Gel-Eluted Liquid Fraction Entrapment Electrophoresis: An Electrophoretic Method for Broad Molecular Weight Range Proteome Separation

Myoglobin as a molecular biomarker for meat authentication and traceability

The global incidence of economically motivated meat adulteration represents a crucial issue for the food industry. Undeclared addition of cheaper or low-quality species to meat products of high commercial value has become a common practice that needs to be countered with specific measures. In this framework, myoglobin (Mb) is a sarcoplasmic haemoprotein, primarily responsible for meat colour and has been successfully used in meat fraud authentication. Mb is highly soluble in water, easily monitored at 409 nm and species-specific. Knowing that various analytical DNA-based and protein-based methods, as well as spectroscopic techniques have been developed over the years for the detection of meat fraud, the aim of the present review is to take stock of the situation regarding the possible use of Mb as a molecular biomarker for the easy and rapid detection of undeclared species in meat products, avoiding the need of sophisticated or expensive equipment and specialised operators.

Proteomics-The State of the Field: The Definition and Analysis of Proteomes Should Be Based in Reality, Not Convenience

With growing recognition and acknowledgement of the genuine complexity of proteomes, we are finally entering the post-proteogenomic era. Routine assessment of proteomes as inferred correlates of gene sequences (i.e., canonical 'proteins') cannot provide the necessary critical analysis of systems-level biology that is needed to understand underlying molecular mechanisms and pathways or identify the most selective biomarkers and therapeutic targets. These critical requirements demand the analysis of proteomes at the level of proteoforms/protein species, the actual active molecular players. Currently, only highly refined integrated or integrative top-down proteomics (iTDP) enables the analytical depth necessary to provide routine, comprehensive, and quantitative proteome assessments across the widest range of proteoforms inherent to native systems. Here we provide a broad perspective of the field, taking in historical and current realities, to establish a more balanced understanding of where the field has come from (in particular during the ten years since Proteomes was launched), current issues, and how things likely need to proceed if necessary deep proteome analyses are to succeed. We base this in our firm belief that the best proteomic analyses reflect, as closely as possible, the native sample at the moment of sampling. We also seek to emphasise that this and future analytical approaches are likely best based on the broad recognition and exploitation of the complementarity of currently successful approaches. This also emphasises the need to continuously evaluate and further optimize established approaches, to avoid complacency in thinking and expectations but also to promote the critical and careful development and introduction of new approaches, most notably those that address proteoforms. Above all, we wish to emphasise that a rigorous focus on analytical quality must override current thinking that largely values analytical speed; the latter would certainly be nice, if only proteoforms could thus be effectively, routinely, and quantitatively assessed. Alas, proteomes are composed of proteoforms, not molecular species that can be amplified or that directly mirror genes (i.e., 'canonical'). The problem is hard, and we must accept and address it as such, but the payoff in playing this longer game of rigorous deep proteome analyses is the promise of far more selective biomarkers, drug targets, and truly personalised or even individualised medicine.

Small proteins in bacteria - Big challenges in prediction and identification

Proteins with up to 100 amino acids have been largely overlooked due to the challenges associated with predicting and identifying them using traditional methods. Recent advances in bioinformatics and machine learning, DNA sequencing, RNA and Ribo-seq technologies, and mass spectrometry (MS) have greatly facilitated the detection and characterisation of these elusive proteins in recent years. This has revealed their crucial role in various cellular processes including regulation, signalling and transport, as toxins and as folding helpers for protein complexes. Consequently, the systematic identification and characterisation of these proteins in bacteria have emerged as a prominent field of interest within the microbial research community. This review provides an overview of different strategies for predicting and identifying these proteins on a large scale, leveraging the power of these advanced technologies. Furthermore, the review offers insights into the future developments that may be expected in this field.

The γ-secretase substrate proteome and its role in cell signaling regulation

γ-Secretases mediate the regulated intramembrane proteolysis (RIP) of more than 150 integral membrane proteins. We developed an unbiased γ-secretase substrate identification (G-SECSI) method to study to what extent these proteins are processed in parallel. We demonstrate here parallel processing of at least 85 membrane proteins in human microglia in steady-state cell culture conditions. Pharmacological inhibition of γ-secretase caused substantial changes of human microglial transcriptomes, including the expression of genes related to the disease-associated microglia (DAM) response described in Alzheimer disease (AD). While the overall effects of γ-secretase deficiency on transcriptomic cell states remained limited in control conditions, exposure of mouse microglia to AD-inducing amyloid plaques strongly blocked their capacity to mount this putatively protective DAM cell state. We conclude that γ-secretase serves as a critical signaling hub integrating the effects of multiple extracellular stimuli into the overall transcriptome of the cell.

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.

Multidimensional Separations in Top-Down Proteomics

Top-down proteomics (TDP) identifies, quantifies, and characterizes proteins at the intact proteoform level in complex biological samples to understand proteoform function and cellular mechanisms. However, analyzing complex biological samples using TDP is still challenging due to high sample complexity and wide dynamic range. High-resolution separation methods are often applied prior to mass spectrometry (MS) analysis to decrease sample complexity and increase proteomics throughput. These separation methods, however, may not be efficient enough to characterize low abundance intact proteins in complex samples. As such, multidimensional separation techniques (combination of two or more separation methods with high orthogonality) have been developed and applied that demonstrate improved separation resolution and more comprehensive identification in TDP. A suite of multidimensional separation methods that couple various types of liquid chromatography (LC), capillary electrophoresis (CE), and/or gel electrophoresis-based separation approaches have been developed and applied in TDP to analyze complex biological samples. Here, we reviewed multidimensional separation strategies employed for TDP, summarized current applications, and discussed the gaps that may be addressed in the future.

mTORC2 interactome and localization determine aggressiveness of high-grade glioma cells through association with gelsolin

mTOR complex 2 (mTORC2) has been implicated as a key regulator of glioblastoma cell migration. However, the roles of mTORC2 in the migrational control process have not been entirely elucidated. Here, we elaborate that active mTORC2 is crucial for GBM cell motility. Inhibition of mTORC2 impaired cell movement and negatively affected microfilament and microtubule functions. We also aimed to characterize important players involved in the regulation of cell migration and other mTORC2-mediated cellular processes in GBM cells. Therefore, we quantitatively characterized the alteration of the mTORC2 interactome under selective conditions using affinity purification-mass spectrometry in glioblastoma. We demonstrated that changes in cell migration ability specifically altered mTORC2-associated proteins. GSN was identified as one of the most dynamic proteins. The mTORC2-GSN linkage was mostly highlighted in high-grade glioma cells, connecting functional mTORC2 to multiple proteins responsible for directional cell movement in GBM. Loss of GSN disconnected mTORC2 from numerous cytoskeletal proteins and affected the membrane localization of mTORC2. In addition, we reported 86 stable mTORC2-interacting proteins involved in diverse molecular functions, predominantly cytoskeletal remodeling, in GBM. Our findings might help expand future opportunities for predicting the highly migratory phenotype of brain cancers in clinical investigations.

Quantifying KRAS G12C Covalent Drug Inhibitor Activity in Mouse Tumors Using Mass Spectrometry

The growing opportunities recognized for covalent drug inhibitors, like KRAS G12C inhibitors, are driving the need for mass spectrometry methods that can quickly and robustly measure therapeutic drug activity in vivo for drug discovery research and development. Effective front-end sample preparation is critical for proteins extracted from tumors but is generally labor intensive and impractical for large sample numbers typical in pharmacodynamic (PD) studies. Herein, we describe an automated and integrated sample preparation method for the measurement of activity levels of KRAS G12C drug inhibitor alkylation from complex tumor samples involving high throughput detergent removal and preconcentration followed by quantitation using mass spectrometry. We introduce a robust assay with an average intra-assay coefficient of variation (CV) of 4% and an interassay CV of 6% obtained from seven studies, enabling us to understand the relationship between KRAS G12C target occupancy and the therapeutic PD effect from mouse tumor samples. Further, the data demonstrated that the drug candidate GDC-6036, a KRAS G12C covalent inhibitor, shows dose-dependent target inhibition (KRAS G12C alkylation) and MAPK pathway inhibition, which correlate with high antitumor potency in the MIA PaCa-2 pancreatic xenograft model.

Recent advances in top-down proteome sample processing ahead of MS analysis

Top-down proteomics is emerging as a preferred approach to investigate biological systems, with objectives ranging from the detailed assessment of a single protein therapeutic, to the complete characterization of every possible protein including their modifications, which define the human proteoform. Given the controlling influence of protein modifications on their biological function, understanding how gene products manifest or respond to disease is most precisely achieved by characterization at the intact protein level. Top-down mass spectrometry (MS) analysis of proteins entails unique challenges associated with processing whole proteins while maintaining their integrity throughout the processes of extraction, enrichment, purification, and fractionation. Recent advances in each of these critical front-end preparation processes, including minimalistic workflows, have greatly expanded the capacity of MS for top-down proteome analysis. Acknowledging the many contributions in MS technology and sample processing, the present review aims to highlight the diverse strategies that have forged a pathway for top-down proteomics. We comprehensively discuss the evolution of front-end workflows that today facilitate optimal characterization of proteoform-driven biology, including a brief description of the clinical applications that have motivated these impactful contributions.

Analysis of Isotopically Depleted Proteins Derived from Escherichia coli and Caenorhabditis elegans Cell Lines by Liquid Chromatography 21 T Fourier Transform-Ion Cyclotron Resonance Mass Spectrometry

Protein mass measurement by mass spectrometry is complicated by wide isotopic distributions that result from incorporation of heavy isotopes of C, H, N, O, and S, thereby limiting signal-to-noise ratio (SNR) and accurate intact mass determination, particularly for larger proteins [Fenselau et al. Anal. Chem. 1983, 55 (2), 353-356]. Observation of the monoisotopic mass-to-charge ratio (m/z) is the simplest and most accurate way to determine intact protein mass, but as mass increases, the relative abundance of the monoisotopic peak becomes so low that it is often undetectable. Here, we used an isotopically depleted growth medium to culture bacterial cells (Escherichia coli), resulting in isotopically depleted proteins. Isotopically depleted proteins show increased sequence coverage, mass measurement accuracy, and increased S/N of the monoisotopic peak by Fourier transform ion cyclotron resonance mass spectrometry analysis. We then grew Caenorhabditis elegans cells in a medium containing living isotopically depleted E. coli cells, thereby producing the first isotopically depleted eukaryotic proteins. This is the first time isotopic depletion has been implemented for four isotopes (¹H, ¹²C, ¹⁴N, and ¹⁶O), resulting in the highest degree of depletion ever used for protein analysis and further improving MS analysis.

Sample preparation for structural mass spectrometry via polyacrylamide gel electrophoresis

Mass spectrometry is an analytical technique that can detect protein molecules with high sensitivity. Its use is not limited to the mere identification of protein components in biological samples, but is recently being utilized for large-scale analysis of protein structures in vivo as well. Top-down mass spectrometry with an ultra-high resolution mass spectrometer, for example, ionizes proteins in their intact state and allows rapid analysis of their chemical structure, which is used to determine proteoform profiles. Furthermore, cross-linking mass spectrometry, which analyzes enzyme-digested fragments of chemically cross-linked protein complexes, allows acquisition of conformational information on protein complexes in multimolecular crowding environments. In the analysis workflow of structural mass spectrometry, prior fractionation of crude biological samples is an effective way to obtain more detailed structural information. Polyacrylamide gel electrophoresis (PAGE), known as a simple and reproducible means of protein separation in biochemistry, is one example of an excellent high-resolution sample prefractionation tool for structural mass spectrometry. This chapter describes elemental technologies for PAGE-based sample prefractionation including Passively Eluting Proteins from Polyacrylamide gels as Intact species for Mass Spectrometry (PEPPI-MS), a highly efficient method for intact in-gel protein recovery, and Anion-Exchange disk-assisted Sequential sample Preparation (AnExSP), a rapid enzymatic digestion method using a solid-phase extraction microspin column for gel-recovered proteins, in addition to presenting detailed experimental protocols and examples of their use for structural mass spectrometry.

Validation of Top-Down Proteomics Data by Bottom-Up-Based N-Terminomics Reveals Pitfalls in Top-Down-Based Terminomics Workflows

Bottom-up proteomics (BUP)-based N-terminomics techniques have become standard to identify protein N-termini. While these methods rely on the identification of N-terminal peptides only, top-down proteomics (TDP) comes with the promise to provide additional information about post-translational modifications and the respective C-termini. To evaluate the potential of TDP for terminomics, two established TDP workflows were employed for the proteome analysis of the nematode Caenorhabditis elegans. The N-termini of the identified proteoforms were validated using a BUP-based N-terminomics approach. The TDP workflows used here identified 1658 proteoforms, the N-termini of which were verified by BUP in 25% of entities only. Caveats in both the BUP- and TDP-based workflows were shown to contribute to this low overlap. In BUP, the use of trypsin prohibits the detection of arginine-rich or arginine-deficient N-termini, while in TDP, the formation of artificially generated termini was observed in particular in a workflow encompassing sample treatment with high acid concentrations. Furthermore, we demonstrate the applicability of reductive dimethylation in TDP to confirm biological N-termini. Overall, our study shows not only the potential but also current limitations of TDP for terminomics studies and also presents suggestions for future developments, for example, for data quality control, allowing improvement of the detection of protein termini by TDP.

Fourier-transform ion cyclotron resonance mass spectrometry for characterizing proteoforms

Proteoforms contribute functional diversity to the proteome and aberrant proteoforms levels have been implicated in biological dysfunction and disease. Fourier-transform ion cyclotron resonance mass spectrometry (FT-ICR MS), with its ultrahigh mass-resolving power, mass accuracy, and versatile tandem MS capabilities, has empowered top-down, middle-down, and native MS-based approaches for characterizing proteoforms and their complexes in biological systems. Herein, we review the features which make FT-ICR MS uniquely suited for measuring proteoform mass with ultrahigh resolution and mass accuracy; obtaining in-depth proteoform sequence coverage with expansive tandem MS capabilities; and unambiguously identifying and localizing post-translational and noncovalent modifications. We highlight examples from our body of work in which we have quantified and comprehensively characterized proteoforms from cardiac and skeletal muscle to better understand conditions such as chronic heart failure, acute myocardial infarction, and sarcopenia. Structural characterization of monoclonal antibodies and their proteoforms by FT-ICR MS and emerging applications, such as native top-down FT-ICR MS and high-throughput top-down FT-ICR MS-based proteomics at 21 T, are also covered. Historically, the information gleaned from FT-ICR MS analyses have helped provide biological insights. We predict FT-ICR MS will continue to enable the study of proteoforms of increasing size from increasingly complex endogenous mixtures and facilitate the benchmarking of sensitive and specific assays for clinical diagnostics. © 2020 John Wiley & Sons Ltd. Mass Spec Rev.

Online μSEC2-nRPLC-MS for Improved Sensitivity of Intact Protein Detection of IEF-Separated Nonhuman Primate Cerebrospinal Fluid Proteins

Proteoform-resolved information, obtained by top-down (TD) "intact protein" proteomics, is expected to contribute substantially to the understanding of molecular pathogenic mechanisms and, in turn, identify novel therapeutic and diagnostic targets. However, the robustness of mass spectrometry (MS) analysis of intact proteins in complex biological samples is hindered by the high dynamic range in protein concentration and mass, protein instability, and buffer complexity. Here, we describe an evolutionary step for intact protein investigations through the online implementation of tandem microflow size-exclusion chromatography with nanoflow reversed-phase liquid chromatography and MS (μSEC2-nRPLC-MS). Online serial high-/low-pass SEC filtration overcomes the aforementioned hurdles to intact proteomic analysis through automated sample desalting/cleanup and enrichment of target mass ranges (5-155 kDa) prior to nRPLC-MS. The coupling of μSEC to nRPLC is achieved through a novel injection volume control (IVC) strategy of inserting protein trap columns, pre- and post-μSEC columns, to enable injection of dilute samples in high volumes without loss of sensitivity or resolution. Critical characteristics of the approach are tested via rigorous investigations on samples of varied complexity and chemical background. Application of the platform to cerebrospinal fluid (CSF) prefractionated by OFFGEL isoelectric focusing drastically increases the number of intact mass tags (IMTs) detected within the target mass range (5-30 kDa) in comparison to one-dimensional nRPLC-MS with approximately 100× less CSF than previous OFFGEL studies. Furthermore, the modular design of the μSEC2-nRPLC-MS platform is robust and promises significant flexibility for large-scale TDMS analysis of diverse samples either directly or in concert with other multidimensional fractionation steps.

Proteomes Are of Proteoforms: Embracing the Complexity

Proteomes are complex-much more so than genomes or transcriptomes. Thus, simplifying their analysis does not simplify the issue. Proteomes are of proteoforms, not canonical proteins. While having a catalogue of amino acid sequences provides invaluable information, this is the Proteome-lite. To dissect biological mechanisms and identify critical biomarkers/drug targets, we must assess the myriad of proteoforms that arise at any point before, after, and between translation and transcription (e.g., isoforms, splice variants, and post-translational modifications [PTM]), as well as newly defined species. There are numerous analytical methods currently used to address proteome depth and here we critically evaluate these in terms of the current 'state-of-the-field'. We thus discuss both pros and cons of available approaches and where improvements or refinements are needed to quantitatively characterize proteomes. To enable a next-generation approach, we suggest that advances lie in transdisciplinarity via integration of current proteomic methods to yield a unified discipline that capitalizes on the strongest qualities of each. Such a necessary (if not revolutionary) shift cannot be accomplished by a continued primary focus on proteo-genomics/-transcriptomics. We must embrace the complexity. Yes, these are the hard questions, and this will not be easy…but where is the fun in easy?

Characterizing Endogenous Protein Complexes with Biological Mass Spectrometry

Biological mass spectrometry (MS) encompasses a range of methods for characterizing proteins and other biomolecules. MS is uniquely powerful for the structural analysis of endogenous protein complexes, which are often heterogeneous, poorly abundant, and refractive to characterization by other methods. Here, we focus on how biological MS can contribute to the study of endogenous protein complexes, which we define as complexes expressed in the physiological host and purified intact, as opposed to reconstituted complexes assembled from heterologously expressed components. Biological MS can yield information on complex stoichiometry, heterogeneity, topology, stability, activity, modes of regulation, and even structural dynamics. We begin with a review of methods for isolating endogenous complexes. We then describe the various biological MS approaches, focusing on the type of information that each method yields. We end with future directions and challenges for these MS-based methods.

Quantitative Top-Down Proteomics by Isobaric Labeling with Thiol-Directed Tandem Mass Tags

While identification-centric (qualitative) top-down proteomics (TDP) has seen rapid progress in the recent past, the quantification of intact proteoforms within complex proteomes is still challenging. The by far mostly applied approach is label-free quantification, which, however, provides limited multiplexing capacity, and its use in combination with multidimensional separation is encountered with a number of problems. Isobaric labeling, which is a standard quantification approach in bottom-up proteomics, circumvents these limitations. Here, we introduce the application of thiol-directed isobaric labeling for quantitative TDP. For this purpose, we analyzed the labeling efficiency and optimized tandem mass spectrometry parameters for optimal backbone fragmentation for identification and reporter ion formation for quantification. Two different separation schemes, gel-eluted liquid fraction entrapment electrophoresis × liquid chromatography-mass spectrometry (LC-MS) and high/low-pH LC-MS, were employed for the analyses of either Escherichia coli (E. coli) proteomes or combined E. coli/yeast samples (two-proteome interference model) to study potential ratio compression. While the thiol-directed labeling introduces a bias in the quantifiable proteoforms, being restricted to Cys-containing proteoforms, our approach showed excellent accuracy in quantification, which is similar to that achievable in bottom-up proteomics. For example, 876 proteoforms could be quantified with high accuracy in an E. coli lysate. The LC-MS data were deposited to the ProteomeXchange with the dataset identifier PXD026310.

Advanced Strategies for Proton-Transfer Reactions Coupled with Parallel Ion Parking on a 21 T FT-ICR MS for Intact Protein Analysis

Proton-transfer reactions (PTRs) have emerged as a powerful tool for the study of intact proteins. When coupled with m/z-selective kinetic excitation, such as parallel ion parking (PIP), one can exert exquisite control over rates of reaction with a high degree of specificity. This allows one to "concentrate", in the gas phase, nearly all the signals from an intact protein charge state envelope into a single charge state, improving the signal-to-noise ratio (S/N) by 10× or more. While this approach has been previously reported, here we show that implementing these technologies on a 21 T FT-ICR MS provides a tremendous advantage for intact protein analysis. Advanced strategies for performing PTR with PIP were developed to complement this unique instrument, including subjecting all analyte ions entering the mass spectrometer to PTR and PIP. This experiment, which we call "PTR-MS¹-PIP", generates a pseudo-MS¹ spectrum derived from ions that are exposed to the PTR reagent and PIP waveforms but have not undergone any prior true mass filtering or ion isolation. The result is an extremely rapid and significant improvement in the spectral S/N of intact proteins. This permits the observation of many more proteoforms and reduces ion injection periods for subsequent tandem mass spectrometry characterization. Additionally, the product ion parking waveform has been optimized to enhance the PTR rate without compromise to the parking efficiency. We demonstrate that this process, called "rapid park", can improve reaction rates by 5-10× and explore critical factors discovered to influence this process. Finally, we demonstrate how coupling PTR-MS¹ and rapid park provides a 10-fold reduction in ion injection time, improving the rate of tandem MS sequencing.

Bottom-up and top-down proteomic approaches for the identification, characterization, and quantification of the low molecular weight proteome with focus on short open reading frame-encoded peptides

The recent discovery of alternative open reading frames creates a need for suitable analytical approaches to verify their translation and to characterize the corresponding gene products at the molecular level. As the analysis of small proteins within a background proteome by means of classical bottom-up proteomics is challenging, method development for the analysis of small open reading frame encoded peptides (SEPs) have become a focal point for research. Here, we highlight bottom-up and top-down proteomics approaches established for the analysis of SEPs in both pro- and eukaryotes. Major steps of analysis, including sample preparation and (small) proteome isolation, separation and mass spectrometry, data interpretation and quality control, quantification, the analysis of post-translational modifications, and exploration of functional aspects of the SEPs by means of proteomics technologies are described. These methods do not exclusively cover the analytics of SEPs but simultaneously include the low molecular weight proteome, and moreover, can also be used for the proteome-wide analysis of proteolytic processing events.

Review: Detection and quantification of proteins in human urine

Extensive medical research showed that patients, with high protein concentration in urine, have various kinds of kidney diseases, referred to as proteinuria. Urinary protein biomarkers are useful for diagnosis of many health conditions – kidney and cardio vascular diseases, cancers, diabetes, infections. This review focuses on the instrumental quantification (electrophoresis, chromatography, immunoassays, mass spectrometry, fluorescence spectroscopy, the infrared spectroscopy, and Raman spectroscopy) of proteins (the most of all albumin) in human urine matrix. Different techniques provide unique information on what constituents of the urine are. Due to complex nature of urine, a separation step by electrophoresis or chromatography are often used for proteomics study of urine. Mass spectrometry is a powerful tool for the discovery and the analysis of biomarkers in urine, however, costs of the analysis are high, especially for quantitative analysis. Immunoassays, which often come with fluorescence detection, are major qualitative and quantitative tools in clinical analysis. While Infrared and Raman spectroscopies do not give extensive information about urine, they could become important tools for the routine clinical diagnostics of kidney problems, due to rapidness and low-cost. Thus, it is important to review all the applicable techniques and methods related to urine analysis. In this review, a brief overview of each technique's principle is introduced. Where applicable, research papers about protein determination in urine are summarized with the main figures of merits, such as the limit of detection, the detectable range, recovery and accuracy, when available.

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Urinary protein biomarkers are useful for diagnosis of many conditions: kidney and cardio vascular diseases, cancers.

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Liquid chromatography – mass spectroscopy is a powerful tool for urine proteomics, but used mostly in science.

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Immunoassays are widely used in both clinical and bio-analytical laboratories.

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IR and Raman spectroscopies are promising tools for diagnostics of urine due to low-cost and rapidness.

Spritz: A Proteogenomic Database Engine

Proteoforms are the workhorses of the cell, and subtle differences between their amino acid sequences or post-translational modifications (PTMs) can change their biological function. To most effectively identify and quantify proteoforms in genetically diverse samples by mass spectrometry (MS), it is advantageous to search the MS data against a sample-specific protein database that is tailored to the sample being analyzed, in that it contains the correct amino acid sequences and relevant PTMs for that sample. To this end, we have developed Spritz (https://smith-chem-wisc.github.io/Spritz/), an open-source software tool for generating protein databases annotated with sequence variations and PTMs. We provide a simple graphical user interface for Windows and scripts that can be run on any operating system. Spritz automatically sets up and executes approximately 20 tools, which enable the construction of a proteogenomic database from only raw RNA sequencing data. Sequence variations that are discovered in RNA sequencing data upon comparison to the Ensembl reference genome are annotated on proteins in these databases, and PTM annotations are transferred from UniProt. Modifications can also be discovered and added to the database using bottom-up mass spectrometry data and global PTM discovery in MetaMorpheus. We demonstrate that such sample-specific databases allow the identification of variant peptides, modified variant peptides, and variant proteoforms by searching bottom-up and top-down proteomic data from the Jurkat human T lymphocyte cell line and demonstrate the identification of phosphorylated variant sites with phosphoproteomic data from the U2OS human osteosarcoma cell line.

Distinct hypertrophic cardiomyopathy genotypes result in convergent sarcomeric proteoform profiles revealed by top-down proteomics

Hypertrophic cardiomyopathy (HCM) is the most common heritable heart disease. Although the genetic cause of HCM has been linked to mutations in genes encoding sarcomeric proteins, the ability to predict clinical outcomes based on specific mutations in HCM patients is limited. Moreover, how mutations in different sarcomeric proteins can result in highly similar clinical phenotypes remains unknown. Posttranslational modifications (PTMs) and alternative splicing regulate the function of sarcomeric proteins; hence, it is critical to study HCM at the level of proteoforms to gain insights into the mechanisms underlying HCM. Herein, we employed high-resolution mass spectrometry-based top-down proteomics to comprehensively characterize sarcomeric proteoforms in septal myectomy tissues from HCM patients exhibiting severe outflow track obstruction (n = 16) compared to nonfailing donor hearts (n = 16). We observed a complex landscape of sarcomeric proteoforms arising from combinatorial PTMs, alternative splicing, and genetic variation in HCM. A coordinated decrease of phosphorylation in important myofilament and Z-disk proteins with a linear correlation suggests PTM cross-talk in the sarcomere and dysregulation of protein kinase A pathways in HCM. Strikingly, we discovered that the sarcomeric proteoform alterations in the myocardium of HCM patients undergoing septal myectomy were remarkably consistent, regardless of the underlying HCM-causing mutations. This study suggests that the manifestation of severe HCM coalesces at the proteoform level despite distinct genotype, which underscores the importance of molecular characterization of HCM phenotype and presents an opportunity to identify broad-spectrum treatments to mitigate the most severe manifestations of this genetically heterogenous disease.

Mass spectrometry profiling of low molecular weight proteins and peptides isolated by acetone precipitation

Solvent-based protein precipitation provides exceptional recovery, particularly when the ionic strength of the solution is controlled. While precipitation is ideally suited for intact protein purification ahead of mass-spectrometry, low molecular weight (LMW) proteins and peptides are considered less susceptible to aggregation in organic solvent. As the combination of salt and organic solvent (i.e. acetone) has yet to be exploited to precipitate LMW proteins, we herein determine the low mass limit for solvent-based protein precipitation. We establish optimized conditions for high recovery precipitation of LMW proteins and peptides. Our results demonstrate a strong dependence on the type of salt to recover LMW components from complex mixtures. Inclusion of 100 mM ZnSO₄ with 97% acetone provides near quantitative recovery of all peptides down to 2 kDa, and continues to exceed 90% yield for peptides at a molecular weight of 1 kDa. A detailed characterization of the precipitated peptides resulting from trypsin and pepsin digestion of complex systems is provided by bottom-up mass spectrometry.

MASH Explorer: A Universal Software Environment for Top-Down Proteomics

Top-down mass spectrometry (MS)-based proteomics enable a comprehensive analysis of proteoforms with molecular specificity to achieve a proteome-wide understanding of protein functions. However, the lack of a universal software for top-down proteomics is becoming increasingly recognized as a major barrier, especially for newcomers. Here, we have developed MASH Explorer, a universal, comprehensive, and user-friendly software environment for top-down proteomics. MASH Explorer integrates multiple spectral deconvolution and database search algorithms into a single, universal platform which can process top-down proteomics data from various vendor formats, for the first time. It addresses the urgent need in the rapidly growing top-down proteomics community and is freely available to all users worldwide. With the critical need and tremendous support from the community, we envision that this MASH Explorer software package will play an integral role in advancing top-down proteomics to realize its full potential for biomedical research.

PEPPI-MS: Polyacrylamide-Gel-Based Prefractionation for Analysis of Intact Proteoforms and Protein Complexes by Mass Spectrometry

Prefractionation of complex mixtures of proteins derived from biological samples is indispensable for proteome analysis via top-down mass spectrometry (MS). Polyacrylamide gel electrophoresis (PAGE), which enables high-resolution protein separation based on molecular size, is a widely used technique in biochemical experiments and has the potential to be useful in sample fractionation for top-down MS analysis. However, the lack of a means to efficiently recover the separated proteins in-gel has always been a barrier to its use in sample prefractionation. In this study, we present a novel experimental workflow, called Passively Eluting Proteins from Polyacrylamide gels as Intact species for MS ("PEPPI-MS"), which allows top-down MS of PAGE-separated proteins. The optimization of Coomassie brilliant blue staining followed by the passive extraction step in the PEPPI-MS workflow enabled the efficient recovery of proteins, separated on commercial precast gels, from a wide range of molecular weight regions in under 10 min. Two-dimensional separation combining offline PEPPI-MS with online reversed-phase liquid chromatographic separation resulted in identification of over 1000 proteoforms recovered from the target region of the gel (≤50 kDa). Given the widespread availability and relatively low cost of traditional sodium dodecyl sulfate (SDS)-PAGE equipment, the PEPPI-MS workflow will be a powerful prefractionation strategy for top-down proteomics.

Improving Proteoform Identifications in Complex Systems Through Integration of Bottom-Up and Top-Down Data

Cellular functions are performed by a vast and diverse set of proteoforms. Proteoforms are the specific forms of proteins produced as a result of genetic variations, RNA splicing, and post-translational modifications (PTMs). Top-down mass spectrometric analysis of intact proteins enables proteoform identification, including proteoforms derived from sequence cleavage events or harboring multiple PTMs. In contrast, bottom-up proteomics identifies peptides, which necessitates protein inference and does not yield proteoform identifications. We seek here to exploit the synergies between these two data types to improve the quality and depth of the overall proteomic analysis. To this end, we automated the large-scale integration of results from multiprotease bottom-up and top-down analyses in the software program Proteoform Suite and applied it to the analysis of proteoforms from the human Jurkat T lymphocyte cell line. We implemented the recently developed proteoform-level classification scheme for top-down tandem mass spectrometry (MS/MS) identifications in Proteoform Suite, which enables users to observe the level and type of ambiguity for each proteoform identification, including which of the ambiguous proteoform identifications are supported by bottom-up-level evidence. We used Proteoform Suite to find instances where top-down identifications aid in protein inference from bottom-up analysis and conversely where bottom-up peptide identifications aid in proteoform PTM localization. We also show the use of bottom-up data to infer proteoform candidates potentially present in the sample, allowing confirmation of such proteoform candidates by intact-mass analysis of MS1 spectra. The implementation of these capabilities in the freely available software program Proteoform Suite enables users to integrate large-scale top-down and bottom-up data sets and to utilize the synergies between them to improve and extend the proteomic analysis.

Developing front-end devices for improved sample preparation in MS-based proteome analysis

Chemical analysis has long relied on instrumentation, from the simplest (eg, burets) to the more sophisticated (eg, mass spectrometers) to facilitate precision measurements. Regardless of their complexity, the development of a new instrumental device can be a valued approach to address problems in science. In this perspective, we outline the process of novel device design, from early phase conception to the manufacturing and testing of the tool or gadget. Focus is placed on the development of improved front-end devices to facilitate protein sample manipulations ahead of mass spectrometry, which therefore augment the proteomics workflow. Highlighted are some of the many training secrets, choices, and challenges that are inherent to the often iterative process of device design. In hopes of inspiring others to pursue instrument design to address relevant research questions, we present a summary list of points to consider prior to innovating their own devices.

Thorough Performance Evaluation of 213 nm Ultraviolet Photodissociation for Top-down Proteomics

Top-down proteomics studies intact proteoform mixtures and offers important advantages over more common bottom-up proteomics technologies, as it avoids the protein inference problem. However, achieving complete molecular characterization of investigated proteoforms using existing technologies remains a fundamental challenge for top-down proteomics. Here, we benchmark the performance of ultraviolet photodissociation (UVPD) using 213 nm photons generated by a solid-state laser applied to the study of intact proteoforms from three organisms. Notably, the described UVPD setup applies multiple laser pulses to induce ion dissociation, and this feature can be used to optimize the fragmentation outcome based on the molecular weight of the analyzed biomolecule. When applied to complex proteoform mixtures in high-throughput top-down proteomics, 213 nm UVPD demonstrated a high degree of complementarity with the most employed fragmentation method in proteomics studies, higher-energy collisional dissociation (HCD). UVPD at 213 nm offered higher average proteoform sequence coverage and degree of proteoform characterization (including localization of post-translational modifications) than HCD. However, previous studies have shown limitations in applying database search strategies developed for HCD fragmentation to UVPD spectra which contains up to nine fragment ion types. We therefore performed an analysis of the different UVPD product ion type frequencies. From these data, we developed an ad hoc fragment matching strategy and determined the influence of each possible ion type on search outcomes. By paring down the number of ion types considered in high-throughput UVPD searches from all types down to the four most abundant, we were ultimately able to achieve deeper proteome characterization with UVPD. Lastly, our detailed product ion analysis also revealed UVPD cleavage propensities and determined the presence of a product ion produced specifically by 213 nm photons. All together, these observations could be used to better elucidate UVPD dissociation mechanisms and improve the utility of the technique for proteomic applications.

Considerations for mass spectrometry-based multi-omic analysis of clinical samples

Introduction: The role of mass spectrometry in biomolecule analysis has become paramount over the last several decades ranging in the analysis across model systems and human specimens. Accordingly, the presence of mass spectrometers in clinical laboratories has also expanded alongside the number of researchers investigating the protein, lipid, and metabolite composition of an array of biospecimens. With this increase in the number of omic investigations, it is important to consider the entire experimental strategy from sample collection and storage, data collection and analysis.Areas covered: In this short review, we outline considerations for working with clinical (e.g. human) specimens including blood, urine, and cerebrospinal fluid, with emphasis on sample handling, profiling composition, targeted measurements and relevance to disease. Discussions of integrated genomic or transcriptomic datasets are not included. A brief commentary is also provided regarding new technologies with clinical relevance.Expert opinion: The role of mass spectrometry to investigate clinically related specimens is on the rise and the ability to integrate multiple omics datasets from mass spectrometry measurements will be crucial to further understanding human health and disease.

Constructing Human Proteoform Families Using Intact-Mass and Top-Down Proteomics with a Multi-Protease Global Post-Translational Modification Discovery Database

Complex human biomolecular processes are made possible by the diversity of human proteoforms. Constructing proteoform families, groups of proteoforms derived from the same gene, is one way to represent this diversity. Comprehensive, high-confidence identification of human proteoforms remains a central challenge in mass spectrometry-based proteomics. We have previously reported a strategy for proteoform identification using intact-mass measurements, and we have since improved that strategy by mass calibration based on search results, the use of a global post-translational modification discovery database, and the integration of top-down proteomics results with intact-mass analysis. In the present study, we combine these strategies for enhanced proteoform identification in total cell lysate from the Jurkat human T lymphocyte cell line. We collected, processed, and integrated three types of proteomics data (NeuCode-labeled intact-mass, label-free top-down, and multi-protease bottom-up) to maximize the number of confident proteoform identifications. The integrated analysis revealed 5950 unique experimentally observed proteoforms, which were assembled into 848 proteoform families. Twenty percent of the observed proteoforms were confidently identified at a 3.9% false discovery rate, representing 1207 unique proteoforms derived from 484 genes.

Top-Down Proteomics Applied to Human Cerebrospinal Fluid

Cerebrospinal fluid (CSF) is the fluid of choice to study pathologies and disorders of the central nervous system (CNS). Its composition, especially its proteins and peptides, holds the promise that it may reflect the pathological state of an individual. Traditionally, proteins and peptides in CSF have been analyzed using bottom-up proteomics technologies in the search of high proteome coverage. However, the limited protein sequence coverage of this technology means that information regarding post-translational modifications (PTMs) and alternative splice variants is lost. As an alternative technology, top-down proteomics offers low to medium proteome coverage, but high protein coverage enabling almost a full characterization of the proteins' primary structure. This allows us to precisely identify distinct molecular forms of proteins (proteoforms) as well as naturally occurring bioactive peptide fragments, which could be of critical biological relevance and would otherwise remain undetected with a classical proteomics approach.Here, we describe various strategies including sample preparation protocols, off-line intact protein prefractionation, and LC-MS/MS methods together with data analysis pipelines to analyze cerebrospinal fluid (CSF) by top-down proteomics. However, there is not a unique or standardized method and the selection of the top-down strategy will depend on the exact goal of the study. Here, we describe various top-down proteomics methods that enable rapid protein characterization and may be an excellent companion analytical workflow in the search for new protein biomarkers in neurodegenerative diseases.

[Comparing nanoflow reversed-phase liquid chromatography-tandem mass spectrometry and capillary zone electrophoresis-tandem mass spectrometry for top-down proteomics]

One of the major shortcomings in top-down proteomics is the lack of efficient separations for intact proteins that can be effectively coupled to mass spectrometry. Capillary zone electrophoresis (CZE) and nanoflow reversed-phase liquid chromatography (nanoRPLC) are two methods that can be coupled to mass spectrometry directly and have been recently advanced in terms of their ability to separate intact proteins in complex biological mixtures. In this work, for the first time, we compared the state-of-the-art nanoRPLC-MS/MS and CZE-MS/MS platforms for top-down characterization of a standard protein mixture and an Escherichia coli (E. coli) proteome sample. CZE-MS produced comparable signals of standard proteins to RPLC-MS with 10-times less sample consumption. Interestingly, the proteins in RPLC-MS tended to have higher charge states than in CZE-MS, most likely due to the high acetonitrile concentration in RPLC mobile phase, leading to the more extensive unfolding of proteins in RPLC compared to in CZE. CZE-MS/MS identified 159 proteins and 513 proteoforms using 1-μg E. coli proteins in a single run and outperformed RPLC-MS/MS using 1-μg E. coli proteins in terms of protein and proteoform identifications (159 vs. 105 proteins and 513 vs. 277 proteoforms). The RPLC-MS/MS using 8-μg E. coli proteins identified 245 proteins and 1004 proteoforms in a single run, and the data was much better than that from CZE-MS/MS (1-μg E. coli proteins) regarding the number of identifications because of the 8-times higher sample loading amount and significantly wider separation window of RPLC-MS/MS compared to CZE-MS/MS.

Advances in biomarker detection: Alternative approaches for blood-based biomarker detection

In the clinical setting, a blood sample is typically the starting point for biomarker search and discovery. Mass spectrometry (MS) is a highly sensitive and informative method for characterizing a very wide range of metabolites and proteins and is therefore a potentially powerful tool for biomarker discovery. However, the physicochemical characteristics of blood coupled with very large ranges of protein and metabolite concentrations present a significant technical obstacle for resolving and quantifying putative biomarkers by MS. Blood fractionation procedures are being developed to reduce the proteome/metabolome complexity and concentration ranges, allowing a greater diversity of analytes, including those at very low concentrations, to be quantified. In this chapter, several strategies for enriching and/or isolating specific blood components are summarized, including methods for the analysis of low and high molecular weight compounds, usually neglected in this type of assays, extracellular vesicles, and peripheral blood mononuclear cells (PBMCs). For each method, relevant practical information is presented for effective implementation.

Identification and Quantification of Proteoforms by Mass Spectrometry

A proteoform is a defined form of a protein derived from a given gene with a specific amino acid sequence and localized post-translational modifications. In top-down proteomic analyses, proteoforms are identified and quantified through mass spectrometric analysis of intact proteins. Recent technological developments have enabled comprehensive proteoform analyses in complex samples, and an increasing number of laboratories are adopting top-down proteomic workflows. In this review, some recent advances are outlined and current challenges and future directions for the field are discussed.

A comprehensive pipeline for translational top-down proteomics from a single blood draw

Top-down proteomics (TDP) by mass spectrometry (MS) is a technique by which intact proteins are analyzed. It has become increasingly popDesalting and concentrating GELFrEEular in translational research because of the value of characterizing distinct proteoforms of intact proteins. Compared to bottom-up proteomics (BUP) strategies, which measure digested peptide mixtures, TDP provides highly specific molecular information that avoids the bioinformatic challenge of protein inference. However, the technique has been difficult to implement widely because of inherent limitations of existing sample preparation methods and instrumentation. Recent improvements in proteoform pre-fractionation and the availability of high-resolution benchtop mass spectrometers have made it possible to use high-throughput TDP for the analysis of complex clinical samples. Here, we provide a comprehensive protocol for analysis of a common sample type in translational research: human peripheral blood mononuclear cells (PBMCs). The pipeline comprises multiple workflows that can be treated as modular by the reader and used for various applications. First, sample collection and cell preservation are described for two clinical biorepository storage schemes. Cell lysis and proteoform pre-fractionation by gel-eluted liquid fractionation entrapment electrophoresis are then described. Importantly, instrument setup and liquid chromatography-tandem MS are described for TDP analyses, which rely on high-resolution Fourier-transform MS. Finally, data processing and analysis are described using two different, application-dependent software tools: ProSight Lite for targeted analyses of one or a few proteoforms and TDPortal for high-throughput TDP in discovery mode. For a single sample, the minimum completion time of the entire experiment is 72 h.

A Top-Down Proteomics Platform Coupling Serial Size Exclusion Chromatography and Fourier Transform Ion Cyclotron Resonance Mass Spectrometry

Mass spectrometry (MS) based top-down proteomics provides rich information about proteoforms arising from combinatorial amino acid sequence variations and post-translational modifications (PTMs). Fourier transform ion cyclotron resonance (FT-ICR) MS affords ultrahigh resolving power and provides high-accuracy mass measurements, presenting a powerful tool for top-down MS characterization of proteoforms. However, the detection and characterization of large proteins from complex mixtures remain challenging due to the exponential decrease in S: N with increasing molecular weight (MW) and coeluting low-MW proteins; thus, size-based fractionation of complex protein mixtures prior to MS analysis is necessary. Here, we directly combine MS-compatible serial size exclusion chromatography (sSEC) fractionation with 12 T FT-ICR MS for targeted top-down characterization of proteins from complex mixtures extracted from human and swine heart tissue. Benefiting from the ultrahigh resolving power of FT-ICR, we isotopically resolved 31 distinct proteoforms (30-50 kDa) simultaneously in a single mass spectrum within a 100 m/ z window. Notably, within a 5 m/ z window, we obtained baseline isotopic resolution for 6 distinct large proteoforms (30-50 kDa). The ultrahigh resolving power of FT-ICR MS combined with sSEC fractionation enabled targeted top-down analysis of large proteoforms (>30 kDa) from the human heart proteome without extensive chromatographic separation or protein purification. Further separation of proteoforms inside the mass spectrometer (in-MS) allowed for isolation of individual proteoforms and targeted electron capture dissociation (ECD), yielding high sequence coverage. sSEC/FT-ICR ECD facilitated the identification and sequence characterization of important metabolic enzymes. This platform, which facilitates deep interrogation of proteoform primary structure, is highly tunable, allows for adjustment of MS and MS/MS parameters in real time, and can be utilized for a variety of complex protein mixtures.

3D printed gel electrophoresis device coupling with ICP-MS for online separation and detection of metalloproteins

We successfully developed a strategy to combine a customized gel electrophoresis device with ICP-MS for online separation and detection of metalloproteins. The self-designed horizontal column gel electrophoresis device was rapidly and easily fabricated in the laboratory via 3D printing with a low cost. The feasibility of 3D printing to fabricate this device was investigated by offline separation of commercial protein standards. And a better separation efficiency was found when using gel tubes printed with higher printing precision. As a proof-of-concept, the performance of the whole system is demonstrated by online separation and detection of both iodinated protein standards and proteins in rat blood plasma samples. Benefits from 3D printing, customized modification or further optimization can be readily achieved for a better protein separation and detection efficiency.

Top-Down Protein Identification using a Time-of-Flight Mass Spectrometer and Data Independent Acquisition

Top-down mass spectrometry and direct dissociation of gas phase intact proteins have been demonstrated to be a powerful platform for identifying proteins from complex mixtures and for elucidating post-translational modifications (PTMs). Fragmentation of proteins in the atmospheric pressure/vacuum interface of the electrospray ionization mass spectrometer is an effective dissociation technique that can be utilized for on-line HPLC top-down analysis. We demonstrate the capability to perform intact protein identifications in a single-stage time-of- flight (TOF) mass spectrometer in a data independent (DIA) acquisition fashion by rapidly switching the in-source dissociation (ISD) energy during protein elution from a liquid chromatography (LC) column. The intact protein and product ion masses obtained at low and high ISD energies, respectively, were measured using a TOF mass analyzer. By coupling on-line protein separations to dissociation in the atmospheric pressure/vacuum interface region of the mass spectrometer, we identified proteins in simple complexity mixtures, including subunits from the human 20S proteasome complex, and PTMs such as phosphorylation and N-terminal acetylation events. This proof-of-principle study demonstrates that a data-independent pseudo- MS/MS method could be a relatively in-expensive platform for top-down MS.

Disruption of microglia histone acetylation and protein pathways in mice exhibiting inflammation-associated depression-like symptoms

BACKGROUND

Peripheral immune challenge can elicit microglia activation and depression-related symptoms. The balance of inflammatory signals in the tryptophan pathway can skew the activity of indoleamine-pyrrole 2,3 dioxygenase (IDO1) towards the metabolization of tryptophan into kynurenine (rather than serotonin), and towards neuroprotective or neurotoxic metabolites. The proteome changes that accompany inflammation-associated depression-related behaviors are incompletely understood.

METHODS

The changes in microglia protein abundance and post-translational modifications in wild type (WT) mice that exhibit depression-like symptoms after recovery from peripheral Bacille Calmette-Guerin (BCG) challenge were studied. This WT_BGG group was compared to mice that do not express depression-like symptoms after BCG challenge due to IDO1 deficiency by means of genetic knockout (BCG_KO group), and to WT Saline-treated (Sal) mice (WT_Sal group) using a mass spectrometry-based label-free approach.

RESULTS

The comparison of WT_BCG relative to WT_Sal and KO_BCG mice uncovered patterns of protein abundance and acetylation among the histone families that could influence microglia signaling and transcriptional rates. Members of the histone clusters 1, 2 and 3 families were less abundant in WT_BCG relative to WT_Sal whereas members in the H2A family exhibited the opposite pattern. Irrespective of family, the majority of the histones were less abundant in WT_BCG relative to KO_BCG microglia. Homeostatic mechanisms may temper the potentially toxic effects of high histone levels after BCG challenge to levels lower than Sal. Histone acetylation was highest in WT_BCG and the similar levels observed in WT_Sal and KO_BCG. This result suggest that histone acetylation levels are similar between IDO1 deficient mice after immune challenge and unchallenged WT mice. The over-abundance of tyrosine 3-monooxygenase/tryptophan 5-monooxygenase activation proteins (14-3-3 series) in WT_BCG relative to KO_BCG is particularly interesting because these proteins activate another rate-limiting enzyme in the tryptophan pathway. The over-representation of alcoholism and systemic lupus erythematosus pathways among the proteins exhibiting differential abundance between the groups suggest that these disorders share microglia activation pathways with BCG challenge. The over-representation of phagosome pathway among proteins differentially abundant between WT_BCG and KO_BCG microglia suggest an association between IDO1 deficiency and phagocytosis. Likewise, the over-representation of the gap junction pathway among the differentially abundant proteins between KO_BCG and WT_Sal suggest a multifactorial effect of BCG and IDO1 deficiency on cell communication.

CONCLUSIONS

The present study of histone acetylation and differential protein abundance furthers the understanding of the long lasting effects of peripheral immune challenges. Our findings offer insights into target proteins and mechanisms that provide clues for therapies to ameliorate inflammation-associated depression-related behaviors.

Identification and Quantification of Murine Mitochondrial Proteoforms Using an Integrated Top-Down and Intact-Mass Strategy

The development of effective strategies for the comprehensive identification and quantification of proteoforms in complex systems is a critical challenge in proteomics. Proteoforms, the specific molecular forms in which proteins are present in biological systems, are the key effectors of biological function. Thus, knowledge of proteoform identities and abundances is essential to unraveling the mechanisms that underlie protein function. We recently reported a strategy that integrates conventional top-down mass spectrometry with intact-mass determinations for enhanced proteoform identifications and the elucidation of proteoform families and applied it to the analysis of yeast cell lysate. In the present work, we extend this strategy to enable quantification of proteoforms, and we examine changes in the abundance of murine mitochondrial proteoforms upon differentiation of mouse myoblasts to myotubes. The integrated top-down and intact-mass strategy provided an increase of ∼37% in the number of identified proteoforms compared to top-down alone, which is in agreement with our previous work in yeast; 1779 unique proteoforms were identified using the integrated strategy compared to 1301 using top-down analysis alone. Quantitative comparison of proteoform differences between the myoblast and myotube cell types showed 129 observed proteoforms exhibiting statistically significant abundance changes (fold change >2 and false discovery rate <5%).

Preparation and Immunoaffinity Depletion of Fresh Frozen Tissue Homogenates for Mass Spectrometry-Based Proteomics in the Context of Drug Target/Biomarker Discovery

The discovery of novel drug targets and biomarkers via mass spectrometry (MS)-based proteomic analysis of clinical specimens has proven to be challenging. The wide dynamic range of protein concentration in clinical specimens and the high background/noise originating from highly abundant proteins in tissue homogenates and serum/plasma encompass two major analytical obstacles. Immunoaffinity depletion of highly abundant blood-derived proteins from serum/plasma is a well-established approach adopted by numerous researchers; however, the utilization of this technique for immunodepletion of tissue homogenates obtained from fresh frozen clinical specimens is lacking. We first developed immunoaffinity depletion of highly abundant blood-derived proteins from tissue homogenates, using renal cell carcinoma as a model disease, and followed this study by applying it to different tissue types. Tissue homogenate immunoaffinity depletion of highly abundant proteins may be equally important as is the recognized need for depletion of serum/plasma, enabling more sensitive MS-based discovery of novel drug targets, and/or clinical biomarkers from complex clinical samples. Provided is a detailed protocol designed to guide the researcher through the preparation and immunoaffinity depletion of fresh frozen tissue homogenates for two-dimensional liquid chromatography, tandem mass spectrometry (2D-LC-MS/MS)-based molecular profiling of tissue specimens in the context of drug target and/or biomarker discovery.

Membrane-Based SDS Depletion Ahead of Peptide and Protein Analysis by Mass Spectrometry

SDS interferes with both bottom-up and top-down MS analysis, requiring removal prior to detection. Filter-aided sample preparation (FASP) is favored for bottom-up proteomics (BUP) while acetone precipitation is popular for top-down proteomics (TDP). We recently demonstrated acetone precipitation in a membrane filter cartridge. Alternatively, our automated electrophoretic device, termed transmembrane electrophoresis (TME), depletes SDS for both TDP and BUP studies. Here TME is compared to these two alternative methods of SDS depletion in both BUP and TDP workflows. To do so, a modified FASP method is described applicable to the SDS purification and recovery of intact proteins, suitable for LC/MS. All three methods reliably deplete >99.8% SDS. TME provide higher sample yields (average 90%) than FASP (55%) or acetone precipitation (57%), translating into higher total protein identifications (973 vs 877 FASP or 890 acetone) and higher spectral matches (2.5 times) per protein. In a top down workflow, each SDS-depletion method yields high-quality MS spectra for intact proteins. These results show each of these membrane-based strategies is capable of depleting SDS with high sample recovery and high spectra quality for both BUP and TDP studies.