyme installs copper-binding oxazolone/thioamide pairs on a nontypeable Haemophilus influenzae virulence factor.

The multinuclear nonheme iron-dependent oxidases (MNIOs) are a rapidly growing family of enzymes involved in the biosynthesis of ribosomally synthesized, posttranslationally modified peptide natural products (RiPPs). Recently, a secreted virulence factor from nontypeable Haemophilus influenzae (NTHi) was found to be expressed from an operon, which we designate the hvf operon, that also encodes an MNIO. Here, we show by Mössbauer spectroscopy that the MNIO HvfB contains a triiron cofactor. We demonstrate that HvfB works together with HvfC [a RiPP recognition element (RRE)-containing partner protein] to perform six posttranslational modifications of cysteine residues on the virulence factor precursor peptide HvfA. Structural characterization by tandem mass spectrometry and NMR shows that these six cysteine residues are converted to oxazolone and thioamide pairs, similar to those found in the RiPP methanobactin. Like methanobactin, the mature virulence factor, which we name oxazolin, uses these modified residues to coordinate Cu(I) ions. Considering the necessity of oxazolin for host cell invasion by NTHi, these findings point to a key role for copper during NTHi infection. Furthermore, oxazolin and its biosynthetic pathway represent a potential therapeutic target for NTHi.

MSModDetector: a tool for detecting mass shifts and post-translational modifications in individual ion mass spectrometry data.

MOTIVATION: Post-translational modifications (PTMs) on proteins regulate protein structures and functions. A single protein molecule can possess multiple modification sites that can accommodate various PTM types, leading to a variety of different patterns, or combinations of PTMs, on that protein. Different PTM patterns can give rise to distinct biological functions. To facilitate the study of multiple PTMs on the same protein molecule, top-down mass spectrometry (MS) has proven to be a useful tool to measure the mass of intact proteins, thereby enabling even PTMs at distant sites to be assigned to the same protein molecule and allowing determination of how many PTMs are attached to a single protein. RESULTS: We developed a Python module called MSModDetector that studies PTM patterns from individual ion mass spectrometry (I2MS) data. I2MS is an intact protein mass spectrometry approach that generates true mass spectra without the need to infer charge states. The algorithm first detects and quantifies mass shifts for a protein of interest and subsequently infers potential PTM patterns using linear programming. The algorithm is evaluated on simulated I2MS data and experimental I2MS data for the tumor suppressor protein p53. We show that MSModDetector is a useful tool for comparing a protein's PTM pattern landscape across different conditions. An improved analysis of PTM patterns will enable a deeper understanding of PTM-regulated cellular processes. AVAILABILITY AND IMPLEMENTATION: The source code is available at https://github.com/marjanfaizi/MSModDetector.

Single Cell Analysis of Proteoforms.

We introduce single cell Proteoform imaging Mass Spectrometry (scPiMS), which realizes the benefit of direct solvent extraction and MS detection of intact proteins from single cells dropcast onto glass slides. Sampling and detection of whole proteoforms by individual ion mass spectrometry enable a scalable approach to single cell proteomics. This new scPiMS platform addresses the throughput bottleneck in single cell proteomics and boosts the cell processing rate by several fold while accessing protein composition with higher coverage.

Characterization of the Antibody Response to SARS-CoV-2 Infection in COVID-19 Transplant versus Nontransplant Recipients by Ig-MS.

Solid organ transplant recipients with immunosuppressant regimens to prevent rejection are less able to mount effective immune responses to pathogenic infection. Here, we apply a recently reported mass spectrometry-based serological approach known as Ig-MS to characterize immune responses against infection with SARS-CoV-2 in cohorts of transplant recipients and immunocompetent controls, both at a single early time point following COVID-19 diagnosis as well as over the course of one-month postdiagnosis. We found that the antibody repertoires generated by transplant recipients against SARS-CoV-2 do not differ significantly compared to immunocompetent individuals with regard to repertoire titer, clonality, or glycan composition. Importantly, our study is the first to characterize the evolution of antibody glycan profiles in transplant recipients with COVID-19 disease, presenting evidence that the evolution of glycan composition in these immunocompromised individuals is similar to that in immunocompetent people.

Precise Readout of MEK1 Proteoforms upon MAPK Pathway Modulation by Individual Ion Mass Spectrometry.

The functions of proteins bearing multiple post-translational modifications (PTMs) are modulated by their modification patterns, yet precise characterization of them is difficult. MEK1 (also known as MAP2K1) is one such example that acts as a gatekeeper of the mitogen-activating protein kinase (MAPK) pathway and propagates signals via phosphorylation by upstream kinases. In principle, top-down mass spectrometry can precisely characterize whole MEK1 proteoforms, but fragmentation methods that would enable the site-specific characterization of labile modifications on 43 kDa protein ions result in overly dense tandem mass spectra. By using the charge-detection method called individual ion mass spectrometry, we demonstrate how complex mixtures of phosphoproteoforms and their fragment ions can be reproducibly handled to provide a "bird's eye" view of signaling activity through mapping proteoform landscapes in a pathway. Using this approach, the overall stoichiometry and distribution of 0-4 phosphorylations on MEK1 was determined in a cellular model of drug-resistant metastatic melanoma. This approach can be generalized to other multiply modified proteoforms, for which PTM combinations are key to their function and drug action.

Automated Immunoprecipitation, Sample Preparation, and Individual Ion Mass Spectrometry Platform for Proteoforms.

Charge detection mass spectrometry (CDMS) is a well-established technique that provides direct mass spectral outputs regardless of analyte heterogeneity or molecular weight. Over the past few years, it has been demonstrated that CDMS can be multiplexed on Orbitrap analyzers utilizing an integrated approach termed individual ion mass spectrometry (I2MS). To further increase adaptability, robustness, and throughput of this technique, here, we present a method that utilizes numerous integrated equipment components including a Kingfisher system, SampleStream platform, and Q Exactive mass spectrometer to provide a fully automated workflow for immunoprecipitation, sample preparation, injection, and subsequent I2MS acquisition. This automated workflow has been applied to a cohort of 58 test subjects to determine individualized patient antibody responses to SARS-CoV-2 antigens. Results from a range of serum donors include 37 subject I2MS spectra that contained a positive COVID-19 antibody response and 21 I2MS spectra that contained a negative COVID-19 antibody response. This high-throughput automated I2MS workflow can currently process over 100 samples per week and is general for making immunoprecipitation-MS workflows achieve proteoform resolution.

Targeted Quantification of Proteoforms in Complex Samples by Proteoform Reaction Monitoring.

Existing mass spectrometric assays used for sensitive and specific measurements of target proteins across multiple samples, such as selected/multiple reaction monitoring (SRM/MRM) or parallel reaction monitoring (PRM), are peptide-based methods for bottom-up proteomics. Here, we describe an approach based on the principle of PRM for the measurement of intact proteoforms by targeted top-down proteomics, termed proteoform reaction monitoring (PfRM). We explore the ability of our method to circumvent traditional limitations of top-down proteomics, such as sensitivity and reproducibility. We also introduce a new software program, Proteoform Finder (part of ProSight Native), specifically designed for the easy analysis of PfRM data. PfRM was initially benchmarked by quantifying three standard proteins. The linearity of the assay was shown over almost 3 orders of magnitude in the femtomole range, with limits of detection and quantification in the low femtomolar range. We later applied our multiplexed PfRM assay to complex samples to quantify biomarker candidates in peripheral blood mononuclear cells (PBMCs) from liver-transplanted patients, suggesting their possible translational applications. These results demonstrate that PfRM has the potential to contribute to the accurate quantification of protein biomarkers for diagnostic purposes and to improve our understanding of disease etiology at the proteoform level.

Bioactivity-driven fungal metabologenomics identifies antiproliferative stemphone analogs and their biosynthetic gene cluster.

INTRODUCTION: Fungi biosynthesize chemically diverse secondary metabolites with a wide range of biological activities. Natural product scientists have increasingly turned towards bioinformatics approaches, combining metabolomics and genomics to target secondary metabolites and their biosynthetic machinery. We recently applied an integrated metabologenomics workflow to 110 fungi and identified more than 230 high-confidence linkages between metabolites and their biosynthetic pathways. OBJECTIVES: To prioritize the discovery of bioactive natural products and their biosynthetic pathways from these hundreds of high-confidence linkages, we developed a bioactivity-driven metabologenomics workflow combining quantitative chemical information, antiproliferative bioactivity data, and genome sequences. METHODS: The 110 fungi from our metabologenomics study were tested against multiple cancer cell lines to identify which strains produced antiproliferative natural products. Three strains were selected for further study, fractionated using flash chromatography, and subjected to an additional round of bioactivity testing and mass spectral analysis. Data were overlaid using biochemometrics analysis to predict active constituents early in the fractionation process following which their biosynthetic pathways were identified using metabologenomics. RESULTS: We isolated three new-to-nature stemphone analogs, 19-acetylstemphones G (1), B (2) and E (3), that demonstrated antiproliferative activity ranging from 3 to 5 µM against human melanoma (MDA-MB-435) and ovarian cancer (OVACR3) cells. We proposed a rational biosynthetic pathway for these compounds, highlighting the potential of using bioactivity as a filter for the analysis of integrated-Omics datasets. CONCLUSIONS: This work demonstrates how the incorporation of biochemometrics as a third dimension into the metabologenomics workflow can identify bioactive metabolites and link them to their biosynthetic machinery.

Short-chain fatty acids propionate and butyrate control growth and differentiation linked to cellular metabolism.

The short-chain fatty acids (SCFA) propionate and butyrate are produced in large amounts by microbial metabolism and have been identified as unique acyl lysine histone marks. In order to better understand the function of these modifications we used ChIP-seq to map the genome-wide location of four short-chain acyl histone marks H3K18pr/bu and H4K12pr/bu in treated and untreated colorectal cancer (CRC) and normal cells, as well as in mouse intestines in vivo . We correlate these marks with open chromatin regions along with gene expression to access the function of the target regions. Our data demonstrate that propionate and butyrate act as promoters of growth, differentiation as well as ion transport. We propose a mechanism involving direct modification of specific genomic regions, resulting in increased chromatin accessibility, and in case of butyrate, opposing effects on the proliferation of normal versus CRC cells.

Short-chain fatty acids propionate and butyrate control growth and differentiation linked to cellular metabolism.

The short-chain fatty acids (SCFA) propionate and butyrate are produced in large amounts by microbial metabolism and have been identified as unique acyl lysine histone marks. In order to better understand the function of these modifications we used ChIP-seq to map the genome-wide location of four short-chain acyl histone marks H3K18pr/bu and H4K12pr/bu in treated and untreated colorectal cancer (CRC) and normal cells, as well as in mouse intestines in vivo. We correlate these marks with open chromatin regions along with gene expression to access the function of the target regions. Our data demonstrate that propionate and butyrate act as promoters of growth, differentiation as well as ion transport. We propose a mechanism involving direct modification of specific genomic regions, resulting in increased chromatin accessibility, and in case of butyrate, opposing effects on the proliferation of normal versus CRC cells.

Improved Signal Processing for Mass Shifting Ions in Charge Detection Mass Spectrometry.

The quality of data in charge detection mass spectrometry depends on accurate determination of ion charge. While the method of selective temporal overview of resonant ions (STORI) has proven to be highly enabling for determining the charge of ions that survive for variable amounts of time, it assumes that the ion frequency exactly matches the frequency being used in the calculation. Any mismatches result in low charge estimates. To address this, the misSTORI method was developed to correct these discrepancies. This can significantly reduce the charge measurement errors for samples with unstable masses. As an example, the misSTORI approach can eliminate a 5.7% charge determination error for a VP3-only AAV capsid that shifts 25 ppm in mass.

Target Identification of a Class of Pyrazolone Protein Aggregation Inhibitor Therapeutics for Amyotrophic Lateral Sclerosis.

Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease with no cure, and current treatment options are very limited. Previously, we performed a high-throughput screen to identify small molecules that inhibit protein aggregation caused by a mutation in the gene that encodes superoxide dismutase 1 (SOD1), which is responsible for about 25% of familial ALS. This resulted in three hit series of compounds that were optimized over several years to give three compounds that were highly active in a mutant SOD1 ALS model. Here we identify the target of two of the active compounds (6 and 7) with the use of photoaffinity labeling, chemical biology reporters, affinity purification, proteomic analysis, and fluorescent/cellular thermal shift assays. Evidence is provided to demonstrate that these two pyrazolone compounds directly interact with 14-3-3-E and 14-3-3-Q isoforms, which have chaperone activity and are known to interact with mutant SOD1G93A aggregates and become insoluble in the subcellular JUNQ compartment, leading to apoptosis. Because protein aggregation is the hallmark of all neurodegenerative diseases, knowledge of the target compounds that inhibit protein aggregation allows for the design of more effective molecules for the treatment of ALS and possibly other neurodegenerative diseases.

Terpenoid balance in Aspergillus nidulans unveiled by heterologous squalene synthase expression.

Filamentous fungi produce numerous uncharacterized natural products (NPs) that are often challenging to characterize because of cryptic expression in laboratory conditions. Previously, we have successfully isolated novel NPs by expressing fungal artificial chromosomes (FACs) from a variety of fungal species into Aspergillus nidulans. Here, we demonstrate a twist to FAC utility wherein heterologous expression of a Pseudogymnoascus destructans FAC in A. nidulans altered endogenous terpene biosynthetic pathways. In contrast to wild type, the FAC transformant produced increased levels of squalene and aspernidine type compounds, including three new nidulenes (1- 2, and 5), and lost nearly all ability to synthesize the major A. nidulans characteristic terpene, austinol. Deletion of a squalene synthase gene in the FAC restored wild-type chemical profiles. The altered squalene to farnesyl pyrophosphate ratio leading to synthesis of nidulenes and aspernidines at the expense of farnesyl pyrophosphate-derived austinols provides unexpected insight into routes of terpene synthesis in fungi.

Deep Profiling of Plasma Proteoforms with Engineered Nanoparticles for Top-down Proteomics.

The dynamic range challenge for detection of proteins and their proteoforms in human plasma has been well documented. Here, we use the nanoparticle protein corona approach to enrich low-abundant proteins selectively and reproducibly from human plasma and use top-down proteomics to quantify differential enrichment for the 2841 detected proteoforms from 114 proteins. Furthermore, nanoparticle enrichment allowed top-down detection of proteoforms between ∼1 µg/mL and ∼10 pg/mL in absolute abundance, providing up to 10 5 -fold increase in proteome depth over neat plasma in which only proteoforms from abundant proteins (>1 µg/mL) were detected. The ability to monitor medium and some low abundant proteoforms through reproducible enrichment significantly extends the applicability of proteoform research by adding depth beyond albumin, immunoglobins and apolipoproteins to uncover many involved in immunity and cell signaling. As proteoforms carry unique information content relative to peptides, this report opens the door to deeper proteoform sequencing in clinical proteomics of disease or aging cohorts.

Design, Synthesis, and Mechanistic Studies of (R)-3-Amino-5,5-difluorocyclohex-1-ene-1-carboxylic Acid as an Inactivator of Human Ornithine Aminotransferase.

Human ornithine aminotransferase (hOAT), a pyridoxal 5'-phosphate (PLP)-dependent enzyme, has been shown to play an essential role in the metabolic reprogramming and progression of hepatocellular carcinoma (HCC). HCC accounts for approximately 75% of primary liver cancers and is within the top three causes of cancer death worldwide. As a result of treatment limitations, the overall 5-year survival rate for all patients with HCC is under 20%. The prevalence of HCC necessitates continued development of novel and effective treatment methods. In recent years, the therapeutic potential of selective inactivation of hOAT has been demonstrated for the treatment of HCC. Inspired by previous increased selectivity for hOAT by the expansion of the cyclopentene ring scaffold to a cyclohexene, we designed, synthesized, and evaluated a series of novel fluorinated cyclohexene analogues and identified (R)-3-amino-5,5-difluorocyclohex-1-ene-1-carboxylic acid as a time-dependent inhibitor of hOAT. Structural and mechanistic studies have elucidated the mechanism of inactivation of hOAT by 5, resulting in a PLP-inactivator adduct tightly bound to the active site of the enzyme. Intact protein mass spectrometry, 19F NMR spectroscopy, transient state kinetic studies, and X-ray crystallography were used to determine the structure of the final adduct and elucidate the mechanisms of inactivation. Interestingly, despite the highly electrophilic intermediate species conferred by fluorine and structural evidence of solvent accessibility in the hOAT active site, Lys292 and water did not participate in nucleophilic addition during the inactivation mechanism of hOAT by 5. Instead, rapid aromatization to yield the final adduct was favored.

Top-Down Proteomics Identifies Plasma Proteoform Signatures of Liver Cirrhosis Progression.

Cirrhosis, advanced liver disease, affects 2-5 million Americans. While most patients have compensated cirrhosis and may be fairly asymptomatic, many decompensate and experience life-threatening complications such as gastrointestinal bleeding, confusion (hepatic encephalopathy), and ascites, reducing life expectancy from 12 to less than 2 years. Among patients with compensated cirrhosis, identifying patients at high risk of decompensation is critical to optimize care and reduce morbidity and mortality. Therefore, it is important to preferentially direct them towards specialty care which cannot be provided to all patients with cirrhosis. We used discovery Top-down Proteomics (TDP) to identify differentially expressed proteoforms (DEPs) in the plasma of patients with progressive stages of liver cirrhosis with the ultimate goal to identify candidate biomarkers of disease progression. In this pilot study, we identified 209 DEPs across three stages of cirrhosis (compensated, compensated with portal hypertension, and decompensated), of which 115 derived from proteins enriched in the liver at a transcriptional level and discriminated the three stages of cirrhosis. Enrichment analyses demonstrated DEPs are involved in several metabolic and immunological processes known to be impacted by cirrhosis progression. We have preliminarily defined the plasma proteoform signatures of cirrhosis patients, setting the stage for ongoing discovery and validation of biomarkers for early diagnosis, risk stratification, and disease monitoring.

Mass spectrometry-based proteomics for advancing solid organ transplantation research.

Scarcity of high-quality organs, suboptimal organ quality assessment, unsatisfactory pre-implantation procedures, and poor long-term organ and patient survival are the main challenges currently faced by the solid organ transplant (SOT) field. New biomarkers for assessing graft quality pre-implantation, detecting, and predicting graft injury, rejection, dysfunction, and survival are critical to provide clinicians with invaluable prediction tools and guidance for personalized patients' treatment. Additionally, new therapeutic targets are also needed to reduce injury and rejection and improve transplant outcomes. Proteins, which underlie phenotypes, are ideal candidate biomarkers of health and disease statuses and therapeutic targets. A protein can exist in different molecular forms, called proteoforms. As the function of a protein depends on its exact composition, proteoforms can offer a more accurate basis for connection to complex phenotypes than protein from which they derive. Mass spectrometry-based proteomics has been largely used in SOT research for identification of candidate biomarkers and therapeutic intervention targets by so-called "bottom-up" proteomics (BUP). However, such BUP approaches analyze small peptides in lieu of intact proteins and provide incomplete information on the exact molecular composition of the proteins of interest. In contrast, "Top-down" proteomics (TDP), which analyze intact proteins retaining proteoform-level information, have been only recently adopted in transplantation studies and already led to the identification of promising proteoforms as biomarkers for organ rejection and dysfunction. We anticipate that the use of top-down strategies in combination with new technological advancements in single-cell and spatial proteomics could drive future breakthroughs in biomarker and therapeutic target discovery in SOT.