Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data-Independent Acquisition

Discovery of specific protein markers in multiple body fluids and their application in forensic science

Identification of multiple body fluids is crucial for the reconstruction and corroboration of crime event. However, for the body fluids with high component similarities, such as peripheral blood and menstrual blood, reliable distinguishing markers are still lacking. Furthermore, a comprehensive protein marker assay for multiple body fluids is urgently necessary for complex crime events. Herein, we established a highly specific and detectable method for discovering protein markers in peripheral blood, menstrual blood, saliva, semen and vaginal fluid through integrating in-depth discovery proteomics and a two-step targeted screening approach. Four menstrual blood markers with high endometrial specificities were identified for differentiation from peripheral blood and exhibited moderate protein concentrations for reproducible analysis with a protein quantitation CV value of 8.66%. Finally, a targeted discrimination method with 16 protein markers was established. We successfully identified 47 blind samples with 100% specificity and detection rate, sourced from five types of body fluids and presented on matrices such as cotton, tissues, slides or fluid. Overall, this work developed an effective method for discovering body fluid biomarkers, obtained specific protein markers to identify five kinds of body fluids and their targeted monitoring will show great significance for forensic science.

Podophyllum hexandrum Royle mitigates perimenopausal symptoms in an OVX rat model by activating the PI3K/AKT/mTOR pathway and enhancing estrogen receptor expression

ETHNOPHARMACOLOGICAL RELEVANCE

Podophyllum hexandrum Royle, recorded in the Pharmacopoeia of the People's Republic of China as Sinopodophyllum hexandrum (Royle) Ying (SH), is a nationally protected Tibetan medicinal plant in China, which has been traditionally used to regulate menstruation, enhance blood circulation, and treat blood stasis and dystocia. However, its potential role and mechanisms in managing perimenopausal syndrome (PMS) remain unclear.

AIM OF THE STUDY

This study evaluates the therapeutic potential of Sinopodophyllum hexandrum (Royle) Ying rhizomes (SHR) and fruits (SHF) in PMS and investigates their underlying molecular mechanisms.

MATERIALS AND METHODS

The anti-PMS effects of SHR and SHF were examined in an ovariectomized (OVX) rat model by assessing uterine histopathology and hormone levels. Serum lipid profiles, including triglycerides (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-C), and high-density lipoprotein cholesterol (HDL-C), as well as malondialdehyde (MDA) levels and superoxide dismutase (SOD) levels, were analyzed using biochemical assays. Astral-DIA proteomics identified differentially expressed proteins (DEPs) and key signaling pathways affected by SHF. Protein expression was evaluated via western blotting, immunohistochemistry, and RT-qPCR. Estrogenic activity was further assessed in vitro through MCF-7 cell viability and estrogen receptor (ER) expression analysis.

RESULTS

SHR and SHF treatment significantly improved uterine morphology in OVX rats, restoring endometrial and epithelial thickness. High-dose SHF (SHF-H) increased serum estradiol (E2) by 100.02 %, anti-Müllerian hormone (AMH) by 34.68 %, and progesterone (PROG) by 39.96 % while decreasing luteinizing hormone (LH) by 31.53 %. High-dose SHR (SHR-H) treatment resulted in a 112.89 % increase in E2 levels and a 23.88 % decrease in LH levels. Additionally, SHR-H and SHF-H regulated the level of oxidative stress and serum lipid levels, showing a significant decline in MDA (48.32 %, 65.52 %), TG (34.71 %, 33.30 %), TC (22.34 %, 27.77 %), and LDL-C (57.09 %, 42.96 %). Proteomic analysis identified the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT)/mammalian target of rapamycin (mTOR) pathway and apoptotic regulation as key mechanisms underlying SHF's effects. SHF reversed the OVX-induced suppression of p-PI3K/PI3K, p-AKT/AKT, and p-mTOR in the uterus. SHR and SHF also modulated apoptosis-related proteins, downregulating Bax and Cleaved caspase-3/9 while upregulating Bcl-2. Moreover, SHF significantly increased uterine ERα and ERβ expression at both mRNA and protein levels. In vitro, SHR and SHF extracts promoted MCF-7 cell viability and upregulated ERα, ERβ, and proliferating cell nuclear antigen (PCNA), indicating estrogenic activity.

CONCLUSIONS

SH alleviates PMS by inhibiting uterine apoptosis via PI3K/AKT/mTOR pathway activation and enhancing estrogen receptor expression. It also regulates hormone levels, lipid metabolism, and oxidative stress, potentially slowing PMS progression. These findings highlight SH as a promising therapeutic agent for PMS and provide novel insights into the molecular mechanisms of Tibetan medicine.

Two-Step Peptide Solubilization Increases Coverage in High-Sensitivity NanoHILIC/MS/MS-Based Proteomics

Nanoscale hydrophilic-interaction chromatography coupled with tandem mass spectrometry (nanoHILIC/MS/MS) is a promising alternative to reversed-phase liquid chromatography for proteomics, but its application is limited by the poor solubility of peptides in organic solvent-rich sample solutions. To overcome this issue, we have developed a two-step solubilization method, in which peptides are first solubilized in a solvent with an optimal acetonitrile (ACN) concentration of 25% and then diluted into a high ACN concentration solution of 95%. This procedure increases the peptide solubility without compromising compatibility with nanoHILIC/MS/MS. Compared to direct solubilization in 95% ACN, this approach increased the intensity of 82.8% of commonly quantified peptides in nanoHILIC/MS/MS, with an average intensity gain of 20.9%. Furthermore, nanoHILIC/MS/MS with this two-step solubilization outperformed nanoRPLC/MS/MS, identifying 8.47 times more peptides and 3.54 times more protein groups from 2.5 ng of tryptic peptides extracted from HeLa cells. The high sensitivity of nanoHILIC/MS/MS can be attributed to the enhanced loading of peptides as a result of the two-step solubilization, together with superior ESI efficiency arising from the use of the ACN-rich mobile phase. This high-sensitivity proteomics system is a promising platform for clinical and single-cell applications.

From blood drops to biomarkers: a scoping review of microsampling in mass spectrometry-based proteomics

BACKGROUND

Microsamples are simple blood sampling procedures utilizing small blood draws. Although microsamples are regularly used in some disciplines, proteomic analysis of these samples is an emerging field. Currently, it is unclear whether the quantitative precision and proteome coverage achieved in microsamples is comparable to plasma or serum. As a consequence, microsamples are not used in proteomics to the same degree as more traditional blood samples.

OBJECTIVES

The objective of this scoping review was to report the applications of microsamples within clinical mass spectrometry-based proteomics. This was accomplished by describing both proof-of-concept and clinical proteomics research within this field, with an additional evaluation of the newest advances regarding clinical proteomics.

INCLUSION CRITERIA

Original scientific literature was included where bottom-up mass spectrometry was used to analyze endogenous proteins from human microsamples.

METHODS

Relevant publications were sourced through three scientific databases (MEDLINE, EMBASE and Scopus) in addition to backward and forward citation searches through Scopus. Record screening was performed independently by two separate authors. The review was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Reviews (PRISMA-ScR) guidelines.

RESULTS

A total of 209 records were screened for inclusion from database searches and 3157 records were screened from forward and backward citation searches, resulting in 64 eligible studies. An evaluation of proof-of-concept research within this field revealed that although microsamples are amenable to high-throughput proteomics using a variety of targeted and untargeted acquisition methods, quantification remained a relevant issue. Microsampling practices were heterogeneous, and no standard procedure existed for protein quantification. Clinical studies investigated protein expression in numerous disease or experimental groups, including hemoglobinopathies and immunodeficiency disorders.

CONCLUSION

The use of microsamples is increasing within the proteomics field and these samples are amenable to standard bottom-up workflows. Although microsamples present a clear advantage in terms of sampling procedure, both the sample collection and quantification procedures remain to be standardized. However, there is an incentive to address the remaining issues, since microsampling would greatly reduce the resources necessary to sample large cohorts within clinical proteomics, a field that currently lacks large discovery and validation cohorts.

Technical Evaluation of Plasma Proteomics Technologies

Plasma proteomics technologies are rapidly evolving and of critical importance to the field of biomedical research. Here, we report a technical evaluation of six notable plasma proteomics technologies─unenriched (Neat), acid depletion, PreOmics ENRICHplus, Mag-Net, Seer Proteograph XT, and Olink Explore HT. The methods were compared on proteomic depth, reproducibility, linearity, tolerance to lipid interference, and limit of detection/quantification. In total, we performed 618 LC-MS/MS experiments and 93 Olink Explore HT assays. The Seer method achieved the greatest proteomic depth (∼4500 proteins detected), while Olink detected ∼2600 proteins. Other MS-based methods ranged from ∼500-2200 proteins detected. In our analysis, Neat, Mag-Net, Seer, and Olink had good reproducibility, while PreOmics and Acid had higher variability (>20% median coefficient of variation). All MS methods showed good linearity with spiked-in C-reactive protein (CRP); CRP was surprisingly not in the Olink assay. None of the methods were affected by lipid interference. Seer produced the highest number of quantifiable proteins with a measurable LOD (4407) and LOQ (2696). Olink had the next highest number of quantifiable proteins, with 2002 having an LOD and 1883 having an LOQ. Finally, we tested the applicability of these methods for detecting differences between healthy and cancer groups in a nonsmall cell lung cancer (NSCLC) cohort. All six methods detected differentially abundant proteins between the cancer and healthy samples but disagreed on which proteins were significant, highlighting the contrast between each method.

Advances in Spatial Multi-Omics: A Review of Multi-Modal Mass Spectrometry Imaging and Laser Capture Microdissection-LCMS Integration

Mass spectrometry has long been utilized to characterize a variety of biomolecules such as proteins, metabolites, and lipids. Most MS-based omics studies rely on bulk analysis; however, bulk approaches often overlook low-abundance molecules that may exert critical biological effects. Recently, multi-omics analyses have been driving an explosion of knowledge about how biomolecules interact within biological systems. In particular, spatial multi-omics has emerged as a groundbreaking approach for implementing multi-omic and multi-modal analyses. Broadly defined, spatial omics has the ability to analyze biomolecules within their native spatial contexts, offering transformative insights. This review focuses on mass spectrometry-based spatial omics, specifically matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI-MSI). We will explore how MALDI-MSI, in combination with laser capture microdissection (LCM) and traditional liquid chromatography-mass spectrometry (LC-MS) workflow, is advancing spatially resolved multi-omics research.

Multistage Linear Frequency Scanning Mass Analysis Processed by Fractional Fourier Transform

The common method of mass analysis in a linear ion trap mass spectrometer is to eject ions with different mass-to-charge ratios (m/z) at different times by resonance excitation. Ions are ejected onto an electron multiplier (EM), generating pulsed signals called the ejection signal. Typically, the ejection signal consisting of multiple pulses is smoothed into a wider Gaussian-like pulse due to the limited bandwidth of the electronic system. For different scan rates and different samples, this bandwidth-limited electronic system and signal smoothing process will differentially increase the peak width and thus decrease the mass resolution. In this study, experiments at different scan rates were performed on a "Brick" miniature linear ion trap mass spectrometer. We propose a multistage linear frequency scanning mode that achieves improved mass resolution and extended mass range, in which fractional Fourier transform is applied to process the ejection signals. The proposed signal processing method improves the mass resolution and mitigates the impact of ghost peaks attributed to scattered ion ejection. A peak width of 0.84 Da at a m/z value of 242 and a scan rate of 8000 Da/s was achieved in experiments.

Unifying the analysis of bottom-up proteomics data with CHIMERYS

Proteomic workflows generate vastly complex peptide mixtures that are analyzed by liquid chromatography-tandem mass spectrometry, creating thousands of spectra, most of which are chimeric and contain fragment ions from more than one peptide. Because of differences in data acquisition strategies such as data-dependent, data-independent or parallel reaction monitoring, separate software packages employing different analysis concepts are used for peptide identification and quantification, even though the underlying information is principally the same. Here, we introduce CHIMERYS, a spectrum-centric search algorithm designed for the deconvolution of chimeric spectra that unifies proteomic data analysis. Using accurate predictions of peptide retention time, fragment ion intensities and applying regularized linear regression, it explains as much fragment ion intensity as possible with as few peptides as possible. Together with rigorous false discovery rate control, CHIMERYS accurately identifies and quantifies multiple peptides per tandem mass spectrum in data-dependent, data-independent or parallel reaction monitoring experiments.

Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome

Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being data-dependent acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-independent acquisition mass spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. In this study, DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory for the particular instruments and software parameters chosen. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.

SPE-CZE-MS Quantifies Zeptomole Amounts of Phosphorylated Peptides

Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultralow-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electropherographic time scales. Here, we address these two challenges as applied to single-cell-equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phase-extraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fit-for-purpose applications in single-cell-equivalent phosphoproteomics.

Rapid assay development for low input targeted proteomics using a versatile linear ion trap

Advances in proteomics and mass spectrometry enable the study of limited cell populations, where high-mass accuracy instruments are typically required. While triple quadrupoles offer fast and sensitive low-mass specificity measurements, these instruments are effectively restricted to targeted proteomics. Linear ion traps (LITs) offer a versatile, cost-effective alternative capable of both targeted and global proteomics. Here, we describe a workflow using a hybrid quadrupole-LIT instrument that rapidly develops targeted proteomics assays from global data-independent acquisition (DIA) measurements without high-mass accuracy. Using an automated software approach for scheduling parallel reaction monitoring assays (PRM), we show consistent quantification across three orders of magnitude in a matched-matrix background. We demonstrate measuring low-level proteins such as transcription factors and cytokines with quantitative linearity below two orders of magnitude in a 1 ng background proteome without requiring stable isotope-labeled standards. From a 1 ng sample, we found clear consistency between proteins in subsets of CD4+ and CD8+ T cells measured using high dimensional flow cytometry and LIT-based proteomics. Based on these results, we believe hybrid quadrupole-LIT instruments represent a valuable solution to expanding mass spectrometry in a wide variety of laboratory settings.

Chemoproteomic Profiling of C. albicans for Characterization of Antifungal Kinase Inhibitors

Candida albicans is a major cause of systemic candidiasis, a severe fungal infection with a ∼40% mortality rate. Yck2, a casein kinase 1 (CK1) in C. albicans, is targeted by antifungal inhibitors YK-I-02 (YK) and MN-I-157 (MN). Using multiplexed inhibitor beads and mass spectrometry (MIB/MS), the selectivity of these inhibitors was determined across the fungal kinome. The MIB matrix captured 89% of C. albicans protein kinases, revealing that YK and MN selectively engage three CK1 homologues (Yck2, Yck22, and Hrr25) and a human p38α homologue (Hog1). Chemoproteomics using a custom MN-kinobead confirmed the remarkable fungal kinome selectivity. To identify new Yck2 inhibitors with selectivity over Hog1, 13 human CK1 inhibitors were screened, leading to the discovery of a new chemotype with antifungal activity. These findings highlight the utility of MIB/MS in profiling nonhuman kinomes and developing selective fungal kinase inhibitors as antimicrobial agents.

TMT-Based Multiplexed (Chemo)Proteomics on the Orbitrap Astral Mass Spectrometer

Ongoing advancements in instrumentation has established mass spectrometry (MS) as an essential tool in proteomics research and drug discovery. The newly released Asymmetric Track Lossless (Astral) analyzer represents a major step forward in MS instrumentation. Here, we evaluate the Orbitrap Astral mass spectrometer in the context of tandem mass tag (TMT)-based multiplexed proteomics and activity-based proteome profiling, highlighting its sensitivity boost relative to the Orbitrap Tribrid platform-50% at the peptide and 20% at the protein level. We compare TMT data-dependent acquisition and label-free data-independent acquisition on the same instrument, both of which quantify over 10,000 human proteins per sample within 1 h. TMT offers higher quantitative precision and data completeness, while data-independent acquisition is free of ratio compression and is thereby more accurate. Our results suggest that ratio compression is prevalent with the high-resolution MS2-based quantification on the Astral, while real-time search-based MS3 quantification on the Orbitrap Tribrid platform effectively restores accuracy. Additionally, we benchmark TMT-based activity-based proteome profiling by interrogating cysteine ligandability. The Astral measures over 30,000 cysteines in a single-shot experiment, a 54% increase relative to the Orbitrap Eclipse. We further leverage this remarkable sensitivity to profile the target engagement landscape of FDA-approved covalent drugs, including sotorasib and adagrasib. We herein provide a reference for the optimal use of the advanced MS platform.

Pooled scanning of protein variants identifies novel RNA-binding mutants

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

Toward Real-Time Proteomics: Blood to Biomarker Quantitation in under One Hour

Multistep multihour tryptic proteolysis has limited the utility of bottom-up proteomics for cases that require immediate quantitative information. The power of proteomics to quantify biomarkers of health status cannot practically assist in clinical care if the dynamics of disease outpaces the turnaround of analysis. The recently available hyperthermoacidic archaeal (HTA) protease "Krakatoa" digests samples in a single 5 to 30 min step at pH 3 and >80 °C in conditions that disrupt most cells and tissues, denature proteins, and block disulfide reformation thereby dramatically expediting and simplifying sample preparation. The combination of quick single-step proteolysis with high-throughput dual-trapping single analytical column (DTSC) liquid chromatography-mass spectrometry (LC-MS) returns actionable data in less than 1 h from collection of unprocessed biofluid. The systematic evaluation of this methodology finds that over 160 proteins are quantified in less than 1 h from 1 μL of whole blood. Furthermore, labile Angiotensin I and II bioactive peptides along with a panel of protein species can be measured at 8 min intervals with a 20 min initial lag using targeted MS. With these methods, we analyzed serum and plasma from 53 individuals and quantified Angiotensin I and II and over 150 proteins including at least 46 that were not detected with trypsin. We discuss some of the implications of real-time proteomics including the immediate potential to advance several clinical and research applications.

Integrating -Omic Technologies across Modality, Space, and Time to Decipher Remodeling in Cardiac Disease

PURPOSE OF REVIEW

Despite significant efforts to understand pathophysiological processes underlying cardiac diseases, the molecular causes for the most part remain unresolved. Rapid advancements in -omics technologies, and their application in cardiac research, offer new insight into cardiac remodeling in disease states. This review aims to provide an accessible overview of recent advances in omics approaches for studying cardiac remodeling, catering to readers without extensive prior expertise.

RECENT FINDINGS

We provide a methodologically focused overview of current methods for performing transcriptomics and proteomics, including their extensions for single-cell and spatial measurements. We discuss approaches to integrate data across modalities, resolutions and time. Key recent applications within the cardiac field are highlighted. Each -omics modality can provide insight, yet each existing experimental method has technical or conceptual limitations. Integrating data across multiple modalities can leverage strengths and mitigate weaknesses, ultimately enhancing our understanding of cardiac pathophysiology.

In-depth plasma N-glycoproteome profiling using narrow-window data-independent acquisition on the Orbitrap Astral mass spectrometer

Recently, a conceptually new mass analyzer was introduced by pairing a quadrupole Orbitrap mass spectrometer with an asymmetric track lossless (Astral™) analyzer. This system provides >200 Hz MS/MS scanning speed, high resolving power, sensitivity, and mass accuracy. Due to its speed, the instrument allows for a narrow-window data-independent acquisition (nDIA) strategy, representing a new technical milestone in peptide-centric proteomics. However, this new system may also be applied to other complex and clinically important proteomes, such as the human plasma N-glycoproteome. Here, we evaluate the Orbitrap Astral mass spectrometer for the in-depth analysis of the plasma N-glycoproteome and pioneer a dedicated nDIA workflow, termed "nGlycoDIA", on glycopeptide enriched and crude plasma. This strategy leads to the cumulative identification of over 3000 unique glycoPSMs derived from 181 glycoproteins in just 40 minutes and covers a dynamic range of 7 orders of magnitude for a glycopeptide enriched plasma sample. Notably, we detect several glycosylated cytokines that have reported plasma concentrations in the ng/L range. Furthermore, shortening the gradient to 10 min still allows for the detection of almost 1850 (95% CI [1840-1860]) unique glycoPSMs, indicating that high-throughput in-depth clinical plasma glycoproteomics may be within reach.

Recent Advances in Mass Spectrometry-Based Bottom-Up Proteomics

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

A Scalable, Web-Based Platform for Proteomics Data Processing, Result Storage and Analysis

The exponential increase in proteomics data presents critical challenges for conventional processing workflows. These pipelines often consist of fragmented software packages, glued together using complex in-house scripts or error-prone manual workflows running on local hardware, which are costly to maintain and scale. The MSAID Platform offers a fully automated, managed proteomics data pipeline, consolidating formerly disjointed functions into unified, API-driven services that cover the entire process from raw data to biological insights. Backed by the cloud-native search algorithm CHIMERYS, as well as scalable cloud compute instances and data lakes, the platform facilitates efficient processing of large data sets, automation of processing via the command line, systematic result storage, analysis, and visualization. The data lake supports elastically growing storage and unified query capabilities, facilitating large-scale analyses and efficient reuse of previously processed data, such as aggregating longitudinally acquired studies. Users interact with the platform via a web interface, CLI client, or API, providing flexible, automated access. Readily available tools for accessing result data include browser-based interrogation and one-click visualizations for statistical analysis. The platform streamlines research processes, making advanced and automated proteomic workflows accessible to a broader range of scientists. The MSAID Platform is globally available via https://platform.msaid.io.

Isobaric Tagging and Data Independent Acquisition as Complementary Strategies for Proteome Profiling on an Orbitrap Astral Mass Spectrometer

Comprehensive global proteome profiling that is amenable to high throughput processing will broaden our understanding of complex biological systems. Here, we evaluate two leading mass spectrometry techniques, Data Independent Acquisition (DIA) and Tandem Mass Tagging (TMT), for extensive protein abundance profiling. DIA provides label-free quantification with a broad dynamic range, while TMT enables multiplexed analysis using isobaric tags for efficient cross-sample comparisons. We analyzed 18 samples, including four cell lines (IHCF, HCT116, HeLa, MCF7) under standard growth conditions, in addition to IHCF treated with two H2O2 concentrations, all in triplicate. Experiments were conducted on an Orbitrap Astral mass spectrometer, employing Field Asymmetric Ion Mobility Spectrometry (FAIMS). Despite utilizing different acquisition strategies, both the DIA and TMT approaches achieved comparable proteome depth and quantitative consistency, with each method quantifying over 10,000 proteins across all samples, with marginally higher protein-level precision for the TMT strategy. Relative abundance correlation analysis showed strong agreement at both peptide and protein levels. Our findings highlight the complementary strengths of DIA and TMT for high-coverage proteomic studies, providing flexibility in method selection based on specific experimental needs.

Deciphering functional tumor-immune crosstalk through highly multiplexed imaging and deep visual proteomics

Deciphering the intricate tumor-immune interactions within the microenvironment is crucial for advancing cancer immunotherapy. Here, we introduce mipDVP, an advanced approach integrating highly multiplexed imaging, single-cell laser microdissection, and sensitive mass spectrometry to spatially profile the proteomes of distinct cell populations in a human colorectal and tonsil cancer with high sensitivity. In a colorectal tumor-a representative cold tumor-we uncovered spatial compartmentalization of an immunosuppressive macrophage barrier that potentially impedes T cell infiltration. Spatial proteomic analysis revealed distinct functional states of T cells in different tumor compartments. In a tonsil cancer sample-a hot tumor-we identified significant proteomic heterogeneity among cells influenced by proximity to cytotoxic T cell subtypes. T cells in the tumor parenchyma exhibit metabolic adaptations to hypoxic regions. Our spatially resolved, highly multiplexed strategy deciphers the complex cellular interplay within the tumor microenvironment, offering valuable insights for identifying immunotherapy targets and predictive signatures.

Uncovering toxin production and molecular-level responses in Microcystis aeruginosa exposed to the flame retardant Tetrabromobisphenol A

Tetrabromobisphenol A (TBBPA) poses significant ecological risks owing to its toxicity; however, its specific effects on toxin-producing cyanobacteria in aquatic environments remain poorly understood. This study systematically investigated the effects of TBBPA at concentrations ranging from 100 ng/L to 100 mg/L on Microcystis aeruginosa (M. aeruginosa) by examining growth, photosynthesis, toxin production, antioxidant responses, and molecular-level changes. The results indicated that low levels of TBBPA (0.1-1000 μg/L) induced stimulatory effects on the growth and microcystin-leucine-arginine (MC-LR) production of M. aeruginosa. Metabolomic analysis revealed that low levels of TBBPA significantly upregulated metabolites associated with energy metabolism, xenobiotic biodegradation, oxidative stress responses, and protein biosynthesis in M. aeruginosa, potentially contributing to the observed hormetic effect. Conversely, higher doses (40-100 mg/L) inhibited growth and significantly increased MC-LR release by compromising cellular structural integrity. Proteomic analysis revealed that toxic levels of TBBPA significantly affected the expression of proteins associated with energy harvesting and utilization. Specifically, TBBPA disrupted electron flow in oxidative phosphorylation and the photosynthetic system (PS) by targeting PSI, PSII, and Complex I, impairing energy acquisition and causing oxidative damage, ultimately leading to algal cell death. Additionally, proteins involved in the biosynthesis and metabolism of cysteine, methionine, phenylalanine, tyrosine, and tryptophan were upregulated, potentially enhancing M. aeruginosa resistance to TBBPA-induced stress. This study offers insights into the effects of TBBPA on M. aeruginosa and its potential risks to aquatic ecosystems.

Proteomics of Extracellular Vesicles: Recent Updates, Challenges and Limitations

Extracellular vesicles (EVs) are lipid-bound vesicles secreted by cells, including exosomes, microvesicles, and apoptotic bodies. Proteomic analyses of EVs, particularly in relation to cancer, reveal specific biomarkers crucial for diagnosis and therapy. However, isolation techniques such as ultracentrifugation, size-exclusion chromatography, and ultrafiltration face challenges regarding purity, contamination, and yield. Contamination from other proteins complicates downstream processing, leading to difficulties in identifying biomarkers and interpreting results. Future research will focus on refining EV characterization for diagnostic and therapeutic applications, improving proteomics tools for greater accuracy, and exploring the use of EVs in drug delivery and regenerative medicine. In this review, we provide a bird's eye view of various challenges, starting with EV isolation methods, yield, purity, and limitations in the proteome analysis of EVs for identifying protein targets.

Enhanced sensitivity and scalability with a Chip-Tip workflow enables deep single-cell proteomics

Single-cell proteomics (SCP) promises to revolutionize biomedicine by providing an unparalleled view of the proteome in individual cells. Here, we present a high-sensitivity SCP workflow named Chip-Tip, identifying >5,000 proteins in individual HeLa cells. It also facilitated direct detection of post-translational modifications in single cells, making the need for specific post-translational modification-enrichment unnecessary. Our study demonstrates the feasibility of processing up to 120 label-free SCP samples per day. An optimized tissue dissociation buffer enabled effective single-cell disaggregation of drug-treated cancer cell spheroids, refining overall SCP analysis. Analyzing nondirected human-induced pluripotent stem cell differentiation, we consistently quantified stem cell markers OCT4 and SOX2 in human-induced pluripotent stem cells and lineage markers such as GATA4 (endoderm), HAND1 (mesoderm) and MAP2 (ectoderm) in different embryoid body cells. Our workflow sets a benchmark in SCP for sensitivity and throughput, with broad applications in basic biology and biomedicine for identification of cell type-specific markers and therapeutic targets.

Mass spectrometry-based ligand binding assays in biomedical research

INTRODUCTION

Ligand binding assays combining immunoaffinity enrichment steps with mass spectrometry (MS) readout have gained attention as a highly specific and sensitive tool for protein quantification. These techniques typically combine enzymatic fragmentation of the sample or enriched protein with capture on the protein or peptide-level for quantification. Antibodies ensure specific target recognition, while MS offers quantitative accuracy with isotopically labeled internal standards. This dual approach supports a broad dynamic range, enabling protein measurements from picomolar to nanomolar levels. These methods have diverse applications, from quantifying signaling proteins in basic research to biomarker monitoring in clinical trials and analyzing the pharmacokinetics of therapeutic proteins.

AREAS COVERED

This review delves into the diverse workflows of immunoaffinity-MS, shedding light on the innovative strategies employed, their practical applications, efficacy, and inherent limitations in the realm of protein quantification.

EXPERT OPINION

Immunoaffinity-MS has transformed protein analysis, but widespread adoption is hindered by complex workflows, high instrument costs, and limited capture molecule availability. Efforts to enhance automation, standardize workflows, and advance technological innovation aim to overcome these barriers. Improvements in mass spectrometer sensitivity, advances in recombinant capture technologies, and support from public initiatives are poised to further improve the reliability and accessibility of this method.

Navigating the landscape of plant proteomics

In plants, proteins are fundamental to virtually all biological processes, such as photosynthesis, signal transduction, metabolic regulation, and stress responses. Studying protein distribution, function, modifications, and interactions at the cellular and tissue levels is critical for unraveling the complexities of these biological pathways. Protein abundance and localization are highly dynamic and vary widely across the proteome, presenting a challenge for global protein quantification and analysis. Mass spectrometry-based proteomics approaches have proven to be powerful tools for addressing this complex issue. In this review, we summarize recent advancements in proteomics research and their applications in plant biology, with an emphasis on the current state and challenges of studying post-translational modifications, single-cell proteomics, and protein-protein interactions. Additionally, we discuss future prospects for plant proteomics, highlighting potential opportunities that proteomics technologies offer in advancing plant biology research.

Decoding Sugars: Mass Spectrometric Advances in the Analysis of the Sugar Alphabet

Monosaccharides play a central role in metabolic networks and in the biosynthesis of glycomolecules, which perform essential functions across all domains of life. Thus, identifying and quantifying these building blocks is crucial in both research and industry. Routine methods have been established to facilitate the analysis of common monosaccharides. However, despite the presence of common metabolites, most organisms utilize distinct sets of monosaccharides and derivatives. These molecules therefore display a large diversity, potentially numbering in the hundreds or thousands, with many still unknown. This complexity presents significant challenges in the study of glycomolecules, particularly in microbes, including pathogens and those with the potential to serve as novel model organisms. This review discusses mass spectrometric techniques for the isomer-sensitive analysis of monosaccharides, their derivatives, and activated forms. Although mass spectrometry allows for untargeted analysis and sensitive detection in complex matrices, the presence of stereoisomers and extensive modifications necessitates the integration of advanced chromatographic, electrophoretic, ion mobility, or ion spectroscopic methods. Furthermore, stable-isotope incorporation studies are critical in elucidating biosynthetic routes in novel organisms.

Automated High-Throughput Affinity Capture-Mass Spectrometry Platform with Data-Independent Acquisition

Affinity capture (AC) combined with mass spectrometry (MS)-based proteomics is highly utilized throughout the drug discovery pipeline to determine small-molecule target selectivity and engagement. However, the tedious sample preparation steps and time-consuming MS acquisition process have limited its use in a high-throughput format. Here, we report an automated workflow employing biotinylated probes and streptavidin magnetic beads for small-molecule target enrichment in the 96-well plate format, ending with direct sampling from EvoSep Solid Phase Extraction tips for liquid chromatography (LC)-tandem mass spectrometry (MS/MS) analysis. The streamlined process significantly reduced both the overall and hands-on time needed for sample preparation. Additionally, we developed a data-independent acquisition-mass spectrometry (DIA-MS) method to establish an efficient label-free quantitative chemical proteomic kinome profiling workflow. DIA-MS yielded a coverage of ∼380 kinases, a > 60% increase compared to using a data-dependent acquisition (DDA)-MS method, and provided reproducible target profiling of the kinase inhibitor dasatinib. We further showcased the applicability of this AC-MS workflow for assessing the selectivity of two clinical-stage CDK9 inhibitors against ∼250 probe-enriched kinases. Our study here provides a roadmap for efficient target engagement and selectivity profiling in native cell or tissue lysates using AC-MS.

A semi-automated workflow for DIA-based global discovery to pathway-driven PRM analysis

Targeted proteomics, which includes parallel reaction monitoring (PRM), is typically utilized for more precise detection and quantitation of key proteins and/or pathways derived from complex discovery proteomics datasets. Initial discovery-based analysis using data independent acquisition (DIA) can obtain deep proteome coverage with low data missingness while targeted PRM assays can provide additional benefits in further eliminating missing data and optimizing measurement precision. However, PRM method development from bioinformatic predictions can be tedious and time-consuming because of the DIA output complexity. We address this limitation with a Python script that rapidly generates a PRM method for the TIMS-TOF platform using DIA data and a user-defined target list. To evaluate the script, DIA data obtained from HeLa cell lysate (200 ng, 45-min gradient method) as well as canonical pathway information from Ingenuity Pathway Analysis was utilized to generate a pathway-driven PRM method. Subsequent PRM analysis of targets within the example pathway, regulation of apoptosis, resulted in improved chromatographic data and enhanced quantitation precision (100% peptides below 10% CV with a median CV of 2.9%, n = 3 technical replicates). The script is freely available at https://github.com/StevensOmicsLab/PRM-script and provides a framework that can be adapted to multiple DDA/DIA data outputs and instrument-specific PRM method types.

Mass-spectrometry-based proteomics: from single cells to clinical applications

Mass-spectrometry (MS)-based proteomics has evolved into a powerful tool for comprehensively analysing biological systems. Recent technological advances have markedly increased sensitivity, enabling single-cell proteomics and spatial profiling of tissues. Simultaneously, improvements in throughput and robustness are facilitating clinical applications. In this Review, we present the latest developments in proteomics technology, including novel sample-preparation methods, advanced instrumentation and innovative data-acquisition strategies. We explore how these advances drive progress in key areas such as protein-protein interactions, post-translational modifications and structural proteomics. Integrating artificial intelligence into the proteomics workflow accelerates data analysis and biological interpretation. We discuss the application of proteomics to single-cell analysis and spatial profiling, which can provide unprecedented insights into cellular heterogeneity and tissue architecture. Finally, we examine the transition of proteomics from basic research to clinical practice, including biomarker discovery in body fluids and the promise and challenges of implementing proteomics-based diagnostics. This Review provides a broad and high-level overview of the current state of proteomics and its potential to revolutionize our understanding of biology and transform medical practice.

Size-dependent composition and in-situ structure analysis of the milk fat globule membrane in buffalo milk

This study provides insights into the composition and in-situ structures of the milk fat globule membrane (MFGM) in buffalo milk with different fat globule sizes (0.55 μm and 8.04 μm). Small fat globules contained a higher amount of MFGM proteins and polar lipids, while the content of MFGM components (except for ADPH) was greater per unit membrane area in large fat globules. A total of 386 differentially expressed proteins were identified, with many of the most differentially expressed proteins being associated with human diseases, such as cancer and elderly diseases. The coverage of sphingomyelin and certain MFGM proteins (BTN and PAS 6/7) on large fat globules was higher, potentially linked to the presence of larger, irregular lipid rafts and patch-shaped glycocalyxes, respectively. These findings suggest that small fat globules are suitable for nutritional fortification of buffalo milk, while large fat globules are appropriate for the preparation of functional dairy-based ingredients.

The right tool for the job: Chemical biology and microbiome science

Microbiomes exist in ecological niches ranging from the ocean and soil to inside of larger organisms like plants and animals. Within these niches, microbes play key roles in biochemical processes that impact larger phenomena, such as biogeochemical cycling or health. By understanding of how these processes occur at the molecular level, it may be possible to develop new interventions to address global problems. The complexity of these systems poses challenges to more traditional techniques. Chemical biology can help overcome these challenges by providing tools that are broadly applicable and can obtain molecular-level information about complex systems. This primer is intended to serve as a brief introduction to chemical biology and microbiome science, to highlight some of the ways that these two disciplines complement each other, and to encourage dialog and collaboration between these fields.

A Technical Evaluation of Plasma Proteomics Technologies

Plasma proteomic technologies are rapidly evolving and of critical importance to the field of biomedical research. Here we report a technical evaluation of six notable plasma proteomic technologies - unenriched (Neat), Acid depletion, PreOmics ENRICHplus, Mag-Net, Seer Proteograph XT, Olink Explore HT. The methods were compared on proteomic depth, reproducibility, linearity, tolerance to lipid interference, and limit of detection/quantification. In total we performed 618 LC-MS/MS experiments and 93 Olink Explore HT assays. The Seer method achieved the greatest proteomic depth (∼4,500), while Olink detected ∼2,600 proteins. Other MS-based methods ranged from ∼500-2,200. Neat, Mag-Net, Seer, and Olink had strong reproducibility, while PreOmics and Acid showed higher variability. All MS methods showed good linearity with spiked-in C-Reactive Protein (CRP); CRP was surprisingly not in the Olink assay. None of the methods were affected by lipid interference. Seer had more than double the number of quantifiable proteins (4,800) for both LOD and LOQ than the next best method. Olink was comparable to Neat and Mag-Net for LOD, but worse for LOQ. Finally, we tested the applicability of these methods for detecting differences between healthy and cancer groups in a non-small cell lung cancer (NSCLC) cohort.

Chemoproteomic Profiling of C. albicans for Characterization of Anti-fungal Kinase Inhibitors

Candida albicans is a growing health concern as the leading causal agent of systemic candidiasis, a life-threatening fungal infection with a mortality rate of ~40% despite best available therapy. Yck2, a fungal casein kinase 1 (CK1) family member, is the cellular target of inhibitors YK-I-02 (YK) and MN-I-157 (MN). Here, multiplexed inhibitor beads paired with mass spectrometry (MIB/MS) employing ATP-competitive kinase inhibitors were used to define the selectivity of these Yck2 inhibitors across the global C. albicans proteome. The MIB matrix captured 89% of the known and predicted C. albicans protein kinases present in cell lysate. In MIB/MS competition assays, YK and MN demonstrated exquisite selectivity across the C. albicans fungal kinome with target engagement of only three CK1 homologs (Yck2, Yck22, and Hrr25) and a homolog of human p38α (Hog1). Additional chemoproteomics using a custom MN-kinobead identified only one additional C. albicans protein, confirming its remarkable fungal proteome-wide selectivity. To identify new Yck2 inhibitors with selectivity over Hog1, thirteen human CK1 kinase inhibitors were profiled for fungal kinase-binding activity using MIB/MS competition assays and in-cell NanoBRET target engagement assays. A new chemotype of family-selective Yck2 inhibitors with antifungal activity was identified. Together, these findings expand the application of MIB/MS proteomic profiling for non-human kinomes and demonstrate its utility in the discovery and development of selective inhibitors of fungal kinases with potential antimicrobial activity.

Proteomics: An In-Depth Review on Recent Technical Advances and Their Applications in Biomedicine

Proteins hold pivotal importance since many diseases manifest changes in protein activity. Proteomics techniques provide a comprehensive exploration of protein structure, abundance, and function in biological samples, enabling the holistic characterization of overall changes in organisms. Nowadays, the breadth of emerging methodologies in proteomics is unprecedentedly vast, with constant optimization of technologies in sample processing, data collection, data analysis, and its scope of application is steadily transitioning from the bench to the clinic. Here, we offer an insightful review of the technical developments in proteomics and its applications in biomedicine over the past 5 years. We focus on its profound contributions in profiling disease spectra, discovering new biomarkers, identifying promising drug targets, deciphering alterations in protein conformation, and unearthing protein-protein interactions. Moreover, we summarize the cutting-edge technologies and potential breakthroughs in the proteomics pipeline and provide the principal challenges in proteomics. Based on these, we aspire to broaden the applicability of proteomics and inspire researchers to enhance our understanding of complex biological systems by utilizing such techniques.

Proteomic analysis of egg production peak and senescence in the ovaries of Taihe black-boned silky fowl (Gallus gallus domesticus Brisson)

BACKGROUND

The Taihe black-boned silky fowl, a distinguished indigenous breed of chicken, is renowned for its dual utility in both traditional medicinal and culinary applications. However, the breed faces significant challenges due to its suboptimal reproductive capabilities and a notably brief egg-laying period, which have impeded its broader development and cultivation. In this research endeavor, we employed an advanced, rapid DIA (Data independent acquisition) quantitative proteomics method on the Astral platform to meticulously analyze the ovarian proteome of these chickens. By analyzing the ovarian proteomic information of Taihe black-boned silky fowl during peak and decline egg-laying periods, we aim to identify potential reproductive candidate proteins and the molecular mechanisms underlying egg-laying decline. This could enable us to implement interventions to improve the reproductive efficiency of this valuable breed.

RESULT

In this study, a total of 8,281 proteins were identified within the ovarian proteome of the Taihe black-boned silky fowl. Among these, 303 proteins exhibited significant differential expression, with 98 proteins significantly up-regulated and 205 proteins significantly down-regulated. The functional annotation of these proteins illuminated their crucial roles in the steroid hormone synthesis pathways, which are pivotal during the peak of egg production. Furthermore, during the later stages of laying, there was a noticeable upregulation of proteins associated with inflammatory senescence and oxidative stress. This change suggests an increase in reproductive stress within the ovary, highlighting the physiological shifts that affect productivity as the chickens age.

CONCLUSION

This study identified key candidate protein markers in the Taihe black-boned silky fowl during critical phases of their reproductive cycle, specifically peak and late egg-laying periods. These findings contribute valuable new scientific insights that can be utilized for the breeding optimization and effective management of this unique breed. By elucidating the protein dynamics during different laying phases, the research offers potential strategies aimed at enhancing reproductive performance and extending the reproductive lifespan of the Taihe black-boned silky fowl. This could lead to significant improvements in both the sustainability and profitability of farming this indigenous breed.

JA, Meyer A, Vintila S, McIlvin MR, Van Den Bossche T, Searle BC, Griffin TJ, Saito MA, Kleiner M, Jagtap PD. Data-Independent Acquisition Mass Spectrometry as a Tool for Metaproteomics: Interlaboratory Comparison Using a Model Microbiome

Mass spectrometry (MS)-based metaproteomics is used to identify and quantify proteins in microbiome samples, with the frequently used methodology being Data-Dependent Acquisition mass spectrometry (DDA-MS). However, DDA-MS is limited in its ability to reproducibly identify and quantify lower abundant peptides and proteins. To address DDA-MS deficiencies, proteomics researchers have started using Data-Independent Acquisition Mass Spectrometry (DIA-MS) for reproducible detection and quantification of peptides and proteins. We sought to evaluate the reproducibility and accuracy of DIA-MS metaproteomic measurements relative to DDA-MS using a mock community of known taxonomic composition. Artificial microbial communities of known composition were analyzed independently in three laboratories using DDA- and DIA-MS acquisition methods. DIA-MS yielded more protein and peptide identifications than DDA-MS in each laboratory. In addition, the protein and peptide identifications were more reproducible in all laboratories and provided an accurate quantification of proteins and taxonomic groups in the samples. We also identified some limitations of current DIA tools when applied to metaproteomic data, highlighting specific needs to improve DIA tools enabling analysis of metaproteomic datasets from complex microbiomes. Ultimately, DIA-MS represents a promising strategy for MS-based metaproteomics due to its large number of detected proteins and peptides, reproducibility, deep sequencing capabilities, and accurate quantitation.

Recent Advancements in Proteomic Sample Preparation from Recombinant Chinese Hamster Ovary Cells

Chinese hamster ovary (CHO) cells are the most commonly used mammalian host cell line for biopharmaceutical production because of their ability to correctly fold and post-translationally modify recombinant proteins that are compatible with human use. Proteomics, along with other "omic platforms," are being used to understand the biology of CHO cells with the ultimate aim to enhance CHO cell factories for more efficient production of biopharmaceuticals. Liquid chromatography-mass spectrometry (LC-MS) for proteomic analysis has become the standard technique for profiling proteomes. There are three stages to a typical bottom-up approach, namely, sample preparation, LC-MS/MS, and data analysis. Although there have been major advances in LC-MS/MS instrumentation and data analysis tools, sample preparation is still the crucial stage that affects the overall efficiency of any proteomic study. In this chapter, we present a comparison of a number of widely used sample preparation methods for proteomic applications, including in-solution digestion and commercially available device-based kits. All methods performed well; however, each method has inherent advantages and disadvantages.

Review and Practical Guide for Getting Started With Single-Cell Proteomics

Single-cell proteomics (SCP) has advanced significantly in recent years, with new tools specifically designed for the preparation and analysis of single cells now commercially available to researchers. The field is sufficiently mature to be broadly accessible to any lab capable of isolating single cells and performing bulk-scale proteomic analyses. In this review, we highlight recent work in the SCP field that has significantly lowered the barrier to entry, thus providing a practical guide for those who are newly entering the SCP field. We outline the fundamental principles and report multiple paths to accomplish the key steps of a successful SCP experiment including sample preparation, separation, and mass spectrometry data acquisition and analysis. We recommend that researchers start with a label-free SCP workflow, as achieving high-quality and quantitatively accurate results is more straightforward than label-based multiplexed strategies. By leveraging these accessible means, researchers can confidently perform SCP experiments and make meaningful discoveries at the single-cell level.

Towards routine proteome profiling of FFPE tissue: insights from a 1,220-case pan-cancer study

Proteome profiling of formalin-fixed paraffin-embedded (FFPE) specimens has gained traction for the analysis of cancer tissue for the discovery of molecular biomarkers. However, reports so far focused on single cancer entities, comprised relatively few cases and did not assess the long-term performance of experimental workflows. In this study, we analyze 1220 tumors from six cancer entities processed over the course of three years. Key findings include the need for a new normalization method ensuring equal and reproducible sample loading for LC-MS/MS analysis across cohorts, showing that tumors can, on average, be profiled to a depth of >4000 proteins and discovering that current software fails to process such large ion mobility-based online fractionated datasets. We report the first comprehensive pan-cancer proteome expression resource for FFPE material comprising 11,000 proteins which is of immediate utility to the scientific community, and can be explored via a web resource. It enables a range of analyses including quantitative comparisons of proteins between patients and cohorts, the discovery of protein fingerprints representing the tissue of origin or proteins enriched in certain cancer entities.

Data acquisition approaches for single cell proteomics

Single-cell proteomics (SCP) aims to characterize the proteome of individual cells, providing insights into complex biological systems. It reveals subtle differences in distinct cellular populations that bulk proteome analysis may overlook, which is essential for understanding disease mechanisms and developing targeted therapies. Mass spectrometry (MS) methods in SCP allow the identification and quantification of thousands of proteins from individual cells. Two major challenges in SCP are the limited material in single-cell samples necessitating highly sensitive analytical techniques and the efficient processing of samples, as each biological sample requires thousands of single cell measurements. This review discusses MS advancements to mitigate these challenges using data-dependent acquisition (DDA) and data-independent acquisition (DIA). Additionally, we examine the use of short liquid chromatography gradients and sample multiplexing methods that increase the sample throughput and scalability of SCP experiments. We believe these methods will pave the way for improving our understanding of cellular heterogeneity and its implications for systems biology.

Spatial Proteomics towards cellular Resolution

INTRODUCTION

Spatial biology is an emerging interdisciplinary field facilitating biological discoveries through the use of spatial omics technologies. Recent advancements in spatial transcriptomics, spatial genomics (e.g. genetic mutations and epigenetic marks), multiplexed immunofluorescence, and spatial metabolomics/lipidomics have enabled high-resolution spatial profiling of gene expression, genetic variation, protein expression, and metabolites/lipids profiles in tissue. These developments contribute to a deeper understanding of the spatial organization within tissue microenvironments at the molecular level.

AREAS COVERED

This report provides an overview of the untargeted, bottom-up mass spectrometry (MS)-based spatial proteomics workflow. It highlights recent progress in tissue dissection, sample processing, bioinformatics, and liquid chromatography (LC)-MS technologies that are advancing spatial proteomics toward cellular resolution.

EXPERT OPINION

The field of untargeted MS-based spatial proteomics is rapidly evolving and holds great promise. To fully realize the potential of spatial proteomics, it is critical to advance data analysis and develop automated and intelligent tissue dissection at the cellular or subcellular level, along with high-throughput LC-MS analyses of thousands of samples. Achieving these goals will necessitate significant advancements in tissue dissection technologies, LC-MS instrumentation, and computational tools.

A Proteomics Pipeline for Generating Clinical Grade Biomarker Candidates from Data-Independent Acquisition Mass Spectrometry (DIA-MS) Discovery

Clinical biomarker development has been stymied by inaccurate protein quantification from mass spectrometry (MS) discovery data and a prolonged validation process. To mitigate these issues, we created the Targeted Extraction Assessment of Quantification (TEAQ) software package that uses data-independent acquisition analysis from a discovery cohort to select precursors, peptides, and proteins that adhere to analytical criteria required for established targeted assays. TEAQ was applied to DIA-MS data from plasma samples acquired on a new high resolution accurate mass (HRAM) mass spectrometry platform where precursors were evaluated for linearity, specificity, repeatability, reproducibility, and intra-protein correlation based on 8- or 11-point loading curves at three throughputs. This data can be used as a general resource for developing other targeted assays. TEAQ analysis of data from a case and control cohort for inflammatory bowel disease (n=492) identified 1110 signature peptides for 326 quantifiable proteins from the 1179 identified proteins. Applying TEAQ analysis to discovery data will streamline targeted assay development and the transition to validation and clinical studies.

SPE-CZE-MS quantifies zeptomole concentrations of phosphorylated peptides

Capillary zone electrophoresis (CZE) is gaining attention in the field of single-cell proteomics for its ultra-low-flow and high-resolution separation abilities. Even more sample-limited yet rich in biological information are phosphoproteomics experiments, as the phosphoproteome composes only a fraction of the whole cellular proteome. Rapid analysis, high sensitivity, and maximization of sample utilization are paramount for single-cell analysis. Some challenges of coupling CZE analysis with mass spectrometry analysis (MS) of complex mixtures include 1. sensitivity due to volume loading limitations of CZE and 2. incompatibility of MS duty cycles with electrophoretic timescales. Here, we address these two challenges as applied to single-cell equivalent phosphoproteomics experiments by interfacing a microchip-based CZE device integrated with a solid-phase-extraction (SPE) bed with the Orbitrap Astral mass spectrometer. Using 225 phosphorylated peptide standards and phosphorylated peptide-enriched mouse brain tissue, we investigate microchip-based SPE-CZE functionality, quantitative performance, and complementarity to nano-LC-MS (nLC-MS) analysis. We highlight unique SPE-CZE separation mechanisms that can empower fit-for-purpose applications in single-cell-equivalent phosphoproteomics.

The 2024 Report on the Human Proteome from the HUPO Human Proteome Project

The Human Proteome Project (HPP), the flagship initiative of the Human Proteome Organization (HUPO), has pursued two goals: (1) to credibly identify at least one isoform of every protein-coding gene and (2) to make proteomics an integral part of multiomics studies of human health and disease. The past year has seen major transitions for the HPP. neXtProt was retired as the official HPP knowledge base, UniProtKB became the reference proteome knowledge base, and Ensembl-GENCODE provides the reference protein target list. A function evidence FE1-5 scoring system has been developed for functional annotation of proteins, parallel to the PE1-5 UniProtKB/neXtProt scheme for evidence of protein expression. This report includes updates from neXtProt (version 2023-09) and UniProtKB release 2024_04, with protein expression detected (PE1) for 18138 of the 19411 GENCODE protein-coding genes (93%). The number of non-PE1 proteins ("missing proteins") is now 1273. The transition to GENCODE is a net reduction of 367 proteins (19,411 PE1-5 instead of 19,778 PE1-4 last year in neXtProt). We include reports from the Biology and Disease-driven HPP, the Human Protein Atlas, and the HPP Grand Challenge Project. We expect the new Functional Evidence FE1-5 scheme to energize the Grand Challenge Project for functional annotation of human proteins throughout the global proteomics community, including π-HuB in China.

Hybrid Quadrupole Mass Filter-Radial Ejection Linear Ion Trap and Intelligent Data Acquisition Enable Highly Multiplex Targeted Proteomics

Targeted mass spectrometry (MS) methods are powerful tools for the selective and sensitive analysis of peptides identified in global discovery experiments. Selected reaction monitoring (SRM) is the most widely accepted clinical MS method due to its reliability and performance. However, SRM and parallel reaction monitoring (PRM) are limited in throughput and are typically used for assays with around 100 targets or fewer. Here we introduce a new MS platform featuring a quadrupole mass filter, collision cell, and linear ion trap architecture, capable of targeting 5000-8000 peptides per hour. This high multiplexing capability is facilitated by acquisition rates of 70-100 Hz and real-time chromatogram alignment. We present a Skyline external software tool for building targeted methods based on data-independent acquisition chromatogram libraries or unscheduled analysis of heavy labeled standards. Our platform demonstrates ∼10× lower limits of quantitation (LOQs) than traditional SRM on a triple quadrupole instrument for highly multiplexed assays, due to parallel product ion accumulation. Finally, we explore how analytical figures of merit vary with method duration and the number of analytes, providing insights into optimizing assay performance.

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

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