Comprehensive Overview of Bottom-Up Proteomics Using Mass Spectrometry

In Situ Metal-Organic Framework Growth in Serum Encapsulates and Depletes Abundant Proteins for Integrated Plasma Proteomics

Protein biomarkers in human serum provide critical insights into various physiological conditions and diseases, enabling early diagnosis, prognosis, and personalized treatment. However, detecting low-abundance protein biomarkers is challenging due to the presence of highly abundant proteins that make up ∼99% of the plasma proteome. Here, we report the use of in situ metal-organic framework (MOF) growth in serum to effectively deplete highly abundant serum proteins for integrated proteomic analysis. Through biomolecule-mediated nucleation of a zeolitic imidazolate framework (ZIF-8), abundant plasma proteins are selectively encapsulated within ZIF-8 and removed from serum via centrifugation, leaving a depleted protein fraction in the supernatant. Bottom-up proteomics analysis confirmed significant depletion of the topmost abundant proteins, many at depletion levels exceeding 95%. Such depletion enabled the identification of 277 total proteins in the supernatant (uncaptured) fraction in a single-shot analysis, including 54 proteins that were only identified after depletion, 12 drug targets, and many potential disease biomarkers. Top-down proteomics characterization of the captured and uncaptured protein fractions at the proteoform-level confirmed this method is not biased toward any specific proteoform of individual proteins. These results demonstrate that in situ MOF growth can selectively and effectively deplete high-abundance proteins from serum in a simple, low cost, one-pot synthesis to enable integrated top-down and bottom-up proteomic analysis of serum protein biomarkers.

Recent implementations of data-independent acquisition for cancer biomarker discovery in biological fluids

INTRODUCTION

Cancer is the second leading cause of death worldwide and accurate biomarkers for early detection and disease monitoring are needed to improve outcomes. Biological fluids, such as blood and urine, are ideal samples for biomarker measurements as they can be routinely collected with relatively minimally invasive methods. However, proteomics analysis of fluids has been a challenge due to the high dynamic range of its protein content. Advances in data-independent acquisition (DIA) mass spectrometry-based proteomics can address some of the technical challenges in the analysis of biofluids, thus enabling the ability for mass spectrometry to propel large-scale biomarker discovery.

AREAS COVERED

We reviewed principles of DIA and its recent applications in cancer biomarker discovery using biofluids. We summarized DIA proteomics studies using biological fluids in the context of cancer research over the past decade, and provided a comprehensive overview of the benefits and challenges of DIA-MS.

EXPERT OPINION

Various studies showed the potential of DIA-MS in identifying putative cancer biomarkers in a high-throughput manner. However, the lack of proper study design and standardization of methods across platforms still need to be addressed to fully utilize the benefits of DIA-MS to accelerate the biomarker discovery and verification processes.

Production and application of peptidyl-lys metalloendopeptidase: advances, challenges, and future perspectives

Peptidyl-lys metalloendopeptidases (PKMs) are enzymes that selectively cleave peptide bonds at the N-terminus of lysine residues present in the P1' position, making them valuable tools in proteomics. This mini-review presents an overview of PKMs, covering their traditional production from native sources, recent advances in recombinant production, and the current limitations in availability. The historical and current applications of PKMs in proteomics are discussed, highlighting their role in protein sequencing, peptide mapping, and mass spectrometry-based studies. Advances in recombinant technology now enable tailored modifications to PKM, allowing it to function not only as a sister enzyme to LysC but also to trypsin, thereby enhancing its suitability for specific analytical applications. The mini-review concludes with a forward-looking statement on PKM research, emphasizing the potential to broaden its use in novel proteomic methods and other applications.

TMT-based Multiplexed (Chemo)proteomics on the Orbitrap Astral Mass Spectrometer

Ongoing advancements in instrumentation has established mass spectrometry (MS) as an essential tool in proteomics research and drug discovery. The newly released Asymmetric Track Lossless (Astral) analyzer represents a major step forward in MS instrumentation. Here, we evaluate the Orbitrap Astral mass spectrometer in the context of tandem mass tag-based multiplexed proteomics and activity-based proteome profiling, highlighting its sensitivity boost relative to the Orbitrap Tribrid platform-50% at the peptide and 20% at the protein level. We compare TMT DDA and label-free DIA on the same instrument, both of which quantify over 10,000 human proteins per sample within one hour. TMT offers higher quantitative precision and data completeness, while DIA is free of ratio compression and is thereby more accurate. Our results suggest that ratio compression is prevalent with the high-resolution MS2-based quantification on the Astral, while real-time search-based MS3 quantification on the Orbitrap Tribrid platform effectively restores accuracy. Additionally, we benchmark TMT-based activity-based proteome profiling by interrogating cysteine ligandability. The Astral measures over 30,000 cysteines in a single-shot experiment, a 54% increase relative to the Orbitrap Eclipse. We further leverage this remarkable sensitivity to profile the target engagement landscape of FDA-approved covalent drugs, including Sotorasib and Adagrasib. We herein provide a reference for the optimal use of the advanced MS platform.

MSConnect: Open-Source, End-to-End Platform for Automated Mass Spectrometry Data Management, Analysis, and Visualization

The scale of mass spectrometry-based proteomics data sets continues to increase, and the analysis workflows are becoming more complex as various steps are carried out using a multitude of software programs developed by both commercial providers and the research community. Manually shepherding data across multiple programs and in-house-developed scripts can be error prone and labor intensive. It is also difficult for others to follow the same steps, leading to poor repeatability. We have developed an integrated data management and analysis platform termed MSConnect that enables simple and traceable processing workflows across multiple programs, thus improving repeatability and automating common backup and analysis steps from the point of data collection through summarization and visualization. The open nature of the MSConnect platform enables the diverse omics community to seamlessly integrate third-party tools or develop and automate their own unique workflows. With an open license and design architecture, MSConnect has the potential to become a community-driven platform serving a wide range of MS-based omics researchers.

Top-Down Proteomic Profiling of Protein Corona by High-Throughput Capillary Isoelectric Focusing-Mass Spectrometry

In the rapidly evolving field of nanomedicine, understanding the interactions between nanoparticles (NPs) and biological systems is crucial. A pivotal aspect of these interactions is the formation of a protein corona when NPs are exposed to biological fluids (e.g., human plasma), which significantly influences their behavior and functionality. This study introduces an advanced capillary isoelectric focusing tandem mass spectrometry (cIEF-MS/MS) platform designed to enable high-throughput and reproducible top-down proteomic analysis of protein corona. Our cIEF-MS/MS technique completed each analysis within 30 min. It produced reproducible proteoform measurements of protein corona for at least 50 runs regarding the proteoforms' migration time [relative standard deviations (RSDs) <4%], the proteoforms' intensity (Pearson's correlation coefficients between any two runs >0.90), the number of proteoform identifications (71 ± 10), and the number of proteoform-spectrum matches (PrSMs) (196 ± 30). Of the 53 identified genes, 33 are potential biomarkers of various diseases (e.g., cancer, cardiovascular disease, and Alzheimer's disease). We identified 1-102 proteoforms per potential protein biomarker, containing various sequence variations or post-translational modifications. Delineating proteoforms in protein corona by our cIEF-MS/MS in a reproducible and high-throughput fashion will benefit our understanding of nanobiointeractions and advance both diagnostic and therapeutic nanomedicine technologies.

Synergistic effect of Ag/MXene for efficient protein ionization in paper spray mass spectrometry

Ti3C2Tx (MXene) was coated with silver (Ag) nanoparticles using a bio-inspired surface coating method. The resulting composite material, Ag/MXene (AgMX), was applied in paper spray ionization mass spectrometry (PSI-MS) for efficient protein ionization. The intensity of protein obtained by AgMX PSI-MS was enhanced about 3-6 times when compared to conventional PSI. AgMX PSI-MS demonstrated strong potential for quantitative analysis and exhibited good salt tolerance.

Pyruvate Kinase M1/2 Proteoformics for Accurate Insights into Energy Metabolism Abnormity to Promote the Overall Management of Ovarian Cancer Towards Predictive, Preventive, and Personalized Medicine Approaches

Ovarian cancer (OC) is a global health problem that frequently presents at advanced stages, is predisposed to recurrence, readily develops resistance to platinum-based drugs, and has a low survival rate. Predictive, preventive, and personalized medicine (PPPM/3PM) offers an integrated solution with the use of genetic, proteomic, and metabolic biomarkers to identify high-risk individuals for early detection. Metabolic reprogramming is one of the key strategies employed by tumor cells to adapt to the microenvironment and support unlimited proliferation. Pyruvate kinases M1 and M2 (PKM1/2) are encoded by the PKM gene, a pivotal enzyme in the last step of the glycolytic pathway, which is at the crossroads of aerobic oxidation and the Warburg effect to serve as a potential regulator of glucose metabolism and influence cellular energy production and metabolic reprogramming. Commonly, the ratio of PKM1-to-PKM2 is changed in tumors compared to normal controls, and PKM2 is highly expressed in OC to induce a high glycolysis rate and participate in the malignant invasion and metastatic characteristics of cancer cells with epithelial/mesenchymal transition (EMT). PKM2 inhibitors suppress the migration and growth of OC cells by interfering with the Warburg effect. Proteoforms are the final structural and functional forms of a gene/protein, and the canonical protein PKM contains all proteoforms encoded by the same PKM gene. The complexity of PKM can be elucidated by proteoformics. The OC-specific PKM proteoform might represent a specific target for therapeutic interventions against OC. In the framework of PPPM/3PM, the OC-specific PKM proteoform might be the early warning and prognosis biomarker. It is important to clarify the molecular mechanisms of PKM proteoforms in cancer metabolism. This review analyzes the expression, function, and molecular mechanisms of PKM proteoforms in OC, which help identify specific biomarkers for OC.

Recent Advances in Mass Spectrometry-Based Bottom-Up Proteomics

Mass spectrometry-based proteomics is about 35 years old, and recent progress appears to be speeding up across all subfields. In this review, we focus on advances over the last two years in select areas within bottom-up proteomics, including approaches to high-throughput experiments, data analysis using machine learning, drug discovery, glycoproteomics, extracellular vesicle proteomics, and structural proteomics.

Topology-driven discovery of transmembrane protein S-palmitoylation

Protein S-palmitoylation is a reversible lipophilic posttranslational modification regulating diverse signaling pathways. Within transmembrane proteins (TMPs), S-palmitoylation is implicated in conditions from inflammatory disorders to respiratory viral infections. Many small-scale experiments have observed S-palmitoylation at juxtamembrane Cys residues. However, most large-scale S-palmitoyl discovery efforts rely on trypsin-based proteomics within which hydrophobic juxtamembrane regions are likely underrepresented. Machine learning-by virtue of its freedom from experimental constraints-is particularly well suited to address this discovery gap surrounding TMP S-palmitoylation. Utilizing a UniProt-derived feature set, a gradient-boosted machine learning tool (TopoPalmTree) was constructed and applied to a holdout dataset of viral S-palmitoylated proteins. Upon application to the mouse TMP proteome, 1591 putative S-palmitoyl sites (i.e. not listed in SwissPalm or UniProt) were identified. Two lung-expressed S-palmitoyl candidates (synaptobrevin Vamp5 and water channel Aquaporin-5) were experimentally assessed, as were three Type I transmembrane proteins (Cadm4, Chodl, and Havcr2). Finally, TopoPalmTree was used for the rational design of an S-palmitoyl site on KDEL-Receptor 2. This readily interpretable model aligns the innumerable small-scale experiments observing juxtamembrane S-palmitoylation into a proteomic tool for TMP S-palmitoyl discovery and design, thus facilitating future investigations of this important modification.

Honeybee proteins in Saudi honeys: A shotgun gel-free proteomic study

This study investigated the protein content of Acacia and Ziziphus honey samples from the southwestern region of Saudi Arabia following the shotgun gel-free proteomics. Honey proteins were extracted, digested by trypsin and the trypsin digests were separated and characterized using the LC-ESI-QTOF-MS (SCIEX X500R QTOF). The precursor masses of the trypsin digests were used to identify the proteins through searching the mascot spectral database search engine. Nine protein classes originated from honeybees were identified as follows: 1) Gene expression regulatory proteins, 2) Enzymes, 3) Bee venom proteins, 4) Major Royal Jelly Proteins (MRJP), 5) Immune proteins, 6) Structural proteins, 7) Neuropeptides, 8) Vision protein and 9) Olfactory proteins. This study reported, for the first time, the presence of sixteen honeybee proteins in Acacia and Ziziphus honey samples from the southwestern region of Saudi Arabia. Moreover, this study reported that the honey proteomics can predict the honeybee origin of honey samples.

Standard operating procedure combined with comprehensive quality control system for multiple LC-MS platforms urinary proteomics

Urinary proteomics is emerging as a potent tool for detecting sensitive and non-invasive biomarkers. At present, the comparability of urinary proteomics data across diverse liquid chromatography-mass spectrometry (LC-MS) platforms remains an area that requires investigation. In this study, we conduct a comprehensive evaluation of urinary proteome across multiple LC-MS platforms. To systematically analyze and assess the quality of large-scale urinary proteomics data, we develop a comprehensive quality control (QC) system named MSCohort, which extracted 81 metrics for individual experiment and the whole cohort quality evaluation. Additionally, we present a standard operating procedure (SOP) for high-throughput urinary proteome analysis based on MSCohort QC system. Our study involves 20 LC-MS platforms and reveals that, when combined with a comprehensive QC system and a unified SOP, the data generated by data-independent acquisition (DIA) workflow in urine QC samples exhibit high robustness, sensitivity, and reproducibility across multiple LC-MS platforms. Furthermore, we apply this SOP to hybrid benchmarking samples and clinical colorectal cancer (CRC) urinary proteome including 527 experiments. Across three different LC-MS platforms, the analyses report high quantitative reproducibility and consistent disease patterns. This work lays the groundwork for large-scale clinical urinary proteomics studies spanning multiple platforms, paving the way for precision medicine research.

Identification of Protein Networks and Biological Pathways Driving the Progression of Atherosclerosis in Human Carotid Arteries Through Mass Spectrometry-Based Proteomics

Vulnerable atherosclerotic plaques, especially hemorrhaged lesions, are the major cause of mortalities related to vascular pathologies. The early identification of vulnerable plaques helps to stratify patients at risk of developing acute vascular events. In this study, proteomics analyses of human carotid artery samples collected from patients with atheromatous plaques and complicated lesions, respectively, as well as from healthy controls were performed. The proteins isolated from the carotid artery samples were analyzed by a bottom-up shotgun approach that relied on nanoflow liquid chromatography-tandem mass spectrometry analyses (LC-MS/MS) using both data-dependent (DDA) and data-independent (DIA) acquisitions. The data obtained by high-resolution DIA analyses displayed a stronger distinction among groups compared to DDA analyses. Differentially expressed proteins were further examined using Ingenuity Pathway Analysis® with focus on pathological and molecular processes driving atherosclerosis. From the more than 150 significantly regulated canonical pathways, atherosclerosis signaling and neutrophil extracellular trap signaling were verified by protein-targeted data extraction. The results of our study are expected to facilitate a better understanding of the disease progression's molecular drivers and provide inspiration for further multiomics and hypothesis-driven studies.

The Role of Snake Venom Proteins in Inducing Inflammation Post-Envenomation: An Overview on Mechanistic Insights and Treatment Strategies

The intricate combination of organic and inorganic compounds found in snake venom includes proteins, peptides, lipids, carbohydrates, nucleotides, and metal ions. These components work together to immobilise and consume prey through processes such as paralysis and hypotension. Proteins, both enzymatic and non-enzymatic, form the primary components of the venom. Based on the effects they produce, venom can be classified as neurotoxic, hemotoxic, and cytotoxic. Studies have shown that, after envenomation, proteins in snake venom also contribute significantly to the induction of inflammatory responses which can either have systemic or localized consequences. This review delves into the mechanisms by which snake venom proteins trigger inflammatory responses, focusing on key families such as phospholipase A2, metalloproteinases, serine proteases, C-type lectins, cysteine-rich secretory proteins, and L-amino acid oxidase. In addition, the role of venom proteins in activating various inflammatory pathways, including the complement system, inflammasomes, and sterile inflammation are also summarized. The available therapeutic options are examined, with a focus on antivenom therapy and its side effects. In general, this review offers a comprehensive understanding of the inflammatory mechanisms that are triggered by snake venom proteins and the side effects of antivenom treatment. All these emphasize the need for effective strategies to mitigate these detrimental effects.

Proteomic Signatures of Multisystem Inflammatory Syndrome in Children (MIS-C) Associated with COVID-19: A Narrative Review

BACKGROUND/OBJECTIVES

Multisystem Inflammatory Syndrome in Children (MIS-C) is a post-infectious complication of COVID-19. MIS-C has overlapping features with other pediatric inflammatory disorders including Kawasaki Disease (KD), Macrophage Activation Syndrome (MAS), Toxic Shock Syndrome and sepsis. The exact mechanisms responsible for the clinical overlap between MIS-C and these conditions remain unclear, and biomarkers that could distinguish MIS-C from its clinical mimics are lacking. This study aimed to provide an overview of how proteomic methods, like Mass Spectrometry (MS) and affinity-based proteomics, can offer a detailed understanding of pathophysiology and aid in the diagnosis and prognosis of MIS-C.

METHODS

A narrative review of relevant studies published up to July 2024 was conducted.

RESULTS

We identified 15 studies and summarized their key proteomic findings. These studies investigated the serum or plasma proteome of MIS-C patients using MS, Proximity Extension, or Aptamer-based assays. The studies associated the proteomic profile of MIS-C with laboratory and clinical parameters and/or compared it with that of other diseases including acute COVID-19, KD, MAS, pediatric rheumatic diseases, sepsis and myocarditis or pericarditis following COVID-19 mRNA immunization. Depending on the method and the control group, different proteins were increased or decreased in the MIS-C group. The limitations and challenges in MIS-C proteomic research are also discussed, and future research recommendations are provided.

CONCLUSIONS

Although proteomics appear to be a promising approach for understanding the pathogenesis and uncovering candidate biomarkers in MIS-C, proteomic studies are still needed to recognize and validate biomarkers that could accurately discriminate MIS-C from its clinical mimics.

The Current Molecular and Cellular Landscape of Chronic Obstructive Pulmonary Disease (COPD): A Review of Therapies and Efforts towards Personalized Treatment

Chronic obstructive pulmonary disease (COPD) ranks as the third leading cause of global illness and mortality. It is commonly triggered by exposure to respiratory irritants like cigarette smoke or biofuel pollutants. This multifaceted condition manifests through an array of symptoms and lung irregularities, characterized by chronic inflammation and reduced lung function. Present therapies primarily rely on maintenance medications to alleviate symptoms, but fall short in impeding disease advancement. COPD's diverse nature, influenced by various phenotypes, complicates diagnosis, necessitating precise molecular characterization. Omics-driven methodologies, including biomarker identification and therapeutic target exploration, offer a promising avenue for addressing COPD's complexity. This analysis underscores the critical necessity of improving molecular profiling to deepen our comprehension of COPD and identify potential therapeutic targets. Moreover, it advocates for tailoring treatment strategies to individual phenotypes. Through comprehensive exploration-based molecular characterization and the adoption of personalized methodologies, innovative treatments may emerge that are capable of altering the trajectory of COPD, instilling optimism for efficacious disease-modifying interventions.

Rapid Plasma Proteome Profiling via Nanoparticle Protein Corona and Direct Infusion Mass Spectrometry

Noninvasive detection of protein biomarkers in plasma is crucial for clinical purposes. Liquid chromatography-mass spectrometry (LC-MS) is the gold standard technique for plasma proteome analysis, but despite recent advances, it remains limited by throughput, cost, and coverage. Here, we introduce a new hybrid method that integrates direct infusion shotgun proteome analysis (DISPA) with nanoparticle (NP) protein corona enrichment for high-throughput and efficient plasma proteomic profiling. We realized over 280 protein identifications in 1.4 min collection time, which enables a potential throughput of approximately 1000 samples daily. The identified proteins are involved in valuable pathways, and 44 of the proteins are FDA-approved biomarkers. The robustness and quantitative accuracy of this method were evaluated across multiple NPs and concentrations with a mean coefficient of variation of 17%. Moreover, different protein corona profiles were observed among various NPs based on their distinct surface modifications, and all NP protein profiles exhibited deeper coverage and better quantification than neat plasma. Our streamlined workflow merges coverage and throughput with precise quantification, leveraging both DISPA and NP protein corona enrichment. This underscores the significant potential of DISPA when paired with NP sample preparation techniques for plasma proteome studies.