Proteomic Methods Research Articles

A Primer on Proteomic Characterization of Intercellular Communication in a Virus Microenvironment.

Intercellular communication is fundamental to multicellular life and a core determinant of outcomes during viral infection, where the common goals of virus and host for persistence and replication are generally at odds. Hosts rely on encoded innate and adaptive immune responses to detect and clear viral pathogens, while viruses can exploit or disrupt these pathways and other intercellular communication processes to enhance their spread and promote pathogenesis. While virus-induced signaling can result in systemic changes to the host, striking alterations are observed within the cellular microenvironment directly surrounding a site of infection, termed the virus microenvironment (VME). Mechanisms employed by viruses to condition their VMEs are emerging and are critical for understanding the biology and pathologies of viral infections. Recent advances in experimental approaches, including proteomic methods, have enabled study of the VME in unprecedented detail. In this review article, we provide a primer on proteomic approaches used to study how viral infections alter intercellular communication, highlighting the ways in which these approaches have been implemented and the exciting biology they have uncovered. First, we consider the different molecules secreted by an infected cell, including proteins, either soluble or contained within extracellular vesicles, and metabolites. We further discuss the modalities of interactions facilitated by alteration at the cell surface of infected cells, including immunopeptide presentation and interactions with the extracellular matrix. Finally, we review spatial profiling approaches that have allowed distinguishing how specific subpopulations of cells within a VME respond to infection and alter their protein composition, discussing valuable insights these methods have offered.

Spatial Localization of Collagen Hydroxylated Proline Site Variation as an Ancestral Trait in the Breast Cancer Microenvironment.

Collagen stroma interactions within the extracellular microenvironment of breast tissue play a significant role in breast cancer, including risk, progression, and outcomes. Hydroxylation of proline (HYP) is a common post-translational modification directly linked to breast cancer survival and progression. Changes in HYP status lead to alterations in epithelial cell signaling, extracellular matrix remodeling, and immune cell recruitment. In the present study, we test the hypothesis that the breast cancer microenvironment presents unique PTMs of collagen, which form bioactive domains at these sites that are associated with spatial histopathological characteristics and influence breast epithelial cell signaling. Mass spectrometry imaging proteomics targeting collagens were paired with comprehensive proteomic methods to identify novel breast cancer-related collagen domains based on spatial localization and regulation in 260 breast tissue samples. As ancestry plays a significant role in breast cancer outcomes, these methods were performed on ancestry diverse breast cancer tissues. Lumpectomies from the Cancer Genome Atlas (TCGA; n=10) reported increased levels of prolyl 4-hydroxylase subunit alpha-3 (P4HA3) accompanied by spatial regulation of fibrillar collagen protein sequences. A concise set of triple negative breast cancer lumpectomies (n=10) showed spatial regulation of specific domain sites from collagen alpha-1(I) chain. Tissue microarrays identified proteomic alterations around post-translationally modified collagen sites in healthy breast (n=81) and patient matched normal adjacent (NAT; n=76) and invasive ductal carcinoma (n=83). A collagen alpha-1(I) chain domain encompassing amino acids 506-514 with site-specific proline hydroxylation reported significant alteration between patient matched normal adjacent tissue and invasive breast cancer. Functional testing of domain 506-514 on breast cancer epithelial cells showed proliferation, chemotaxis and cell signaling response dependent on site localization of proline hydroxylation within domain 506-514 variants. These findings support site localized collagen HYP forms novel bioactive domains that are spatially distributed within the breast cancer microenvironment and may play a role in ancestral traits of breast cancer.

Gel-Based Sample Fractionation with SP3-Purification for Top-Down Proteomics.

Precise prefractionation of proteome samples is a potent method for realizing in-depth analysis in top-down proteomics. PEPPI-MS (Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS), a gel-based sample fractionation method, enables high-resolution proteome fractionation based on molecular weight by highly efficient extraction of proteins from polyacrylamide gels after SDS-PAGE separation. Thereafter it is essential to effectively remove contaminants such as CBB and SDS from the PEPPI fraction prior to mass spectrometry. In this study, we developed a complete, robust, and simple sample preparation workflow named PEPPI-SP3 for top-down proteomics by combining PEPPI-MS with the magnetic bead-based protein purification approach used in SP3 (single-pot, solid-phase-enhanced sample preparation), now one of the standard sample preparation methods in bottom-up proteomics. In PEPPI-SP3, proteins extracted from the gel are collected on the surface of SP3 beads, washed with organic solvents, and recovered intact with 100 mM ammonium bicarbonate containing 0.05% (w/v) SDS. The recovered proteins are subjected to mass spectrometry after additional purification using an anion-exchange StageTip. Performance validation using human cell lysates showed a significant improvement in low-molecular-weight protein recovery with a lower coefficient of variation compared to conventional PEPPI workflows using organic solvent precipitation or ultrafiltration.

Decoding the MMP14 Integrin Link: Key Player in the Secretome Landscape.

Rapid progress has been made in the exciting field of secretome research in health and disease. The tumor secretome, which is a significant proportion of the tumor proteome, is secreted into the extracellular space to promote intercellular communication and thus tumor progression. Among the many molecules of the secretome, integrins and matrix metalloproteinase 14 (MMP14) stand out as the interplay of adhesion and proteolysis drives invasion. Integrins serve as mechanosensors that mediate the contact of cells with the scaffold of the extracellular matrix and are significantly involved in the precise positioning and activity control of the membrane-bound collagenase MMP14. As a secretome proteinase, MMP14 influences and modifies the secretome itself. While integrins and MT-MMPs are membrane bound, but can be released and are therefore border crossers between the cell surface and the secretome, the extracellular matrix is not constitutively cell-bound, but its binding to integrins and other cell receptors is a stringently regulated process. To understand the mutual interactions in detail, we first summarize the structure and function of MMP14 and how it is regulated at the enzymatic and cellular level. In particular, the mutual interactions between integrins and MMP14 include the proteolytic cleavage of integrins themselves by MMP14. We then review the biochemical, cell biological and physiological effects of MMP14 on the composition and associated functions in the tumor secretome when either bound to the cell membrane, or located on extracellular microvesicles, or as a proteolytically shed non-membrane-bound ectodomain. Novel methods of proteomics, including the analysis of extravesicular vesicles, and new methods for the quantification of MMP14 will provide new research and diagnostic tools. The proteolytic modification of the tumor secretome, especially by MMP14, may bring an additional aspect to tumor secretome studies and will have an impact on the diagnosis and most likely also on the therapy of cancer patients.

The association of high-density lipoprotein cargo proteins with brain volume in older adults in the Atherosclerosis Risk in Communities (ARIC).

High-density lipoprotein (HDL) modulates the blood-brain barrier and cerebrovascular integrity, likely influencing the risk of Alzheimer's disease (AD), neurodegeneration, and cognitive decline. This study aims to identify HDL protein cargo associated with brain amyloid deposition and brain volume in regions vulnerable to AD pathology in older adults. HDL was separated from the plasma of 65 non-demented participants of the Atherosclerosis Risk in Communities (ARIC) study using a fast protein liquid chromatography method. HDL cargo proteins were measured using a label-free, untargeted proteomic method based on mass spectrometry and data-independent acquisition. Linear regression with multiple imputations assessed the associations between each HDL cargo protein (log2-transformed) and brain amyloid deposition or temporal-parietal meta-ROI volume, adjusting for covariates. The mean (SD) age of the participants was 76.3 (5.4) years old, 53.8% (35/65) female, 30.8% (20/65) black, and 28.1% (18/64, 1 missing) APOE4 carriers. We found few HDL cargo proteins associated with brain amyloid deposition and considerably more HDL cargo proteins associated with temporal-parietal meta-ROI volume. Two HDL cargo proteins mostly associated with temporoparietal meta-ROI volume were fibrinogen B (FGB) and plasminogen (PLG). A doubling of FGB in HDL was associated with a greater temporoparietal meta-ROI volume of 1638 mm3 (95% CI [688, 2589]). In comparison, a doubling of PLG in HDL was associated with a lower temporoparietal meta-ROI of 2025 mm3 (95% CI [-3669, -1034]). This study suggests that HDL cargo proteins associated with temporal-parietal meta-ROI volume are involved in complement and coagulation pathways.

Moving Toward Metaproteogenomics: A Computational Perspective on Analyzing Microbial Samples via Proteogenomics.

Microbial sample analysis has received growing attention within the last decade, driven by important findings in microbiome research and promising applications in the biotechnological field. Modern mass spectrometry-based methodology has been established in this context, providing sufficient sensitivity, resolution, dynamic range, and throughput to analyze the so-called metaproteome of complex microbial mixtures from clinical or environmental samples. While proteomic analyses were previously restricted to common model organisms, next-generation sequencing technologies nowadays allow for the rapid and cost-efficient characterization of whole metagenomes of microbial consortia and specific genomes from non-model organisms to which microbes contribute by significant amounts. This proteogenomic approach, meaning the combined application of genomic and proteomic methods, enables researchers to create a protein database that presents a tailored blueprint of the microbial sample under investigation. This contribution provides an overview of the computational challenges and opportunities in proteogenomics and metaproteomics as of January 2018. For practical application, we first showcase an integrative proteogenomic method that circumvents existing reference databases by creating sample-specific transcripts. The underlying algorithm uses a graph network approach that combines RNA-Seq and peptide information. As a second example, we provide a tutorial for a simulation tool that estimates the computational limits of detecting microbial non-model organisms. This method evaluates the potential influence of error-tolerant searches and proteogenomic approaches on databases of interest. Finally, we discuss recommendations for developing future strategies that may help overcome present limitations by combining the strengths of genome- and proteome-based methods and moving toward an integrated metaproteogenomics approach.

Proteogenomics for Non-model Ocean-Derived Fungi.

Most biological and biomedical experiments are designed and studied using the most common model organisms (MOs) like humans, mice, Escherichia coli, Saccharomyces cerevisiae, Neurospora crassa, worms, fruit flies, zebrafish, and Arabidopsis thaliana. These model organisms have been extensively studied and have a well-established set of genetic, physiological, and other tools available for research. In contrast, non-model organisms (NMOs) are those that are not traditionally used in scientific research and do not have a well-established set of genetic or other biological tools available for their study. The majority of MOs are associated with land habitats but rarely with ocean environments. The ocean forms the largest portion of our planet, yet ocean-derived organisms are the least explored, and these organisms are primarily NMOs. However, these are thrilling living entities, such as ocean-derived fungi (ODF). These ODFs are a diverse group of fungi that live in different ocean sectors, including the ocean, estuaries, and coastal ecosystems. These fungi are found to colonize and adapt to different substrates. They are important decomposers in marine ecosystems, breaking down dead organic matter and recycling nutrients. ODFs have adapted to survive in the unique and challenging conditions of the ocean environment, including high salt concentrations, low nutrient availability, and exposure to waves and currents. ODFs are potent producers of natural compounds with pharmaceutical and industrial applications, such as antibiotics, anticancer agents, antivirals, and enzymes for industrial processes. ODFs are an exciting group of fungi; however, these are the least studied because of the nonavailability of MOs from this group. Hence, there is a massive scope of expanding our current knowledge about ODFs, their genetic traits, potential future drug-producing capabilities, and lifestyle traits.With the advent of next-generation DNA sequencing, there is huge potential for the characterization of the genetic material of ODF as NMOs. Parallel proteomic methods also pose huge potential. A marriage of NGS and proteomic methods generates a new avenue called proteogenomics, which focuses on better annotation of existing genomic data. Both methods are getting cheaper and accessible to the research community for studying the proteogenomics of NMOs. Herein, the proteogenomic protocol development and data analyses are illustrated for the ocean-derived fungus Scopulariopsis brevicaulis.

Application of Proteomic Methods in Oomycete Biology.

The biochemical makeup of any organism provides insight into key factors regarding its biological functions. These factors can be explored using proteomics, which allows us to obtain a snapshot of the protein content and abundance in an organism, cell type or sub-cellular compartment. Here, we describe proteomic methodologies that can be used to dissect the biochemical mechanism of phytopathogenicity in oomycetes. These methodologies include protein extraction, purification, subsequent processing, mass spectrometry analysis, and qualitative and quantitative data processing of oomycete proteomes for comparative studies. Additionally, the use of mass spectra to assist in gene validation and modelling in unfinished oomycete genomes is also described.

Quantitative Profiling of Histone Variants and Posttranslational Modifications by Tandem Mass Spectrometry in Arabidopsis.

Histone dynamics constitute an important layer of gene regulations associated with development and growth in multicellular eukaryotes. They also stand as key determinants of plant responses to environmental changes. Histone dynamics include the exchange of histone variants as well as post-translational modifications of their amino acid residues (such as acetylation and mono/di/trimethylation), commonly referred to as histone marks. Investigating histone dynamics with a focus on combinatorial changes occurring at their residues will greatly help unravel how plants achieve phenotypic plasticity.Mass spectrometry (MS) analysis offers unequaled resolution of the abundance of histone variants and of their marks. Indeed, relative to other techniques such as western blot or genome-wide profiling, this powerful technique allows quantifying the relative abundances of histone forms, as well as revealing coexisting marks on the same histone molecule. Yet, while MS-based histone analysis has proven efficient in several animals and other model organisms, this method stands out as more challenging in plants. One major challenge is the isolation of sufficient amounts of pure, high-quality histones, likely rendered difficult by the presence of the cell wall, for sufficiently deep and resolutive identification of histone species.In this chapter, we describe a straightforward MS-based proteomic method, implemented to characterize histone marks from Arabidopsis thaliana seedling tissues and cell culture suspensions. After acid extraction of histones, in vitro propionylation of free lysine residues, and digestion with trypsin, a treatment at highly basic pH allows obtaining sharp spectral signals of biologically relevant histone peptide forms.The method workflow described here shall be used to measure changes in histone marks between Arabidopsis thaliana genotypes, along developmental time-courses, or upon various stresses and treatments.

Proteomic Identification and Functional Analysis of Babesia microti Reveals Heparin-Binding Proteins.

Glycosaminoglycan (GAG) molecules on the surface of red blood cells play an important regulatory role in the invasion of merozoites of apicomplexan protozoa. Heparan sulfate, a type of GAG molecule, has been identified as an important receptor facilitating the invasion of red blood cells by these parasites. Proteins in the parasite that exhibit strong affinity for heparin may play a pivotal role in this invasion process. This study aims to use proteomics to identify Babesia microti proteins with high binding affinity to heparin. Bioinformatics was utilized to analyze the subcellular localization and biological functions of these proteins. Candidate genes encoding proteins with strong heparin affinity will be expressed in a prokaryotic system to produce recombinant proteins. The interaction between these recombinant proteins and heparin will be characterized through heparin-binding experiments and other methods. Initially, a mouse model of B. microti was established and high-density B. microti were obtained. Heparin affinity chromatography was then used to purify natural B. microti proteins that can bind to heparin, identifying 186 B. microti proteins via ESI-MS that specifically interact with heparin. Further studies were carried out to analyze those specific proteins with unique peptide segments of two or more, yielding 15 B. microti proteins, most of which are cell surface proteins and secretory proteins. Based on mass spectrometry identification and subsequent analyses, BMSA5-1-1, B. microti peptidyl-prolyl cis-trans isomerase (BmPPIase), and chaperonin were selected for further study due to their potential impact on the invasion of red blood cells by B. microti. These candidate proteins were expressed as recombinant proteins using a prokaryotic expression system. In vitro heparin-binding assays demonstrated that these recombinant proteins specifically bind to heparin. Notably, BmPPIase and chaperonin recombinant proteins exhibited activity in specific heparin binding. Molecular interaction studies further confirmed the strong interaction between BmPPIase and heparin. In conclusion, this study used proteomic methods to identify 186 specific B. microti proteins with specific binding affinity to heparin, providing in-depth analysis of 15 key proteins. The findings confirmed that BmPPIase and chaperonin specifically bind to heparin, with molecular interaction experiments substantiating the strong interaction between BmPPIase and heparin.

Single-cell multi-omics analysis of in vitro post-ovulatory aged oocytes revealed aging-dependent protein degradation

Once ovulated, the oocyte has to be fertilized in a short time window, or it will undergo post-ovulation aging (POA), whose underlying mechanisms are still not elucidated. Here, we optimized single-cell proteomics methods and performed single-cell transcriptomic, proteomic and phosphoproteomic analysis of fresh, POA, and melatonin-treated POA oocytes. POA oocytes showed down-regulation of most differentially expressed proteins, with little correlation with mRNA expression, and the protein changes can be rescued by melatonin treatment. MG132 treatment rescued the decreased fertilization and polyspermy rates, and up-regulated fragmentation and parthenogenesis rates of POA oocytes. MG132-treated oocytes displayed health status at proteome, phosphoproteome and fertilization ability similar to fresh oocytes, suggesting that protein stabilization might be the underlying mechanism for melatonin to rescue POA. The important roles of proteasome-mediated protein degradation during oocyte POA revealed by single-cell multi-omics analyses offer new perspectives for increasing oocyte quality during POA, and improving assisted reproduction technologies.

Improving the Depth and Reliability of Glycopeptide Identification Using Protein Prospector.

Glycosylation is the most common and diverse modification of proteins. It can affect protein function and stability and is associated with many diseases. While proteomic methods to study most post-translational modifications are now quite mature, glycopeptide analysis is still a challenge, particularly from the aspect of data analysis. Several software packages have been developed in the last few years that aim to support omic-level N-linked glycopeptide analysis. This study presents developments of Protein Prospector for the analysis of N-glycopeptide data. Results are compared to other software, showing that Protein Prospector reports many more glycoforms of glycopeptides than competing software. The advantages and disadvantages of considering glycan adducts are also evaluated, showing how considering them can correct previously wrong assignments.

Quantitative Proteomics Identifies Profilin-1 as a Pseudouridine-Binding Protein.

Pseudouridine (Ψ) is the most abundant RNA modification in nature; however, not much is known about the biological functions of this modified nucleoside. Employing an unbiased quantitative proteomics method, we identified multiple candidate reader proteins of Ψ in RNA, including a cytoskeletal protein profilin-1 (PFN1). We demonstrated that PFN1 binds directly and selectively to Ψ-containing RNA. Additionally, we discovered approximately 4000 binding sites of PFN1 in human cells, including a known dyskerin (DKC1)-installed Ψ site in TPI1 mRNA, which encodes triosephosphate isomerase. Moreover, we showed that PFN1 and DKC1 are crucial for regulating the stability and translation efficiency of TPI1 mRNA through modulating PFN1-Ψ interaction. Together, we identified PFN1 as a reader protein of Ψ in RNA and illustrated a potential role of PFN1-Ψ interaction in post-transcriptional regulation. These findings provide new insights into the functions of Ψ in RNA biology and in modulating the expression of an important metabolic enzyme.

Relationship between <I>E. coli, Enterobacter</i> spp. and <i>S. aureus</i> isolated from intestinal microflora and blood proteins associated with the immune system and infectious diseases during 3-day dry immersion

“Dry” immersion is one of the methods for simulating some factors of a space flight. Volunteer-derived intestinal microbiota previously studied by “dry” immersion showed profoundly deteriorated state of microflora and blood protein composition. The study was aimed to analyze mechanisms underlying a positive correlation with amount of intestinal E. coli, and negative correlation between S. aureus and Enterobacter spp. with the number of human blood proteins assessed by proteomics methods based on mass spectrometry, in a 3-day experiment “dry” female immersion. 6 female volunteers aged from 25 to 40 years took part in the 3-days “dry” immersion experiment. During the experiment, the subjects did not take any drugs that could affect the microflora. Fecal samples were collected once per 1–2 days before the onset of the experiment and once on days 1–3 after the end of the “dry” immersion, number of microorganisms in the above-mentioned samples was assessed. Capillary blood samples were obtained by puncture of the terminal phalanx of the ring finger 2 days before the onset of the experiment, on day 1, 2 and 3 during dry immersion and 2 days afterwards. The relationship between the level of proteins in the samples and the number of intestinal microorganisms was described using a regression model in which the blood specific protein was a dependent variable, and the number of microorganisms was an independent variable. The STATISTICA 12.0 program was used for data processing. When analyzing the data obtained, 30 proteins were identified, which positively correlated with the amount of E. coli and negatively correlated with the amount of S. aureus and Enterobacter spp. While considering the events in which these proteins are involved in the human body, they were divided into several groups. In the current study, there were examined 6 proteins associated with infectious diseases (PSMA2, PSMC3, PSME2, NCKAP1, LTF, ENO1) and 10 immune-related proteins (the above-mentioned proteins, as well as CCT2, APOB, FGB, CA1, STOM). Thus, it is necessary to continue close examination of the mechanisms underlying this relationship in the interest of ensuring spaceflight medical safety.

Study of Urinary Protein Biomarkers in Hereditary Angioedema.

Hereditary angioedema (HAE) is a rare and potentially life-threatening disease, and diagnosis is often missed or delayed. We aimed to identify noninvasive urinary protein biomarkers and to evaluate their potential roles in diagnosis and evaluation of disease severity. Using data-independent acquisition (DIA)-based urinary proteomics, we identified proteins that were differentially expressed between patients with HAE and healthy control (HC) groups. Then, the parallel reaction monitoring (PRM)-targeted proteomics method was used to validate promising biomarker candidates in other HAE patients and HCs. Furthermore, enzyme-linked immunosorbent assay (ELISA) was conducted to verify levels of several key proteins in HAE, histamine-mediated angioedema, and HCs. Differential expression between HAE patients and HCs was observed in 269 of the 2562 urinary proteins identified. In the biofunction analysis, these differentially expressed proteins were significantly enriched in leukocyte migration, adhesion of immune cells, endothelial cell development, permeability of the vascular system, and death of immune cells. Moreover, a biomarker panel (C1 esterase inhibitor, pro-epidermal growth factor, and kininogen-1) was validated in 2 independent clinical cohorts with area under the curve values of 0.910 and 0.949 for a diagnosis of HAE. Additionally, the urinary clusterin level was found to be significantly correlated with HAE severity scores (R=-0.758, P<.01). This study describes the first application of a DIA-PRM-ELISA workflow to identify noninvasive urine biomarkers of HAE. The results will contribute to our understanding of the pathogenesis of HAE and may also provide a potential alternative method for diagnosis and evaluation of disease severity.

Laboratory detection of carbapenemases among Gram-negative organisms.

SUMMARYThe carbapenems remain some of the most effective options available for treating patients with serious infections due to Gram-negative bacteria. Carbapenemases are enzymes that hydrolyze carbapenems and are the primary method driving carbapenem resistance globally. Detection of carbapenemases is required for patient management, the rapid implementation of infection prevention and control (IP&C) protocols, and for epidemiologic purposes. Therefore, clinical and public health microbiology laboratories must be able to detect and report carbapenemases among predominant Gram-negative organisms from both cultured isolates and direct from clinical specimens for treatment and surveillance purposes. There is not a "one size fits all" laboratory approach for the detection of bacteria with carbapenemases, and institutions need to determine what fits best with the goals of their antimicrobial stewardship and IP&C programs. Luckily, there are several options and approaches available for clinical laboratories to choose methods that best suits their individual needs. A laboratory approach to detect carbapenemases among bacterial isolates consists of two steps, namely a screening process (e.g., not susceptible to ertapenem, meropenem, and/or imipenem), followed by a confirmation test (i.e., phenotypic, genotypic or proteomic methods) for the presence of a carbapenemase. Direct from specimen testing for the most common carbapenemases generally involves detection via rapid, molecular approaches. The aim of this article is to provide brief overviews on Gram-negative bacteria carbapenem-resistant definitions, types of carbapenemases, global epidemiology, and then describe in detail the laboratory methods for the detection of carbapenemases among Gram-negative bacteria. We will specifically focus on the Enterobacterales, Pseudomonas aeruginosa, and Acinetobacter baumannii complex.

Co-Cultivation of Fungi and Microalgae for Biotechnology

The review examines the results of studies of the last decade on the co-cultivation of fungi and microalgae. It outlines the mechanisms of interaction between fungi and microscopic algae during associative cultivation and briefly discusses the methods for the formation of flocs. Key importance for biotechnology is the ability of fungi and algae to form granules (floccules), which are easy to separate from the culture liquid. The synergistic effect of these relationships results in a higher level of biomass accumulation, synthesis of lipids, polyunsaturated fatty acids, and other metabolites, as well as the removal of various pollutants from wastewater. By selecting specific strains and optimizing cultivation conditions, it is possible to enhance the composition of the resulting products. So far, mostly successful laboratory experiments have been carried out in this direction, which need to be expanded and transferred to production projects. For large-scale application of these systems, it is necessary to continue research into the mechanisms of interaction between fungi and microalgae, their metabolism, regulation of biosynthetic processes using modern methods of metabolomics and proteomics, and to develop engineering solutions for their cultivation.

The Circulating Proteome─Technological Developments, Current Challenges, and Future Trends.

Recent improvements in proteomics technologies have fundamentally altered our capacities to characterize human biology. There is an ever-growing interest in using these novel methods for studying the circulating proteome, as blood offers an accessible window into human health. However, every methodological innovation and analytical progress calls for reassessing our existing approaches and routines to ensure that the new data will add value to the greater biomedical research community and avoid previous errors. As representatives of HUPO's Human Plasma Proteome Project (HPPP), we present our 2024 survey of the current progress in our community, including the latest build of the Human Plasma Proteome PeptideAtlas that now comprises 4608 proteins detected in 113 data sets. We then discuss the updates of established proteomics methods, emerging technologies, and investigations of proteoforms, protein networks, extracellualr vesicles, circulating antibodies and microsamples. Finally, we provide a prospective view of using the current and emerging proteomics tools in studies of circulating proteins.

Quantitative Top-down Proteomics Revealed Kinase Inhibitor-Induced Proteoform-Level Changes in Cancer Cells.

Quantitative analysis of proteins and their post-translational modifications (PTMs) in complex biological samples is critical to understanding cellular biology as well as disease detection and treatment. Top-down proteomics methods provide a "bird's eye" view of the proteome by directly detecting and quantifying intact proteoforms. Here, we developed a high-throughput quantitative top-down proteomics platform to probe intact proteoform and phosphoproteoform abundance changes in HeLa cells as a result of treatment with staurosporine (STS), a broad-spectrum kinase inhibitor. In total, we identified and quantified 1187 proteoforms from 215 proteoform families. Among them, 55 proteoforms from 37 proteoform families were significantly changed upon STS treatment. These proteoforms were primarily related to catabolic, metabolic, and apoptotic pathways that are expected to be impacted as a result of kinase inhibition. In addition, we manually evaluated 25 proteoform families that expressed one or more phosphorylated proteoforms. We observed that phosphorylated proteoforms in the same proteoform family, such as eukaryotic initiation factor 4E binding protein 1 (4EBP1), were differentially regulated relative to the unphosphorylated proteoforms. Combining relative profiling of proteoforms within these proteoform families with individual proteoform profiling results in a more comprehensive picture of STS treatment-induced proteoform abundance changes that cannot be achieved using bottom-up methods.

Applications of Mass Spectrometry Proteomic Methods to Immunoglobulins in the Clinical Laboratory.

Immunoglobulin (Ig) measurements in the clinical laboratory have been traditionally performed by nephelometry, turbidimetry, electrophoresis, and ELISA assays. Mass spectrometry (MS) measurements have the potential to provide deeper insights on the nature of these markers. Different approaches-top-down, middle-down, or bottom-up-have been described for measuring specific Igs for endogenous monoclonal immunoglobulins (M-proteins) and exogenous therapeutic monoclonal antibody therapies (t-mAbs). Challenges arise in distinguishing the Ig of interest from the polyclonal Ig background. MS is emerging as a practical method to provide quantitative analysis and information about structural and clonal features that are not easily determined by current clinical laboratory methods. This review discusses clinically implemented examples, including isotyping and quantification of M-proteins and quantitation of t-mAbs within the polyclonal Ig background, as examples of how MS can enhance our detection and characterization of Igs. This review of current clinically available MS proteomic tests for Igs highlights both analytical and nonanalytical challenges for implementation. Given the new insight into Igs from these methods, it is hoped that vendors, laboratorians, healthcare providers, and payment systems can work to overcome these challenges and advance the care of patients.