Progress in Top-Down Proteomics and the Analysis of Proteoforms

Combination of hydrophilic interaction liquid chromatography and top-down mass spectrometry for characterisation of adeno-associated virus capsid proteins

Adeno-associated virus (AAV) viral vector-based gene therapy is advancing rapidly, offering potential treatments for rare and severe diseases. The AAV capsid consists of a combination of three viral proteins (VPs), VP1, VP2, and VP3, ranging from 59 to 81 kDa and present at a theoretical bulk ratio of 1:1:10. This study employed hydrophilic interaction liquid chromatography (HILIC) and mass spectrometry (MS) to achieve robust separation and detailed characterisation of AAV9 capsid proteins. Advanced top-down MS approaches combining multiple fragmentation techniques (HCD, ETD, EThcD, and UVPD) were successfully applied, increasing the sequence coverage up to 40% for VP3 and confirming N-terminal acetylation on VP1 and VP3. The workflow demonstrated high reproducibility between injection duplicates and was subsequently applied to the characterisation of in-house produced biological replicates of AAV9 samples from HEK293 cells, showing consistent results across them. Analysis of AAV9 derived from Sf9 insect cells, a more complex sample due to higher levels of modification of the capsid VPs, further evidenced method versatility. Overall, this study highlights the potential of HILIC-MS and advanced top-down MS approaches for detailed characterisation of AAV capsid proteins.

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.

Proteoform-predictor: Increasing the Phylogenetic Reach of Top-Down Proteomics

Proteoforms are distinct molecular forms of proteins that act as building blocks of organisms, with post-translational modifications (PTMs) being one of the key changes that generate these variations. Mass spectrometry (MS)-based top-down proteomics (TDP) is the leading technology for proteoform identification due to its preservation of intact proteoforms for analysis, making it well-suited for comprehensive PTM characterization. A crucial step in TDP is searching MS data against a database of candidate proteoforms. To extend the reach of TDP to organisms with limited PTM annotations, we developed Proteoform-predictor, an open-source tool that integrates homology-based PTM site prediction into proteoform database creation. The new tool creates databases of proteoform candidates after registration of homologous sequences, transferring PTM sites from well-characterized species to those with less comprehensive proteomic data. Our tool features a user-friendly interface and intuitive workflow, making it accessible to a wide range of researchers. We demonstrate that Proteoform-predictor expands proteoform databases with tens of thousands of proteoforms for three bacterial strains by comparing them to the reference proteome of Escherichia coli (E. coli) K12. Subsequent TDP analysis for Serratia marcescens (S. marcescens) and Salmonella typhimurium (S. typhimurium) demonstrated significant improvement in protein and proteoform identification, even for proteins with variant sequences. As TDP technology advances, Proteoform-predictor will become an important tool for expanding the applicability of proteoform identification and PTM biology to more diverse species across the phylogenetic tree of life.

Pooled scanning of protein variants identifies novel RNA-binding mutants

Binding to RNA has been observed for an ever-increasing number of proteins, which often have other functions. The contributions of RNA binding to protein function are best discerned by studying separation-of-function mutants that hamper interaction with RNA without affecting other aspects of protein function. To design these mutants, we need precise knowledge of the residues that contribute to the affinity of the protein for its RNA ligands. Here, we present RBR-scan: a technology to simultaneously measure RNA-binding affinity of a large number of protein variants. We fused individual variants with unique peptide barcodes optimized for detection by mass spectrometry (MS), purified protein pools from single bacterial culture, and assayed proteins in parallel for RNA binding. Mutations in the MS2 coat protein known to impair RNA-binding were correctly identified, as well as a previously unreported mutant, which we validated with orthogonal biochemical methods. We used RBR-scan to discover novel RNA-binding mutants in the cancer-associated splicing regulator SRSF2. Together, our results demonstrate that RBR-scan is a powerful and scalable platform for linking RNA-binding affinity to protein sequence, offering a novel strategy to decode the functional consequences of protein-RNA interactions.

Native Top-Down Proteomics of Endogenous Protein Complexes Enabled by Online Two-Dimensional Liquid Chromatography

Protein complexes are essential for virtually all biological processes, yet their structural characterization remains a major challenge due to their heterogeneous, dynamic nature and the complexity of the proteome. Native top-down mass spectrometry (nTDMS) has emerged as a powerful tool for comprehensive structural characterization of purified protein complexes, but its application to endogenous protein complexes in the proteome is challenging and typically requires labor-intensive and time-consuming prefractionation. Here, for the first time, we develop a nondenaturing online two-dimensional liquid chromatography (2D-LC) method for native top-down proteomics (nTDP), enabling high-throughput structural analysis of endogenous protein complexes. The automated, online interfacing of size-exclusion and mixed-bed ion-exchange chromatography achieves high coverage of endogenous protein complexes. We further develop a multistage nTDMS approach that enables comprehensive structural characterization within the chromatographic timescale, capturing intact non-covalent complexes, released subunits/cofactors, and backbone fragments. Our analysis detected 133 native proteoforms and endogenous protein complexes (up to 350 kDa) from human heart tissue in less than two hours. Such technological leaps in high-throughput structural characterization of endogenous protein complexes will advance large-scale nTDP studies in health and disease.

Deciphering Proteoform Landscape of Mammary Carcinoma by Top-Down Proteomics

Defining the proteoform landscape of breast cancer can provide unique insights into the signaling pathways driving disease progression. While bottom-up proteomics has been utilized to profile breast cancer, it lacks the ability to capture intact proteoforms that may underpin the disease. Top-down proteomics is ideally suited to characterize intact proteoforms; however, most top-down proteomics studies have been limited to low molecular weight (MW) proteins (<50 kDa). Herein, we employed a two-dimensional (2D) liquid chromatography combining size exclusion chromatography (SEC) with reverse phase chromatography (RPC) followed by high-resolution mass spectrometry (MS) to expand the coverage for high MW proteoforms. Using this 2D-SEC-RPC-MS approach, we observed a 5-fold increase in the detection of high MW proteoforms (>50 kDa) compared to the conventional 1D-RPC-MS. SEC separation significantly enhanced the detection of high MW proteoforms (>104 kDa), including intermediate filament proteins, vimentin and keratins. Based on accurate mass measurements and MS/MS data, we identified 775 proteoforms from both TFA and HEPES extracts and detected PTMs, such as acetylation, glutathionylation, and myristoylation. Pathway analysis uncovered many proteoforms involved in processes dysregulated in cancer progression. Overall, our findings illustrate the power of top-down proteomics in defining the proteoform landscape of breast carcinoma.

Establishing a Top-Down Proteomics Platform on a Time-of-Flight Instrument with Electron-Activated Dissociation

Top-down proteomics is the study of intact proteins and their post-translational modifications with mass spectrometry. Historically, this field is more challenging than its bottom-up counterpart because the species are much bigger and have a larger number of possible combinations of sequences and modifications; thus, there is a great need for technological development. With improvements in instrumentation and a multiplicity of fragmentation modes available, top-down proteomics is quickly gaining in popularity with renewed attention on increasing confidence in identification and quantification. Here, we systematically evaluated the Sciex ZenoTOF 7600 system for top-down proteomics, applying standards in the field to validate the platform and further experimenting with its capabilities in electron-activated dissociation and post-translational modification site localization. The instrument demonstrated robustness in standard proteins for platform QC, as aided by zeno trapping. We were also able to apply this to histone post-translational modifications, achieving high sequence coverage that allowed PTM's site localization across protein sequences with optimized EAD fragmentation. We demonstrated the ability to analyze proteins spanning the mass range and included analysis of glycosylated proteins. This is a reference point for future top-down proteomics experiments to be conducted on the ZenoTOF 7600 system.

Spatial top-down proteomics for the functional characterization of human kidney

BACKGROUND

The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging.

RESULTS

Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions.

CONCLUSIONS

We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) while discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

Proteo-SAFARI: An R Application for Identification of Fragment Ions in Top-Down MS/MS Spectra of Proteins

Proteo-SAFARI is a shiny application for fragment assignment by relative isotopes, an R-based software application designed for identification of protein fragment ions directly in the m/z domain. This program provides an open-source, user-friendly application for identification of fragment ions from a candidate protein sequence with support for custom covalent modifications and various visualizations of identified fragments. Additionally, Proteo-SAFARI includes a nonnegative least-squares fitting approach to determine the contributions of various hydrogen shifted fragment ions (a + 1, x + 1, y - 1, y - 2) observed in UVPD mass spectra which exhibit overlapping isotopic distributions. To show its utility, Proteo-SAFARI is applied to various MS/MS spectra of intact proteins, including proteins exhibiting dynamic hydrogen shifts in y ions, ubiquitin charge-reduced to the 1+ charge state, and a large protein recorded in full profile mode. Proteo-SAFARI is available at: github.com/mblanzillotti/Proteo-SAFARI.

Chitosan functionalized two-dimensional covalent organic framework nanosheets with high hydrophilicity for efficient glycopeptide enrichment

Glycopeptides are an important biomarker, which play a crucial role in various biological processes. Due to their low abundance and the presence of interfering macromolecular proteins, enrichment of glycopeptides is necessary before testing. However, most materials for enriching glycopeptides have high site resistance, relatively low surface area, and limited recognition sites. Herein, a highly hydrophilic two-dimensional (2-D) covalent organic framework (NUS-10) loaded with chitosan (CS) (denoted as NUS-10@CS) had been synthesized. After enrichment with NUS-10@CS, a total of 34 glycopeptides from horseradish peroxidase (HRP) tryptic digests were detected, demonstrating a high enrichment efficiency for glycopeptides from model glycoprotein digestion. Meanwhile, the material exhibited ultra-high adsorption capacity (1 fmol/μL HRP), excellent selectivity (HRP tryptic digest/bovine serum albumin (BSA) tryptic digest = 1:2000), macromolecular protein anti-interference ability (HRP tryptic digest/BSA = 1:2000) and good binding capacity (200 mg/g). Additionally, 712 glycopeptides corresponding to 200 glycoproteins were identified from 3 µL human serum. NUS-10@CS was promising for glycopeptide analysis, helping to identify potential disease biomarkers more efficiently, and leading to easier and more accurate diagnosis of diseases, which was essential for early intervention and treatment.

Immunoaffinity Intact Top-Down Mass Spectrometry for Quantification of Neuron-Specific Enolase Gamma, a Low-Abundance Protein Biomarker

Quantification of intact proteins in serum by liquid chromatography high-resolution mass spectrometry (HRMS) may be a useful alternative to bottom-up LC-MS or conventional ligand binding assays, due to reduced assay complexity and by providing additional information, such as isoform differentiation or detection of post-translational modifications. The 47.2 kDa lung cancer tumor marker neuron-specific enolase γ (NSEγ) was quantified in a clinically relevant concentration range of 6.25 to 100 ng/mL in NSE-depleted human serum using magnetic bead immunoprecipitation coupled to LC-high-resolution quadrupole-time-of-flight MS. The novelty of the described approach is in the combined setup of immunoaffinity extraction and the use of a full-length NSEγ calibrator and labeled NSEγ internal standard (IS) to reliably quantify the post-translationally acetylated form of this protein tumor marker in a top-down proteomics workflow. Isolation parameters and quantification using deconvolution and reconstructed extracted ion chromatograms were evaluated, and the development of a suitable liquid chromatography method was demonstrated. Various validation parameters were determined using both quantification methods, both showing acceptable performance. Additionally, deconvolution-based quantification enabled an accurate mass determination. The developed method was compared to a commercially available ECLIA and showed good correlation in sera of patients suspected of lung cancer. This assay may form the starting point for the development of a reference method for the standardization of immunoassays.

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.

Standardized workflow for multiplexed charge detection mass spectrometry on orbitrap analyzers

Individual ion mass spectrometry (I2MS) is the Orbitrap-based extension of the niche mass spectrometry technique known as charge detection mass spectrometry (CDMS). While traditional CDMS analysis is performed on in-house-built instruments such as the electrostatic linear ion trap, I2MS extends CDMS analysis to Orbitrap analyzers, allowing charge detection analysis to be available to the scientific community at large. I2MS simultaneously measures the mass-to-charge ratios (m/z) and charges (z) of hundreds to thousands of individual ions within one acquisition event, creating a spectral output directly into the mass domain without the need for further spectral deconvolution. A mass distribution or 'profile' can be created for any desired sample regardless of composition or heterogeneity. To assist in reducing I2MS analysis to practice, we developed this workflow for data acquisition and subsequent data analysis, which includes (i) protein sample preparation, (ii) attenuation of ion signals to obtain individual ions, (iii) the creation of a charge-calibration curve from standard proteins with known charge states and finally (iv) producing a meaningful mass spectral output from a complex or unknown sample by using the STORIboard software. This protocol is suitable for users with prior experience in mass spectrometry and bioanalytical chemistry. First, the analysis of protein standards in native and denaturing mode is presented, setting the foundation for the analysis of complex mixtures that are intractable via traditional mass spectrometry techniques. Examples of complex mixtures included here demonstrate the relevant analysis of an intact human monoclonal antibody and its intricate glycosylation patterns.

Leveraging Ion-Ion and Ion-Photon Activation to Improve the Sequencing of Proteins Carrying Multiple Disulfide Bonds: The Human Serum Albumin Case Study

Gas-phase sequencing of large intact proteins (>30 kDa) via tandem mass spectrometry is an inherently challenging process that is further complicated by the extensive overlap of multiply charged product ion peaks, often characterized by a low signal-to-noise ratio. Disulfide bonds exacerbate this issue because of the need to cleave both the S-S and backbone bonds to liberate sequence informative fragments. Although electron-based ion activation techniques such as electron transfer dissociation (ETD) have been proven to rupture disulfide bonds in whole protein ions, they still struggle to produce extensive sequencing when multiple, concatenated S-S bonds are present on the same large polypeptide chain. Here, we evaluate the increase in sequence coverage obtained by combining activated-ion ETD (AI-ETD) and proton transfer charge reduction (PTCR) in the analysis of 66 kDa human serum albumin, which holds 17 disulfide bridges. We also describe the combination of AI-ETD with supplemental postactivation of the ETD reaction products via higher-energy collisional dissociation─a hybrid fragmentation method termed AI-EThcD. AI-EThcD leads to a further improvement compared to AI-ETD in both the global number of cleaved backbone bonds and the number of ruptured backbone bonds from disulfide-protected regions. Our results also demonstrate that the full potential of AI-ETD and AI-EThcD is unveiled only when combined with PTCR: reduction in overlap of ion signals leads to a sequence coverage as high as 39% in a single experiment, highlighting the relevance of spectral simplification in top-down mass spectrometry of large proteins.

Proteomics: An Essential Tool to Study Plant-Specialized Metabolism

Plants are a valuable source of specialized metabolites that provide a plethora of therapeutic applications. They are natural defenses that plants use to adapt and respond to their changing environment. Decoding their biosynthetic pathways and understanding how specialized plant metabolites (SPMs) respond to biotic or abiotic stress will provide vital knowledge for plant biology research and its application for the future sustainable production of many SPMs of interest. Here, we focus on the proteomic approaches and strategies that help with the study of plant-specialized metabolism, including the: (i) discovery of key enzymes and the clarification of their biosynthetic pathways; (ii) study of the interconnection of both primary (providers of carbon and energy for SPM production) and specialized (secondary) metabolism; (iii) study of plant responses to biotic and abiotic stress; (iv) study of the regulatory mechanisms that direct their biosynthetic pathways. Proteomics, as exemplified in this review by the many studies performed to date, is a powerful tool that forms part of omics-driven research. The proteomes analysis provides an additional unique level of information, which is absent from any other omics studies. Thus, an integrative analysis, considered versus a single omics analysis, moves us more closely toward a closer interpretation of real cellular processes. Finally, this work highlights advanced proteomic technologies with immediate applications in the field.

Decoding the Challenges: navigating Intact Peptide Mass Spectrometry-Based Analysis for Biological Applications

Quantitative analysis of peptides in biological fluids offers a high diagnostic and prognostic tool to reflect the pathophysiological condition of the patient. Recently, methods based on liquid chromatography coupled with mass spectrometry (LC-MS) for the quantitative determination of intact peptides have been replacing traditionally used ligand-binding assays, which suffer from cross-reactivity issues. The use of "top-down" analysis of peptides is rapidly increasing since it does not undergo incomplete or non-reproducible digestion like "bottom-up" approaches. However, the low abundance of peptides and their peculiar characteristics, as well as the complexity of biological fluids, make their quantification challenging. Herein, the analytical pitfalls that may be encountered during the development of an LC-MS method for the analysis of intact peptides in biological fluids are discussed. Challenges in the pre-analytical phase, stability after sampling and sample processing, significantly impact the accuracy of peptide quantification. Emerging techniques, such as microextractions, are becoming crucial for improved sample cleanup and enrichment of target analytes. A comparison between the roles of high-resolution and low-resolution mass spectrometry in the quantification of intact peptides, as well as the introduction of supercharging reagents to enhance ionization, will be discussed.

Small molecule modulation of protein corona for deep plasma proteome profiling

The protein corona formed on nanoparticles (NPs) has potential as a valuable diagnostic tool for improving plasma proteome coverage. Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules allows for the detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 µg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depletes the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. Employing an optimized data-independent acquisition approach, the inclusion of phosphatidylcholine leads to the detection of 1436 proteins in a single plasma sample. Our molecular dynamics results reveal that phosphatidylcholine interacts with albumin via hydrophobic interactions, H-bonds, and water bridges. The addition of phosphatidylcholine also enables the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate the widespread adoption of this methodology for the identification and clinical translation of biomarkers.

Characterizing age-related changes in intact mitochondrial proteoforms in murine hearts using quantitative top-down proteomics

BACKGROUND

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying proteoform sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

METHODS

Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

RESULTS

From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation. Data are available via ProteomeXchange with the identifier PXD051505.

CONCLUSION

By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Characterization of a Monoclonal Antibody by Native and Denaturing Top-Down Mass Spectrometry

Established in recent years as an important approach to unraveling the heterogeneity of intact monoclonal antibodies, native mass spectrometry has been rarely utilized for sequencing these complex biomolecules via tandem mass spectrometry. Typically, top-down mass spectrometry has been performed starting from highly charged precursor ions obtained via electrospray ionization under denaturing conditions (i.e., in the presence of organic solvents and acidic pH). Here we systematically benchmark four distinct ion dissociation methods─namely, higher-energy collisional dissociation, electron transfer dissociation, electron transfer dissociation/higher-energy collisional dissociation, and 213 nm ultraviolet photodissociation─in their capability to characterize a therapeutic monoclonal antibody, trastuzumab, starting from denatured and native-like precursor ions. Interestingly, native top-down mass spectrometry results in higher sequence coverage than the experiments carried out under denaturing conditions, with the exception of ultraviolet photodissociation. Globally, electron transfer dissociation followed by collision-based activation of product ions generates the largest number of backbone cleavages in disulfide protected regions, including the complementarity determining regions, regardless of electrospray ionization conditions. Overall, these findings suggest that native mass spectrometry can certainly be used for the gas-phase sequencing of whole monoclonal antibodies, although the dissociation of denatured precursor ions still returns a few backbone cleavages not identified in native experiments. Finally, a comparison of the fragmentation maps obtained under denaturing and native conditions strongly points toward disulfide bonds as the primary reason behind the largely overlapping dissociation patterns.

Quantitative protein mass spectrometry for multiplex measurement of coagulation and fibrinolytic proteins towards clinical application: What, why and how?

Plasma proteins involved in coagulation and fibrinolysis are essential to hemostasis. Consequently, their circulating levels and functionality are critical in bleeding and thrombosis development. Well-established laboratory tests to assess these are available; however, said tests do not allow high multiplicity, require large volumes of plasma and are often costly. A novel technology to quantify plasma proteins is quantitative protein mass spectrometry (QPMS). Aided by stable isotope-labeled internal standards a large number of proteins can be quantified in one single analytical run requiring <30 μL of plasma. This provides an opportunity to improve insight in the etiology and prognosis of bleeding and thrombotic disorders, in which the balance between different proteins plays a crucial role. This manuscript aims to give an overview of the QPMS potential applications in thrombosis and hemostasis research (quantifying the 38 proteins assigned to coagulation and fibrinolysis by the KEGG database), but also to explore the potential and hurdles if designed for clinical practice. Advantages and limitations of QPMS are described and strategies for improved analysis are proposed, using as an example the test requirements for antithrombin. Application of this technology in the future could represent a step towards individualized patient care.

Quantification of snake venom proteomes by mass spectrometry-considerations and perspectives

The advent of soft ionization mass spectrometry-based proteomics in the 1990s led to the development of a new dimension in biology that conceptually allows for the integral analysis of whole proteomes. This transition from a reductionist to a global-integrative approach is conditioned to the capability of proteomic platforms to generate and analyze complete qualitative and quantitative proteomics data. Paradoxically, the underlying analytical technique, molecular mass spectrometry, is inherently nonquantitative. The turn of the century witnessed the development of analytical strategies to endow proteomics with the ability to quantify proteomes of model organisms in the sense of "an organism for which comprehensive molecular (genomic and/or transcriptomic) resources are available." This essay presents an overview of the strategies and the lights and shadows of the most popular quantification methods highlighting the common misuse of label-free approaches developed for model species' when applied to quantify the individual components of proteomes of nonmodel species (In this essay we use the term "non-model" organisms for species lacking comprehensive molecular (genomic and/or transcriptomic) resources, a circumstance that, as we detail in this review-essay, conditions the quantification of their proteomes.). We also point out the opportunity of combining elemental and molecular mass spectrometry systems into a hybrid instrumental configuration for the parallel identification and absolute quantification of venom proteomes. The successful application of this novel mass spectrometry configuration in snake venomics represents a proof-of-concept for a broader and more routine application of hybrid elemental/molecular mass spectrometry setups in other areas of the proteomics field, such as phosphoproteomics, metallomics, and in general in any biological process where a heteroatom (i.e., any atom other than C, H, O, N) forms integral part of its mechanism.

Present and future perspectives on mass spectrometry for clinical microbiology

In the last decade, MALDI-TOF Mass Spectrometry (MALDI-TOF MS) has been introduced and broadly accepted by clinical laboratory laboratories throughout the world as a powerful and efficient tool for rapid microbial identification. During the MALDI-TOF MS process, microbes are identified using either intact cells or cell extracts. The process is rapid, sensitive, and economical in terms of both labor and costs involved. Whilst MALDI-TOF MS is currently the gold-standard, it suffers from several shortcomings such as lack of direct information on antibiotic resistance, poor depth of analysis and insufficient discriminatory power for the distinction of closely related bacterial species or for reliably sub-differentiating isolates to the level of clones or strains. Thus, new approaches targeting proteins and allowing a better characterization of bacterial strains are strongly needed, if possible, on a very short time scale after sample collection in the hospital. Bottom-up proteomics (BUP) is a nice alternative to MALDI-TOF MS, offering the possibility for in-depth proteome analysis. Top-down proteomics (TDP) provides the highest molecular precision in proteomics, allowing the characterization of proteins at the proteoform level. A number of studies have already demonstrated the potential of these techniques in clinical microbiology. In this review, we will discuss the current state-of-the-art of MALDI-TOF MS for the rapid microbial identification and detection of resistance to antibiotics and describe emerging approaches, including bottom-up and top-down proteomics as well as ambient MS technologies.

Exploring snake venoms beyond the primary sequence: From proteoforms to protein-protein interactions

Snakebite envenomation has been a long-standing global issue that is difficult to treat, largely owing to the flawed nature of current immunoglobulin-based antivenom therapy and the complexity of snake venoms as sophisticated mixtures of bioactive proteins and peptides. Comprehensive characterisation of venom compositions is essential to better understanding snake venom toxicity and inform effective and rationally designed antivenoms. Additionally, a greater understanding of snake venom composition will likely unearth novel biologically active proteins and peptides that have promising therapeutic or biotechnological applications. While a bottom-up proteomic workflow has been the main approach for cataloguing snake venom compositions at the toxin family level, it is unable to capture snake venom heterogeneity in the form of protein isoforms and higher-order protein interactions that are important in driving venom toxicity but remain underexplored. This review aims to highlight the importance of understanding snake venom heterogeneity beyond the primary sequence, in the form of post-translational modifications that give rise to different proteoforms and the myriad of higher-order protein complexes in snake venoms. We focus on current top-down proteomic workflows to identify snake venom proteoforms and further discuss alternative or novel separation, instrumentation, and data processing strategies that may improve proteoform identification. The current higher-order structural characterisation techniques implemented for snake venom proteins are also discussed; we emphasise the need for complementary and higher resolution structural bioanalytical techniques such as mass spectrometry-based approaches, X-ray crystallography and cryogenic electron microscopy, to elucidate poorly characterised tertiary and quaternary protein structures. We envisage that the expansion of the snake venom characterisation "toolbox" with top-down proteomics and high-resolution protein structure determination techniques will be pivotal in advancing structural understanding of snake venoms towards the development of improved therapeutic and biotechnology applications.

Mass spectrometry-intensive top-down proteomics: an update on technology advancements and biomedical applications

Proteoforms are all forms of protein molecules from the same gene because of variations at the DNA, RNA, and protein levels, e.g., alternative splicing and post-translational modifications (PTMs). Delineation of proteins in a proteoform-specific manner is crucial for understanding their biological functions. Mass spectrometry (MS)-intensive top-down proteomics (TDP) is promising for comprehensively characterizing intact proteoforms in complex biological systems. It has achieved substantial progress in technological development, including sample preparation, proteoform separations, MS instrumentation, and bioinformatics tools. In a single TDP study, thousands of proteoforms can be identified and quantified from a cell lysate. It has also been applied to various biomedical research to better our understanding of protein function in regulating cellular processes and to discover novel proteoform biomarkers of diseases for early diagnosis and therapeutic development. This review covers the most recent technological development and biomedical applications of MS-intensive TDP.

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we describe how surface-enhanced Raman spectroscopy (SERS) assisted with machine learning (ML) can expand its capabilities to enable interpretable insights into the transcriptome, proteome, and metabolome at the single-cell level. We first review how advances in nanophotonics-including plasmonics, metamaterials, and metasurfaces-enhance Raman scattering for rapid, strong label-free spectroscopy. We then discuss ML approaches for precise and interpretable spectral analysis, including neural networks, perturbation and gradient algorithms, and transfer learning. We provide illustrative examples of single-cell Raman phenotyping using nanophotonics and ML, including bacterial antibiotic susceptibility predictions, stem cell expression profiles, cancer diagnostics, and immunotherapy efficacy and toxicity predictions. Lastly, we discuss exciting prospects for the future of single-cell Raman spectroscopy, including Raman instrumentation, self-driving laboratories, Raman data banks, and machine learning for uncovering biological insights.

Spatial top-down proteomics for the functional characterization of human kidney

Background

The Human Proteome Project has credibly detected nearly 93% of the roughly 20,000 proteins which are predicted by the human genome. However, the proteome is enigmatic, where alterations in amino acid sequences from polymorphisms and alternative splicing, errors in translation, and post-translational modifications result in a proteome depth estimated at several million unique proteoforms. Recently mass spectrometry has been demonstrated in several landmark efforts mapping the human proteoform landscape in bulk analyses. Herein, we developed an integrated workflow for characterizing proteoforms from human tissue in a spatially resolved manner by coupling laser capture microdissection, nanoliter-scale sample preparation, and mass spectrometry imaging.

Results

Using healthy human kidney sections as the case study, we focused our analyses on the major functional tissue units including glomeruli, tubules, and medullary rays. After laser capture microdissection, these isolated functional tissue units were processed with microPOTS (microdroplet processing in one-pot for trace samples) for sensitive top-down proteomics measurement. This provided a quantitative database of 616 proteoforms that was further leveraged as a library for mass spectrometry imaging with near-cellular spatial resolution over the entire section. Notably, several mitochondrial proteoforms were found to be differentially abundant between glomeruli and convoluted tubules, and further spatial contextualization was provided by mass spectrometry imaging confirming unique differences identified by microPOTS, and further expanding the field-of-view for unique distributions such as enhanced abundance of a truncated form (1-74) of ubiquitin within cortical regions.

Conclusions

We developed an integrated workflow to directly identify proteoforms and reveal their spatial distributions. Where of the 20 differentially abundant proteoforms identified as discriminate between tubules and glomeruli by microPOTS, the vast majority of tubular proteoforms were of mitochondrial origin (8 of 10) where discriminate proteoforms in glomeruli were primarily hemoglobin subunits (9 of 10). These trends were also identified within ion images demonstrating spatially resolved characterization of proteoforms that has the potential to reshape discovery-based proteomics because the proteoforms are the ultimate effector of cellular functions. Applications of this technology have the potential to unravel etiology and pathophysiology of disease states, informing on biologically active proteoforms, which remodel the proteomic landscape in chronic and acute disorders.

Proteomics of the heart

Mass spectrometry-based proteomics is a sophisticated identification tool specializing in portraying protein dynamics at a molecular level. Proteomics provides biologists with a snapshot of context-dependent protein and proteoform expression, structural conformations, dynamic turnover, and protein-protein interactions. Cardiac proteomics can offer a broader and deeper understanding of the molecular mechanisms that underscore cardiovascular disease, and it is foundational to the development of future therapeutic interventions. This review encapsulates the evolution, current technologies, and future perspectives of proteomic-based mass spectrometry as it applies to the study of the heart. Key technological advancements have allowed researchers to study proteomes at a single-cell level and employ robot-assisted automation systems for enhanced sample preparation techniques, and the increase in fidelity of the mass spectrometers has allowed for the unambiguous identification of numerous dynamic posttranslational modifications. Animal models of cardiovascular disease, ranging from early animal experiments to current sophisticated models of heart failure with preserved ejection fraction, have provided the tools to study a challenging organ in the laboratory. Further technological development will pave the way for the implementation of proteomics even closer within the clinical setting, allowing not only scientists but also patients to benefit from an understanding of protein interplay as it relates to cardiac disease physiology.

Top-down proteomics

Proteoforms, which arise from post-translational modifications, genetic polymorphisms and RNA splice variants, play a pivotal role as drivers in biology. Understanding proteoforms is essential to unravel the intricacies of biological systems and bridge the gap between genotypes and phenotypes. By analysing whole proteins without digestion, top-down proteomics (TDP) provides a holistic view of the proteome and can decipher protein function, uncover disease mechanisms and advance precision medicine. This Primer explores TDP, including the underlying principles, recent advances and an outlook on the future. The experimental section discusses instrumentation, sample preparation, intact protein separation, tandem mass spectrometry techniques and data collection. The results section looks at how to decipher raw data, visualize intact protein spectra and unravel data analysis. Additionally, proteoform identification, characterization and quantification are summarized, alongside approaches for statistical analysis. Various applications are described, including the human proteoform project and biomedical, biopharmaceutical and clinical sciences. These are complemented by discussions on measurement reproducibility, limitations and a forward-looking perspective that outlines areas where the field can advance, including potential future applications.

Solid-Phase Microextraction-Aided Capillary Zone Electrophoresis-Mass Spectrometry: Toward Bottom-Up Proteomics of Single Human Cells

Capillary zone electrophoresis-mass spectrometry (CZE-MS) has been recognized as a valuable technique for the proteomics of mass-limited biological samples (i.e., single cells). However, its broad adoption for single cell proteomics (SCP) of human cells has been impeded by the low sample loading capacity of CZE, only allowing us to use less than 5% of the available peptide material for each measurement. Here we present a reversed-phase-based solid-phase microextraction (RP-SPME)-CZE-MS platform to solve the issue, paving the way for SCP of human cells using CZE-MS. The RP-SPME-CZE system was constructed in one fused silica capillary with zero dead volume for connection via in situ synthesis of a frit, followed by packing C8 beads into the capillary to form a roughly 2 mm long SPME section. Peptides captured by SPME were eluted with a buffer containing 30% (v/v) acetonitrile and 50 mM ammonium acetate (pH 6.5), followed by dynamic pH junction-based CZE-MS. The SPME-CZE-MS enabled the injection of nearly 40% of the available peptide sample for each measurement. The system identified 257 ± 24 proteins and 523 ± 69 peptides (N = 2) using a Q-Exactive HF mass spectrometer when only 0.25 ng of a commercial HeLa cell digest was available in the sample vial and 0.1 ng of the sample was injected. The amount of available peptide is equivalent to the protein mass of one HeLa cell. The data indicate that SPME-CZE-MS is ready for SCP of human cells.

Reading and Writing the Ubiquitin Code Using Genetic Code Expansion

Deciphering ubiquitin proteoform signaling and its role in disease has been a long-standing challenge in the field. The effects of ubiquitin modifications, its relation to ubiquitin-related machineries, and its signaling output has been particularly limited by its reconstitution and means of characterization. Advances in genetic code expansion have contributed towards addressing these challenges by precision incorporation of unnatural amino acids through site selective codon suppression. This review discusses recent advances in studying the 'writers', 'readers', and 'erasers' of the ubiquitin code using genetic code expansion. Highlighting strategies towards genetically encoded protein ubiquitination, ubiquitin phosphorylation, acylation, and finally surveying ubiquitin interactions, we strive to bring attention to this unique approach towards addressing a widespread proteoform problem.

Panda-UV Unlocks Deeper Protein Characterization with Internal Fragments in Ultraviolet Photodissociation Mass Spectrometry

Ultraviolet photodissociation (UVPD) mass spectrometry unlocks insights into the protein structure and sequence through fragmentation patterns. While N- and C-terminal fragments are traditionally relied upon, this work highlights the critical role of internal fragments in achieving near-complete sequencing of protein. Previous limitations of internal fragment utilization, owing to their abundance and potential for random matching, are addressed here with the development of Panda-UV, a novel software tool combining spectral calibration, and Pearson correlation coefficient scoring for confident fragment assignment. Panda-UV showcases its power through comprehensive benchmarks on three model proteins. The inclusion of internal fragments boosts identified fragment numbers by 26% and enhances average protein sequence coverage to a remarkable 93% for intact proteins, unlocking the hidden region of the largest protein carbonic anhydrase II in model proteins. Notably, an average of 65% of internal fragments can be identified in multiple replicates, demonstrating the high confidence of the fragments Panda-UV provided. Finally, the sequence coverages of mAb subunits can be increased up to 86% and the complementary determining regions (CDRs) are nearly completely sequenced in a single experiment. The source codes of Panda-UV are available at https://github.com/PHOENIXcenter/Panda-UV.

Cyclic Ion Mobility-Mass Spectrometry and Tandem Collision Induced Unfolding for Quantification of Elusive Protein Biomarkers

Sensitive analytical techniques that are capable of detecting and quantifying disease-associated biomolecules are indispensable in our efforts to understand disease mechanisms and guide therapeutic intervention through early detection, accurate diagnosis, and effective monitoring of disease. Parkinson's Disease (PD), for example, is one of the most prominent neurodegenerative disorders in the world, but the diagnosis of PD has primarily been based on the observation of clinical symptoms. The protein α-synuclein (α-syn) has emerged as a promising biomarker candidate for PD, but a lack of analytical methods to measure complex disease-associated variants of α-syn has prevented its widespread use as a biomarker. Antibody-based methods such as immunoassays and mass spectrometry-based approaches have been used to measure a limited number of α-syn forms; however, these methods fail to differentiate variants of α-syn that display subtle differences in only the sequence and structure. In this work, we developed a cyclic ion mobility-mass spectrometry method that combines multiple stages of activation and timed ion selection to quantify α-syn variants using both mass- and structure-based measurements. This method can allow for the quantification of several α-syn variants present at physiological levels in biological fluid. Taken together, this approach can be used to galvanize future efforts aimed at understanding the underlying mechanisms of PD and serves as a starting point for the development of future protein-structure-based diagnostics and therapeutic interventions.

Pilot Evaluation of the Long-Term Reproducibility of Capillary Zone Electrophoresis-Tandem Mass Spectrometry for Top-Down Proteomics of a Complex Proteome Sample

Mass spectrometry (MS)-based top-down proteomics (TDP) has revolutionized biological research by measuring intact proteoforms in cells, tissues, and biofluids. Capillary zone electrophoresis-tandem MS (CZE-MS/MS) is a valuable technique for TDP, offering a high peak capacity and sensitivity for proteoform separation and detection. However, the long-term reproducibility of CZE-MS/MS in TDP remains unstudied, which is a crucial aspect for large-scale studies. This work investigated the long-term qualitative and quantitative reproducibility of CZE-MS/MS for TDP for the first time, focusing on a yeast cell lysate. Over 1000 proteoforms were identified per run across 62 runs using one linear polyacrylamide (LPA)-coated separation capillary, highlighting the robustness of the CZE-MS/MS technique. However, substantial decreases in proteoform intensity and identification were observed after some initial runs due to proteoform adsorption onto the capillary inner wall. To address this issue, we developed an efficient capillary cleanup procedure using diluted ammonium hydroxide, achieving high qualitative and quantitative reproducibility for the yeast sample across at least 23 runs. The data underscore the capability of CZE-MS/MS for large-scale quantitative TDP of complex samples, signaling its readiness for deployment in broad biological applications. The MS RAW files were deposited in ProteomeXchange Consortium with the data set identifier of PXD046651.

Fast peak error correction algorithms for proteoform identification using top-down tandem mass spectra

MOTIVATION

Proteoform identification is an important problem in proteomics. The main task is to find a modified protein that best fits the input spectrum. To overcome the combinatorial explosion of possible proteoforms, the proteoform mass graph and spectrum mass graph are used to represent the protein database and the spectrum, respectively. The problem becomes finding an optimal alignment between the proteoform mass graph and the spectrum mass graph. Peak error correction is an important issue for computing an optimal alignment between the two input mass graphs.

RESULTS

We propose a faster algorithm for the error correction alignment of spectrum mass graph and proteoform mass graph problem and produce a program package TopMGFast. The newly designed algorithms require less space and running time so that we are able to compute global optimal alignments for the two input mass graphs in a reasonable time. For the local alignment version, experiments show that the running time of the new algorithm is reduced by 2.5 times. For the global alignment version, experiments show that the maximum mass errors between any pair of matched nodes in the alignments obtained by our method are within a small range as designed, while the alignments produced by the state-of-the-art method, TopMG, have very large maximum mass errors for many cases. The obtained alignment sizes are roughly the same for both TopMG and TopMGFast. Of course, TopMGFast needs more running time than TopMG. Therefore, our new algorithm can obtain more reliable global alignments within a reasonable time. This is the first time that global optimal error correction alignments can be obtained using real datasets.

AVAILABILITY AND IMPLEMENTATION

The source code of the algorithm is available at https://github.com/Zeirdo/TopMGFast.

Uncommon posttranslational modifications in proteomics: ADP-ribosylation, tyrosine nitration, and tyrosine sulfation

Posttranslational modifications (PTMs) are covalent modifications of proteins that modulate the structure and functions of proteins and regulate biological processes. The development of various mass spectrometry-based proteomics workflows has facilitated the identification of hundreds of PTMs and aided the understanding of biological significance in a high throughput manner. Improvements in sample preparation and PTM enrichment techniques, instrumentation for liquid chromatography-tandem mass spectrometry (LC-MS/MS), and advanced data analysis tools enhance the specificity and sensitivity of PTM identification. Highly prevalent PTMs like phosphorylation, glycosylation, acetylation, ubiquitinylation, and methylation are extensively studied. However, the functions and impact of less abundant PTMs are not as well understood and underscore the need for analytical methods that aim to characterize these PTMs. This review focuses on the advancement and analytical challenges associated with the characterization of three less common but biologically relevant PTMs, specifically, adenosine diphosphate-ribosylation, tyrosine sulfation, and tyrosine nitration. The advantages and disadvantages of various enrichment, separation, and MS/MS techniques utilized to identify and localize these PTMs are described.

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.

Mass Spectrometry Strategies for O-Glycoproteomics

Glycoproteomics has accelerated in recent decades owing to numerous innovations in the analytical workflow. In particular, new mass spectrometry strategies have contributed to inroads in O-glycoproteomics, a field that lags behind N-glycoproteomics due to several unique challenges associated with the complexity of O-glycosylation. This review will focus on progress in sample preparation, enrichment strategies, and MS/MS techniques for the identification and characterization of O-glycoproteins.

Precursor deconvolution error estimation: The missing puzzle piece in false discovery rate in top-down proteomics

Top-down proteomics (TDP) directly analyzes intact proteins and thus provides more comprehensive qualitative and quantitative proteoform-level information than conventional bottom-up proteomics (BUP) that relies on digested peptides and protein inference. While significant advancements have been made in TDP in sample preparation, separation, instrumentation, and data analysis, reliable and reproducible data analysis still remains one of the major bottlenecks in TDP. A key step for robust data analysis is the establishment of an objective estimation of proteoform-level false discovery rate (FDR) in proteoform identification. The most widely used FDR estimation scheme is based on the target-decoy approach (TDA), which has primarily been established for BUP. We present evidence that the TDA-based FDR estimation may not work at the proteoform-level due to an overlooked factor, namely the erroneous deconvolution of precursor masses, which leads to incorrect FDR estimation. We argue that the conventional TDA-based FDR in proteoform identification is in fact protein-level FDR rather than proteoform-level FDR unless precursor deconvolution error rate is taken into account. To address this issue, we propose a formula to correct for proteoform-level FDR bias by combining TDA-based FDR and precursor deconvolution error rate.

Characterizing Age-related Changes in Intact Mitochondrial Proteoforms in Murine Hearts using Quantitative Top-Down Proteomics

Cardiovascular diseases (CVDs) are the leading cause of death worldwide, and the prevalence of CVDs increases markedly with age. Due to the high energetic demand, the heart is highly sensitive to mitochondrial dysfunction. The complexity of the cardiac mitochondrial proteome hinders the development of effective strategies that target mitochondrial dysfunction in CVDs. Mammalian mitochondria are composed of over 1000 proteins, most of which can undergo post-translational protein modifications (PTMs). Top-down proteomics is a powerful technique for characterizing and quantifying all protein sequence variations and PTMs. However, there are still knowledge gaps in the study of age-related mitochondrial proteoform changes using this technique. In this study, we used top-down proteomics to identify intact mitochondrial proteoforms in young and old hearts and determined changes in protein abundance and PTMs in cardiac aging.

METHODS

Intact mitochondria were isolated from the hearts of young (4-month-old) and old (24-25-month-old) mice. The mitochondria were lysed, and mitochondrial lysates were subjected to denaturation, reduction, and alkylation. For quantitative top-down analysis, there were 12 runs in total arising from 3 biological replicates in two conditions, with technical duplicates for each sample. The collected top-down datasets were deconvoluted and quantified, and then the proteoforms were identified.

RESULTS

From a total of 12 LC-MS/MS runs, we identified 134 unique mitochondrial proteins in the different sub-mitochondrial compartments (OMM, IMS, IMM, matrix). 823 unique proteoforms in different mass ranges were identified. Compared to cardiac mitochondria of young mice, 7 proteoforms exhibited increased abundance and 13 proteoforms exhibited decreased abundance in cardiac mitochondria of old mice. Our analysis also detected PTMs of mitochondrial proteoforms, including N-terminal acetylation, lysine succinylation, lysine acetylation, oxidation, and phosphorylation.

CONCLUSION

By combining mitochondrial protein enrichment using mitochondrial fractionation with quantitative top-down analysis using ultrahigh-pressure liquid chromatography (UPLC)-MS and label-free quantitation, we successfully identified and quantified intact proteoforms in the complex mitochondrial proteome. Using this approach, we detected age-related changes in abundance and PTMs of mitochondrial proteoforms in the heart.

Nanomaterials Connected to Bioreceptors to Introduce Efficient Biosensing Strategy for Diagnosis of the TORCH Infections: A Critical Review

TORCH infection is a significant risk factor for severe fetal damage, especially congenital malformations. Screening pregnant women for TORCH pathogens could reduce the incidence of adverse pregnancy outcomes and prevent birth defects. Hence, timely identification and inhibition of TORCH infections are effective ways to successfully prevent them in pregnant women. Recently, the superiority of biosensors in TORCH pathogen sensing has been emphasized due to their intrinsic benefits, such as rapid response time, portability, cost-effectiveness, much friendlier preparation and determination steps. With the introduction of advanced nanomaterials into biosensing, the diagnostic properties of biosensors have significantly improved. This study core presents and debates the current progress in biosensing systems for TORCH pathogens using various artificial and natural receptors. The incorporation of nanomaterials into various transduction systems can enhance diagnostic performance. The key performance characteristics of optical and electrochemical biosensors, such as response time, limit of detection (LOD), and linear detection range, are systematically discussed, along with the current TORCH pathogens used for constructing biosensors. Finally, the major problems that exist for converting scientific investigation into product development are also outlined.

Proteomic Profiling of Samples Derived from a Murine Model Following Cryptococcus neoformans Infection

Proteomic profiling provides in-depth information about the regulation of diverse biological processes, activation of and communication across signaling networks, and alterations to protein production, modifications, and interactions. For infectious disease research, mass spectrometry-based proteomics enables detection of host defenses against infection and mechanisms used by the pathogen to evade such responses. In this chapter, we outline protein extraction from organs, tissues, and fluids collected following intranasal inoculation of a murine model with the human fungal pathogen Cryptococcus neoformans. We describe sample preparation, followed by purification, processing on the mass spectrometer, and a robust bioinformatics analysis. The information gleaned from proteomic profiling of fungal infections supports the detection of novel biomarkers for diagnostic and prognostic purposes.

Triboelectric Nanogenerators: Low-Cost Power Supplies for Improved Electrospray Ionization

Electrospray ionization (ESI) is one of the most popular methods to generate ions for mass spectrometry (MS). When compared with other ionization techniques, it can generate ions from liquid-phase samples without additives, retaining covalent and non-covalent interactions of the molecules of interest. When hyphenated to liquid chromatography, it greatly expands the versatility of MS analysis of complex mixtures. However, despite the extensive growth in the application of ESI, the technique still suffers from some drawbacks when powered by direct current (DC) power supplies. Triboelectric nanogenerators promise to be a new power source for the generation of ions by ESI, improving on the analytical capabilities of traditional DC ESI. In this review we highlight the fundamentals of ESI driven by DC power supplies, its contrasting qualities to triboelectric nanogenerator power supplies, and its applications to three distinct fields of research: forensics, metabolomics, and protein structure analysis.

Top-Down Proteomics and the Challenges of True Proteoform Characterization

Top-down proteomics (TDP) aims to identify and profile intact protein forms (proteoforms) extracted from biological samples. True proteoform characterization requires that both the base protein sequence be defined and any mass shifts identified, ideally localizing their positions within the protein sequence. Being able to fully elucidate proteoform profiles lends insight into characterizing proteoform-unique roles, and is a crucial aspect of defining protein structure-function relationships and the specific roles of different (combinations of) protein modifications. However, defining and pinpointing protein post-translational modifications (PTMs) on intact proteins remains a challenge. Characterization of (heavily) modified proteins (>∼30 kDa) remains problematic, especially when they exist in a population of similarly modified, or kindred, proteoforms. This issue is compounded as the number of modifications increases, and thus the number of theoretical combinations. Here, we present our perspective on the challenges of analyzing kindred proteoform populations, focusing on annotation of protein modifications on an "average" protein. Furthermore, we discuss the technical requirements to obtain high quality fragmentation spectral data to robustly define site-specific PTMs, and the fact that this is tempered by the time requirements necessary to separate proteoforms in advance of mass spectrometry analysis.

How can we use proteomics to learn more about platelets?

Proteomics tools provide a powerful means to identify, detect, and quantify protein-related details in studies of platelet phenotype and function. Here, we consider how historical and recent advances in proteomics approaches have informed our understanding of platelet biology, and, how proteomics tools can be used going forward to advance studies of platelets. It is now apparent that the platelet proteome is comprised of thousands of different proteins, where specific changes in platelet protein systems can accompany alterations in platelet function in health and disease. Going forward, many challenges remain in how to best carry out, validate and interpret platelet proteomics experiments. Future studies of platelet protein post-translational modifications such as glycosylation, or studies that take advantage of single cell proteomics and top-down proteomics methods all represent areas of interest to profiling and more richly understanding platelets in human wellness and disease.

Global detection of human variants and isoforms by deep proteome sequencing

An average shotgun proteomics experiment detects approximately 10,000 human proteins from a single sample. However, individual proteins are typically identified by peptide sequences representing a small fraction of their total amino acids. Hence, an average shotgun experiment fails to distinguish different protein variants and isoforms. Deeper proteome sequencing is therefore required for the global discovery of protein isoforms. Using six different human cell lines, six proteases, deep fractionation and three tandem mass spectrometry fragmentation methods, we identify a million unique peptides from 17,717 protein groups, with a median sequence coverage of approximately 80%. Direct comparison with RNA expression data provides evidence for the translation of most nonsynonymous variants. We have also hypothesized that undetected variants likely arise from mutation-induced protein instability. We further observe comparable detection rates for exon-exon junction peptides representing constitutive and alternative splicing events. Our dataset represents a resource for proteoform discovery and provides direct evidence that most frame-preserving alternatively spliced isoforms are translated.

Orbitrap Mass Spectrometry and High-Field Asymmetric Waveform Ion Mobility Spectrometry (FAIMS) Enable the in-Depth Analysis of Human Serum Proteoforms

Blood serum and plasma are arguably the most commonly analyzed clinical samples, with dozens of proteins serving as validated biomarkers for various human diseases. Top-down proteomics may provide additional insights into disease etiopathogenesis since this approach focuses on protein forms, or proteoforms, originally circulating in blood, potentially providing access to information about relevant post-translational modifications, truncations, single amino acid substitutions, and many other sources of protein variation. However, the vast majority of proteomic studies on serum and plasma are carried out using peptide-centric, bottom-up approaches that cannot recapitulate the original proteoform content of samples. Clinical laboratories have been slow to adopt top-down analysis, also due to higher sample handling requirements. In this study, we describe a straightforward protocol for intact proteoform sample preparation based on the depletion of albumin and immunoglobulins, followed by simplified protein fractionation via polyacrylamide gel electrophoresis. After molecular weight-based fractionation, we supplemented the traditional liquid chromatography-tandem mass spectrometry (LC-MS2) data acquisition with high-field asymmetric waveform ion mobility spectrometry (FAIMS) to further simplify serum proteoform mixtures. This LC-FAIMS-MS2 method led to the identification of over 1000 serum proteoforms < 30 kDa, outperforming traditional LC-MS2 data acquisition and more than doubling the number of proteoforms identified in previous studies.

The Emerging Concept of Transportome: State of the Art

The array of ion channels and transporters expressed in cell membranes, collectively referred to as the transportome, is a complex and multifunctional molecular machinery; in particular, at the plasma membrane level it finely tunes the exchange of biomolecules and ions, acting as a functionally adaptive interface that accounts for dynamic plasticity in the response to environmental fluctuations and stressors. The transportome is responsible for the definition of membrane potential and its variations, participates in the transduction of extracellular signals, and acts as a filter for most of the substances entering and leaving the cell, thus enabling the homeostasis of many cellular parameters. For all these reasons, physiologists have long been interested in the expression and functionality of ion channels and transporters, in both physiological and pathological settings and across the different domains of life. Today, thanks to the high-throughput technologies of the postgenomic era, the omics approach to the study of the transportome is becoming increasingly popular in different areas of biomedical research, allowing for a more comprehensive, integrated, and functional perspective of this complex cellular apparatus. This article represents a first effort for a systematic review of the scientific literature on this topic. Here we provide a brief overview of all those studies, both primary and meta-analyses, that looked at the transportome as a whole, regardless of the biological problem or the models they used. A subsequent section is devoted to the methodological aspect by reviewing the most important public databases annotating ion channels and transporters, along with the tools they provide to retrieve such information. Before conclusions, limitations and future perspectives are also discussed.

Determination of adulteration, geographical origins, and species of food by mass spectrometry

Food adulteration, mislabeling, and fraud, are rising global issues. Therefore, a number of precise and reliable analytical instruments and approaches have been proposed to ensure the authenticity and accurate labeling of food and food products by confirming that the constituents of foodstuffs are of the kind and quality claimed by the seller and manufacturer. Traditional techniques (e.g., genomics-based methods) are still in use; however, emerging approaches like mass spectrometry (MS)-based technologies are being actively developed to supplement or supersede current methods for authentication of a variety of food commodities and products. This review provides a critical assessment of recent advances in food authentication, including MS-based metabolomics, proteomics and other approaches.

Cysteine Counting via Isotopic Chemical Labeling for Intact Mass Proteoform Identifications in Tissue

Top-down proteomics, the tandem mass spectrometric analysis of intact proteoforms, is the dominant method for proteoform characterization in complex mixtures. While this strategy produces detailed molecular information, it also requires extensive instrument time per mass spectrum obtained and thus compromises the depth of proteoform coverage that is accessible on liquid chromatography time scales. Such a top-down analysis is necessary for making original proteoform identifications, but once a proteoform has been confidently identified, the extensive characterization it provides may no longer be required for a subsequent identification of the same proteoform. We present a strategy to identify proteoforms in tissue samples on the basis of the combination of an intact mass determination with a measured count of the number of cysteine residues present in each proteoform. We developed and characterized a cysteine tagging chemistry suitable for the efficient and specific labeling of cysteine residues within intact proteoforms and for providing a count of the cysteine amino acids present. On simple protein mixtures, the tagging chemistry yields greater than 98% labeling of all cysteine residues, with a labeling specificity of greater than 95%. Similar results are observed on more complex samples. In a proof-of-principle study, proteoforms present in a human prostate tumor biopsy were characterized. Observed proteoforms, each characterized by an intact mass and a cysteine count, were grouped into proteoform families (groups of proteoforms originating from the same gene). We observed 2190 unique experimental proteoforms, 703 of which were grouped into 275 proteoform families.