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Cirrhosis, advanced liver disease, affects 2 to 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 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., Competing Interests: Conflicts of interest N. L. K. is involved in entrepreneurial activities in Top-down proteomics and consults for Thermo Fisher Scientific. R. D. M. is a current Thermo Fisher Scientific employee. The other authors have declared that they have no conflict of interest with the contents of this article., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

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.

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 (I 2 MS). 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 I 2 MS 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 I 2 MS spectra that contained a positive COVID-19 antibody response and 21 I 2 MS spectra that contained a negative COVID-19 antibody response. This high-throughput automated I 2 MS workflow can currently process over 100 samples per week and is general for making immunoprecipitation-MS workflows achieve proteoform resolution.

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., Competing Interests: Conflict-of-interest statement: NLK is involved in entrepreneurial activities in top-down proteomics and consults for Thermo Fisher Scientific. RDM is a current Thermo Fisher Scientific employee. The other authors have declared that no conflict of interest exists.

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.

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.

The molecular identification of tissue proteoforms by top-down mass spectrometry (TDMS) is significantly limited by throughput and dynamic range. We introduce AutoPiMS, a single-ion MS based multiplexed workflow for top-down tandem MS (MS 2 ) directly from tissue microenvironments in a semi-automated manner. AutoPiMS directly off human ovarian cancer sections allowed for MS 2 identification of 73 proteoforms up to 54 kDa at a rate of <1 min per proteoform. AutoPiMS is directly interfaced with multifaceted proteoform imaging MS data modalities for the identification of proteoform signatures in tumor and stromal regions in ovarian cancer biopsies. From a total of ~1000 proteoforms detected by region-of-interest label-free quantitation, we discover 303 differential proteoforms in stroma versus tumor from the same patient. 14 of the top proteoform signatures are corroborated by MSI at 20 micron resolution including the differential localization of methylated forms of CRIP1, indicating the importance of proteoform-enabled spatial biology in ovarian cancer., (© 2023. Springer Nature Limited.)

Alternative splicing is pivotal to the regulation of gene expression and protein diversity in eukaryotic cells. The detection of alternative splicing events requires specific omics technologies. Although short-read RNA sequencing has successfully supported a plethora of investigations on alternative splicing, the emerging technologies of long-read RNA sequencing and top-down mass spectrometry open new opportunities to identify alternative splicing and protein isoforms with less ambiguity. Here, we summarize improvements in short-read RNA sequencing for alternative splicing analysis, including percent splicing index estimation and differential analysis. We also review the computational methods used in top-down proteomics analysis regarding proteoform identification, including the construction of databases of protein isoforms and statistical analyses of search results. While many improvements in sequencing and computational methods will result from emerging technologies, there should be future endeavors to increase the effectiveness, integration, and proteome coverage of alternative splicing events.

SARS-CoV-2 Omicron (B.1.1.529) and its subvariants are currently the most common variants of concern worldwide, featuring numerous mutations in the spike protein and elsewhere that collectively make Omicron variants more transmissible and more resistant to antibody-mediated neutralization provided by vaccination, previous infections, and monoclonal antibody therapies than their predecessors. We recently reported the creation and characterization of Ig-MS, a new mass spectrometry-based serology platform that can define the repertoire of antibodies against an antigen of interest at single proteoform resolution. Here, we applied Ig-MS to investigate the evolution of plasma antibody repertoires against the receptor-binding domain (RBD) of SARS-CoV-2 in response to the booster shot and natural viral infection. We also assessed the capacity for antibody repertoires generated in response to vaccination and/or infection with the Omicron variant to bind to both Wuhan- and Omicron-RBDs. Our results show that (1) the booster increases antibody titers against both Wuhan- and Omicron- RBDs and elicits an Omicron-specific response and (2) vaccination and infection act synergistically in generating anti-RBD antibody repertoires able to bind both Wuhan- and Omicron-RBDs with variant-specific antibodies.

Imaging of proteoforms in human tissues is hindered by low molecular specificity and limited proteome coverage. Here, we introduce proteoform imaging mass spectrometry (PiMS), which increases the size limit for proteoform detection and identification by fourfold compared to reported methods and reveals tissue localization of proteoforms at <80-μm spatial resolution. PiMS advances proteoform imaging by combining ambient nanospray desorption electrospray ionization with ion detection using individual ion mass spectrometry. We demonstrate highly multiplexed proteoform imaging of human kidney, annotating 169 of 400 proteoforms of <70 kDa using top-down MS and a database lookup of ~1000 kidney candidate proteoforms, including dozens of key enzymes in primary metabolism. PiMS images reveal distinct spatial localizations of proteoforms to both anatomical structures and cellular neighborhoods in the vasculature, medulla, and cortex regions of the human kidney. The benefits of PiMS are poised to increase proteome coverage for label-free protein imaging of tissues.

The Human Proteoform Atlas (HPfA) is a web-based repository of experimentally verified human proteoforms on-line at http://human-proteoform-atlas.org and is a direct descendant of the Consortium of Top-Down Proteomics' (CTDP) Proteoform Atlas. Proteoforms are the specific forms of protein molecules expressed by our cells and include the unique combination of post-translational modifications (PTMs), alternative splicing and other sources of variation deriving from a specific gene. The HPfA uses a FAIR system to assign persistent identifiers to proteoforms which allows for redundancy calling and tracking from prior and future studies in the growing community of proteoform biology and measurement. The HPfA is organized around open ontologies and enables flexible classification of proteoforms. To achieve this, a public registry of experimentally verified proteoforms was also created. Submission of new proteoforms can be processed through email vianrtdphelp@northwestern.edu, and future iterations of these proteoform atlases will help to organize and assign function to proteoforms, their PTMs and their complexes in the years ahead., (© The Author(s) 2021. Published by Oxford University Press on behalf of Nucleic Acids Research.)