SP2: Rapid and Automatable Contaminant Removal from Peptide Samples for Proteomic Analyses

Refinement of paramagnetic bead-based digestion protocol for automatic sample preparation using an artificial neural network

Despite technological advances in the proteomics field, sample preparation still represents the main bottleneck in mass spectrometry (MS) analysis. Bead-based protein aggregation techniques have recently emerged as an efficient, reproducible, and high-throughput alternative for protein extraction and digestion. Here, a refined paramagnetic bead-based digestion protocol is described for Opentrons® OT-2 platform (OT-2) as a versatile, reproducible, and affordable alternative for the automatic sample preparation for MS analysis. For this purpose, an artificial neural network (ANN) was applied to maximize the number of peptides without missed cleavages identified in HeLa extract by combining factors such as the quantity (μg) of trypsin/Lys-C and beads (MagReSyn® Amine), % (w/v) SDS, % (v/v) acetonitrile, and time of digestion (h). ANN model predicted the optimal conditions for the digestion of 50 μg of HeLa extract, pointing to the use of 2.5% (w/v) SDS and 300 μg of beads for sample preparation and long-term digestion (16h) with 0.15 μg Lys-C and 2.5 μg trypsin (≈1:17 ratio). Based on the results of the ANN model, the manual protocol was automated in OT-2. The performance of the automatic protocol was evaluated with different sample types, including human plasma, Arabidopsis thaliana leaves, Escherichia coli cells, and mouse tissue cortex, showing great reproducibility and low sample-to-sample variability in all cases. In addition, we tested the performance of this method in the preparation of a challenging biological fluid such as rat bile, a proximal fluid that is rich in bile salts, bilirubin, cholesterol, and fatty acids, among other MS interferents. Compared to other protocols described in the literature for the extraction and digestion of bile proteins, the method described here allowed identify 385 unique proteins, thus contributing to improving the coverage of the bile proteome.

Optimized Workflow for Proteomics and Phosphoproteomics With Limited Tissue Samples

Proteomics and phosphoproteomics play crucial roles in elucidating the dynamics of post-transcriptional processes. While experimental methods and workflows have been established in this field, a persistent challenge arises when dealing with small samples containing a limited amount of protein. This limitation can significantly impact the recovery of peptides and phosphopeptides. In response to this challenge, we have developed a comprehensive experimental workflow tailored specifically for small-scale samples, with a special emphasis on neuronal tissues like the trigeminal ganglion. Our proposed workflow consists of seven steps aimed at optimizing the preparation of limited tissue samples for both proteomic and phosphoproteomic analyses. One noteworthy innovation in our approach involves the utilization of a dual enrichment strategy for phosphopeptides. Initially, we employ Fe-NTA Magnetic beads, renowned for their specificity and effectiveness in capturing phosphopeptides. Subsequently, we complement this approach with the TiO2-based method, which offers a broader spectrum of phosphopeptide recovery. This innovative workflow not only overcomes the challenges posed by limited sample sizes but also establishes a new benchmark for precision and efficiency in proteomic investigations. Published 2024. This article is a U.S. Government work and is in the public domain in the USA. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Protein extraction and digestion Basic Protocol 2: TMT labeling and peptide cleanup Basic Protocol 3: IMAC Fe-NTA magnetic beads phosphopeptide enrichment Basic Protocol 4: TiO2 enrichment Basic Protocol 5: Fe-NTA phosphopeptide Enrichment Basic Protocol 6: High pH peptide fractionation Basic protocol 7: LC-MS/MS analysis and database search.

Veneer Is a Webtool for Rapid, Standardized, and Transparent Interpretation, Annotation, and Reporting of Mammalian Cell Surface N-Glycocapture Data

Currently, no consensus exists regarding criteria required to designate a protein within a proteomic data set as a cell surface protein. Most published proteomic studies rely on varied ontology annotations or computational predictions instead of experimental evidence when attributing protein localization. Consequently, standardized approaches for analyzing and reporting cell surface proteome data sets would increase confidence in localization claims and promote data use by other researchers. Recently, we developed Veneer, a web-based bioinformatic tool that analyzes results from cell surface N-glycocapture workflows─the most popular cell surface proteomics method used to date that generates experimental evidence of subcellular location. Veneer assigns protein localization based on defined experimental and bioinformatic evidence. In this study, we updated the criteria and process for assigning protein localization and added new functionality to Veneer. Results of Veneer analysis of 587 cell surface N-glycocapture data sets from 32 published studies demonstrate the importance of applying defined criteria when analyzing cell surface proteomics data sets and exemplify how Veneer can be used to assess experimental quality and facilitate data extraction for informing future biological studies and annotating public repositories.

Contaminant Spot Check and Removal Assay (ContamSPOT) for Mass Spectrometry Analysis

Mass spectrometry (MS) analysis is often challenged by contaminations from detergents, salts, and polymers that compromise data quality and can damage the chromatography and MS instruments. However, researchers often discover contamination issues only after they acquire the data. There is no existing contaminant assay that is sensitive enough to detect trace amounts of contaminants from a few microliters of samples prior to MS analysis. To address this crucial need in the field, we developed a sensitive, rapid, and cost-effective contaminant spot check and removal assay (ContamSPOT) to detect and quantify trace amounts of contaminants, such as detergents, salts, and other chemicals commonly used in the MS sample preparation workflow. Only 1 μL of the sample was used prior to MS injection to quantify contaminants by ContamSPOT colorimetric or fluorometric assay on a thin layer chromatography (TLC) plate. We also optimized contaminant removal methods to salvage samples with minimal loss when ContamSPOT showed a positive result. ContamSPOT was then successfully applied to evaluate commonly used bottom-up proteomic methods regarding the effectiveness of removing detergent, peptide recovery, reproducibility, and proteome coverage. We expect ContamSPOT to be widely adopted by MS laboratories as a last-step quality checkpoint prior to MS injection. We provided a practical decision tree and a step-by-step protocol with a troubleshooting guide to facilitate the use of ContamSPOT by other researchers. ContamSPOT can also provide a unique readout of sample cleanliness for developing new MS-based sample preparation methods in the future.

Recent developments in mass-spectrometry-based targeted proteomics of clinical cancer biomarkers

Routine measurement of cancer biomarkers is performed for early detection, risk classification, and treatment monitoring, among other applications, and has substantially contributed to better clinical outcomes for patients. However, there remains an unmet need for clinically validated assays of cancer protein biomarkers. Protein tumor markers are of particular interest since proteins carry out the majority of biological processes and thus dynamically reflect changes in cancer pathophysiology. Mass spectrometry-based targeted proteomics is a powerful tool for absolute peptide and protein quantification in biological matrices with numerous advantages that make it attractive for clinical applications in oncology. The use of liquid chromatography-tandem mass spectrometry (LC-MS/MS) based methodologies has allowed laboratories to overcome challenges associated with immunoassays that are more widely used for tumor marker measurements. Yet, clinical implementation of targeted proteomics methodologies has so far been limited to a few cancer markers. This is due to numerous challenges associated with paucity of robust validation studies of new biomarkers and the labor-intensive and operationally complex nature of LC-MS/MS workflows. The purpose of this review is to provide an overview of targeted proteomics applications in cancer, workflows used in targeted proteomics, and requirements for clinical validation and implementation of targeted proteomics assays. We will also discuss advantages and challenges of targeted MS-based proteomics assays for clinical cancer biomarker analysis and highlight some recent developments that will positively contribute to the implementation of this technique into clinical laboratories.

The nitrate transporter-sensor MtNPF6.8 regulates the branched chain amino acid/pantothenate metabolic pathway in barrel medic (Medicago truncatula Gaertn.) root tip

Nitrogen is the most limiting nutrient for plants, and it is preferentially absorbed in the form of nitrate by roots, which adapt to nitrate fluctuations by remodelling their architecture. Although core mechanisms of the response to nitrate availability are relatively well-known, signalling events controlling root growth and architecture have not all been identified, in particular in Legumes. However, the developmental effect of nitrate in Legumes is critical since external nitrate not only regulates root architecture but also N2-fixing nodule development. We have previously shown that in barrel medic (Medicago truncatula), the nitrate transporter MtNPF6.8 is required for nitrate sensitivity in root tip. However, uncertainty remains as to whether nitrogen metabolism itself is involved in the MtNPF6.8-mediated response. Here, we examine the metabolic effects of MtNPF6.8-dependent nitrate signalling using metabolomics and proteomics in WT and mtnpf6.8 root tips in presence or absence of nitrate. We found a reorchestration of metabolism due to the mutation, in favour of the branched chain amino acids/pantothenate metabolic pathway, and lipid catabolism via glyoxylate. That is, the mtnpf6.8 mutation was likely associated with a specific rerouting of acetyl-CoA production (glyoxylic cycle) and utilisation (pantothenate and branched chain amino acid synthesis). In agreement with our previous findings, class III peroxidases were confirmed as the main protein class responsive to nitrate, although in an MtNPF6.8-independent fashion. Our data rather suggest the involvement of other pathways within mtnpf6.8 root tips, such as Ca2+ signalling or cell wall methylation.

Benchmarking of Two Peptide Clean-Up Protocols: SP2 and Ethyl Acetate Extraction for Sodium Dodecyl Sulfate or Polyethylene Glycol Removal from Plant Samples before LC-MS/MS

The success of bottom-up proteomic analysis frequently depends on the efficient removal of contaminants from protein or peptide samples before LC-MS/MS. For a peptide clean-up workflow, single-pot solid-phase-enhanced peptide sample preparation on carboxylate-modified paramagnetic beads (termed SP2) was evaluated for sodium dodecyl sulfate or polyethylene glycol removal from Arabidopsis thaliana tryptic peptides. The robust and efficient 40-min SP2 protocol, tested for 10-ng, 250-ng, and 10-µg peptide samples, was proposed and benchmarked thoroughly against the ethyl acetate extraction protocol. The SP2 protocol on carboxylated magnetic beads proved to be the most robust approach, even for the simultaneous removal of massive sodium dodecyl sulfate (SDS) and polyethylene glycol (PEG) contaminations from AT peptide samples in respect of the LC-MS/MS data outperforming ethyl acetate extraction.

Combining Selective Enrichment and a Boosting Approach to Globally and Site-Specifically Characterize Protein Co-translational O-GlcNAcylation

Protein O-GlcNAcylation plays extremely important roles in mammalian cells, regulating signal transduction and gene expression. This modification can happen during protein translation, and systematic and site-specific analysis of protein co-translational O-GlcNAcylation can advance our understanding of this important modification. However, it is extraordinarily challenging because normally O-GlcNAcylated proteins are very low abundant and the abundances of co-translational ones are even much lower. Here, we developed a method integrating selective enrichment, a boosting approach, and multiplexed proteomics to globally and site-specifically characterize protein co-translational O-GlcNAcylation. The boosting approach using the TMT labeling dramatically enhances the detection of co-translational glycopeptides with low abundance when enriched O-GlcNAcylated peptides from cells with a much longer labeling time was used as a boosting sample. More than 180 co-translational O-GlcNAcylated proteins were site-specifically identified. Further analyses revealed that among co-translational glycoproteins, those related to DNA binding and transcription are highly overrepresented using the total identified O-GlcNAcylated proteins in the same cells as the background. Compared with the glycosylation sites on all glycoproteins, co-translational sites have different local structures and adjacent amino acid residues. Overall, an integrative method was developed to identify protein co-translational O-GlcNAcylation, which is very useful to advance our understanding of this important modification.

Automated proteomic sample preparation: The key component for high throughput and quantitative mass spectrometry analysis

Sample preparation for mass spectrometry-based proteomics has many tedious and time-consuming steps that can introduce analytical errors. In particular, the steps around the proteolytic digestion of protein samples are prone to inconsistency. One route for reliable sample processing is the development and optimization of a workflow utilizing an automated liquid handling workstation. Diligent assessment of the sample type, protocol design, reagents, and incubation conditions can significantly improve the speed and consistency of preparation. When combining robust liquid chromatography-mass spectrometry with either discovery or targeted methods, automated sample preparation facilitates increased throughput and reproducible quantitation of biomarker candidates. These improvements in analysis are also essential to process the large patient cohorts necessary to validate a candidate biomarker for potential clinical use. This article reviews the steps in the workflow, optimization strategies, and known applications in clinical, pharmaceutical, and research fields that demonstrate the broad utility for improved automation of sample preparation in the proteomic field.

Mass Spectrometry-Based Proteomics Workflows in Cancer Research: The Relevance of Choosing the Right Steps

The qualitative and quantitative evaluation of proteome changes that condition cancer development can be achieved with liquid chromatography-mass spectrometry (LC-MS). LC-MS-based proteomics strategies are carried out according to predesigned workflows that comprise several steps such as sample selection, sample processing including labeling, MS acquisition methods, statistical treatment, and bioinformatics to understand the biological meaning of the findings and set predictive classifiers. As the choice of best options might not be straightforward, we herein review and assess past and current proteomics approaches for the discovery of new cancer biomarkers. Moreover, we review major bioinformatics tools for interpreting and visualizing proteomics results and suggest the most popular machine learning techniques for the selection of predictive biomarkers. Finally, we consider the approximation of proteomics strategies for clinical diagnosis and prognosis by discussing current barriers and proposals to circumvent them.

Surfaceome mapping of primary human heart cells with CellSurfer uncovers cardiomyocyte surface protein LSMEM2 and proteome dynamics in failing hearts

Cardiac cell surface proteins are drug targets and useful biomarkers for discriminating among cellular phenotypes and disease states. Here we developed an analytical platform, CellSurfer, that enables quantitative cell surface proteome (surfaceome) profiling of cells present in limited quantities, and we apply it to isolated primary human heart cells. We report experimental evidence of surface localization and extracellular domains for 1,144 N-glycoproteins, including cell-type-restricted and region-restricted glycoproteins. We identified a surface protein specific for healthy cardiomyocytes, LSMEM2, and validated an anti-LSMEM2 monoclonal antibody for flow cytometry and imaging. Surfaceome comparisons among pluripotent stem cell derivatives and their primary counterparts highlighted important differences with direct implications for drug screening and disease modeling. Finally, 20% of cell surface proteins, including LSMEM2, were differentially abundant between failing and non-failing cardiomyocytes. These results represent a rich resource to advance development of cell type and organ-specific targets for drug delivery, disease modeling, immunophenotyping and in vivo imaging.

Ocular proteomic and transcriptomic changes with aging in a rabbit model of lensectomy with intraocular lens insertion

Children that undergo intraocular surgery have an exaggerated postoperative response compared to adults that can result in significant postoperative challenges and reduced post-operative visual acuity. Rabbits were used as an animal model for investigating aging differences, treatment options, and surgical techniques for anterior chamber surgical interventions due to similarities in anterior chamber size and decreasing postoperative response with age. In our study, juvenile and adult rabbits underwent lensectomy with intraocular lens (IOL) insertion to determine how ocular RNA transcripts and proteins change with age. Rabbits underwent lensectomy with IOL insertion, and aqueous humor (AH) was collected immediately prior to surgery and at the peak of the postoperative response on post-operative day 3. Proteins related to coagulation and inflammation were assessed using targeted mass spectrometry. In addition, the cornea and iris/ciliary body tissues were dissected, and transcripts analyzed using RNA sequencing. While clinically, juvenile rabbits have greater fibrin formation following intraocular surgery compared to older rabbits, this change does not appear to be related to relative abundance levels of coagulation and inflammatory proteins in the AH. Gene transcript levels from a variety of immune response and inflammatory pathways reflected significant increases when comparing operated to unoperated ocular tissues, indicating the significant impact that surgery has on each ocular structure. This work further advances our understanding of how the rabbit eye proteomic and transcriptomic changes in response to surgery with aging, as we seek to ultimately identify the mechanisms for the exaggerated postoperative responses after pediatric intraocular surgery.

Isobaric labeling: Expanding the breadth, accuracy, depth, and diversity of sample multiplexing

Isobaric labeling has rapidly become a predominant strategy for proteome-wide abundance measurements. Coupled to mass spectrometry, sample multiplexing techniques using isobaric labeling are unparalleled for profiling proteins and posttranslational modifications across multiple samples in a single experiment. Here, I highlight aspects of isobaric labeling in the context of expanding the breadth of multiplexing, improving quantitative accuracy and proteome depth, and developing a wide range of diverse applications. I underscore two facets that enhance quantitative accuracy and reproducibility, specifically the availability of quality control standards for isobaric labeling experiments and the evolution of data acquisition methods. I also emphasize the necessity for standardized methodologies, particularly for emerging high-throughput workflows. Future developments in sample multiplexing will further strengthen the importance of isobaric labeling for comprehensive proteome profiling.

Fe3+-NTA magnetic beads as an alternative to spin column-based phosphopeptide enrichment

Protein phosphorylation is a central mechanism of cellular signal transduction in living organisms. Phosphoproteomic studies systematically catalogue and characterize alterations in phosphorylation states across multiple cellular conditions and are often incorporated into global proteomics experiments. Previously, we found that spin column-based Fe³⁺-NTA enrichment integrated well with our workflow but remained a bottleneck for methods that require higher throughput or a scale that is beyond the capacity of these columns. Here, we compare our well-established spin column-based enrichment strategy with one encompassing magnetic beads. Our data show little difference when using either method in terms of the number of identified phosphopeptides as well as their physicochemical properties. In all, we illustrate how the potentially scalable and automation-friendly magnetic Fe³⁺-NTA beads can seamlessly substitute spin column-based Fe³⁺-NTA agarose beads for global phosphoproteome profiling. SIGNIFICANCE: Protein phosphorylation plays a key role in regulating a multitude of biological processes and can lead to insights into disease pathogenesis. Methodologies which can efficiently enrich phosphopeptides in a scalable and high-throughput manner are essential for profiling dynamic phosphoproteomes. Here we compare two phosphopeptide enrichment workflows, a well-established spin column-based strategy with agarose Fe³⁺-NTA beads and a strategy using magnetic Fe³⁺-NTA beads. Our data suggest that the scalable and automation-friendly magnetic bead-based workflow is an equivalent, but more flexible, enrichment strategy for phosphoproteome profiling experiments.

Release of CHK-2 from PPM-1.D anchorage schedules meiotic entry

Transition from the stem/progenitor cell fate to meiosis is mediated by several redundant posttranscriptional regulatory pathways in Caenorhabditis elegans. Interfering with all three branches causes tumorous germ lines. SCFPROM-1 comprises one branch and mediates a scheduled degradation step at entry into meiosis. prom-1 mutants show defects in the timely initiation of meiotic prophase I events, resulting in high rates of embryonic lethality. Here, we identify the phosphatase PPM-1.D/Wip1 as crucial substrate for PROM-1. We report that PPM-1.D antagonizes CHK-2 kinase, a key regulator for meiotic prophase initiation, including DNA double-strand breaks, chromosome pairing, and synaptonemal complex formation. We propose that PPM-1.D controls the amount of active CHK-2 via both catalytic and noncatalytic activities; notably, noncatalytic regulation seems to be crucial at meiotic entry. PPM-1.D sequesters CHK-2 at the nuclear periphery, and programmed SCFPROM-1-mediated degradation of PPM-1.D liberates the kinase and promotes meiotic entry.

Tissue Plasminogen Activator Effects on Fibrin Volume and the Ocular Proteome in a Juvenile Rabbit Model of Lensectomy

Purpose

To investigate the use of tissue plasminogen activator (tPA) and its effects on the ocular proteome as a therapeutic intervention for postoperative inflammation and fibrin formation following intraocular lens (IOL) insertion in a juvenile rabbit model.

Methods

Twenty-six rabbits, 6 to 7 weeks old, underwent lensectomy with IOL insertion. Following examination on day 3, 100 µL of either 25 µg of recombinant rabbit tPA or balanced salt solution (control) was injected into the anterior chamber. On postoperative day 4, rabbits underwent examination, and eyes were harvested and fixed for 9.4-Tesla magnetic resonance imaging (MRI). Three masked observers quantified fibrin scar volume using Horos Project software. Aqueous humor (AH) was collected immediately prior to surgery and on postoperative days 3 and 4. Proteins related to coagulation and inflammation were assessed in AH samples using targeted mass spectrometry via parallel reaction monitoring.

Results

tPA significantly reduced the volume of fibrin 24 hours following administration compared with control eyes (0.560 mm³ vs. 3.29 mm³; P < 0.0001). Despite the reduced fibrin scar, proteins related to the coagulation and complement cascade were not significantly different following tPA injection.

Conclusions

tPA may be a safe candidate for reduction of postoperative fibrin scarring after intraocular surgery. MRI can provide a quantitative value for fibrin volume changes.

Translational Relevance

tPA is a candidate to treat ocular fibrin scarring. MRI can quantify the efficacy of treatments in future dose-response studies. Targeted mass spectrometry can provide critical data necessary to help decipher the effect on the abundance of targeted proteins following pharmacological intervention.

Direct Target Site Identification of a Sulfonyl-Triazole Covalent Kinase Probe by LC-MS Chemical Proteomics

Chemical proteomics is widely used for the global investigation of protein activity and binding of small molecule ligands. Covalent probe binding and inhibition are assessed using liquid chromatography-tandem mass spectrometry (LC-MS/MS) to gain molecular information on targeted proteins and probe-modified sites. The identification of amino acid sites modified by large complex probes, however, is particularly challenging because of the increased size, hydrophobicity, and charge state of peptides derived from modified proteins. These studies are important for direct evaluation of proteome-wide selectivity of inhibitor scaffolds used to develop targeted covalent inhibitors. Here, we disclose reverse-phase chromatography and MS dissociation conditions tailored for binding site identification using a clickable covalent kinase inhibitor containing a sulfonyl-triazole reactive group (KY-26). We applied this LC-MS/MS strategy to identify tyrosine and lysine sites modified by KY-26 in functional sites of kinases and other ATP-/NAD-binding proteins (>65 in total) in live cells. Our studies revealed key bioanalytical conditions to guide future chemical proteomic workflows for direct target site identification of complex irreversible probes and inhibitors.

Proteomics for Low Cell Numbers: How to Optimize the Sample Preparation Workflow for Mass Spectrometry Analysis

Nowadays, massive genomics and transcriptomics data can be generated at the single-cell level. However, proteomics in this setting is still a big challenge. Despite the great improvements in sensitivity and performance of mass spectrometry instruments and the better knowledge on sample preparation processing, it is widely acknowledged that multistep proteomics workflows may lead to substantial sample loss, especially when working with paucicellular samples. Still, in clinical fields, frequently limited sample amounts are available for downstream analysis, thereby hampering comprehensive characterization at protein level. To aim at better protein and peptide recoveries, we compare existing and novel approaches in the multistep sample preparation protocols for mass spectrometry studies, from sample collection, cell lysis, protein quantification, and electrophoresis/staining to protein digestion, peptide recovery, and LC-MS/MS instruments. From this critical evaluation, we conclude that the recent innovations and technologies, together with high quality management of samples, make proteomics on paucicellular samples possible, which will have immediate impact for the proteomics community.

The Roseoloviruses Downregulate the Protein Tyrosine Phosphatase PTPRC (CD45)

Like all herpesviruses, the roseoloviruses (HHV6A, -6B, and -7) establish lifelong infection within their host, requiring these viruses to evade host antiviral responses. One common host-evasion strategy is the downregulation of host-encoded, surface-expressed glycoproteins. Roseoloviruses have been shown to evade the host immune response by downregulating NK-activating ligands, class I MHC, and the TCR/CD3 complex. To more globally identify glycoproteins that are differentially expressed on the surface of HHV6A-infected cells, we performed cell surface capture of N-linked glycoproteins present on the surface of T cells infected with HHV6A, and compared these to proteins present on the surface of uninfected T cells. We found that the protein tyrosine phosphatase CD45 is downregulated in T cells infected with HHV6A. We also demonstrated that CD45 is similarly downregulated in cells infected with HHV7. CD45 is essential for signaling through the T cell receptor and, as such, is necessary for developing a fully functional immune response. Interestingly, the closely related betaherpesviruses human cytomegalovirus (HCMV) and murine cytomegalovirus (MCMV) have also separately evolved unique mechanisms to target CD45. While HCMV and MCMV target CD45 signaling and trafficking, HHV6A acts to downregulate CD45 transcripts. IMPORTANCE Human herpesviruses-6 and -7 infect essentially 100% of the world's population before the age of 5 and then remain latent or persistent in their host throughout life. As such, these viruses are among the most pervasive and stealthy of all viruses. Host immune cells rely on the presence of surface-expressed proteins to identify and target virus-infected cells. Here, we investigated the changes that occur to proteins expressed on the cell surface of T cells after infection with human herpesvirus-6A. We discovered that HHV-6A infection results in a reduction of CD45 on the surface of infected T cells and impaired activation in response to T cell receptor stimulation.

A Semiautomated Paramagnetic Bead-Based Platform for Isobaric Tag Sample Preparation

The development of streamlined and high-throughput sample processing workflows is important for capitalizing on emerging advances and innovations in mass spectrometry-based applications. While the adaptation of new technologies and improved methodologies is fast paced, automation of upstream sample processing often lags. Here we have developed and implemented a semiautomated paramagnetic bead-based platform for isobaric tag sample preparation. We benchmarked the robot-assisted platform by comparing the protein abundance profiles of six common parental laboratory yeast strains in triplicate TMTpro16-plex experiments against an identical set of experiments in which the samples were manually processed. Both sets of experiments quantified similar numbers of proteins and peptides with good reproducibility. Using these data, we constructed an interactive website to explore the proteome profiles of six yeast strains. We also provide the community with open-source templates for automating routine proteomics workflows on an opentrons OT-2 liquid handler. The robot-assisted platform offers a versatile and affordable option for reproducible sample processing for a wide range of protein profiling applications.

Facile Preparation of Peptides for Mass Spectrometry Analysis in Bottom-Up Proteomics Workflows

Mass spectrometry (MS) is routinely used to identify, characterize, and quantify biological molecules. For protein analysis, MS‐based workflows can be broadly categorized as top‐down or bottom‐up, depending on whether the proteins are analyzed as intact molecules or first digested into peptides. This article outlines steps for preparing peptide samples for MS as part of a bottom‐up proteomics workflow, providing versatile methods suitable for discovery and targeted analyses in qualitative and quantitative workflows. Resulting samples contain peptides of suitable size for analysis by MS instrumentation generally available to modern research laboratories, including MS coupled to either liquid chromatography (LC) or matrix‐assisted laser desorption/ionization (MALDI) interfaces. This article incorporates recent developments in methodologies and consumables to facilitate sample preparation. The protocols are well‐suited to users without prior experience in proteomics and include methods for universally applicable suspension trap processing and for alternate in‐solution processing to accommodate a range of sample types. Cleanup, quantification, and fractionation procedures are also described. © 2021 The Authors.

Basic Protocol: Preparation of high‐complexity peptide samples for mass spectrometry analysis using S‐Trap™ processing

Alternate Protocol 1: Preparation of low‐ to moderate‐complexity peptide samples for mass spectrometry analysis using in‐solution processing

Alternate Protocol 2: Detergent, polymer, and salt removal from peptide samples before mass spectrometry analysis using SP2 processing

Support Protocol 1: Protein quantification using Pierce 660 nm assay

Support Protocol 2: Peptide quantification using Pierce quantitative fluorometric peptide assay

Support Protocol 3: High‐pH fractionation of complex peptide samples

Automated 16-Plex Plasma Proteomics with Real-Time Search and Ion Mobility Mass Spectrometry Enables Large-Scale Profiling in Naked Mole-Rats and Mice

Performing large-scale plasma proteome profiling is challenging due to limitations imposed by lengthy preparation and instrument time. We present a fully automated multiplexed proteome profiling platform (AutoMP3) using the Hamilton Vantage liquid handling robot capable of preparing hundreds to thousands of samples. To maximize protein depth in single-shot runs, we combined 16-plex Tandem Mass Tags (TMTpro) with high-field asymmetric waveform ion mobility spectrometry (FAIMS Pro) and real-time search (RTS). We quantified over 40 proteins/min/sample, doubling the previously published rates. We applied AutoMP3 to investigate the naked mole-rat plasma proteome both as a function of the circadian cycle and in response to ultraviolet (UV) treatment. In keeping with the lack of synchronized circadian rhythms in naked mole-rats, we find few circadian patterns in plasma proteins over the course of 48 h. Furthermore, we quantify many disparate changes between mice and naked mole-rats at both 48 h and one week after UV exposure. These species differences in plasma protein temporal responses could contribute to the pronounced cancer resistance observed in naked mole-rats. The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE [1] partner repository with the dataset identifier PXD022891.

A Pragmatic Guide to Enrichment Strategies for Mass Spectrometry-Based Glycoproteomics

Glycosylation is a prevalent, yet heterogeneous modification with a broad range of implications in molecular biology. This heterogeneity precludes enrichment strategies that can be universally beneficial for all glycan classes. Thus, choice of enrichment strategy has profound implications on experimental outcomes. Here we review common enrichment strategies used in modern mass spectrometry-based glycoproteomic experiments, including lectins and other affinity chromatographies, hydrophilic interaction chromatography and its derivatives, porous graphitic carbon, reversible and irreversible chemical coupling strategies, and chemical biology tools that often leverage bioorthogonal handles. Interest in glycoproteomics continues to surge as mass spectrometry instrumentation and software improve, so this review aims to help equip researchers with the necessary information to choose appropriate enrichment strategies that best complement these efforts.

Sexual Dimorphic Role of CD14 (Cluster of Differentiation 14) in Salt-Sensitive Hypertension and Renal Injury

Genomic sequence and gene expression association studies in animals and humans have identified genes that may be integral in the pathogenesis of various diseases. CD14 (cluster of differentiation 14)-a cell surface protein involved in innate immune system activation-is one such gene associated with cardiovascular and hypertensive disease. We previously showed that this gene is upregulated in renal macrophages of Dahl salt-sensitive animals fed a high-salt diet; here we test the hypothesis that CD14 contributes to the elevated pressure and renal injury observed in salt-sensitive hypertension. Using CRISPR/Cas9 (clustered regularly interspaced short palindromic repeats/clustered regularly interspaced short palindromic repeat-associated 9), we created a targeted mutation in the CD14 gene on the Dahl SS (SS/JrHSDMcwi) background and validated the absence of CD14 peptides via mass spectrometry. Radiotelemetry was used to monitor blood pressure in wild-type and CD14^-/- animals challenged with high salt and identified infiltrating renal immune cells via flow cytometry. Germline knockout of CD14 exacerbated salt-sensitive hypertension and renal injury in female animals but not males. CD14^-/- females demonstrated increased infiltrating macrophages but no difference in infiltrating lymphocytes. Transplant of CD14^+/+ or CD14^-/- bone marrow was used to isolate the effects of CD14 knockout to hematopoietic cells and confirmed that the differential phenotype observed was due to knockout of CD14 in hematopoietic cells. Ovariectomy was used to remove the influence of female sex hormones, which completely abrogated the effect of CD14 knockout. These studies provide a novel treatment target and evidence of a new dichotomy in immune activation between sexes within the context of hypertensive disease where CD14 regulates immune cell activation and renal injury.

Research on the Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project

According to the 2020 Metrics of the HUPO Human Proteome Project (HPP), expression has now been detected at the protein level for >90% of the 19 773 predicted proteins coded in the human genome. The HPP annually reports on progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. NeXtProt release 2020-01 classified 17 874 proteins as PE1, having strong protein-level evidence, up 180 from 17 694 one year earlier. These represent 90.4% of the 19 773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the "missing proteins" (MPs), was reduced by 230 from 2129 to 1899 since the neXtProt 2019-01 release. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry data for neXtProt, supplemented this year with extensive data from MassIVE. PeptideAtlas 2020-01 added 362 canonical proteins between 2019 and 2020 and MassIVE contributed 84 more, many of which converted PE1 entries based on non-MS evidence to the MS-based subgroup. The 19 Biology and Disease-driven B/D-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions, and the progression of transitions from correlation to coexpression to causal networks after system perturbations. And the Human Protein Atlas published Blood, Brain, and Metabolic Atlases.

Addressing Cellular Heterogeneity in Cancer through Precision Proteomics

Cells exhibit a broad spectrum of functions driven by differences in molecular phenotype. Understanding the heterogeneity between and within cell types has led to advances in our ability to diagnose and manipulate biological systems. Heterogeneity within and between tumors still poses a challenge to the development and efficacy of therapeutics. In this Perspective we review the toolkit of protein-level experimental approaches for investigating cellular heterogeneity. We describe how innovative approaches and technical developments have supported the advent of bottom-up single-cell proteomic analysis and present opportunities and challenges within cancer research. Finally, we introduce the concept of "precision proteomics" and discuss how the advantages and limitations of various experimental approaches render them suitable for different biological systems and questions.

Discovery and validation of surface N-glycoproteins in MM cell lines and patient samples uncovers immunotherapy targets

BACKGROUND

Multiple myeloma (MM) is characterized by clonal expansion of malignant plasma cells in the bone marrow. While recent advances in treatment for MM have improved patient outcomes, the 5-year survival rate remains ~50%. A better understanding of the MM cell surface proteome could facilitate development of new directed therapies and assist in stratification and monitoring of patient outcomes.

METHODS

In this study, we first used a mass spectrometry (MS)-based discovery-driven cell surface capture (CSC) approach to map the cell surface N-glycoproteome of MM cell lines. Next, we developed targeted MS assays, and applied these to cell lines and primary patient samples to refine the list of candidate tumor markers. Candidates of interest detected by MS on MM patient samples were further validated using flow cytometry (FCM).

RESULTS

We identified 696 MM cell surface N-glycoproteins by CSC, and developed 73 targeted MS detection assays. MS-based validation using primary specimens detected 30 proteins with significantly higher abundance in patient MM cells than controls. Nine of these proteins were identified as potential immunotherapeutic targets, including five that were validated by FCM, confirming their expression on the cell surface of primary MM patient cells.

CONCLUSIONS

This MM surface N-glycoproteome will be a valuable resource in the development of biomarkers and therapeutics. Further, we anticipate that our targeted MS assays will have clinical benefit for the diagnosis, stratification, and treatment of MM patients.

SurfaceGenie: a web-based application for prioritizing cell-type-specific marker candidates

MOTIVATION

Cell-type-specific surface proteins can be exploited as valuable markers for a range of applications including immunophenotyping live cells, targeted drug delivery and in vivo imaging. Despite their utility and relevance, the unique combination of molecules present at the cell surface are not yet described for most cell types. A significant challenge in analyzing 'omic' discovery datasets is the selection of candidate markers that are most applicable for downstream applications.

RESULTS

Here, we developed GenieScore, a prioritization metric that integrates a consensus-based prediction of cell surface localization with user-input data to rank-order candidate cell-type-specific surface markers. In this report, we demonstrate the utility of GenieScore for analyzing human and rodent data from proteomic and transcriptomic experiments in the areas of cancer, stem cell and islet biology. We also demonstrate that permutations of GenieScore, termed IsoGenieScore and OmniGenieScore, can efficiently prioritize co-expressed and intracellular cell-type-specific markers, respectively.

AVAILABILITY AND IMPLEMENTATION

Calculation of GenieScores and lookup of SPC scores is made freely accessible via the SurfaceGenie web application: www.cellsurfer.net/surfacegenie.

CONTACT

Rebekah.gundry@unmc.edu.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Automated sample preparation with SP3 for low-input clinical proteomics

High-throughput and streamlined workflows are essential in clinical proteomics for standardized processing of samples from a variety of sources, including fresh-frozen tissue, FFPE tissue, or blood. To reach this goal, we have implemented single-pot solid-phase-enhanced sample preparation (SP3) on a liquid handling robot for automated processing (autoSP3) of tissue lysates in a 96-well format. AutoSP3 performs unbiased protein purification and digestion, and delivers peptides that can be directly analyzed by LCMS, thereby significantly reducing hands-on time, reducing variability in protein quantification, and improving longitudinal reproducibility. We demonstrate the distinguishing ability of autoSP3 to process low-input samples, reproducibly quantifying 500-1,000 proteins from 100 to 1,000 cells. Furthermore, we applied this approach to a cohort of clinical FFPE pulmonary adenocarcinoma (ADC) samples and recapitulated their separation into known histological growth patterns. Finally, we integrated autoSP3 with AFA ultrasonication for the automated end-to-end sample preparation and LCMS analysis of 96 intact tissue samples. Collectively, this constitutes a generic, scalable, and cost-effective workflow with minimal manual intervention, enabling reproducible tissue proteomics in a broad range of clinical and non-clinical applications.

Miniaturized sample preparation on a digital microfluidics device for sensitive bottom-up microproteomics of mammalian cells using magnetic beads and mass spectrometry-compatible surfactants

While LC-MS-based proteomics with high nanograms to micrograms of total protein has become routine, the analysis of samples derived from low cell numbers is challenged by factors such as sample losses, or difficulties encountered with the manual manipulation of small liquid volumes. Digital microfluidics (DMF) is an emerging technique for miniaturized and automated droplet manipulation, which has been proposed as a promising tool for proteomic sample preparation. However, proteome analysis of samples prepared on-chip by DMF has previously been unfeasible, due to incompatibility with down-stream LC-MS instrumentation. To overcome these limitations, we here developed protocols for bottom-up LC-MS based proteomics sample preparation of as little as 100 mammalian cells on a commercially available digital microfluidics device. To this end, we developed effective cell lysis conditions optimized for DMF, as well as detergent-buffer systems compatible with downstream proteolytic digestion on DMF chips and subsequent LC-MS analysis. A major step was the introduction of the single-pot, solid-phase-enhanced sample preparation (SP3) approach on-chip, which allowed the removal of salts and anti-fouling polymeric detergents, thus rendering sample preparation by DMF compatible with LC-MS-based proteome analysis. Application of DMF-SP3 to the proteome analysis of Jurkat T cells led to the identification of up to 2500 proteins from approximately 500 cells, and up to 1200 proteins from approximately 100 cells on an Orbitrap mass spectrometer, emphasizing the high compatibility of DMF-SP3 with low protein input and minute volumes handled by DMF. Taken together, we demonstrate the first sample preparation workflow for proteomics on a DMF chip device reported so far, allowing the sensitive analysis of limited biological material.